KR20080011294A - Methods and devices for relieving stress - Google Patents

Abstract

Easy to use, cost-effective methods and devices for evaluating and treating stress and thereby disorders caused or exacerbated by stress are provided. More particularly methods and devices for identifying RSA waves during respiration which provide a subject with realtime RSA wave information are provided. These methods and devices also can be used to identify drop points in RSA waves. Such methods and devices provide subjects with the ability to maintain parasympathetic outflow and thereby prevent and/or reduce levels of stress.

Description

METHODS AND DEVICES FOR RELIEVING STRESS}

This application is a continuation partial application to US application Ser. No. 11 / 084,456, filed Mar. 18, 2005, which claims priority from and benefits from the US application. This application also discloses US application no. 60 / 673,148 filed April 20, 2005, US application no. 60 / 673,627 filed April 21, 2005, US application filed August 4, 2005. Claim priority and benefit from splitting application 60 / 705,883. All contents of each of the above referenced applications are incorporated herein by reference.

The present invention relates to methods and apparatus for assessing and treating stress and diseases associated with stress. In particular, the present invention relates to biofeedback devices and methods for increasing parasympathetic nerve activity by providing information on respiratory sinus arrhythmia patterns.

Despite the presence of many stress reduction products and services, stress and stress-related diseases still lead to uneconomical costs and economic instability. In the United States, occupational stress is estimated to cause nearly $ 300 billion in losses annually in terms of productivity, long-term absenteeism and turnover. In addition to the direct costs associated with work, attempts to treat stress and stress-related diseases accounted for more than $ 17 billion in antidepressant and anti-anxiety drugs in 2002. In the future, the cost of such pharmacological treatment is increasing year by year.

In addition, stress incurs an incalculable cost due to ancillary health problems that are directly or indirectly derived from potential stress diseases. For example, studies show that people under stress are more susceptible to viral and nonviral diseases. Its stress and general known examples are the relationship between stress and respiratory infections. In addition, stressed people take longer to recover from illness.

Chronic stress can adversely affect both the autonomic nervous system (ANS) and the balance of efficacy of ANS, resulting in countless stress related diseases. Disorders of ANS result in degenerative diseases and early death. For example, a clinical study examined single, 2-minute measurements of 14,025 healthy men and women between 45 and 64 years of age. After eight years, the group with lower parasympathetic measures had higher disease and mortality. Three different studies (US, Denmark, and Finland) also investigated ANS function as being related to "all cause mortality." In each study, low parasympathetic ANS function predicted and predicted disease and death. Literally, hundreds of studies have found that ANS function is associated with individual diseases such as heart disease, diabetes and stroke. For example, UK information was commissioned to study ANS function and heart disease. The group with the lowest parasympathetic ANS function had a 1,000% increase in mortality from heart attack. The uneconomic costs of stress are also very large and have a detrimental effect on relationships with family, friends, neighbors and colleagues.

The stress response affects two basic systems: the automatic nervous system and the endocrine system. ANS generally stimulates the smooth muscles of internal organs and consists of sympathetic and parasympathetic parts. In short, the sympathetic part is responsible for responding to emergencies (flight or flight), mobilizing energy to express emotions or perform intense reactions, while the parasympathetic part has a calming effect. Balance the sympathetic nervous system by working to exert. As the sympathetic nerves become more active, they increase heart rate, blood pressure, respiratory rate, mental activity (and thus excite the brain), and other physical functions. Thus, stress is maintained by high activity of the sympathetic nerves.

Endocrine systems are also involved in stress-related processes. In particular, the hypothalamic-pituitary adrenal (HPA) axis plays a major role in the stress response of the endocrine system. The hypothalamus secretes peptide hormones to stimulate the pituitary gland, which in turn secretes its own hormones to stimulate other endocrine glands. The adrenal glands secrete cortisol, which regulates metabolism and energy production and regulates responses to sympathetic and parasympathetic branches of the autonomic nervous system. Cortisol levels are directly related to the degree of individual stress response.

In the early 1970s, Dr. Herbert Benson reported in detail the existence of neurological and physiological conditions against "stress response." This condition, called the "relaxation response," has been demonstrated by other clinical researchers. From the autonomic nervous system, the stress response is characterized by high activity of the sympathetic branch, while the relaxation response is characterized by high activity of the parasympathetic branch. Induction of a relaxation response, by definition, blocks the active stress response. Thus, frequent activation of the relaxation response can prevent stressors from producing ongoing (ie chronic) stress. In addition, frequent activation of the relaxation response has been shown to reverse many of the injuries, including hypertension, caused by chronic stress previously experienced.

The free nervous system (sympathetic and parasympathetic) can be characterized by examining the small changes in time that occur between each successive heart beat. When an individual takes a break, the change in beat to beat time is caused by the parasympathetic branch. These changes will increase and decrease with individual breathing patterns. During inhalation, the parasympathetic branch will be suppressed and the heart rate will begin to rise. During exhalation, the parasympathetic branch engages in heart rate and lowers heart rate. This relationship between heart rate changes and breathing is called respiratory sinus arrhythmia (RSA). RSA measurements are mathematical calculations of the rate at which the heart rate rises and falls. If the rise and fall is large, then the activity of the parasympathetic nervous system becomes large. In other words, an increase in RSA indicates an increase in parasympathetic activity. As previously disclosed, a sufficient increase in parasympathetic activity changes the body to a state of relaxation response, stopping any already existing stress response.

Many attempts have been made to activate relaxation reactions to address and control stress, including invasive and non-invasive techniques and processes. For example, acupuncture, prescription and non-prescription pharmacological treatments and psychlotherapy have all been used in attempts to relieve and control stress. However, each of these therapies involves enormous time and expense. In addition, the effectiveness of these treatments is often not perfect and practically not practical. Effectiveness is difficult to assess and in many cases is temporary. In addition, pharmacological treatments often have undesirable side effects, and some also pose a risk of poisoning. In addition, with all possible alternatives, stress is still the cause of more than 80% of cases (directly or indirectly) visiting doctors.

Thus, there is a clear need for methods and devices for assessing and treating stress, which are effective, non-invasive, simple to use, and inexpensive. In addition, methods and apparatus that do not have unwanted side effects and that there is no risk of poisoning are clearly required. In particular, there is a clear need for methods and devices that can provide high levels of uninterrupted parasympathetic activity to facilitate the reduction of stress and to immediately stop the stress response.

The present invention provides easy-to-use and cost-effective methods and devices for evaluating and treating stress and diseases caused or aggravated by stress. In particular, the present invention provides methods and apparatuses for identifying an RSA wave in an individual and providing RSA wave information to a patient. This information can be used, for example, in biomagnetic control settings to help the patient to reduce stress levels and achieve regular breathing.

The present invention also provides methods and apparatuses that allow for immediate discontinuation of the physiological stress response that prevents the stress response from harming the body and spirit. The periodic use of the methods and apparatuses according to the present invention allows the reversal of physiological damage caused by exposure to previous stresses, including the cumulative effects of chronic stress.

Accordingly, one exemplary embodiment of the present invention provides compact portable biomagnetic control devices for preventing, reducing or eliminating the stress of a patient.

Yet another exemplary embodiment of the present invention provides methods and apparatuses for maintaining high parasympathetic nerve activity that continues substantially over a sustained period of time.

Yet another exemplary embodiment of the present invention provides compact portable biomagnetic control devices that include a photoplethysmograph (PPG) sensor and display on a screen to provide information on its RSA wave to a patient.

A further exemplary embodiment of the present invention provides methods and apparatus for training a patient to reduce stress levels by achieving a cycle of breathing close to six breaths per minute.

Another exemplary embodiment of the present invention provides methods and apparatus for facilitating the reduction of stress by providing real-time feedback of its activity to uninterrupted parasympathetic nerve activity.

A further exemplary embodiment of the present invention provides methods and apparatuses for providing a user with information about the transition of the RSA from rising points to falling points, the information to guide the user's breathing. Can be used.

Yet another exemplary embodiment of the present invention provides methods for detecting and correcting false data related to an RSA wave and apparatuses using such methods.

Another exemplary embodiment of the present invention provides methods for adjusting scaling on a display screen of portable biomagnetically controlled devices and devices using such methods.

Another embodiment of the present invention identifies and displays respiratory patterns including depth, velocity and size by analyzing the RSA.

FIG. 1 illustrates a typical heart rate variability (HRV) caused by respiratory dynamic arrhythmias (RSA).

2 shows a series of exemplary RSA waves and identifies multiple pulse peaks.

3 shows a series of exemplary RSA waves and calculates the interbeat interval (IBI) time between successive pulse peaks.

4A-4B reveal typical peaks, bottoms, rising transition points and falling transition points, respectively.

5 illustrates a typical continuous rising and falling transition points.

6 illustrates an example method for identifying peaks.

7 illustrates an example method for identifying the lowest point.

8A and 8B show an example process flow for an example process for finding RSA waves in a data set in accordance with an exemplary embodiment of the present invention.

9 illustrates an example process for identifying RSA waves in a data set.

10 illustrates an exemplary double top wave.

11 shows an exemplary method for correcting data from a typical double top wave.

12 shows an exemplary display of a stress meter.

13 illustrates an example method for determining the long term direction of RSA waves.

14 shows an example process flow for an example process for determining wave phase.

15 shows an example process flow for an example process for determining wave aspects.

16A and 16B show example methods for determining wave completion.

17 illustrates an example method for depicting wave boundaries.

18 illustrates an example method for assessing continuous parasympathetic nerve activity.

19 illustrates an example method for assessing continuity of parasympathetic nerve activity.

Figure 20 illustrates one embodiment of the apparatus according to the present invention and identifies the potential location for the power switch.

21 shows a typical location for a PPG sensor capable of collecting data from a patient's finger.

22A and 22B show alternative ways in which the patient grabs the exemplary device while the patient's finger is in the PPG sensor.

23 shows an exemplary display of a countdown meter.

24 shows an exemplary display of pulses over time and typical average pulses.

25 shows an exemplary error message display.

26 illustrates an example embodiment of a countdown timer.

FIG. 27 provides a typical diagram of RSA waves in which the patient's breathing slows down over time.

FIG. 28 provides a typical view of an RSA wave in which a patient deepens breathing over time.

29 shows a typical RSA pattern that breathes regularly.

30 provides a wave frequency of 6 for a typical display of a patient.

31 provides a wave frequency of 6 on another typical display of a patient.

32 shows an exemplary display of RSA wave history of a patient.

FIG. 33 shows an exemplary display of a patient in which the depth of respiration is increased and relatively large waves are generated, each with a period of about 10 seconds.

FIG. 34 shows a typical location for a guiding breathing switch for activating a guiding breathing function in exemplary devices of the present invention.

35A and 35B show exemplary displays for guided breathing with increasing breathing bars to guide inhalation and decreasing breathing bars to guide exhalation.

36 shows an exemplary display of a session summary screen.

Figure 37 shows an exemplary display of various types of RSA information that may be represented by typical devices in accordance with the present invention.

38 illustrates an alternative to form a factor for exemplary devices of the present invention.

39A and 39B show a display having a size sufficient to represent both correct data and wrong data, respectively, and a display of a small portable device capable of recognizing only wrong data.

40 shows a series of typical pulse peaks.

41A and 41B show typical false positive pulse peaks and typical false negative pulse peaks, respectively.

42 shows an example process for an exemplary error correction method used during a typical error correction mode.

43 illustrates typical wave features that can be used to determine when a patient achieves regular breathing.

44 illustrates an example system in which a software process may be executed in accordance with an exemplary embodiment of the present invention.

45 and 46 illustrate example processes for an exemplary top level process for interacting with a user in accordance with an exemplary embodiment of the present invention.

47 and 51 illustrate exemplary process flows for an exemplary process for processing a detected pulse in accordance with an exemplary embodiment of the present invention.

52-54 illustrate an example process flow for an example process for error correction for a sequence of detected pulses in accordance with an exemplary embodiment in accordance with the present invention.

55 and 56 illustrate exemplary process flows for an exemplary process for error detection for a sequence of detected pulses in accordance with an exemplary embodiment of the present invention.

57 shows an example process flow for an example embodiment for initializing a range for a detected pulse in accordance with an example embodiment of the present invention.

58 and 59 show example process flows for an example process for processing RSA waves in a sequence of detected pulses in accordance with an exemplary embodiment of the present invention.

60-62 illustrate an exemplary process flow for an exemplary process for processing RSA wavelengths within a sequence of detected pulses to determine stress levels for a user in accordance with an exemplary embodiment of the present invention.

63 shows an example process flow for an example process for assigning wavelengths to RSA waves in accordance with an exemplary embodiment of the present invention.

64 to 74 illustrate phases of RSA waves in real time, uses phase shifts to detect falling points, phase shifts to detect wave completion, and to determine parasympathetic intensity of newly formed waves. An example process flow for an example process is shown.

75-83 illustrate another example process flow for an example process for determining wave phase and depicting pulse-by pulse waves.

84-87 illustrate example process flows for example processes for determining completion and falling points of waves in real time.

Studies have shown that control of breathing can shift the balance between sympathetic and parasympathetic branches. Three specific respiratory configurations bidirectionally determine a number of parasympathetic nerve responses. These three configurations include frequency, time-varying volume, and inhalation / exhalation ratio. In general, parasympathetic nerve activity may be increased by decreasing respiratory frequency, increasing in volume over time and / or increasing inhalation / exhalation ratio. Thus, changing these three variables has the potential to increase parasympathetic activity enough to effectively elicit non-invasive, simple and inexpensive relaxation responses without negative side effects.

Generally speaking, biomagnetic control methods and devices involve training processes that facilitate changes in the behavior or activity of a patient to improve or maintain one or more physiological functions. Over time, a patient can be trained with biomagnetic control methods and devices to practice better control over these functions. In contrast to other forms of therapy where treatment is weighted to the patient, biomagnetically controlled methods and devices allow the patient to gradually integrate the training process into near automatic responses.

The present invention relates to methods and apparatuses that can provide biocontrol information and training for patients suffering from stress and stress related diseases. Such biomagnetic control information and training can be based on analysis of respiratory tract arrhythmia patterns and breathing that can affect those patterns.

Methods for identifying individual RSA waves during natural respiration using only the RSA data set are not known. In order to correlate RSA waves with respiration, heart rate and respiratory rate information is typically collected and individually mapped. One aspect of the invention includes the identification of individual waves in an RSA data set. Additional aspects of the present invention include the use of RSA wave patterns to provide a patient with real-time respiratory feedback information based on heart rate data. Means are also provided for reducing or appropriately controlling stress levels based on wave pattern analysis and respiration feedback.

In addition, methods for identifying individual RSA waves in real time during natural respiration using only the RSA data set are not known. Additional aspects of the present invention allow for such real-time identification and use this information to facilitate the generation of uninterrupted high levels of parasympathetic activity.

Example Method of Wave Pattern Identification

In an exemplary embodiment of the present invention, the identification and analysis of respiratory dynamic arrhythmia wave patterns begins by measuring the patient's pulse rate in beats to beats. It is well known in medical books that human heart rate and pulse rate fluctuate up and down in wave form (FIG. 1). These waves are known as heart rate fluctuation (HRV) waves. When a person is physically stationary and at rest, HRV waves are associated with the person's breathing. These resting HRV waves are medically known as respiratory dysmorphic arrhythmias or RSA waves, the size and shape of these waves being related to speed, rhythm and depth of human breathing. As long as a person breathes between 4 and 15 times per minute, the frequency of the waves will substantially match the frequency of breathing. Most people breathe within this range, but even if they breathe outside this range, the wave frequency will still have an approximation of the breathing frequency.

Although the correlation between waves and breathing is well known in the medical literature by visual analysis, there are non-automated methods for identifying individual waves in the heart rate data set. Exemplary embodiments of the invention include a novel method for identifying each individual wave for a heart rate data set.

For example, the amount of time (in milliseconds) between two consecutive pulse peaks (peak-to-peak time) is called the so-called pp interval (FIG. 2). In an exemplary embodiment of the invention, the device records successive pp intervals. The description of pp interval points is also applied to rr intervals (interval between ECG recording or successive R waves of the ECG), any derivative of pp intervals such as pulse points, any derivative of rr intervals such as heart rate. do. Collectively, these intervals can be referred to as "heart rate intervals". Also, the same method of obtaining RSA waves from pp intervals can be applied directly to these other points. Certain preferred embodiments of the present invention, however, parse waves in pp interval data sets.

The pulse rate (60,000 / pp) of each recorded pp interval can be displayed on the screen each time a new pulse peak occurs. The perfect time difference between successive pp intervals (absolute (pp [n] -pp [n-1])) is called the inter-bit interval (IBI) time (FIG. 3). One aspect of the invention uses pp interval times to identify individual RSA waves. The methods disclosed herein can be used for natural, guided breathing.

Each p-p can be categorized by examining its relationship to the immediately preceding p-p (previous pp) and the immediately following p-p (next p-p). p-p may be considered the highest point (tp) if the previous p-p is less than or equal to itself, and likewise the next p-p is less than or equal to itself (FIG. 4A). p-p may be considered the lowest point (bp) if the previous p-p is equal to or greater than itself, and likewise the next p-p is greater than or equal to itself (FIG. 4B). p-p may be considered an ascending transition point (at) if the previous p-p is less than itself and the next p-p is greater than itself (FIG. 4C). p-p may be considered a falling transition point (dt) if the previous p-p is larger than it and the next p-p is smaller than it (Fig. 4d). Thus, p-p may be categorized as one of the highest (tp), lowest (bp), rising transition (at) or falling transition point (dt). The term "transition point" may be used to refer to both ascending and falling transition points when not limited to the terms "rising" or "falling". Successive transition points are referred to as a series of successive ascending transition points or successive descending transition points (FIG. 5).

The term "top level" can be used to refer to the relative height of the highest point. The level of the peak may be calculated as follows. L = The number of consecutive points immediately to the left of the highest point that is below the highest point. R = The number of consecutive points just to the right of the highest point that is below the highest point. If L <R, then the top level is equal to L, otherwise the top level is equal to R. 6 illustrates how peak levels are categorized, using three embodiments.

The term "lowest level" can be used to refer to the relative height of the lowest point. The lowest level can be calculated as follows. L = The number of consecutive points immediately to the left of the lowest point above the lowest point. R = The number of consecutive points just to the right of the lowest point that is above the lowest point. If L <R, the lowest level is equal to L, otherwise the lowest level is equal to R. 7 illustrates how the lowest level is categorized, using three embodiments.

8A and 8B provide an example flow diagram illustrating an example process for discovering RSA waves in a data set, while FIG. 9 shows how this process can be applied. In an exemplary embodiment of the invention, the first step is to locate the highest number of consecutive transition points (ctp) in the data set. In FIG. 9, the highest number of consecutive transition points starts at point 1. There are two consecutive transition points. The wave depth is equal to the number of these transition points. Therefore, the wave depth of this embodiment is two. In preferred embodiments, if the wave depth is greater than four, the wave depth value is adjusted down to four.

The next step is to place the lowest point on the right of successive transition points where the lowest label is above the wave depth. This is the right valley point (v2) of the RSA wave. In the embodiment of FIG. 9, the lowest eighth has a level of three and is greater than the wave depth. The next step is to place the lowest point to the right of successive transition points whose lowest level is above the wave depth. This is the left valley point (v1) of the RSA wave. In the embodiment provided in FIG. 9, the lowest point 0 has level 4 and is greater than the wave length. The next step is to find the highest point between the left valley point and the right valley point. This is the peak p of the RSA wave. In the embodiment of FIG. 9, point 6 is the highest point between two valley points. All data from the left valley point v1 to the right valley point v2 are considered processed data. The same process is repeated on the remaining raw data until all possible waves are identified.

There are a number of variations in the disclosed method which should be considered within the scope of the present invention. For example, a similar method can be used to find peaks on each side of the transition point series. The valley between the two peak points will thus be the lowest point between the two peaks. Furthermore, the wavelength depth may be based on the number derived (eg, the number of transition points x 75%) derived based on the complete number of transition points or the number of transition points. In addition, v1 may be identified before the v2 point.

In a preferred embodiment, the wave analysis method discussed above is used each time four points of the new lowest level are identified. Thus, devices in accordance with exemplary embodiments of the present invention “find” RSA waves between the lowest level four points. In other example embodiments, the devices may be configured to “find” the RSA waves after each point or after a certain time period has elapsed. The example embodiments use the lowest level four points because the lowest level four points have a very high probability of contouring the RSA waves. That is, they have a high likelihood that they can be valley points (v1, v2) of RSA waves.

There are two examples where the basic RSA wave analysis methods disclosed above can accurately describe an RSA wave. One method may appear when a double top wave occurs. The best waves can form when an individual waits a long time to breathe after already exhaling. Another method may appear when double bottom waves are formed. Dual lowest waves can form when you hold your breath for a long time after you inhale. Double top waves are easily identified by examining the ratio of the lengths of the two waves (FIG. 10). When (p1-v2) is much smaller than (p1-v1), (p2-v2) is much smaller than (p2-v3), and (p1-v2) is very close to (p2-v3), the double top wave This happens. In preferred embodiments, the double top waves can be defined in the following situations: ((p1-v2) / (p1-v2)) <0.50 and ((p2-v2) / (p2-v3)) < 0.50 and ((p1-v1) (p2-v3))> 0.75. The double lowest waves can be defined as the inverse of the double top waves.

Whenever double top waves or double bottom waves are generated from the basic analysis method, the two waves forming the pattern can be merged together into one wave. Point v1 is v1 of the new wave. Point v3 becomes v2 of the new wave. The highest value between v1 and v3 is the peak of the new wave. This is illustrated by FIG.

Exemplary embodiments of the invention may use the RSA wave information disclosed above to calculate the mental stress level of a user. This mental stress measurement can be represented on the devices as a stress meter (FIG. 12 (5)). For example, when an individual is under stress, breathing is usually faster and more irregular than in an unstressed state. This rapid and irregular breathing can lead to the formation of short and uneven RSA waves. The methods and apparatuses according to the present invention can be used to determine the stress level of a user by determining the average wavelength of the user deviating from the level representing the relaxed state and how much dust. Such methods and devices can also calculate how irregular the (irregular) user's waves are. These two estimates can be used separately or mixed into a single value to represent the overall stress level.

The findings demonstrated that people tend to breathe at regular rhythms of about six breaths per minute when they are very comfortable (as in deep meditation). Such regular breathing causes the RSA wavelengths to change in cycle of breathing frequency. Thus, six regular breaths per minute results in a series of RSA wavelengths with a wavelength of 10 seconds. Thus, exemplary embodiments of the present invention use wavelengths of 10 seconds as a relaxation threshold when evaluating a user's stress level. Example embodiments also include methods and apparatus for calculating the average wavelength of the last five waves to determine how far the average is proportionally from 10 seconds. This is an example of a "wavelength score".

Irregular waves can be quantified using a number of standard variance formulas. Exemplary embodiments of the present invention use the summation of each successive wavelength difference in the last five waves to calculate a "variance score". Exemplary embodiments may also use the sum of the differences between successive wavelengths, and may use rank order weighted averaging, so that the variation of the most recent waves is further calculated. The stress level in the exemplary embodiment of the present invention uses 70% of the “wavelength score” + 30% of the “variable score.” The user's stress level can be recalculated each time a new RSA wave is identified. .

Stress can cause various RSA wave actions such as: reduced peak to peak time, increased peak to peak frequency, reduced wavelength, increased wave frequency, reduced amplitude, irregular wavelengths, irregular Wave frequency, irregular amplitude, irregular peak-to-peak time, irregular peak-to-peak frequency, irregular peak placement, or reduced fluctuations. Any one of the foregoing variables or any combination of the above variables may be applied to the RSA waves and used as an indicator of the stress level. Identifying individual RSA waves in cooperation with each other and / or in conjunction with other variables to assess stress and using only any of the preceding variables should be within the scope of the present invention and disclosed in the art. It wasn't.

In addition to using the identified RSA waves to determine stress level, devices and methods in accordance with exemplary embodiments of the present invention can also use RSA wave information to determine and display both average heart rate and wave frequency. have. The average of all pulse rates in the last wave can be used to assess the average heart rate. For example, each time a new RSA wave is identified, the average of the heart rate can be calculated and the heart rate updated. The wave frequency display can also be updated each time a new RSA wave is identified. Exemplary embodiments may indicate frequency in terms of waves per minute (breathings). In exemplary embodiments, the wave frequency and heart rate may be rounded to the nearest integer.

Example Methods of Real-Time Wave Pattern Identification

The present invention also provides a method for identifying a real-time RSA wave pattern. In certain embodiments, such methods involve two main interrupt driving processes.

The first process can be triggered every time a new pulse is detected by the PPG sensor. This process comprises the steps of: (1) converting the received pulses into pulse rate values prv; (2) updating the wave display with a new prv; (3) confirming that the new prv marks the beginning of a new wave (indicating that the previous wave has just been completed); (4) delineating the boundary of the last wave (identifying valley-peak-valley points); (5) evaluating parasympathetic activity of the wave; (6) displaying the appropriate symbol under the wave; (7) updating the wave history; And (8) updating the score.

The second process may detect and display the drop point in real time. This process can be driven by a clock interrupt. In preferred embodiments, this process may occur every 250 milliseconds, for example. When a process detects the occurrence of a drop point, it may be indicated by a drop point indicator, such as a triangle, for example.

Any one of these processes can be executed using standard polling methods. Alternatively, the second process can occur every time a pulse is detected. Exemplary embodiments detect clock drops faster using clock interrupts. However, reasonable result values will be provided by indicating the drop point based on the received pulse bits.

Preferred embodiments of the present invention also provide various methods for real time accurate characterization of RSA wave patterns. Such methods include those that can be conveniently referred to as "wave phase" methods and "wave side" methods.

Wave Phase Determination Methods

The present invention also provides wave phase determination methods and apparatuses using such methods. In exemplary embodiments of the present invention, each time new pulses occur, the long term wave direction can be evaluated. This process is shown in FIG. For example, the slope of the last six (6) pulse points can be used. The resulting values may for example be called "long slope". Alternatively, for example, the slope of the time-based sliding window of the points may be used (eg last 12 seconds, last 5 seconds, etc.), or other general indicators of direction may be used.

Next, for example, a complete amount of long term change can then be calculated. This gives the degree of change. In exemplary embodiments of the present invention, the full value of the long slope may be used, which may be referred to, for example, as a "complete long slope". Alternatively, for example, a complete value or similar transformation of any long term wave estimate can be used.

Next, for example, the short term direction of the wave can be determined. In one embodiment of the invention, for example, the slope of the last three (3) pulse points may be used. This may be called, for example, a "short slope." Alternatively, any direction indicator may be used, for example, on a subset of points smaller than the points selected for long term direction evaluation.

Then, for example, a short term direction indicator and a complete long term indicator can be used to evaluate the actual direction of the wave. In an exemplary embodiment of the present invention, the short slope may be compared to, for example, a complete long slope. If the short slope is for example greater than 30% of the complete long slope, then the wave direction can be regarded as, for example, UP. If the short slope is less than (-1) * 30% of the complete long slope, then, for example, the direction can be considered as DOWN. If both tests fail, then the direction can be considered flat (FLAT).

In alternative exemplary embodiments of the present invention, different percentages may be selected for this delivery. The percentage may be based on the desired degree of parasympathetic nerve sensitivity. Higher percentages may be less sensitive to parasympathetic interrupts, while lower percentages may be more sensitive. About 30% is usually sensitive enough to detect major interrupts, but closes enough to put the action under user control.

Also, in an exemplary embodiment of the present invention, the percentage determining the UP direction may be different from the percentage determining the DOWN direction. Alternatively, other mathematical comparisons of short inclinations to complete long inclinations can be used, for example, to determine the relative relationship between the long inclinations and the short inclinations and thus to determine the wave direction. Alternatively, other mathematical functions may be used in place of complete long slopes and short slopes to evaluate short-term directions and degrees of long-term changes.

Next, the wave direction and the long term direction can be used, for example, to determine the phase of the wave. In exemplary embodiments of the present invention, the wave direction and the long inclination may be checked to make this assessment, for example as shown in the exemplary process flow diagram of FIG. 14. The process flow begins at 301 where the query "A long slope is positive?" Is evaluated. For example, if the long slope is positive at 301, the process flow moves to 310, which evaluates the query "Is the direction UP?". If the direction is UP at 310, the process flow proceeds to 311 and the phase is determined to be RISING. For example, if the long slope is positive at 301, but the direction is not UP at 310, then the process flow proceeds to 312 and the phase is determined as CRESTING. For example, if the long slope is negative at 301 (ie, "No" is returned with the query "Are long slopes positive?" At 301), this moves the process flow to 320, and then at 320 "Yes" is returned to the query "Are Up?" And the process flow proceeds to 330. If the direction is DOWN at 330, then the process flow moves to 331 and the phase is determined to be FALLLING. Alternatively, if the long slope at 320 is negative, the direction is not DOWN at 330, the process flow moves to 332 and the phase may be TROUGHING. At 312, 311, 332 and 331 respectively the result is passed to 350 and the determined phase can be returned to further process or another process for output.

Methods for Determining Wave Aspects

The present invention also provides a method of determining wave aspects and an apparatus using such a method. Thus, in exemplary embodiments of the present invention, an alternative to determine all four phases of the wave may be implemented. This alternative method can only detect the RISING and FALING phases of the wave, for example using a mix of ranges and directions. An exemplary process flow for this method is shown in FIG. 15. The process flow begins at 401, for example, the highest prv in a "High" -given interval, the lowest prv in a "LOW" -given interval, and the "Range" -High to Low values can be obtained. "High", "Low" and "Range" are referenced to evaluate the prv values of the sliding window (e.g., last 12 points, last 12 seconds, etc.). In exemplary embodiments of the present invention, the prv range of the last 12 seconds may be used. The direction can be evaluated as disclosed above at 410.

Once the range and direction are calculated, the phase can be evaluated. This can be done by looking at the current prv and wave direction with respect to the range. If the wave direction is upward at the bottom of the range, then the wave phase is moved to rise. Alternatively, if the wave direction at the top of the range is downward, then the wave phase is moved to falling. Whether the wave is at the top and bottom of its range can be judged by, for example, selecting a percentage or fraction of the full range as shown in FIG. 15, and being within 25% of the top of the range is considered almost the top. And not exceeding 25% of the bottom of the range is considered almost the bottom. In alternative example embodiments, other threshold values may be used.

Referring to FIG. 15, for example, at 420, a current prv may be tested to see if it is at the top 25% of the range. If the last point at 420 is near the top of the range, ie “Yes” at 420, the process flow may proceed to 430 where the wave direction is analyzed. If the wave direction is DOWN at 430, the process flow moves to 431, the wave phase is determined to move to FALLING, and the process exits at 460.

However, if at 420 the current prv is within the top 25% of range, the process flow moves to 440. At 440 the wave is tested to see if it is at the bottom 25% of its range. If yes, the process flow moves to 450, for example, the wave direction can be evaluated. For example, if the wave direction is UP at 450, the process flow moves to 451 where it is determined whether the wave phase moves to RISING and the process exits at 460.

If at 420 the wave is not at the top 25% of the range and at 440 the wave is not at the bottom 25% of its range, the process flow moves to 460 where the process exits. The process also exits if the wave direction is not UP at 450 or if the wave direction is not DOWN at 430.

Thus, in exemplary embodiments of the present invention, either the method Wave Phase (FIG. 15) or Wave Side (FIG. 14) can be used to determine the current phase. In many cases, Wave Side can be used, for example, because the use of range adds accuracy. However, in other embodiments, in other embodiments where it is desirable to track all four phases, the Wave Phase may be used, for example, since the Wave Phase identifies TROUGHING and CRESTING.

How to judge wave completion

The invention also provides a method of determining wave completion and an apparatus using such a method. In exemplary embodiments of the present invention, to determine when a new wave is completed, the current phase is based on a beat-to-beat, for example using a phase determination method as disclosed above. Can be tracked. When the current phase shifts to RISING, it is known that the wave has recently been completed, for example as shown in FIG. 16A. Alternatively, for example, the wave side may be tracked based on bit-to-bit. When the wave side moves to LEFT, it is known that a new wave is completed, for example as shown in FIG. 16B.

How to outline wave boundaries

The invention also provides a method of contouring wave boundaries and an apparatus using such a method. Thus, once it is determined that the new wave has been completed, points between the starting point of the previous wave trough and the point where the new wave rises are obtained, as shown in FIG. The lowest point of the previous wave valley can be referred to as the left-valley point. The lowest point between the left-bend point and the new rise point may be referred to as the right-bend point. The highest point between the left-valley point and the right-valley point can be referred to as a peak.

Alternatively, wave side analysis can be performed using, for example, points from the left side of the previous wave to the end of the right side of the newly formed wave. The lowest point on the right side of the previous wave can be referred to as the left-valley point. The lowest point between the left-valley point and the right side of the new wave can be referred to as the right-valley point. The highest point between the left-valley point and the right-valley point can be referred to as the peak.

How to assess parasympathetic activity

The invention also provides methods of assessing parasympathetic nerve activity and devices using such methods. In exemplary embodiments the wave boundaries can be used to assess parasympathetic activity. In certain embodiments of the present invention, two parasympathetic parameters can be measured for the following resulting waves: parasympathetic response intensity and parasympathetic neuronal activity continuity.

In one embodiment, the intensity of the parasympathetic response can be determined by, for example, the wavelength (timestamp of the right-bend point minus the timestamp of the left-bend point). If the wavelength is less than 6 seconds, for example, the intensity may be determined as LOW. If the wavelength is greater than 6 seconds and less than 9.5 seconds, for example, the intensity may be determined as MEDIUM. If the wavelength is 9.5 seconds or more, the wavelength may be determined as HIGH.

In alternative embodiments, parasympathetic nerve activity levels may be assessed using conventional RSA measurements, such as, for example, continuous heart rate, standard deviation, mean deviation, and the like.

The continuity of parasympathetic responses can be assessed in two parts. First, the slope of all three consecutive points can be calculated by starting with a peak from the left-valley point, for example. If any slope approaches zero or becomes negative, parasympathetic outflow stops, for example, during the rise of the wave (FIG. 18). Similarly, the slope of all three consecutive points can be calculated by starting with the right-valley point from the peak, for example. If any slope approaches zero or becomes positive, parasympathetic outflow stops during the fall of the wave. If the short term slope on the left side of the wave remains high and positive, for example, the short term slope on the right side of the wave remains high and negative and, for example, it is believed that parasympathetic outflow continues without interruption ( 19).

In exemplary embodiments, the threshold for the short term slope may be changed. Exemplary devices may continue to track the highest positive slope, for example, over the last 5 seconds. Such devices can keep track of the complete value of the highest negative slope of the last 5 seconds, for example. If the complete value of the highest negative slope is greater than the highest positive slope, for example, the value can be used to indicate "fastest change". If not, the highest positive slope can be used to indicate the "fastest change".

In certain embodiments, when examining the rise of the wave, parasympathetic nerve disruption is expected if any of the three point slopes is less than 30% of the fastest change, for example. Similarly, during the fall of the wave, if any of the three point slopes is greater than 30% of, for example, (-1) x (fastest change), parasympathetic nerve disruption is expected.

It will be appreciated that other algorithms in accordance with the present invention may be used to evaluate whether a short term slope is interrupted during the rise or fall of a wave.

Descent  Detection method

The present invention also provides a method of detecting a dropping point and a device using the method. In exemplary embodiments, the drop point detection routine may run every 250 ms, for example. For example, each time a 250 ms clock interrupt is triggered, the device may insert a phantom value into the set of received pulse bits. In exemplary devices, the virtual image value is perceived as a newly received pulse, for example at the moment the interrupt is triggered. The routine can then apply a phase determination method having this virtual image value to the data set. If such a phase determination method evaluates that the phase moves to a FALLING having the virtual image value, the drop point is detected because the next actual pulse will occur after the drop point. When a drop point is detected, a symbol such as a triangle can be displayed immediately by the interrupt routine. If the test is false, no symbol is displayed. Methods using such interrupt routines allow for detection and dropping of the dropping point in real time.

Example Devices

The following description relates to exemplary embodiments of the present invention in the form of devices that can be used to assess and treat human stress. In such embodiments, the RSA may be identified and characterized in any of the manners disclosed above and may be used to provide biomagnetic control to the user. Such exemplary devices include devices that provide information to the user in real time to facilitate the generation of uninterrupted high parasympathetic output over a substantial time period. In addition to the specific embodiments disclosed below, it should be understood that other devices and methods may be devised within the scope of the present invention. Alternative embodiments are not explicitly disclosed herein, and the precise description provided herein is not intended to limit the invention. In particular, combinations of the various features described below can be integrated into a single device, and such a device will fall within the scope of the invention disclosed herein. The full scope of the invention is collectively based on the disclosure herein.

The present invention provides, for example, battery powered portable handheld devices that may include a PPG sensor, a display screen, a control button and a power button (FIG. 20). The user can turn on such devices by pressing the power button. If the devices are used in a dark room, the user can turn on the backlight by pressing the power button a second time and holding it pressed for a few seconds. Shortly after the device is powered on, the user inserts a finger into the finger sensor (FIG. 21). The user then gently grips the device with the finger on the top of the sensor throughout the entire session. The device may be comfortably gripped so as to lie perpendicular to the thumb (FIG. 22A) or at an angle on the bent fingers of the hand that grips it (FIG. 22B).

Once the finger is inserted into the finger sensor, the device will then begin calibrating the PPG sensor. The countdown meter will indicate the amount of time required to calibrate. After the PPG sensor is calibrated, the device may use the PPG sensor to detect each pulse of blood in the finger. The resulting pulse (number of milliseconds between 60,000 / two consecutive pulse peaks) can then be recorded on the screen based on the pulse by pulse scheme (FIG. 24 (2)). The display also shows the user's average pulse (FIG. 24 (1)).

PPG sensors can be very sensitive to finger pressure. In other words, if the user grips the device, the resulting finger pressure may prevent the device from collecting accurate pulse information. At any time, if the user applies too much pressure, the device may display an error message informing the user to stop squeezing the device and relax the finger (FIG. 25). As soon as the user relaxes his finger, he can pay attention to the pulse display screen again.

When the device identifies a new RSA wave, the wave information can be used to determine and display one or more of the following: the frequency of the last wave, the average pulse of all pulse points in the wave, session score, remaining session time, and stress Index-How severe mental stress the user is currently experiencing.

The device may update the session countdown clock after all RSA waves have been identified. The devices may include a session countdown clock indicating a decrease periodically (eg, once per second, once every 15 seconds, etc.). In such embodiments, the device may be updated after each RSA wave to prevent involuntary association between the clock and the desired action. In other words, if the clock counts down every second, the user can use the seconds as a guide to breathing consciously or unconsciously at six breaths per minute. Such association can prevent the user from unknowingly learning to breathe six times per minute when under stress. If the user uses the clock consciously (or even unconsciously), they will always depend on the device. However, by updating the clock every wave, such a potential situation can be avoided, and the block can reinforce this learning. The user can see the exact seconds of each breath by the amount the clock represents a decrease. If the clock shows a slower slowdown (eg every 30 seconds), the possibility of involuntary association between time and unwanted action will be avoided. However, in such alternative implementations, the clock will not enhance the learning.

In exemplary embodiments, once the first wave is identified and data is displayed, the session countdown timer will begin to show a decrease (FIG. 26). However, other embodiments may be used when the user starts to breathe regularly, or when a good wave (eg, waves with a frequency less than 6) is achieved, or while the user is practicing regular breathing. You can start to decrease. Another alternative is that the breath button is being used and the counter does not show a decrease when guidance is provided.

Users can change the behavior of the wave and thus the calculated stress level by changing the breathing pattern. As the user lowers his breathing rate, the wavelengths increase and the amplitudes of the wavelengths also increase (FIG. 27). As the user breathes deeper, the amplitude of the wave becomes even larger (Figure 28). If the user breathes regularly at a constant rate, the wavelength entrains the cycle of breathing rate (FIG. 29).

To begin mitigation, a user may begin to exhale deeply and slowly to vent air and extend inhalation. This will result in longer wavelengths and reduced wave frequencies. The user will continue to breathe deeper and breathe more slowly until the wave frequency drops to about 6 (FIG. 30). If the wave frequency drops below 6, the user can breathe a bit faster-that is, not breathing out the next time.

In certain embodiments, once the user reduces the wave frequency to about 6, the user will continue to breathe at the same speed and rhythm that produces a frequency of about 6. If the user's respiratory rate increases, the frequency will increase, indicating that the next breath should have a longer exhalation. If the user's breathing rate becomes excessively slow, the frequency will drop below about 6, indicating that the exhalation of the next breath should be slightly faster. By paying attention to the number of wave frequencies, the user will quickly fill the screen with regular waves of about 10 seconds in length corresponding to the frequency of about 6 breath cycles per minute (FIG. 31).

The session score will be calculated and displayed after each RSA wave is identified. The score may be based on how close the user is to achieving the desired action. The user can accumulate score points, and various methods for scoring a session can be used. In certain embodiments, if the wave has a frequency of less than six, the user may accommodate three points, for example. The user can accept two points for wave frequencies of 7 or 8, one point for wave frequencies of 9 or 10, but not points for frequencies greater than 10. The accumulated session scores can be displayed numerically. Alternatively, each individual score can be displayed. Another alternative is to display the current score (either numerically or graphically) along one side of the previous set of scores. Certain preferred embodiments are graphical display of the current score and the set of previous scores (FIG. 32). In this way, the user can be notified when the user is breathing regularly. When the score display is constant, the user is breathing regularly.

When the user fills the screen with regular waves, the user can focus on deeper and more complete exhalations. That is, a user may attempt to inhale and exhale a greater amount of air (called a "tidal volume"). As the user slowly increases the depth of breathing, the magnitude of the wave will increase (FIG. 33). The user can continue to fill the screen with large waves with a wavelength of about 10 seconds each until the session timer runs out. The user will then know that a very deep relaxation has been achieved.

In certain embodiments, if the user has difficulty breathing deep and regular at about 6 breaths per minute, the user may be guided by activating the breath guide function (FIG. 34). In such embodiments, as soon as the user presses the breathing button, the breathing guide may be shown on the display. The user may be instructed to inhale to raise the breathing bar (FIG. 35A) and to inhale to lower (35b) the breathing bar. In exemplary embodiments, the breathing guide aligns the user's breathing with 6 breaths per minute, for example with a 1: 2 inspiration to exhalation ratio. In alternative embodiments, the breathing guide may be programmed to provide another ratio (eg, 1: 3) at about 6 breaths per minute (eg, 4-8 / minute). The breathing guide may remain active for about 1 minute, for example, and then close automatically. With a temporary breathing guide rather than a constant, the user is encouraged to use a biofeedback protocol to achieve a breathing pattern of about 6 breaths per minute. If the user relies solely on the breathing guide, it may be more difficult to learn how to achieve his or her own pattern. Thus, by separating the user from the breathing guide, the user can use biomagnetic control for unconscious learning. Alternative embodiments allow users to turn off the breathing pattern after an hour period occurs. Other respiratory rates and rhythms can also be used.

The devices according to the invention can show a regular display to the user after the breathing guide is completed. The user can then adjust breathing in the manner previously described to increase the magnitude of the wave by decreasing the wave frequency to about 6, maintaining regular breathing, and breathing deeper. The user can continue this process until the session timer reaches 0:00, where the session summary screen can be displayed (Figure 36).

Example embodiments also include devices that allow the user to use the up / down arrows to select the number of large waves that the user wishes to process during the session. For example, the user may choose to generate ten large waves during the session. The credit area may increase or decrease to accommodate the selected number of session waves.

The devices according to the invention can identify individual RSA waves continuously one at a time. If a new wave is identified, the wave may be categorized as, for example, "small", "medium" or "large". If the wave is small, a single dot can be displayed, for example to display it as a small wave. If the wave is of medium size, two dots may be displayed, for example to display it as a medium size wave. If the wave is large, three dots can be displayed, for example to display it as a large wave. The user may be given one credit in the credit area each time a large wave is identified, and may be given a half credit in the credit area each time a medium size wave is identified. Of course, as long as information regarding the nature of the waves that the user generates is provided, other values may be assigned for waves of different magnitudes.

In certain example embodiments, at the start of the bump of each wave, an acoustic beep may indicate the magnitude of previous waves. If the previous wave was small, for example, a high pitch alarm could be generated. If the previous wave was medium in size, a pitch of, for example, a mid-level pitch may be produced. Otherwise, low pitch tones can be produced, for example. The sound can be controlled by a switch such as the "(O)" button. Such a button can, for example, switch the sound from a small sound, a loud sound and a silent sound. The breathing feature may temporarily activate the breathing metronome to show the user how the user can breathe to produce a large wave.

In some embodiments, if the user accumulates enough credit points, the session is considered completed and a session summary screen may be displayed. In addition, new tracking entries may be added to the tracking system.

In certain embodiments of the invention disclosed below, the biomagnetic control credit is based on achieving two equally important objectives: high levels of parasympathetic nerve intensity and consistent parasympathetic nerve outflow. The present invention can detect each wave of parasympathetic nerve activity in real time. When a new wave is completed, the device can evaluate both the continuity and the intensity of the parasympathetic output that generated the wave. As shown in FIG. 37, if the wave was generated by a continuous level of moderately strong parasympathetic activity, for example, two dot symbols (FIG. 37A) may be located below the wave. If the wave was generated by successive, very strong levels of parasympathetic activity, for example, three dot symbols (FIG. 37B) can be placed below the wave. If the wave is interrupted and / or interrupted or weak, for example, one dot symbol (FIG. 37C) may be located below the wave. Two side-by-side squares may represent an uneven wave (FIG. 37D). These symbols may reflect the activity of the human parasympathetic nervous system (stress recovery system) when the waves are very active (long wavelength), active (medium wavelength), inactive (short wavelength) and interrupted (uneven wavelength). . Such indications may be displayed in real time and may provide information on the wavelengths immediately preceding the last multiple (FIG. 37E). For example, the display may show the last 20 waves or a much larger or very small number of indications. Exemplary embodiments may also summon and display waves from very previous or from previous sessions in a very early breathing session.

The display may also show the cumulative total score for a certain time (eg, 24 hours) (FIG. 37F). The accumulated overall score can be generated, for example, by assigning a single point for long wavelengths, assigning half points for intermediate wavelengths, and assigning no points for short wavelengths. The display may continue to update the accumulated total score, for example, until a predetermined point has been reached, when a predetermined time period has elapsed, or until the accumulated total score is reset. The patient may attempt to achieve a goal, for example, reaching 100 points per day.

Certain preferred embodiments of the present invention may also provide novel forms of biomagnetic control information that can be used to induce a desired physiological state through inherent breathing exercises. Such embodiments avoid the disadvantages of the technique of generating one or more interrupts of the parasympathetic branch every breath. For example, such breathing techniques involve prolonging exhalation for a very long time. In general, longer exhalations are beneficial, but when they are extended over a long period of time, long exhalations can interrupt the parasympathetic response immediately after the goal of the wave. Waiting for an exhalation for an excessively long time can cause an interruption just prior to the uplift of the wave. Similarly, holding your breath for too long or exhaling too long or too short may, for example, strain the parasympathetic nervous system, respectively, causing temporary inhalation of the parasympathetic outflow.

Embodiments of the present invention overcome the drawbacks disclosed above, for example, by guiding a user to discover a rhythm and respiratory rate that produces a consistent level of consistent parasympathetic outflow. The feedback provided by the methods and apparatuses in accordance with the present invention allows the user to maintain a substantially persistent state of parasympathetic outflow, thereby inhibiting parasympathetic nerve activity.

Preferred embodiments of the present invention may also inform the user that the RSA wave is transitioning from the elevation to the descent. Such dropping points can be identified, for example, by marking such points with markers that are readily visible to the user. Such visual indicators can be in the form of a triangle, for example (FIG. 37A). Visual indicators may also be in other forms. The descent point is the ideal time to start an extended exhalation. The indicators may alternatively be acoustic.

By mixing the feedback of the dropping point and the synthetic parasympathetic measurements, the user can quickly learn to extend the exhalation to a length suitable to produce the highest scoring waves (eg three dot waves). The user may also receive guidance to indicate when the exhale extends too long, and the wave will hinder the induction of low scoring waves (eg, one dot wave). Thus, methods and apparatuses in accordance with certain embodiments of the present invention enable a user to discover a unique window of exhalation length that creates a persistent outflow of concentrated parasympathetic nerve activity. In use, the user simply exhales every time a new indicator appears, such as a visually displayed triangle, and inhales until the next indicator appears. By adjusting the length of the exhalation, the user learns to generate perfect waves that appear during the physiological state of continuous concentrated parasympathetic nerve activity.

In another example embodiment, the display may provide Exhale Numbers that correspond to numbers that the user can count during the expiration. Once the breathing session has begun, the patient may breathe, for example, until a descent point appears and exhale while counting (preferably quietly) to the Exhale Number. The timer bar may descend in the Exhale Number column for a fixed time (eg, 30 seconds, 60 seconds, etc.). The Exhale Number column may display, for example, a score of 1 to 9 corresponding to the effectiveness of the patient's breathing in the Exhale Number for a fixed length of time. Longer waves show more effective breathing than shorter waves, which can accommodate higher scores. The score may be based on a single wave from all waves, or a subset of waves. The display may also allow for the selection of alternative Exhale Numbers that allows the patient to experiment with different Exhale Numbers to find one or more that provide the best score. As discussed above, in the exemplary embodiment, the best scores are generated by the longest wave.

In feature embodiments, compact portable devices according to the present invention can be used as follows: the patient turns on the device by pressing the power button; When the patient is encouraged, for example, to insert his forefinger into the pulse detection unit of the device; The sensor is set to the user's pulse rate while the patient is resting (eg, the patient is sitting upright with the foot parallel to the floor); The patient selects a wave number of large waves (eg, 5 to 100 depending on the level of stress perceived by the patient); Observe the pulse rate pulse on the display of the device as the patient breathes at a natural and effortless rate; While breathing slowly and deeply, preferably with the nose, the patient can observe the affect of the frequency on the breathing depth and the wave pattern; The patient produces long waves by very slow exhalation for about twice the inhalation period; Long waves are recorded on the device's display, non-long waves are not recorded; Initiating people can press the breath button on the device to help pace the patient to produce long waves (e.g., a pacer may appear for a certain number of breaths that are recorded or not recorded). Can be); The intermediate user can see the descent indicator on the monitor, exhale at the descent point, and inhale during the rise of the next wave; Advanced users can press the sound button, use the device with their eyes closed, exhale whenever the device produces a specific sound at the descent point, and the pitch of the sound indicates whether the previous wave is credited and added to the recording. Can be further represented.

Multiple aspects of the invention may be combined to create a number of alternative exemplary embodiments. For example, the device may feature a meter that can be used as an amplitude feedback meter rather than a stress meter. The meter may further have a target bar. Thus, the device can graphically display how deep the user is breathing, so that the user can learn to breathe deeper. If a target bar is used, users may attempt to breathe deeply with each breath to cause the meter to rise above the target bar. Any numeric or graphical feedback (either visual or otherwise) of amplitude may be within the scope of this alternative embodiment.

Other alternative embodiments may use pulse information (e.g. , Wavelength, amplitude, and peak placement) can be used. Alternatively, the user may be provided with a breathing guide that provides simultaneous auditory or visual feedback as to how closely following the guided breathing pattern. In addition, a target level may be displayed such that the user is considered compliant if the user is above the target level, and not complying with the respiration protocol if the user is below the level.

Alternative embodiments may also use changes in one or more wave parameters to detect regular breathing. The degree of regular breathing can be displayed numerically, graphically, or otherwise visually. Optionally, acoustic feedback may be provided. For example, in an exemplary embodiment, the pitch may be higher as the breath is irregular, and the pitch may be lower as the breath is regular. Alternatively, a single alert may indicate regular breathing, a double alert may indicate close to regular breathing, and a triple alert may indicate irregular breathing. In principle, any of the previously mentioned feedback techniques or derivatives of these techniques may be used independently in combination with each other, in combination with other techniques, or in combination with each other and with other techniques. Such practice can be used, for example, to practice regular breathing patterns in yoga style. For example, if a yoga learner practices regular breathing at a 1: 1: 1 inhale: exhale: exhale ratio, the user can use the device to ensure that regular breathing is maintained.

In other embodiments of the present invention, a preprogrammed breathing guide may be provided on the device such that the user may follow the breathing guide while receiving visual and / or audio feedback about the regularity of his breathing. In addition, the breathing guide may be programmable. Optionally, feedback may be provided to the respiratory rate as well as to the regularity of breathing. For example, if a user wishes to practice breathing in a 1: 1: 1 analogy with five breaths per minute, visual and / or auditory feedback may indicate the extent to which the user is breathing regularly five times per minute. Breathing at different frequencies and / or irregular breathing will reduce the score.

Another exemplary embodiment provides feedback on the depth of breathing. During regular breathing, the main tidal volume (depth of breathing) at wave amplitude, a phenomenon that is measurable using the methods described above. Thus, amplitude measurements can be used for visual and / or audio feedback to indicate the depth of breath of a user. As mentioned above, deep breathing is a useful way to relieve stress. Exemplary embodiments may provide feedback about the depth of the user's breathing to help teach the user how to breathe deeply and relieve stress.

In sum, exemplary embodiments of the present invention may provide auditory and / or visual feedback for: breathing rate, regularity of breathing, depth of breathing, matching of breathing to a defined rate / rhythm, elevation Transition points from to descent (eg, descent point), and the like. Evaluation can be made for each of these alone or in any combination. Feedback may be provided to one or more such assessments. Any implementation of identifying two or more RSA waves and deriving velocity, rhythm, depth and / or coincidence is within the scope of the present invention.

Exemplary form Factors

Exemplary embodiments of the present invention incorporate multiple features in addition to those disclosed above. One such feature is the device shape design factor. Prior to the present invention, the biomagnetic control program used finger PPG sensors, ear PPG sensors and / or heart rate ECG sensors attached to a computer via a wire. Although PPG sensors are sensitive to movement and finger pressure, conventional devices often used finger PPG sensors located on a table or desk, so they did not have to deal with many of the artificial consequences generated by movement or excessive pressure. In this situation, users could place their hands and fingers on the desk to hold their hands and fingers, preventing excessive movement and finger pressure.

Since external wires are generally not socially (and otherwise) approved, exemplary embodiments of the present invention have integrated external PPG sensors into movable devices to eliminate external wires. As a result, devices in accordance with exemplary embodiments of the present invention can be used comfortably in a public environment. However, integrating PPG sensors in portable devices requires innovative form factor. For example, because the session time may range from 5 to 15 minutes, device users will hold the device without a stabilizing structure such as a desk for an extended period of time. Thus, the present invention provides a device that can be comfortably gripped while at the same time allowing the user to comfortably place a finger on the finger sensor.

The invention also provides formation factors that provide comfort while minimizing the artificial consequences caused by movement and pressure over an extended period of time (eg, 10-15 minutes). Two exemplary form factors accomplish this purpose. Firstly, a finger sensor may be present on top of the device near one of the edges. Ergonomically, the height from the bottom to the top of the device can be between about 1.5 inches and about 3.5 inches, preferably about 2.5 inches. This allows the device to be supported by the thumb when held vertically, or by a bent finger when tilted. Secondly, the finger sensor is located on the rounded back of the device with the display in front, allowing the device to be placed in the palm, for example during use (FIG. 38). A particularly preferred form factor is the first disclosed form factor above, which allows the design of a product with a scientific and medical look and feel.

Error detection and correction method

The present invention also provides a method of detecting and correcting errors in the devices disclosed above and devices using such methods. While any of the disclosed shape factors minimizes artificial results, the hardware shape factors may not eliminate all possible artificial results. Since there is no support structure such as a table or desk, the hands and fingers will move at different times throughout the session. The remaining artificial results can be processed by the software of the exemplary embodiments of the present invention which not only detects when an error occurs but also corrects it.

In general, displays on small portable devices are more susceptible to errors because they are very small, for example compared to the display of a desktop computer. When an error occurs on a desktop computer, the display has sufficient resolution to indicate the correct data and errors (Figure 39A). However, on small portable devices, one error can make it difficult to identify all the correct data due to its low resolution (Figure 39B).

Many statistical methods for detecting errors in data streams already exist in the art. However, these methods require large data sampling before providing high accuracy. As mentioned above, devices with small displays can be adversely affected even by a single error. Therefore, errors must be detected and corrected quickly and accurately. Devices according to an exemplary embodiment of the present invention implement a novel error detection and correction method that requires only a small amount of data (approximately 10 seconds) before it becomes very accurate.

In order to facilitate a better understanding of the error detection and correction method of the present invention, a brief description is provided of how the PPG sensors are used to obtain pulse information with no ideal error. PPG sensors continuously detect the amount of blood pressure in the finger. Each time the heart beats, the pulse of the corresponding blood causes a rapid increase in blood pressure at the finger and then calms down quickly. The PPG sensor continues to search to identify when blood pressure reaches its peak (FIG. 40). This is the pulse peak. As discussed previously, the amount of time (in milliseconds) between two consecutive pulse peaks is called the pp interval (pp). The devices according to the invention can record each successive pp interval. The pulse rate (60,000 / pp) of each recorded pp interval can be displayed on the screen each time a new pulse peak occurs. The complete time difference between successive pp intervals (absolute (pp [n] -pp [n-1])) is called interbeat interval time or IBI.

Two types of errors occur when the PPG sensor attempts to correctly identify the next pulse peak (FIG. 41). One type of error can occur when the PPG sensor incorrectly identifies an artificial result as a pulse peak. That is, the PPG sensor judges that a pulse peak occurs in a place where it does not actually exist (FIG. 41A). This type of error is called a false positive error. The second type of error occurs when the PPG sensor does not identify an existing pulse peak (FIG. 41B). This is called a false negative error. False negatives and false positives result in large IBIs. Error free data may or may not result in large IBIs. However, incorrect data always produces a large IBI. Thus, there is an extended amount of continuity data that does not include large IBIs, and the user can safely evaluate that this data is error free. If large IBIs occur, it may be due to an error, or IBIs may be good data; The device needs to determine what the case is.

According to preferred exemplary embodiments of the present invention, the first step of the error detection policy is to wait for a certain number of heart rate related intervals (eg 10 pp intervals) where all IBI times are less than 200 nm. These data points are considered to be error free. The number of consecutive intervals may be less than 10, but needs to be at least 2, preferably at least 3, more preferably at least 5. Another alternative is to wait for a set of consecutive data points where all IBI times in the continuous data set are less than one third of the lowest heart rate related interval, such as the pp interval (eg, five consecutive pp intervals). The range of these data points can be calculated. As used herein, “range” is a complete range (ie, minimum pp to maximum pp), derived range (eg, (minimum pp-10%)-(maximum pp + 10%)), or calculation Reference deviation (eg, mean deviation, standard deviation, etc.). Any suitable mathematical technique for the range can be used. Preferred embodiments according to the invention use minimum pp-((maximum pp-minimum pp) × 25%) as the bottom of the range. The preferred embodiment uses max pp + ((max pp min min) x 25%) as the top of the range. The range can be derived from the entire data set or a subset of the data set.

Once the range is defined, each new p-p is tested to determine if it is "in range." In exemplary embodiments, if the new pp value is greater than the lower value and less than the upper value, it is considered to be "in range." However, “in range” may also refer to any mathematical judgment of the close proximity of the current p-p to the range as determined by the selected range calculation. For example, if the wave is calculated using the standard deviation, “in range” may refer to a statistical judgment of whether the current p-p has a 80% or more likelihood of being within the calculated deviation.

As a new pp interval arrives, a new IBI can also be calculated (complete new pp-old pp). The new IBI can be tested to determine if it is "big". In preferred embodiments, the device tests if the IBI is greater than half of the lower value of the range. If larger, the IBI is considered large. In other example embodiments, the interval before subtracting the IBI time of the new pp interval may be calculated. Compared to the average p-p of the last n pp intervals, other IBI times, such as the IBI of the new p-p, may be used instead. Also, different implementations may use different thresholds to distinguish large IBIs from less large IBIs. According to embodiments of the present invention, any implementation that uses a difference (such as a mean) or a difference of pp intervals of the pp intervals may be used to detect an error.

To summarize the above disclosure, when the apparatus according to exemplary embodiments of the present invention starts, the apparatus may not enter the error detection mode until ten consecutive pp intervals are located where all the IBI times are less than 200 nm. . The device can then calculate the range of these pp intervals and enter the error detection mode. In the error detection mode, the device can test each new pp to determine if it is "in range," and test each new IBI to determine if it is "in range." Any other suitable method of determining one or both of these two properties for use in error detection is within the scope of the present invention.

If the next p-p is "in range" and the IBI is not "large", then the new p-p may be considered to be error free. If p-p is not "in range" and IBI is not "big", then the new p-p may be considered error free and the range is recalculated to include the newly found pp value. The new p-p is "in range", but if the IBI is "large", the new p-p may be considered error free. However, if the new p-p is "out of range" and the IBI is "large", then the new p-p may be considered to be the result of the error. If an error is detected, the error must be corrected. Therefore, each time an error is detected in the error detection mode, the device changes to the error correction mode. The device may remain in error correction mode until the fault condition is resolved.

42 provides a flow chart showing an exemplary error correction methodology used during error correction mode. Error correction involves combining each successive pp interval together as identified until the sum of the pp intervals is "in range" or until the sum is divided by an integer, so that the result of the division is "in range." When the sum is "in range," all pp intervals forming the sum may be combined together into a single value equal to the sum. When the sum divided by integer is in range, the wrong values can be replaced by the number n (n = integer denominator) of the same values as the result of the division.

The following discussion provides examples of how errors can be corrected in accordance with an exemplary embodiment of the present invention. For example, if the range is 600ms-1,000ms, the wrong pp interval time is 200ms. The next pp interval is 100ms. The sum is now 300ms. It is not "in range." The next pp interval is 400ms. So the sum is now 700ms. It is "in range" and therefore 700 ms is a calibrated value. The three pp intervals (200 ms, 100 ms and 400 ms) will be combined into one value of 700 ms. The device then returns to the error detection mode.

As another example, if the range is 700 ms-1,000 ms, the wrong pp interval is 1,300 ms. There is no integer that can divide 1,300 ms into a value that will result in a "in range" value. Thus, the next pp interval (300 ms) is added together to produce 1,600 ms. At that time, there is an integer that can be used for partitioning to produce a "in range" value. The integer 2 results in a value "in range" (1600/2 = 800 ms). Thus, two incorrect values (1,300 ms and 300 ms) will be replaced by two (integer) values of 800 ms (result of division).

In exemplary embodiments, the apparatuses according to the present invention may generate corrected values within one or two additional pp intervals. However, it is possible for the device to enter the error correction mode indefinitely. Thus, the present invention may include a security mechanism to solve this situation if it must occur. For example, if the device remains in error correction mode too long, the device recalculates the range by applying a statistical method to all the original data points generated. That is, all raw pp intervals received from the PPG sensor are used. The range can be calculated with a statistical based range calculation, eg, a standard deviation formula. In exemplary embodiments, the median pp interval is determined from all unprocessed pp intervals generated (authenticated or incorrect). The range is defined to range from 15 bits per minute below the median to 15 bits per minute above the median. The pp intervals of the error queue are reprocessed according to the new range. Note that the range can also be calculated with a subset of raw data points (eg, the last 50 data points). The present invention may also include any range recalculation method for resolving extended error conditions.

As previously disclosed, PPG sensors are sensitive to finger pressure and movement. PPG sensors are also sensitive to bright light and cold fingers. Thus, there are many factors that can cause a number of errors. In certain embodiments of the present invention, whenever the signal-to-noise ratio for 10 seconds drops below 25%, the device may return error messages (as shown in FIG. 18) until the device exits the error correction mode. You can cycle the display of. Thus, the user will be provided with information and changes can be made to assist the device in collecting accurate pulse information.

The present invention also provides alternative methods for detecting and correcting errors in the heart rate interval data set. For example, there are a number of implementations that may allow range and / or IBI thresholds to change dynamically as new heart rate values are detected. Such implementations may provide a marginal increase in accuracy in certain circumstances.

For example, the range can be continuously evaluated using a rolling window. The range may begin after receiving the first 10 seconds of pp intervals such that each successive IBI is less than 200 ms. After this point, the range can be continuously reevaluated using the rolling window of the last 10 seconds of reliable data. The last 10 seconds of reliable data can be continuous or discontinuous. For example, the top of the range r_top may be the highest p-p in the last 10 seconds of reliable data, and the bottom of the range r_bottom may be the lowest p-p in the last 10 seconds of reliable data.

Another alternative is to lower the rate at which the range can dynamically expand and contract. For example, each time a new pp value is detected, the range can be updated in three steps. First, the data set top (ds_top) and the data set bottom (ds_botoom) are identified from the last 10 seconds of reliable data. Secondly, ds_top and ds_bottom are adjusted in such a way that they do not change significantly from the previous ds_top (p_ds_top) and the previous ds_bottom (p_ds_bottom). For example, if p_ds_top is greater than ds_top, ds_top may be reset to p_ds_top-((p_ds_top-ds_top) / 25 + 1)). If p_ds_top is smaller than ds_top, ds_top may be reset to p_ds_top + ((ds_top-p_ds_top) / 4 + 1). If p_ds_bottom is greater than ds_bottom, ds_bottom may be reset to p_ds_bottom-(p_ds_bottom-ds_bottom) / 2 + 1). If p_ds_bottom is smaller than ds_bottom, ds_bottom may be reset to ((ds_bottom-p_ds_bottom) / 25 + 1). Thus, r_top will be equal to the adjusted ds_top and r_bottom will be equal to the adjusted ds_bottom. If p-p is between r_bottom and r_top, it will be considered to be "in range."

The methodology disclosed above can achieve three purposes. First, the range is dynamically increased and decreased. Second, the range can expand faster than it contracts. Third, the bottom of the range can expand faster than the top of the range. There are a number of ways to implement these methods, and any implementation that achieves any of these three purposes may be devised within the scope of the present invention.

Yet another alternative includes converting the calculated pp range into a range of pulse rate values and comparing each newly detected prv (60,000 / pp) with the pulse rate range. "In range" can be determined by whether the new prv is less than the maximum prv (max_prv) and greater than the minimum prv (min_prv). Or “in range” may refer to whether the new prv is close enough to the range of prv values. For example, the range top and range bottom can be extended by a predetermined number of bits (eg max_prv = max_prv + 9 and min_prv = min_prv-9). Thus, any new prv that is within 9 bpm of the data set range may be considered to be "in range."

Due to the pp range, the prv range calculation can also be dynamic. That is, when a new prv arrives, the range is recalculated if the new prv is considered reliable (ie, the IBI is not excessively large).

Another way to increase the error detection capability is to use two threshold values to determine how close the new IBI is from the previous IBI. For example, if the new IBI is below the low threshold, it may be considered a "small jump." If the new IBI is between two thresholds, it can be considered a "significant jump." And if the new IBI is higher than the second threshold, it can be considered a "big jump." Thus, as new values come in, they can be evaluated whether the new values are "in range" or "out of range," and whether the new IBI is a small jump, a significant jump, or a large jump. The determination of whether to display the value, use the value to update the range, and / or correct the value may be based on such evaluation.

Any heart rate related interval can be used to determine the importance of the IBI levels. For example, the interval between beats of two prv (prv IBI) can be used when evaluating the proximity of the new pulse value to the previous pulse value. Thus, IBIs can be calculated and evaluated for pp intervals, prv values, rr intervals, hr values, and the like.

Another alternative includes using the direction of the IBI change to determine if the jump is small, salient or large. When the user is physically stationary, the pulse rate may rise or fall at different speeds. Thus, different thresholds can be used depending on the direction of change. For example, a prv IBI larger than the previous prv IBI can be considered a small jump if less than 8 bpm, a significant jump if it is between 8 and 15 bpm, and a large jump if greater than 15 bpm. . A prv IBI smaller than the previous prv IBI may be considered a small jump if less than 8 bpm, a significant jump if between 8 and 12 bpm, and a large jump if greater than 12 bpm.

Another exemplary embodiment includes a prv IBI based on the position of the previous prv in the range. If the previous prv is already towards the top of the range, the threshold can be set smaller because in theory the user would not want the next prv to jump too far in the range. Similarly, if the previous prv is already towards the bottom of the range, the prv threshold for jump down can be reduced. Thus, examples of prv IBI thresholds based on the position of the previous prv in the range may include: ((r_top-prev_prv) (1/3) + 10 for small jump ups, to large jump ups) For ((r_top-prev_pr) (2/3)) + 15, ((prev_prv-r_bottom) (1/2) + 10 for small jumpdown, ((prev_prv-r_bottom) × (2 / 3) + 15.

Another exemplary embodiment is to add a third test, such as the direction when determining whether a new heart rate interval needs to be corrected. For example, if a point fails the IBI and range test, but is closer to range than the previous heartbeat interval point, it can still be considered acceptable.

In certain circumstances and implementations, an improvement in the limit may be achieved by combining a dynamic range method, a dual IBI threshold method using a different threshold based on direction and a heart rate interval direction method. Examples of such combinations are as follows. As each new prv is calculated (60,000 / pp), firstly it can be evaluated whether the new prv is 'immediately displayable', if prv is a small jump up or a small jump down (using appropriate thresholds), prv is immediately displayable and is displayed immediately If the prv is a significant jump but is "in range," it is immediately displayable, i.e. it can be reevaluated by orientation to see if it is displayable. If the current prv is closer to the range than the previous prv, the current prv is still displayed, otherwise the current prv is not displayed and must be corrected.

Combinations of the above disclosed methods can also be used to determine if the value is 'highly reliable' or not. That is, these methods can be used to determine if a new prv should be used to recalculate the dynamic range. For example, if the new prv is a small jump, it can be considered 'reliable'. If the new prv is a significant jump or 'in range', the new prv can be considered 'reliable'. If a new prv is a significant jump and 'out of range' but closer to the range than the previous prv, the new prv can be considered 'reliable'.

In determining which method to use to detect and correct errors in the data set, the user can use hardware to determine if the degree of potential statistical advantage of complex combination methods provides better practical use of the underlying IBI / range methodology. Consideration should be given to stability, the environment of use and other factors. In most cases, the default IBI / scope policy is quite satisfactory. However, if significant motion, sunlight, pressure and similar factors are expected to be present, the additional statistical methodology disclosed above may be implemented to provide better accuracy of detection and correction of errors in the data set.

Solve scaling problems and identify regular breathing

The disclosed methods and apparatuses can also use RSA wave information to innovatively scale the area of the display where the wave is seen.

The amplitude of the RSA waves can vary significantly from person to person. As disclosed above, the RSA amplitude depends on the individual's age, gender, fitness level, breathing pattern, and the like. Large display screens can accommodate large waves or small waves, while small display screens on portable devices require very complex scaling. Thus, if the scale on the small display is excessively small, the large waves will not fit on the display. If the scale is too large, the shape and size of the small waves will be difficult to discern. If the scale is excessively dynamic and adjusted too often, the large waves and small waves will appear at the same magnitude, and the user will not be able to discern whether or not his breathing pattern is changing.

Devices in accordance with exemplary embodiments of the present invention may solve the scaling problem by adjusting the display scaling differently during two steps. The first stage continues from the time the device is powered up until the user starts to breathe regularly. The second stage continues from the time when the device detects regular breathing until the device is turned off. During phase 1, a very basic scaling technique can be implemented. During Phase 2, an innovative approach can be used, allowing the user to accurately assess when his breathing should be shallower (less deep).

For example, when the device is first turned on, the scaling is preferably zoomed in to a predetermined small value. The device then zooms out at any time if the pulse point is lower than the lowest value and greater than the highest value that can be written using the current zoom level. The scale is zoomed out so that a new pulse point is written to the edge of the device display area. To give the user an idea of scaling, the device zooms out, not zoomed in at startup. The display also zooms back in after large waves are present on the screen, so that the entire length of the display is used from top to bottom. The display continues to zoom in and out so that the data points shown always consume the entire area of the display until the user starts regular breathing.

Once the user begins to breathe regularly, the device attempts to encourage the user to breathe deeply. If the device continues to zoom in automatically when small waves appear, the small waves produced by shallow breathing will be the same size as the large waves produced by deep breathing. This will not allow the user to visually identify their breathing depth from the magnitude of the wave.

Devices in accordance with exemplary embodiments of the present invention use wave information to detect regular breathing. Regular breaths produce waves with uniform wavelengths, frequencies, amplitudes, peak to peak times and peak placement times (FIG. 43). Regular breathing can be identified by measuring changes in one or more such wave feature parameters. Exemplary embodiments calculate the change in amplitude and wavelengths of the last three waves. If all of these changes are low, regular breathing is considered initiated.

One way to determine change and establish when the change is small can be based on percent related deviations. The present invention is useful when comparing changes in two or more values (eg, peak-to-peak times, wavelengths, frequencies, etc.). This can be done as described below. First, the middle (average) of the values can be determined. Then, the sum sum_dif of the differences of each value from the mean can be calculated. The sum can be divided by the average x number of values. For example, consider four wavelengths of 10, 8, 10, and 8 seconds. The average is nine. The sum of the differences from the mean is 4 (10 differs by 1, 8 differs by 1, 10 differs by 1, and 8 differs by 1). Thus, 4 is divided by the average × number of values (4 / (9 × 4)). The percent related mean deviation is 11.1%. Consider four amplitudes of 30, 28, 30, and 28. The deviation is 4 as in the previous example, but the percent related mean deviation is only 3.4%. Thus, the percent related mean deviation automatically scales itself to the range of analyzed values.

Changes in any of the wave features can be analyzed alone or in combination using multiple methods. Preferred embodiments use percent related mean deviations. The larger the resulting percentage, the greater the change. The change threshold may be set to determine if regular breathing has begun. For example, if three or more waves have a change in wave feature of less than 20%, the user can conclude that regular breathing has begun. In a preferred embodiment, regular breathing is considered to begin when the changes in amplitude and wavelength of the last three waves are each less than 10%.

Once regular breathing begins, the device can continue to track the largest amplitude (maximum amplitude) formed by the resulting regular waves. The device continues to determine, for example, whether the user is still breathing regularly with every respective wave. As long as the user continues to breathe regularly, the device will continue to find the largest amplitude (maximum amplitude). If the newly formed regular wave has an amplitude higher than the current maximum amplitude, the maximum amplitude can be readjusted to be equal to the new amplitude. In general, the display does not zoom in more than the maximum amplitude. In other words, the display scale can be set such that waves with an amplitude equal to the maximum amplitude completely consume the screen from top to bottom. The zoom level can be set not to exceed this set point. As a result, the device may zoom out, but not zoom in beyond the predetermined set point by the maximum amplitude. In this way, the user will notice when he breathes shallowly because he will see relatively small waves on the screen (against the maximum amplitude).

Sometimes the wrong wave (wave with incorrectly reconstructed corrected errors) can have the largest amplitude. This large amplitude can be high enough to be out of order. In addition, the user's greatest possible amplitude may deteriorate over time until their lungs are used for regular breathing. That is, as their lungs wear out, the user will be able to reproduce the waves with amplitudes equal to the maximum amplitude. Since the device should not frustrate the user and should encourage the user to generate the largest wave as comfortable as possible, the device will not be able to time the maximum amplitude value unless a series of waves are approaching close enough to the maximum amplitude. It can be reduced with this sense. In preferred embodiments, if the three continuity regular waves have an amplitude less than 80% of the maximum amplitude, the maximum amplitude can be readjusted using the following formula: (largest amplitude of the last three waves) × ( 100/85). Another alternative is to continue decreasing the maximum amplitude until the waves are close enough to occupy the display from top to bottom. For example, the maximum amplitude may indicate a decrease in the maximum amplitude by 5% each time a newly formed regular wave has an amplitude less than 80% of the current maximum amplitude. Another way to use amplitude may be to take the highest average amplitude. For example, the average amplitude of the last three waves can be calculated each time a new wave is generated. The highest average amplitude can be used as the minimum set point.

The use of high amplitudes resulting from regular breathing to establish set points is a novel and useful component of the disclosed invention. Any scaling based on amplitude, range, change or deviation is contemplated within the scope of the present invention. For example, the standard deviation of a data set or subset of data can be determined. The maximum zoom level can be set such that values with a particular likelihood of deviation consume the screen. For example, all values with an 80% chance of being within the standard deviation will fill the screen from top to bottom.

Additional Example System and Software Processes

The methods and apparatus disclosed above may be executed as a process stored in a memory of a data processing apparatus such as, for example, a computer. Such a process may be in the form of software, for example, and may include, for example, the results displayed on a display such as a data processor or CPU and, for example, a CTR, plasma or other computer display known in the art. Can be executed by Thus, for example, such software can be executed on a system that includes a CPU, a memory and a display connected by one or more buses or data paths. 44 illustrates such an example system.

In this regard, an I / O or input / output interface 5501, a CPU 5505, and a memory 5510 are provided. The three components of the example system are communicatively connected via a system bus 5520. As noted, system bus 5520 is a logical component and, in any given embodiment, may include a plurality of interconnects between system elements. In such example systems, a software process may be loaded into memory 5510 and executed in CPU 5505. In addition, the user may provide input to the process via I / O 5501 and may provide output to the user by visual, audio, tactile or other means that may also be provided to the user using I / O. can do. Such I / O may include a physical interface device including one or more sensors, or may include, for example, one or more microphones and one or more speakers, a keyboard, a mouse and a visual display and a tactile input and output mechanism.

In addition, such a software process may be represented using any suitable computer language or combination of languages, for example, using known techniques, and stored, for example, as a built-in system or conventionally stored using known techniques. It can be executed as a program of instructions. Such a software process can be executed on a device that can be used, for example, to assess human stress, as disclosed above.

Such an exemplary software process is a high level process that interacts with a user by, for example, displaying a message to the user and continuously navigating and responding to various user actions, such as pressing a breath guidance button or releasing a pulse from the user's finger. It can have Such exemplary software processes are shown in FIGS. 45-63 as described below. 8 (a)-(b) disclosed above are integrated with this exemplary software process, so that the “process_waves” subroutine disclosed below in connection with FIG. 58 is the sub-shown in FIGS. 8 (a)-(b). Call the routine "get_waves".

45-46 illustrate exemplary top level processes that can be displayed to a user and control, for example, what can correspond to user actions. This high level process essentially initializes the variable and then waits for the interrupts it responds to. Referring to FIG. 45, variables 3601 may be initialized. Such initialization may include, for example, setting the device mode to "spontaneous", number of raw timesteps, number of timesteps, number of pp intervals, number of intervals between beats, and setting values for variables such as error_sum, the number of waves, the number of pp intervals, and the number of pp interval timesteps to zero, and setting the variable state to RAW. This initialization can be performed, for example, according to the following pseudo code: nrt = 0; n_ts = 0; n_pp = 0; n_ibi = 0; State = RAW; err_sum = 0; n_waves = 0; n_val4 = 0; n_ppts = 0.

Continuing with reference to FIG. 45, at 3602, for example, the message “Please insert a finger” can be displayed to the user. At 3603, the process waits for an interrupt and does not take further action until an interrupt occurs. At 3604, if a finger is inserted by the user, at 3610, for example, the device starts calibration, the display message is updated, and the interrupt is cleared and returns to 3602.

The process flow for this exemplary top level process continues as shown in FIG. 37. Referring to FIG. 46, at 3710, when the user presses a breath button, as described above, this may trigger a breath button press interrupt. The process flow then moves to 3720, for example, where the device mode is set to "guiding" and the variable is set to be the current time and the cleared interrupt. The process flow can then move to 3721 where the clock interrupt can be set, for example, 100 milliseconds. The process flow may then move to 3730 where the guiding mode display can be shown to the user. The process flow then returns via breakpoint 2 in FIG. 37 to 3603 in FIG. 45 again waiting for the upper level process to generate another interrupt. This returns the process flow back to FIG. 46 via breakpoint 1 and at 3711, for example, if a clock interrupt occurs, the process flow moves to 3703, where the user presses the breath button on 3710 to enter the guiding mode. Test for less than 2 minutes elapsed from entry time. If it is still less than 2 minutes, the process flow can move to 3730 through 3731 where the guiding mode display can be updated, for example. At 3703, if more than two minutes have elapsed since the user pressed the breath button, the process flow may move to 3702, so that the variable mode is reset to the "natural" mode and the process flow is, for example, a natural mode display. Go to 3701 to be recovered.

Finally, referring to FIG. 46, at 3712, if a pulse is detected, a pulse detection interrupt is generated and the process flow moves to 3713 where the process pulse subroutine is called, for example. This terminates the example top-level process shown in FIGS. 45 and 46. 47-51 illustrate a process flow of an exemplary main routine in accordance with an exemplary embodiment of the present invention, named Process Pulse. Process Pulse calls the subroutines erroe_correction (FIGS. 52-54), error_detection (FIGS. 55-56), initialize_range (FIG. 57), and process_waves (FIGS. 58-59). In turn, process_waves calls the subroutine get_waves (Figs. 8 (a)-(b)) and determine_stress (Figs. 60-62). Thus, all subroutines are called by Process Pulse directly or indirectly.

Referring to FIG. 47, at 3802, rt [0] and the unprocessed timestep rt [n_rt] given initialization at 3601 in FIG. 45 are set to the current time in milliseconds, and the number of n_rt or unprocessed timesteps is Incremented in advance. Then, for example, at 3803, 3804, and 3805, the variable state may be unprocessed to determine whether the data is error free, suspected or suspected of error, and thus along which path the process flow will continue. Can be tested for detection or correction. If state = correction, then the data path starting at 3805 is taken to call the error_correction subroutine at 3805. If state = detection, then the data path starting at 3804 will be taken, finally calling the error_detection subroutine in 3910 of FIG. These two data paths ultimately reach 4011 in FIG. If state = unprocessed, the process flow can continue immediately through 3902 where the timing variables are initialized and verified with n_ts being greater than 1 to 3901 in FIG. have. If this is the case, at 3903, for example, n_val, the number of pp intervals to be allocated may be set equal to 1, and the process flow continues through breakpoint 9 to 4010 in FIG. 49 and to 4011. Can be. When the process flow reaches 4011, one or more pp values need to be assigned. Thus, at 4011, each pp value is assigned one value, and if more than one pp values are present (i.e., n_val> 1), actual time steps are generated and the instantaneous pulse rate is displayed, which is (60000 / is the frequency of the current pp interval as determined by pp [n_pp-1]). The process flow from 4011 continues to 4110 where it is possible to calculate interbeat intervals (IBIs) if one or more pp values are present. At this 4110, the process tests the state, and if yes, the IBI values can be calculated at 4111, for example. If not, the process flow may repeat back to 4010. At 4111, once the IBI values are calculated, the process flow moves to 4201 to test how many pp values exist. If there are more than eight, i.e. at least nine, there is enough data to identify the level 4 valleys. If there are at least two levels of four valley points, ie num_val4> 1, the example process at 4212 may search for RSA waves as disclosed above. Thus, yes at 4212 may cause the process flow to call the process_wave subroutine, for example at 4213.

52-54 illustrate example process flows for the error correction subroutine. As disclosed above in conjunction with an exemplary process pulse routine, in 3805 of FIG. 38, an error correction subroutine is called. Referring to FIG. 52, the process flow begins at 4301 where the subroutine starts. At 4302, for example, the variable err_sum that accumulates current pp interval times has the most recent pp interval added to it. In addition, the variable n_val is set to zero. The process flow continues at 4303 being tested as to whether the new value for err_sum is within range. If it is in range, the process flow may move to 4310, for example, where the variable n_val is set to 1 indicating that the correct pp interval has been identified, the value of the pp interval being set equal to the number of milliseconds in err_sum, The flow returns to the process pulse at 4320. On the other hand, if the experimental pp interval time at 4303 is not within range, the process flow may move to 4304, for example, where the subroutine tests whether the current pp interval time is below the range. If yes, the process flow returns to 4302 and an additional pp interval time is added to the variable err_sum. If no, the current sum is considered excessively high and must be found to divide it into an appropriate integer to produce two or more "in range" pp intervals. The process flow then continues through breakpoint 20 from 4304 to 4401 in FIG. 53. Where test_integer = 2 is set as the test divisor, and the process flow is set to fix the quotient of err_sum / test_integer, e.g. the temporary variable tmp_val representing the actual calibrated pp interval possible. You can go to The fixed flow may then be moved to 4403, which is tested for example if tmp_val is above range. If yes, then at 4410, for example, the text_integer variable shows an increase and the proposed splitting occurs once again at 4402. On the other hand, if tmp_val is not in range at 4403, then at 4404, tmp_val can be tested again to see if it is in range, and if yes, the process flow goes to 4501 in FIG. 54 (via breakpoint 21). I can move it.

In 4501 of FIG. 54, the count variable may be set to 1, and at 4502, for example, the subroutine may ask whether the count is less than the current value of test_integer. If no, the process flow may move to 4501, for example, and the variable n_val may be set equal to test_integer, returning to Process Pulse at 4520, for example, at breakpoint 6 in FIG. On the other hand, if the count is less than test_integer at 4502, the process flow increments the value that counted each loop until, for example, at the time the process flow returns to Process Pulse, until the count is equal to test_integer, 4503, 4504 and 4502 can be repeated. Next, an exemplary error detection subroutine is disclosed with reference to FIGS. 55-56.

Referring to FIG. 55, the process flow begins at 4601 and continues to 4602 where the current pp interval is loaded with a temporary (temporarily accurate) pp interval tmp_pp. At 4603, tmp_pp is tested in range. If yes, n_val is set to 1, val [0] is set equal to tmp_pp at 4610, and at 4620 the process flow returns to the calling program, Process Pulse, particularly 3911 of FIG. However, at 4603, if tmp_pp is found to be out of range, at 4604, a temporary interbeat interval variable tmp_ibi is created for use in detecting any errors as disclosed above. The process flow can then continue to 4701 in FIG. 56 where tmp_ibi is tested (via breakpoint 22) is greater than the lower end of the half of the range, which is a test to see if it is excessively large as disclosed above. If yes, an error is assumed, and the process continues to 4702 where the variable err_sum is set equal to tmp_pp (err_sum is the input to the error correction subroutine disclosed above), and the "state" is set to correction, and the process The flow may move to 4703 where, for example, n_val is set to 0, the process flow returns to Process Pulse, and returns from 3911 of FIG. 48, based on n_val = 0 and state = correction, and 3820 of FIG. 47. Return to the error correction subroutine at 3805.

If 4701 tmp_ibi is not greater than the lower end of the half of the range, it is not considered large in this case, no error appears in the pp interval data, and the process flow continues to 4710, for example, if tmp_pp is greater than the top of the range. You can test it. Since tmp_ibi was not found to be large at 4801, if the tmp_pp interval at 4710 is still greater than the current top of the range, it is assumed that no error appears, and the range needs to be recalculated using the new pp interval as max_pp, This fixes the value for the maximum possible pp interval that is not the result of an error in the data. At 4711, for example, max_pp can be set equal to tmp_pp using this new value, and at 4712, for example, the upper and lower ends of the range are recalculated. The flow can then continue to 4713 where n_val is set equal to 1 and val [0] is set equal to the current pp interval, tmp_pp. At 4714, for example, the process flow can return the calling routine Process Pulse. If at 4710 the current pp interval is not greater than the current upper end of the range, for example, at 4720, the minimum possible pp interval is set equal to the current pp interval. The process flow then continues as described above through 4712, 4713, and 4714, where the process flow returns to the calling program.

Referring to FIG. 57, the process flow for the subroutine initialize_range is described next. This subroutine can be used in exemplary embodiments of the present invention to calculate a range for pp intervals where the data is assumed to be error free for use in the error detection and correction routine. Starting at 4801 in the subroutine call, the process flow moves to 4902, for example, where variables min_pp and max_pp are set using the following pseudo code: min_pp = lowest pp in the data set; max_pp = The highest pp in the data set. Thereafter, at 4803, the upper and lower ends of the range of data points are used for error detection and correction as disclosed above. This can be done, for example, using the following pseudo code: range_high = max_pp + ((max_pp-min_pp) * 0.25; range_low = min_pp-((max_pp-min_pp) * 0.25) .Using these example values , The range is now set, and the process flow returns to the calling routine, Process Pulse, at 4804. In particular, the process flow returns to 4102 in FIG.

58-59 show exemplary process flows for the wave treatment subroutine. In an exemplary embodiment of the present invention, as such disclosed above, the subroutine may be called by a pulse acquisition processing routine such as Process Pulse. After the subroutine is called at 4901, for example, the process flow can continue to 4902 where the get_waves subroutine disclosed above can be called to input the wave identified from the pulse data. The process flow can be assigned using the example determine_stress subroutine, for example, given the acquired waves, a score representing the user's stress level reflected in the identified waves. The flow is then classified into waves, and the instantaneous frequency is based on the current pp interval using the formula frequency = 60000 / (ppts [v2 [nwaves-1]]-ppt [v] [n_waves-1]]). Calculation continues at 4904, where ppts [v] is the pulse point timestamp at the data point (t). From there, for example, the process flow may continue to 5001 on FIG. 59, where a score between 0-3 may be assigned to the user based on the frequency of the current wave, with higher scores resulting in lower stress levels. Indicates. At 5002, for example, the subroutines may, for example, tell the user their respective (i) stress level (obtained from call to determine_stress at 4903); (Ii) frequency (from 4904); And (iii) a score (from 5001), for example, at 5003 the process flow can return to the calling routine, Process Pulse.

60-62 illustrate example subroutines for determining stress scores. By operating at the wavelengths of the user's RSA waves, it is measured how tense the user is. Referring to FIG. 60, at 5104 the determine_stress subroutine calls assigned_wavelengths, which assigns a wavelength between wl_lo and wl_high (set at 5102) to each wave. Using these wavelengths and how many waves are present (ie, the value of n_waves), FIGS. 60-61 show the process flow for each value of n_waves between 1-4. Score 1 is determined at 5110, 201, 5202 and 5203, respectively, which is the weighted sum of the differences between the wavelength of each wave and w_lo, which measures how dust is from the baseline, which is a particular wave. Thus, a perfect relaxation score would have w [n] = w_lo for all n, with each score 1 equal to zero. In alternative exemplary embodiments of the invention score 1 can be calculated without weighting sums of differences, which is the method disclosed above. Score 1 is disclosed as the "wavelength" score. As shown in 5110, 5201, 5202 and 5203 respectively, Score2, which is a "deviation" score, is also calculated. Score1 and Score2 can be combined at 5302 using a relative contribution factor of 70/30 to obtain score3. Other relative weightings that may be useful may be used in alternative embodiments in accordance with the present invention. Score 3 can be used to calculate stress_level using, for example, the equation stress_level = (score3-21) * (100 / (100-21)). stress_level is returned to process_waves at 4903.

Referring to FIG. 63, an exemplary subroutine for the assigned wavelengths is shown. This subroutine can be used, for example, in the example determine_stress routine shown in FIGS. 60-62 as disclosed above, which takes wavelengths as input. In an exemplary embodiment of the invention, the process flow may begin at 5401 with a call to a subroutine. At 5402, the counter variable n is set equal to 0, and at 5403, for example, the current wavelength w1 is the time of the current v1 using the expression w1 = ts [v2 [n]]-ts [v1 [n]]. Calculated by subtracting the timestamp of the current v2 from the stamp. At 5404 and 5405, for example, the value of w1 is compared to the values of w1_lo and w1_high, which can be set in the calling subroutine as shown at 502 of FIG. 60 (eg, to 3 and 10, respectively). Is set). If w1 is less than w1_lo or greater than w1_high, a_w [n] terminates at either w1_lo or w1_high and the flow continues at 5497 where the value of n is previously incremented. However, if w1 has a value between w1_lo and w1_high, for example, at 5406 a_w [n] is set to w1 and the process flow continues to 5407. At 5408, the value of n is compared with the value of n_waves to ensure that each acquired wave is assigned a wavelength. If they are the same at 5410, for example, the process flow terminates for this subroutine and returns to 5105n in FIG. If they are not the same, the flow then repeats through 5403 for each acquired wavelength until all acquired waves are assigned waves.

Exemplary embodiments of the present invention also use, for example, a phase change to detect a drop point, a phase change to detect the completion of a wave, and determine parasympathetic intensity of a newly formed wave, Methods and apparatuses for determining the phase of RSA waves in real time.

64 to 74 show an RSA wave based on a pulse rate method that uses a phase change to detect the drop point, uses a phase change to detect the completion of the wave, and determines the parasympathetic strength of the newly formed wave. Exemplary flow processes are shown for an exemplary process for determining the phase of the magnetic field. This exemplary embodiment initiates a single interrupt drive process that executes each time a new pulse is received.

The example processes and process flows shown in FIGS. 64-74 and any example functions for executing such a process include any auxiliary functions and / or processes called or used by such example flow processes. And for the purpose of explanation. Those skilled in the art will appreciate that each exemplary process or function may be executed in a variety of functionally equivalent ways, at the function or process level invoked, or at the overall level for a full top level process, as disclosed in FIGS. 64-74. It will be understood that the invention is not intended to limit the wide range of possible implementations in the actual systems or apparatuses or to make the illustrative exemplary process flows literally follow.

For simplicity of representation and simplicity of illustration, the process flows of FIGS. 64 to 74 will be disclosed without continually referring to the exemplary features of each aspect or step of the process flow, and are functional in exemplary embodiments of the invention. Note that equivalent implementations may use different processes, and different sequences of processes and configurations of the process flow, for example, to achieve equivalent functionality. All such alternative embodiments and equivalent functional implementations can be understood to be within the techniques and methods of the present invention.

This exemplary process starts at 6000 (FIG. 64). The first step 6001 in the process is to clear all counters: num_points (track the number of pulses received), num_valley (track the number of identified wave valleys), num_peaks (track the number of identified wave peaks) , prev_phase (track the previous wave phase), prev_direction (track the previous wave direction), prev_side (track the previous wave side), and wave_size (track the length of the last wave).

The process then moves to 6002, waiting for the next pulse bit to arrive. If a new pulse is detected, the process moves to 6003 where the pulse is processed. After the pulse has been processed, the process returns to 6002 waiting for another pulse to reach.

65 discloses an exemplary process for treating a pulse. This process starts at 6004. The first step 6005 in the process is to obtain and record the timestamp in ms of the new pulse bit stored as point [num_points] .ts. The process then moves to 6006 to evaluate whether at least two points are present in the record. If not, the process moves to 6007 where the num-point counter is incremented. The process also proceeds to 6012 and returns. However, if there are at least two points in the record, the process moves to 6008.

At 6008, the peak-to-peak (pp) time of the last two points is calculated and recorded as point [num_points] .pp. In addition, the pulse rate value expressed in pp time is calculated and recorded as point [num_points] .prv. The process then proceeds to 6010.

At 6010, the process evaluates whether there are at least eight points in the record. Otherwise, the process proceeds to 6011 and the num_point counter is incremented. The process also proceeds to 6012 and returns. However, if there are at least eight points in the record, the process moves to 6009 invoking the Process Wave process. After the Process Wave process returns, the process of FIG. 65 moves to 6012 and returns.

66 shows a process for processing wave information. The process starts at 6013. The first step 6014 consists of calculating and storing long_slope, abs_long_slope and short_slope. The process then proceeds to 6015 where the direction is determined by the Get Direction process. After the Get Direction process returns, the process proceeds to 6016 where the phase of the wave is determined by the Get Phase process. After the Get Phase process returns, the process proceeds to 6017 where the side of the wave is determined by the Get Side process. After the Get Side process returns, the process proceeds to 6018.

At 6018 the process determines whether there is a change in aspects. If the wave did not change sides, the process moves to 6020. If not, the process moves to 6019 where peaks and valleys are evaluated by the Get Peaks and Valleys process. After this process returns, the process proceeds to 6020.

At 6020, the process sets a flag that indicates whether the wave has just been completed through a process of checking whether the wave is complete. After these processes return, the process proceeds to 6021 where the wave completion flag is checked. If the wave has just been completed, the process proceeds to 6023. Otherwise, the process proceeds to 6022. At 6022, the wave parasympathetic strength marking process depicts a newly formed wave, evaluates its parasympathetic activity, and uses visual symbols to indicate activity under the wave. After this process returns, the process proceeds to 6023.

At 6023, a flag is set to indicate whether a drop point has occurred. The check process to see if a drop has occurred makes this determination and sets the flag accordingly. After this process returns, the process proceeds to 6024 where the flag is analyzed. If no falling point flag is set, the process proceeds to 6026. Otherwise, the process proceeds to 6025. At 6025, the descent point marking process places a visual symbol on the wave at the descent point and provides an acoustic cue of the descent point. After this process returns, the process proceeds to 6026.

At 6026, prev_phase, prev_side and prev_direction indicators are assigned. The process then proceeds to 6027 where the Process Wave function returns.

67 initiates a Get Direction process. First step 6029 checks to see if the short term slope is greater than 30% of the complete long slope. If the short-term slope is greater, the process proceeds to 6030. Otherwise, the process proceeds to 6032.

At 6030 the direction is recorded as UP. The process then proceeds to 6034.

At 6032 the process checks to see if the short slope is less than -1 × 30% of the complete long slope. If the short slope is smaller, the process proceeds to 6033. Otherwise, the process proceeds to 6031.

At 6033 the direction is recorded as DOWN. The process then proceeds to 6034.

At 6031 the direction is recorded as FLAT. The process then proceeds to 6034.

At 6034 the process checks to see if prev_direction is not set yet. If not set, the process proceeds to 6035. If so, the process proceeds to 6036 where the process returns.

At 6035, prev_direction is recorded in the current direction. The process proceeds to 6036 where the process returns.

68 discloses an example Get Phase process. First step 6038 checks to see if the long slope is positive. If the long slope is positive, the process proceeds to 6040. If the long slope is not positive, the process proceeds to 6044.

At 6040 the process checks whether the direction is UP. If the direction is UP, the process proceeds to 6039. If the direction is not UP, the process proceeds to 6041.

At 6039 the phase is recorded as RISING. The process then proceeds to 6045.

At 6041 the phase is recorded as CRESTING. The process then proceeds to 6045.

At 6044 the process checks whether the direction is DOWN. If the direction is DOWN, the process proceeds to 6042. Otherwise, the process proceeds to 6043.

At 6042 the phase is recorded as FALLING. Thereafter, the process proceeds to 6045.

At 6043 the phase is recorded as TROUGHING. Thereafter, the process proceeds to 6045.

At 6045 the process checks if the prev_phase has not been recorded yet. If not already recorded, the process proceeds to 6046. If so, the process proceeds to 6047.

At 6046 prev_phase is recorded as the current phase. The process then proceeds to 6047.

The Get Phase process returns at 6047.

69 initiates a Get Side process. At 6049, the process checks whether the phase is FALLING. If the phase is FALLING, the process proceeds to 6050. If not, then the process proceeds to 6052.

In 6050 the sides are recorded as RIGHT. The process proceeds to 6053.

At 6052 the process checks whether the phase is RISING. If the phase is RISING, the process proceeds to 6051. Otherwise, the process proceeds to 6053.

In 6051 the sides are recorded as LEFT. The process proceeds to 6053.

At 6053 the process checks if prev_side has not been recorded yet. If not already recorded, the process proceeds to 6054. Otherwise, the process proceeds to 6055.

At 6054, prev_side is recorded as the current side. The process then proceeds to 6055. The Get Side process returns at 6055.

70 discloses an example Get Peaks and Valleys process. In a first step 6058, the process checks whether the wave is currently forming a RIGHT side. If yes, the process proceeds to 6059. Otherwise, the process proceeds to 6057.

The peak at 6057 is identified with the highest prv value during previous RISING and CRESTING phases. This value is recorded as peak [num_peaks]. The process then proceeds to 6060. At 6060, the nm_peaks counter is incremented. The process then proceeds to 6062.

The valley at 6059 is identified as the lowest prv value during the previous FALLIGN and TROUGHING phases. This value is recorded as valley [num_valleys]. The process then proceeds to 6061. At 6061, the num_valleys counter is incremented. The process then proceeds to 6062. The Get Peaks and Valleys process returns at 6062.

71 initiates a check process to see if the wave is complete. In a first step 6064, the process checks whether the current phase is RISING. If the current phase is RISING, then the process proceeds to 6066. Otherwise, the process proceeds to 6065.

At 6065 the wave completion flag is set to false. The process then proceeds to 6069.

At 6066 the process checks if previous_phase is TROUGHING. If so, the process proceeds to 6067. Otherwise, the process proceeds to 6068.

At 6067, the wave completion flag is set to true. The process then proceeds to 6069.

At 6068 the process checks if the previous phase is FALLING. If so, the process proceeds to 6067. Otherwise, the process proceeds to 6069. At 6069 a check process returns to see if the wave is complete.

72 discloses an exemplary wave parasympathetic strength indication process. In a first step 6071 the process checks whether there are at least two valleys in the record. Otherwise, the process proceeds to 6077. If so, the process proceeds to 6072.

At 6072, the wave length is calculated and recorded as wave_length. The process then proceeds to 6074. At 6074 the process checks if the wave length is less than 6 seconds. If less than 6 seconds, the process proceeds to 6073. Otherwise, the process proceeds to 8000.

At 6073, the wave size is determined to be SMALL. This represents very little parasympathetic activity when the wave is formed. The process may then visually display the wave with an appropriate symbol representing parasympathetic activity. In a preferred embodiment, one dot symbol is displayed below the wave. The process then proceeds to 6077.

At 8000 the wave length is checked to see if it is less than 9 seconds. If less than 9 seconds, the process proceeds to 6075. Otherwise, the process proceeds to 6076.

In 6075 the wave size is expressed as MEDIUM. Intermediate levels of parasympathetic activity can form waves. The process may then visually display the wave with the appropriate symbol representing parasympathetic activity. In a preferred embodiment, two dot symbols are located below the wave. The process proceeds to 6077.

In 6076 the wave size is indicated as LARGE. Many parasympathetic activities are represented by such waves. The process may then appraise the waves with appropriate symbols representing parasympathetic activity. In a preferred embodiment, three dot symbols are located below the wave. The process proceeds to 6077.

The parasympathetic strength indication process of the wave returns at 6077.

73 discloses an exemplary process for checking whether a drop has occurred. In a first step 6080, the process checks whether the current phase is CRESTING. If the current phase is CRESTING, the process proceeds to 6082. Otherwise, the process proceeds to 6079.

At 6079 the descent point flag is set to false. The process then proceeds to 6083.

At 6082 the process checks if the previous phase is RISING. If the previous phase is RISING, the process proceeds to 6081. Otherwise, the process proceeds to 6079.

At 6081 the descent point flag is set to true. The process then proceeds to 7083. At 6083, the process checks to see if a drop is occurring.

74 discloses an exemplary descent point marking process. In a first step 6085 a triangle is positioned below the wave. The process then proceeds to 6086 to check whether the sound is on. If the sound is ON, the process proceeds to 6087. Otherwise, the process proceeds to 6092.

At 6078 the process checks whether the wave size is SMALL. If the wave size is SMALL, the process proceeds to 6088. Otherwise, the process proceeds to 6090.

At 6088, the device generates a high pitch beep. This is an audible indication that a drop has occurred, while at the same time an audible indication that the previous wave was formed by low levels of parasympathetic activity. The process then proceeds to 6092.

6090 checks whether the wave size is MEDIUM. If the wave size is MEDIUM, the process proceeds to 6089. Otherwise, the process proceeds to 6091.

At 6089, the device generates a middle pitch horn. This indicates that a drop has occurred and that the previous wave was formed by an intermediate level of parasympathetic activity. The process then proceeds to 6092.

At 6091, the device generates a low pitch horn. This is audible, indicating that the drop has occurred and that the previous wave was formed by high levels of parasympathetic activity. The process then proceeds to 6092. The drop point marking process returns at 6092.

For example, to determine the phase of RSA waves in real time, using phase changes to detect drop points, phase changes to detect wave completion, and determining parasympathetic strength of newly formed waves. Example processes may also be executed using the following pseudo code substantially corresponding to the process shown in FIGS. 64-74.

Also provided are exemplary embodiments of the present invention for identifying peaks and valleys in real time without first identifying TD4 segments. Thus, the values can be processed continuously (eg, one by one).

75-83 illustrate example process flows for an example process for determining wave phase and depicting waves in a pulse rate fashion. These exemplary embodiments use a generic direction indicator and the location of points in a range, for example, to provide better accuracy in phase determination and wave description.

The example processes and process flows shown in FIGS. 75-83 and any example functions for executing such processes may replace any auxiliary functions and / or processes called or used by such example flow processes. And are shown for illustrative purposes. Those skilled in the art can execute in various functionally equivalent ways whether each exemplary process or function can be executed in various functionally equivalent ways at the function or process level being invoked or at the overall level for the entire upper level process. The subsequent disclosure of FIGS. 75-83 does not limit the wide range of possible implementations in an actual system or apparatus or require a schematic exemplary process flow to be disclosed in writing.

For simplicity of explanation, the process flow in each of the figures of FIGS. 75-83 will be disclosed without continuing reference to the typical nature of each step of the process flow, and functionally equivalent implementations in the exemplary embodiment of the invention Note that different sequences of processes, processes, and process flow configurations disclosed, for example, in FIGS. 75-83 can be used to achieve equivalent functionality. All such alternative embodiments and equivalent functional implementations are understood within the techniques and methods of the present invention.

As shown in FIG. 75, the process begins at 6093. The first step is 6094. At 6094, the process sets UP PERCENT to 30 and DOWN PERCENT to 15. The process then proceeds to 6095 where the counter and indicator are started. The process then proceeds to 6096 where the process waits for the value of the 15 second pulse information to arrive. The process proceeds to 6097 where the process waits for the next pulse beat. After the next pulse bit is received, the process proceeds to 6098 where a comprehensive direction indicator is determined by the Get Fast Information process.

When the process returns, the process proceeds to 6099 where the current slope is calculated and recorded. The process then proceeds to 6100 where the lowest prv of the last 12 seconds and the highest prv of the last 20 seconds are calculated and recorded. This gives a range of prv values for the last 12 seconds.

The process then proceeds to 6101. In 6101, the Determine Direction process determines the direction of the wave. When this process returns, the process proceeds to 6102 where the current point peak-to-peak (pp) value, pulse rate value (prv), timestamp (ts), direction and point index are calculated and recorded.

The flow then proceeds to 6103 where the Get Point Position process determines which part of the range the current point is in. The position of 100 means that the point is at the top or above the range. A position of 1 means that the point is either below the pole or below the range. A value between 1 and 100 represents the percent height of the point in the range.

When the Get Point Position process returns, the process proceeds to 6104. The wave write at 6104 is updated on the display. That is, the recently received prv value is written on the display. The process then proceeds to 6105.

At 6105 the process checks to see if the direction changed when the last prv was received. If the direction has not changed, the process proceeds to 6097 where the process waits for the next pulse. If the direction has changed, the process proceeds to 6106 where the change of direction is processed by the Process Direction Change process. When this process returns, the process proceeds to 6097 where the process waits for the next pulse to arrive.

76 discloses an example Get Fast Information process. In the first step 6108, the highest positive slope for the last 5 seconds is recorded as fast_rise. The process then proceeds to 6109. In 6109, the highest negative slope for the last 5 seconds is recorded as fast_drop. The process then proceeds to 6111.

At 6111 the process checks if fast_rise is greater than the complete value of fast_drop. If fast_rise is greater, the process proceeds to 6110. Otherwise, the process then proceeds to 6112.

At 6110, fast_rise is recorded as fastest_change. Thereafter, the process proceeds to 6113.

At 6112, the complete value of fast_drop is recorded as the fastest_change. Thereafter, the process proceeds to 6113. At 6113, the Get Fast Information process returns.

77 discloses an exemplary Determine Direction process. In a first step 6115 of the process, the process checks whether the current slope is greater than the UP PERCENT% of the fastest change. If larger, the process proceeds to 6116. Otherwise, the process then proceeds to 6117.

At 6116 the current direction is recorded as UP. Thereafter, the process proceeds to 6123.

At 6117, the process checks to see if the current slope is below -1 × DOWN PERCENT% of the fastest change. If so, the process proceeds to 6119. If not, then the process proceeds to 6118.

At 6118 the current direction is recorded as DOWN. The process then proceeds to 6123.

At 6119 the process checks whether the current direction is UP. If so, the process proceeds to 6120. Otherwise, the process proceeds to 6121.

The current direction at 6120 is also recorded as PEAK_PLATEAU, also known as CREST. Thereafter, the process proceeds to 6123.

At 6121 the process checks whether the current direction is DOWN. If so, the process proceeds to 6122. Otherwise, the process then proceeds to 6123.

At 6122 the current direction is also recorded as VALLEY_PLATEAU, also known as TROUGH. Thereafter, the process proceeds to 6123. The Determine Direction process returns at 6123.

78 initiates an exemplary Determine Point Position process. In a first step 6125, the process checks whether the prv of the current point is less than the lowest prv in the range. If so, the process proceeds to 6126. Otherwise, the process proceeds to 6127.

At 6126, the point position is recorded as zero. The process then proceeds to 6130.

At 6127 the process checks if the prv of the current point is greater than the highest prv in the range. If so, the process proceeds to 6128. Otherwise, the process then proceeds to 6129.

At 6128 the point position is recorded as 100. The process then proceeds to 6130.

At 6129, the relative position of the point within the range is calculated and recorded. The process then proceeds to 6130. The Determine Point Position process returns at 6130.

79 discloses an exemplary Process Direction Change process. In a first step 6134, the process checks whether the current direction is UP. If so, then the process proceeds to 6135. Otherwise, the process proceeds to 6138.

At 6135 the process checks whether the current direction is DOWN. If so, the process proceeds to 6136. Otherwise, the process proceeds to 7132.

At 6132, the process checks whether the current direction has been recorded. If not recorded, the process proceeds to 6133. If it has been recorded, the process proceeds to 6144.

The up swing of the wave at 6133 is handled by the Process Null Up Swing process. After this process returns, the process proceeds to 6144.

At 6136 the process checks to see if the current point position is within the bottom 25% of the range. If so, the process proceeds to 6137. Otherwise, the process proceeds to 6144.

In 6137 the upswing of the wave is handled by the Process Regular Up Swing process. After this process returns, the process proceeds to 6144.

At 6138 the process checks whether the current direction is DOWN. If so, the process proceeds to 6139. If not, then the process proceeds to 6144.

At 6139 the process checks whether the current direction is UP. If so, then the process proceeds to 6140. Otherwise, the process proceeds to 6143.

At 6140 the process checks to see if the current point is at the top 75% of the range. If so, the process proceeds to 6141. Otherwise, the process proceeds to 6144.

The down swing of the wave at 6141 is handled by the Process Regular Down Swing process. After this process returns, the process proceeds to 6144.

At 6143, the process checks that no previous direction has been recorded. If not recorded, the process proceeds to 6142. If so, the process proceeds to 6144.

At 6142, the wave's down swing is handled by the Process Null Down Swing process. When this process returns, the process proceeds to 6144. Return the Process Change Direction process at 6144.

80 discloses an example Process Regular Up Swing process. In the first step 6146 the lowest prv is recorded as the most recent valley point after the start of the previous direction. The process then proceeds to 6147.

At 6147, the process checks whether there are at least two valley points in the record. If present, the process proceeds to 6148. If not present, the process proceeds to 6150.

At 6148 the wavelength of the last wave is calculated and recorded. The process then proceeds to 6149. At 6149 a stress index is calculated and a score is calculated. In addition, stress indices, wavelengths, history, scores, and other wave based metrics are displayed on the screen. The process then proceeds to 6150.

At 6150, the previous direction is recorded as UP. The process then proceeds to 6151. At 6151, the previous direction index is recorded as having two points previously occurred. The process then proceeds to 6152, which is returned by the Process Regular Up Swing process.

81 discloses an exemplary Process Regular Up Wsing process. Since the start of the last direction change in the first step 6164, the highest prv is recorded as the next peak point. The process then proceeds to 6155.

At 6155 the process checks whether there are at least two recorded peaks. If present, the process proceeds to 6156. If not present, the process proceeds to 6157.

At 6156 the timestamps of the last two peaks are subtracted to calculate and record the last peak to peak time. The process then proceeds to 6157.

At 6157, the previous direction indicator is set to DOWN. The process then proceeds to 6158 where the previous direction index is set to the previous two points. The process then proceeds to 6159, which the Process Regular Up Swing process returns.

82 discloses an exemplary Process Null Up Swing process. In a first step 6161, the previous direction indicator is set to UP. The process then proceeds to 6162 where the previous direction index is set to the previous two points. The process then proceeds to 6163, where the Process Null Up Swing process retunes.

83 discloses an exemplary Process Null Down Swing process. In a first step 6164 the previous direction indicator is set to DOWN. The process then proceeds to 6165 where the previous direction index is set to the previous two points. The process then proceeds to 6167, which the Process Null Up Swing process returns.

For example, example processes for determining the wave phase and depicting the waves in a pulsed manner may also be performed using the following pseudo code substantially corresponding to the flow processes shown in FIGS. 75-83.

The present invention also provides processes for determining the completion and dropping points of RSA waves in real time rather than pulse rate mode. 84-87 disclose two example processes that run simultaneously. The first process, Realtime Process 1 (at 6168), is run in a pulse rate fashion. The second process, Realtime Process 2 (at 6171), is run every 250 ms. The two processes work together to allow real-time detection of dropping points and real-time detection of current wave rejection.

The example processes and process flows disclosed in FIGS. 84-87 and any example functions for executing such processes include any auxiliary functions and / or processes called or used by such example flow processes. And are shown for illustrative purposes. Those skilled in the art will appreciate that each exemplary process or function may be executed in a variety of functionally equivalent ways, whether the function or process level being invoked may be executed in various functionally equivalent ways at the overall level for the entire upper level process. In addition, the subsequent disclosure of FIGS. 84-87 does not limit the wide range of possible implementations in an actual system or apparatus or require a schematic exemplary process flow to be disclosed in writing.

For brevity of description, the process flow in each of the figures of FIGS. 84-87 will be disclosed without continuing reference to the typical nature of each step in the process flow, and functionally equivalent implementations in the exemplary embodiment of the invention Note that different sequences of processes, processes, and process flow configurations, for example, those disclosed in FIGS. 84-87 can be used to achieve equivalent functionality. All such alternative embodiments and equivalent functional implementations can be understood within the techniques and methods of the present invention.

84 discloses the interrupt nature of two example processes. Realtime Process 1 starts at 6168. In a first step 6169, the process waits for the next pulse to be received. When the pulse is received, the process proceeds to 6170 where the pulse is processed by the Handle Pulse Peak process. When this process returns, the process goes back to 6169 where the process waits for the next pulse.

In the meantime, Realtime Process 2, starting at 6171, runs concurrently. The first step 6172 of this process sets the clock interrupt to 250ms so that this process is invoked every 250ms. The process then proceeds to 6173, where the process sleeps until a clock interrupt occurs. When a clock interrupt occurs, the interrupt is handled by the Handle Clock Interrupt process. When this process returns, the process proceeds to 6172 where the clock interrupt is reset.

85 discloses an exemplary Handle Pulse Peak process. In a first step 6176, the direction is determined by the Get Direction process. (The Get Direction process and related processes are described in detail above and thus are not repeated here.) When this process returns, the process proceeds to 6177.

At 6177 the process checks whether the direction is UP. If so, the process proceeds to 6181. Otherwise, the process proceeds to 6178.

At 6178, the process checks whether the direction is PEAK_PLATEAU. If so, the process proceeds to 6182. Otherwise, the process proceeds to 6179.

At 6179 the process checks whether the direction is DOWN. If so, the process proceeds to 6183. Otherwise the process proceeds to 6180.

At 6180, the Handle VALLEY PLATEAU process handles the case where the wave is currently TROUGHING. When this process returns, the process proceeds to 6187.

At 6182 the valley plateau flag is set to false. The process then proceeds to 6184 where the up flag is set to true. The process then proceeds to 6187.

At 6182 the valley plateau flag is set to false. The process then proceeds to 6185 where the up flag is set to true. The process then proceeds to 6187.

At 6183 the valley plateau flag is set to false. The process then proceeds to 6186 where the up flag is set to false. The process then proceeds to 6187. Return the Handle Pulse Peak process at 6187.

86 initiates an exemplary Handle Clock Interrupt process. In a first step 6190 the process checks whether the valley plateau flag is true. If so, the process proceeds to 6191. If not, the process proceeds to 6189.

At 6189 the process checks whether the up flag is true. If so, the process proceeds to 6193. If not, the process proceeds to 6199.

At 6191 the process checks to see if the current time has passed the calculated flat end. If so, the process proceeds to 6192. Otherwise, the process proceeds to 6189.

At 6192 the current direction is recorded as UP. The UP swing is thus detected in real time. Thus, the completion of the previous wave is detected in real time. Wave descriptions, stress metrics, parasympathetic metrics, and the like can be processed, calculated, recorded, displayed, etc. as needed.

The process then proceeds to 6189. At 6189 the process checks whether the up flag is set to true. If so, the process proceeds to 6193. If not, the process proceeds to 6199.

At 6193, the phantom prv value is computed and calls tmp_prv. The process then proceeds to 6194 where the current slope is calculated based on the previous two real time prv and virtual image prv. The process then proceeds to 6195.

At 6195, the process checks if the current slope is less than -1 × DOWN PERCENT% of the fastest change. The calculation of the fastest change is disclosed in the previous embodiments. If less, the process proceeds to 6196. If not, the process proceeds to 6199.

At 6196 the current direction is recorded as DOWN. In other words, the transition to DOWN is detected in real time. The process does not have to wait for the next pulse beat. The next pulse beat will occur after the drop point.

The process proceeds to 6197 where the up flag is set to false. The process then proceeds to 6198 where the descent point can be processed. The descent point can be indicated visually, acoustically, or both. After the descent point information is used, the process proceeds to 6199. At 6199, the Handle Clock Interrupt process returns.

87 discloses an exemplary Handle VALLEY PLATEAU process. In a first step 6201, the up flag is set to false. The process then proceeds to 6202.

At 6202, the process checks whether the valley plateau flag is false. If it is false then the process proceeds to 6203. If not false, the process then proceeds to 6212.

At 6203, the process checks whether the previous point is a bottom point. If so, the process proceeds to 6204. If not, the process proceeds to 6206.

At 6204 the timestamp of the previous point is recorded as the flat end. The process then proceeds to 6208.

At 6206, the process checks whether the previous point is a rising transition point. If so, the process proceeds to 6205. If not, the process proceeds to 6207.

The timestamp of the two points passed in 6205 is recorded as the flat end. The process then proceeds to 6208.

At 6207 the timestamp of the current points is recorded as the flat end. The process then proceeds to 6208.

At 6208 the process checks whether the timestamp of the last known valley is less than the timestamp of the last known peak. If so, the process proceeds to 6209. If not, the process proceeds to 6210.

At 6209 one third of the time between the last peak and the last valley is added to the plateau end. The process then proceeds to 6211.

At 6210 one third of the time between the last peak and the second for the last valley is added to the flat end. The process then proceeds to 6211.

At 6211 the valley plateau flag is set to true. The process then proceeds to 6212. At 6212, the Handle VALLEY PLATEAU process returns.

Exemplary processes for determining both the completion and dropping points of RSA waves in real time may also be performed using the following pseudo code substantially corresponding to the flow processes disclosed in FIGS. 84-87.

The present invention is disclosed with reference to specific embodiments. However, it should be noted that modifications and variations may be made without departing from the scope and spirit of the invention. In particular, it is noted that the various process flows disclosed herein may be modified to provide substantially equivalent functional implementation, which will be accomplished within the spirit and scope of the present invention.

Claims (28)

A compact portable biomagnetic control device for relieving stress of a patient, housing; A PPG sensor for generating data from the patient; A control system coupled to the PPG sensor; And Display screen Wherein the control system is configured to process data from the patient for output to the display screen, the output data providing the patient with information related to the dropping point of at least one RSA wave. Portable biomagnetic control device. The method of claim 1, And said information is visual information. The method of claim 1, And said information is audible information. The method of claim 1, Wherein said information is used to urge a patient to begin exhalation. The method of claim 1, And said information is provided to said patient substantially in real time. The method of claim 1, The device further comprises a breathing metronome that can be activated by the patient, wherein the breathing metronome is programmed to be deactivated after a predetermined time period. The method of claim 1, Wherein said device is configured to extract information related to breathing of a patient. The method of claim 7, wherein And the breath-related information includes a speed, a rhythm, and a breath volume. The method of claim 1, And said housing comprises a power source. The method of claim 1, Compact portable biomagnetic control device characterized in that power is provided by an A / C source. Providing the patient with information on the dropping point of at least one RSA wave. The method of claim 11, Wherein said information is visual information. The method of claim 11, Wherein said information is auditory information. The method of claim 11, Wherein said information is used to urge the patient to begin exhaling. The method of claim 11, Wherein said information is provided to the patient in real time in real time. A compact portable biomagnetic control device for reducing stress of a patient, (a) a housing; (b) a PPG sensor generating data from the patient; (c) a control system coupled to the PPG sensor; And (d) display screen Wherein the device functions while being gripped between the patient's thumb and forefinger. The method of claim 16, And the PPG sensor is configured to contact the index finger of the patient. The method of claim 17, The control system is configured to process data from the patient for output to the display screen, the output data providing the patient with information related to the stress level of the patient. Device. The method of claim 17, The control system is configured to process data from the patient for output to the display screen, the output data providing the patient with information related to the dropping point of at least one RSA wave. Biomagnetic control device. The method of claim 19, And said information is visual information. The method of claim 19, And said information is audible information. The method of claim 19, Wherein said information is used to urge a patient to begin exhaling. The method of claim 19, And the information is provided to the patient in substantially real time. The method of claim 19, The device further comprises a breathing metronome that can be activated by the patient, wherein the breathing metronome is programmed to be deactivated after a predetermined time period. The method of claim 19, Wherein said device is configured to extract information related to breathing of a patient. The method of claim 19, And the breath-related information includes a speed, a rhythm, and a breath volume. The method of claim 19, And said housing comprises a power source. The method of claim 19, Compact portable biomagnetic control device characterized in that power is provided by an A / C source.

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