TWI623299B - Measurement and evaluation system for sleep abnormal operation and method thereof - Google Patents

Abstract

The invention relates to a measurement and evaluation system for sleep abnormal operation and a method thereof, which obtains a plurality of limb frequency domain eigenvalues, a plurality of limb time domain eigenvalues, and a plurality of trunk frequency domains by using a plurality of accelerometer units and a processing unit. The eigenvalue and the plurality of torso time domain feature values are calculated and obtained to obtain the frequency domain feature values of the limbs, the time domain feature values of the limbs, the torso frequency domain feature values, and any of the torso time domain feature values The difference between them is to solve the problem of not being able to record the time domain and frequency domain characteristics during the active state of the limb.

Description

Measurement and evaluation system for sleep abnormal operation and method thereof

The present invention relates to a measurement and evaluation system for sleep abnormality and a method thereof, and more particularly to a method for evaluating sleep abnormality by attaching a plurality of acceleration gauges to a plurality of limb measurement areas and a plurality of torso measurement areas.

According to the Chief Executive of the Executive Yuan, about 24% of the Chinese people have problems with sleep problems, and there is an increasing trend compared with the previous four years. The neuropsychiatrists explain that the sleep system needs internal reflections, sensory activities and body Physical exercise will stop during sleep, but if you give appropriate stimulation, you can wake up. However, lack of proper sleep may lead to sequelae such as daytime sleepiness, emotional instability, depression, stress, anxiety, immunity. Reduced, decreased judgment, lost logical thinking and decreased work efficiency. The state of lack of sleep for a period of time or for a long time is called sleep disorder. Sleep disorders will often indicate poor quality of sleep environment. Among them, the quality of sleep environment is The state of sleep, including the external environment and a state of reflection inside the body.

According to the International Classification of Sleep Disorders 2nd ed. (ICSD-2) published by the American Academy of Sleep Medicine in December 2005, it classifies sleep disorders into eight categories of 97 diseases. It is classified into sleep abnormality, easy sleep syndrome, and medical or neurological related sleep diseases. Among them, patients with abnormal sleep can measure abnormal characteristics by multi-channel physiological tester (PSG). The channel physiology checker monitors the number and type of apnea and respiratory dystrophy during an overnight sleep cycle, the type of hypoxia index and frequency, changes in electrocardiogram, airflow in the mouth and nose, respiratory movements in the chest and abdomen, blood oxygen levels, and snoring. The physiological status such as the number of times can be used as the basis for the diagnosis of the doctor. However, there is no clear measurement method for patients with narcolepsy and medical or neurological diseases. The doctor judges the characteristics of the questionnaire or the patient's description. .

Furthermore, sleep abnormalities are classified into three types: endogenous, extrinsic, and physiological clock disorders. Among them, the intrinsic part is the sleep disorder caused by internal factors, such as sleep apnea, periodic limb tic disorder. And restless legs, etc., the external factors are caused by external factors caused by sleep disorders, physiological clock imbalance is the problem of sleep disorders caused by excessive differences in day and night.

At present, because the multi-channel physiological tester is loaded with several kinds of sensing modules, the whole device is more expensive than the usual single measurement and evaluation device, and can only be set in major medical centers. When the patient with abnormal sleep goes to the clinic, The Epworth Sleepiness Scale (ESS) is the initial assessment. After the physician evaluates the characteristics of sleep abnormalities, the patient takes several months to discharge the sleep examination room. The sleep examination room is As a place for sleep recording, the patient performs about one or two sleep tests. The sleep record is used as the main basis for the evaluation of the physician, and has the purpose of quantitatively displaying various physiological conditions. However, when monitoring with the multi-channel physiology tester, since the movement changes of the hands, legs, and head are not monitored, it is impossible to evaluate the posture change and the change of the limb movement, and for the periodic limb tic disorder and restless legs. The diagnosis of the disease is not enough. It may even need to be assisted by personnel observation or video recording throughout the night. It is characterized by periodic limb tic disorder and restless leg disease, such as: periodic limb tics. The thumb and instep are bent upwards, accompanied by continuous movement of the knee and hip joints; the restless legs are periodically swinging, shaking and shaking after falling asleep.

However, before the diagnosis of the doctor, it is necessary to quantify the physiological data recorded by the analyst for the multi-channel physiological tester and convert it into an index parameter. The parameters for general sleep abnormality include: no-breath-low respiratory index (Apnea) -hypopnea Index) refers to the average number of hours of non-breathing and low-breathing events. It can be comprehensively evaluated according to various physiological record parameters. It is usually necessary to carry out step-by-step analysis of each hour's data, and even perform different groups of signal ratios at the same time. Yes, the number of parameters is confirmed by multiple parameters, and the multi-channel physiological tester is complicated to record, and the whole system cannot be applied to the home environment. Usually, only some physiological recording modules, such as electrocardiogram, The gas flow meter, the chest abdomen strap and the blood oxygen saturation concentration meter, of course, can only be recorded for the respiratory state, and the lack of record of the movement of the limb, that is, the diagnosis of the local body motion cannot be performed.

A sleep measuring device of the Chinese Patent No. 201143715, which provides a sleep efficiency analyzing device, comprising a dynamic sensing unit for sensing a plurality of time points of the dynamic sensing unit itself within a sensing time a state of motion, and a set of acceleration signals and a set of attitude signals are generated for each of the time points, and the acceleration signal and the attitude signal are determined by a state determination unit to determine the dynamic sensing unit at each time by a state determination rule. The point-time is a static state or a motion state to generate a state information, and further includes a posture determining unit receiving the attitude signal, and determining a posture of the dynamic sensing unit in the three-dimensional space according to the attitude signal to generate a Position information, and receiving the status information and posture information by a quality analysis unit, and obtaining a sleep quality analysis result according to the two information analysis, wherein the sleep measurement device is placed on a single part, such as a limb, a neck or a head In order to determine the posture distribution during sleep, the attitude information is taken. However, the measurement of a single site cannot record the full view of the limb movements of the periodic limb tics and restless legs, and the patients with periodic limb tics and restless legs can rely on the limbs of the limbs. Assisting the physician in judging the severity of the symptoms, and the conventional sleep measuring device only reveals a simple posture such as lying on the back, lying down, lying on the left side, or lying on the right side through the dynamic sensing unit, and determining according to a simple posture. In the case of the number of posture changes, it is impossible to know the action of a single limb, or to know the time domain and frequency domain characteristics that occur between the action states, and it is impossible to give substantial help to the diagnosis of the condition.

According to the above, the conventional multi-channel physiological tester can record a plurality of physiological parameters and can assist in judging the accurate features. However, in the manpower dispatch and system resource consumption, the multi-channel physiological tester is also expensive. The waiting time for the patient is much longer than the time for diagnosis, which not only greatly reduces the diagnostic efficiency, but also is not suitable for patients with sleep disorders of periodic limb tics and restless legs. In addition, although the sleep measuring device has been There are attitude recognition and sleep quality assessment. However, it is still not enough for patients with sleep disorders of periodic limb tics and restless legs. It is known that the sleep measurement device can only determine the posture change without knowing the single limb. The occurrence of the action or the time domain and frequency domain characteristics that occur between the action states cannot assist the physician in diagnosis. Therefore, how to provide a measurement and evaluation device for sleep abnormality has become an important topic for researchers involved in the industry.

An object of the present invention is to provide a measurement and evaluation system for sleep abnormality and a method thereof, and record the time domain and frequency domain characteristics of the limb and the trunk by measuring the movement of the limb and the trunk.

Another object of the present invention is to provide a measurement and evaluation system for sleep abnormality and a method thereof, which measure a time domain and a frequency domain characteristic value of a limb obtained by a plurality of limb parts, and can be learned that the human body sleeps after the operation. Hand movements or foot movements.

A further object of the present invention is to provide a measurement and evaluation system for sleep abnormality and a method thereof, which measure the time domain and frequency domain characteristic values of the trunk obtained by a plurality of torso parts, and can be learned that the human body is sleeping after the operation. Heartbeat frequency, respiratory rate, number of rises, or number of turns.

Another object of the present invention is to provide a measurement and evaluation system for sleep abnormality and a method thereof, which measure the time and frequency domain characteristic differences of each limb by measuring the movements of each limb and the trunk, and evaluate each limb. The harmony of interaction.

In order to achieve the foregoing objective, the present invention discloses a measurement and evaluation system for sleep abnormality, which comprises a plurality of acceleration gauge units disposed in a plurality of limb measurement areas and a plurality of trunk measurement areas of a human body for measuring And obtaining a plurality of limb sensing signals and a plurality of body sensing signals; and a processing unit respectively capturing the limb sensing signals and the trunk sensing signals to generate a plurality of limb frequency domain characteristic values and a plurality of limb time domains The eigenvalue, the plurality of torso frequency domain eigenvalues and the plurality of trunk time domain eigenvalues, the frequency domain eigenvalues of the limbs, the time domain eigenvalues of the limbs, the torso frequency domain eigenvalues and the torso time domain characteristics are calculated a difference between the two of the values; wherein the processing unit is before or during the sleep state of the human body, and recording the frequency domain characteristic values of the limbs, the time domain characteristic values of the limbs, the torso frequency domain characteristic values, and the The difference between any of the torso time domain feature values.

One embodiment of the present invention also discloses that the limb measurement regions are located in the right hand wrist and the left leg calf muscle.

One embodiment of the present invention also discloses that the torso measurement regions are located between the navel and the diaphragm and on the sternum.

According to an embodiment of the present invention, the system further includes a storage unit, configured to store the frequency domain feature values of the limbs, the limb time domain feature values, the torso frequency domain feature values, and the trunk time domain feature values. And recording a difference between the limb frequency domain feature values, the limb time domain feature values, the torso frequency domain feature values, and any of the torso time domain feature values.

An embodiment of the present invention further discloses that the limb frequency domain characteristic values and the trunk frequency domain feature values include a first primary frequency, a second primary frequency, a first energy intensity, and a second energy intensity. Subtracting the second main frequency to generate a main frequency difference; the first energy intensity minus the second energy intensity, generating an energy intensity difference, recording the main frequency difference and the energy intensity The difference is used to assess the harmony of the two limbs.

According to an embodiment of the present invention, the frequency domain characteristic values of the limbs and the time domain characteristic values of the limbs are also disclosed, and the hand movement or the foot motion of the human body during sleep can be obtained after calculation. The torso frequency domain characteristic values and the torso time domain characteristic values are calculated to obtain the heartbeat frequency, respiratory rate, number of rises, or number of turns of the human body during sleep.

An embodiment of the present invention further discloses that the limb time domain feature values and the trunk time domain feature values include a first time, a second time, a first amplitude intensity, and a second amplitude intensity. Subtracting the second time for a time, generating a time difference; the first amplitude intensity minus the second amplitude intensity, generating an amplitude intensity difference, recording the time difference value and the amplitude intensity difference for use in Assess the harmony of the two limbs.

An embodiment of the present invention further discloses that the system further includes a reference unit disposed on one of the chest or a back measurement area of the human body, and can be measured to obtain a reference signal, and the processing unit receives the reference signal. And generating a time domain reference value, which is corresponding to a posture of the human body, and the time domain reference value is a complex direction acceleration value when the human body changes the posture, and the storage unit records the directional acceleration values to Used to assess the harmony of the two limbs.

The measurement and evaluation method for using the abnormal operation of the sleep performed by the above system includes the steps of: sensing vibration or motion changes of a plurality of limb measurement regions and a plurality of torso measurement regions, and generating a plurality of limb sensing signals. And a plurality of torso sensing signals; continuously extracting the limb sensing signals and the torso sensing signals, respectively obtaining a plurality of limb frequency domain characteristic values, a plurality of limb time domain characteristic values, a plurality of trunk frequency domain characteristic values, and a plurality of torso time domain feature values; continuously calculating a difference between the limb frequency domain feature values, the limb time domain feature values, the torso frequency domain feature values, and any of the torso time domain feature values; Comparing the difference between the frequency domain feature values of the limbs, the time domain feature values of the limbs, the torso frequency domain feature values, and the torso time domain feature values at different time points to generate at least one self-assessment value.

One embodiment of the present invention also discloses that the limb measurement regions are located in the right hand wrist and the left leg calf muscle.

One embodiment of the present invention also discloses that the torso measurement regions are located between the navel and the diaphragm and on the sternum.

One embodiment of the present invention also discloses that the limb sensing signals and the torso sensing signals are obtained by a plurality of accelerometer sensings.

According to an embodiment of the present invention, the frequency domain characteristic values of the limbs and the time domain characteristic values of the limbs are also disclosed, and the hand movement or the foot motion of the human body during sleep can be obtained after calculation.

According to an embodiment of the present invention, the torso frequency domain characteristic values and the trunk time domain characteristic values are also disclosed, and the heartbeat frequency, respiratory frequency, number of rises, or number of turns of the human body during sleep are obtained after calculation.

An embodiment of the present invention is further disclosed, after the step of generating the self-evaluation value after comparison, further comparing the frequency domain characteristic values of the limbs, the time domain characteristic values of the limbs, and the trunk frequency domain characteristics. The difference between the value and any of the torso time domain eigenvalues and the plurality of limbs, trunk frequency domain feature differences, and the plurality of limb and trunk time domain feature differences stored in a normal group of a database unit, A plurality of limbs, trunk frequency domain characteristic difference of an abnormal group and a plurality of limb and trunk time domain feature differences or a body of limbs, a plurality of frequency domain characteristic differences of the body and a plurality of limb and trunk time domain characteristic differences At least one abnormality evaluation value is generated, and the sleep abnormality is determined accordingly.

According to an embodiment of the present invention, the limb frequency domain characteristic values and the trunk frequency domain feature values include a characteristic frequency, an energy intensity, a bandwidth, an average frequency, and a frequency distribution.

One embodiment of the present invention also discloses that the limb time domain feature values and the trunk time domain feature values include a time and an amplitude intensity.

An embodiment of the present invention further discloses that the limbs, the trunk frequency domain characteristic difference values of the normal group, and the limb and trunk time domain characteristic differences are sensed in a static state and are not detected by the limbs, and are recorded in the Database unit.

According to an embodiment of the present invention, the limbs, the trunk frequency domain characteristic difference, and the limb and trunk time domain characteristic differences of the abnormal group are also obtained by sensing a patient suffering from a sleep abnormal disease.

In order to provide a better understanding and understanding of the features and advantages of the present invention, the preferred embodiments and the detailed description are as follows:

The present invention is directed to a conventional multi-channel physiological tester. Although it can record a plurality of physiological parameters and can assist in judging accurate features, the manpower dispatch and system resource consumption, etc., also result in a higher price of the multi-channel physiological tester. Allowing patients to wait much longer than the time of diagnosis, which not only greatly reduces the diagnostic efficiency, but also is not suitable for patients with sleep disorders of periodic limb tics and restless legs. Therefore, how to provide a diagnostic efficiency tester is to provide a measurement and evaluation device for sleep abnormal operation, thereby overcoming the problem of diagnostic efficiency and simultaneously assessing the harmony between limbs.

Please refer to FIG. 1A, which is a schematic structural diagram of a first embodiment of the present invention. As shown in the figure, the present embodiment provides a measurement and evaluation device for sleep abnormal operation, which includes a measurement and evaluation device 1 . The evaluation device 1 includes a plurality of accelerometer units 10, 100, 11-14, a reference unit 15 (not shown in the first A diagram), and a processing unit 16, wherein in the embodiment, the acceleration is transmitted. The gauge units 10, 100, 11-14 are measured and used for medical evaluation purposes.

Please refer to FIG. 1B, which is another schematic structural diagram of the first embodiment of the present invention, as shown in the figure, wherein the measurement evaluation device 1 is electrically connected to the accelerometer units 10, 100, and 11 In addition to the ~14 measurement, the accelerometer units 10, 100, 11~14 can also be wirelessly transmitted to the measurement evaluation device 1, and the measurement evaluation device 1 also has a display function.

The accelerometer units 10, 100, 11-14, and the reference unit 16 are components implemented by Newton's law and Hooke's law. When the displacement of the accelerometer element is applied, the displacement changes include vibration, and the accelerometer unit The internal mass produces a swing phenomenon, which is calculated to calculate the acceleration actually occurring on the accelerometer element. In addition, the accelerometer component can be composed of a flexible printed circuit (FPC), which has flexibility and three-dimensional space. The characteristics such as wiring enable the accelerometer component to be highly attached to the body surface. The processing unit 16 is a microcontroller (Microcontroller Unit), which is usually divided into 8-bit, 16-bit and 32-bit depending on the processing capability. In this embodiment, the amount of data processed and the size of the generated signal sequence are selected.

According to the foregoing system, the accelerometer unit 10 is disposed in a torso measurement area of a sternum plate; the accelerometer unit 100 is disposed in a torso measurement area between the navel and the diaphragm; the accelerometer unit 11 is disposed in the a limb measurement area of the right wrist portion or a right arm portion; the acceleration gauge unit 12 is disposed on a left wrist portion or a limb measurement region of a left arm portion; the acceleration gauge unit 13 is disposed on a right knee portion, a right tibia or a limb measurement area of a right foot, the accelerometer unit 14 is disposed on a left knee, a left humerus or a left foot, a limb measurement area; the accelerometer unit The vibration or motion change of the measurement area can be measured, and a plurality of limb sensing signals and a plurality of trunk sensing signals are generated.

In addition, a reference unit (not shown in the figure) can be set in a chest or a back measurement area for evaluating the posture and recording, as the physician judges the posture change in the measurement, or according to the set distance In the same time, the measurement data of the reference unit and the measurement data of the accelerometer units are calculated at the same time, thereby overcoming the change of the attitude to obtain the relative value of the sleep abnormal operation, which enables the embodiment to be applied to different postures.

Referring to the second and third figures AD, which is a block diagram of the first embodiment of the present invention and a frequency domain signal diagram of the abnormal evaluation mode of the first embodiment of the present invention, as shown in the figure, the processing is as shown in the figure. The unit 17 is coupled to the accelerometer units 11-14. The accelerometer units 11 to 14 respectively generate a plurality of limb sensing signals. The sensing signals include a frequency domain sensing signal, and the accelerometer unit 11 receives the One of the first sensing signals L1 of the right wrist or the one of the limbs of the right arm is a frequency domain sensing signal L11, and the accelerometer unit 12 receives the limb of the left wrist or the left arm One of the second sensing signals L2 of the measurement area is a frequency domain sensing signal L12, and the acceleration gauge unit 13 receives one of the limb measurement areas of the right knee, the right humerus or the right foot. The frequency sensing signal L13 is one of the three sensing signals L3, and the accelerometer unit 14 receives the fourth sensing signal L4 of the limb measurement area of the left knee, the left tibia or the left foot. a frequency domain sensing signal L14, the processing unit 16 captures the frequency domain sensing signals L 11~L14, generating a plurality of frequency domain feature values M1~M4, wherein the frequency domain feature values M1~M4 are transmitted to a database unit 17, and the database unit 17 records the frequency domain feature values M1~M4. And recording the frequency domain sensing signals L11~L14 received by the processing unit 16, wherein the database unit 17 stores the frequency domain characteristic values M1~M4 and is regarded as a plurality of frequencies of the normal group. The domain eigenvalues are externally input to the database unit 17, and the present embodiment is provided with an evaluation unit 18, which is coupled to the processing unit 16 and the database unit 17 for assessing the abnormality of the limbs during sleep. The data is the aforementioned frequency domain feature values M1 to M4, and the evaluation unit 18 has an abnormal comparison mode. After the evaluation, the data is transmitted to a transmission unit 19 and wirelessly transmitted to the receiving device 3. .

Moreover, in the abnormal comparison mode, the evaluation unit 18 retrieves the data of the normal group of the database unit 17 and compares the acceleration unit 11 to 14, wherein the data of the normal group is No abnormal action, that is, a basic value set value, which is measured and recorded in the static state without limb movement; in the measurement, when the abnormal movement of the limb occurs or before, the evaluation unit 18撷A frequency domain sensing signal L11 is obtained, wherein the frequency domain sensing signal L11 is a position corresponding to the acceleration gauge unit 11, and a characteristic frequency F1 and an energy of the plurality of frequency domain characteristic values M1 of the frequency domain sensing signal L11 The intensity P1 is compared with the basic set value by the evaluation unit 18. Similarly, the accelerometer units 12~14 can also be compared with the basic set value, and thus the plurality of frequency domain characteristic values M1~M4 are transmitted through. A characteristic frequency domain F2~F4 and an energy intensity P2~P4 are compared with the basic set value, and then one of the limbs is evaluated for sleep abnormality, and the energy intensity P1~P4 can be calculated in this embodiment. The difference between the basic settings, depending on a first abnormality evaluation value, and calculating a difference between the characteristic frequency F1~F4 and the basic set value, is regarded as a second abnormal evaluation value, as a basis for the diagnosis of the physician; in addition, the frequency domain characteristic signals are further It can include a bandwidth, an average frequency, and a frequency distribution to improve the accuracy of the evaluation.

In addition, the reference signal L5 is used as a reference signal for the frequency-domain sensing signals L11-L14, and the reference signal L5 has a fifth sensing signal L5. The fifth sensing signal L5 has a plurality of frequency domain features, wherein the evaluation unit 18 captures the frequency domain characteristic M1 of the frequency domain sensing signal L11 of the sensing unit 11, and can be based on the frequency domain features. The difference between the frequency domain features M1 is regarded as a frequency domain feature difference, thereby providing the frequency domain feature difference values as a basis for the physician evaluation, to ensure that the acceleration gauge unit 11 is The sensing unit 11 is only listed in the present embodiment, but is not limited thereto.

Moreover, the basic set value may be obtained from the frequency domain feature values of the abnormal group of the database unit 17, and preferably, the basic set values are generated through the frequency domain feature values, and the basic set value is compared. Jia Wei sets a number of thresholds according to the severity of the limbs.

Please refer to the fourth AB diagram, which is a frequency domain signal diagram of the self-alignment mode of the second embodiment of the present invention. As shown in the figure, the setting positions and block diagrams of the acceleration gauge units 11 to 14 in this embodiment are shown. The same as the previous embodiment, so it will not be described again; however, the difference is that the evaluation unit 18 of the embodiment has a self-alignment mode.

In the self-alignment mode, the evaluation unit 18 needs to record the frequency-domain sensing signals L15 and the frequency-domain eigenvalues M5 measured in a first time quantity; when the sleep abnormality occurs Before the occurrence, the evaluation unit 18 calculates a plurality of frequency domain features M6 of the frequency domain sensing signal L15 at a first time frequency F5 and a second time amount of the frequency domain sensing signal L16. The difference between the characteristic frequency F6 is regarded as a first self-evaluation value, and the difference between the energy intensity P5 of the first time and the energy intensity P6 of the frequency domain sensing signal L16 of the second time is calculated. And regard it as a second self-assessment value, so as to be used as the basis for the diagnosis of the doctor. If the normal scale system is used, it is impossible to know for sure whether the limb measurement area has a significant deterioration in sleep abnormality over a period of time. In addition, the frequency domain characteristic signals may further include a bandwidth, an average frequency, and a frequency distribution, thereby improving the accuracy of the evaluation.

Please refer to the fifth AD diagram, which is a time domain signal diagram of the abnormality evaluation mode of the third embodiment of the present invention. As shown in the figure, the setting positions and blocks of the acceleration gauges 11 to 14 in this embodiment are shown. The figure is the same as the previous embodiment. The difference is that the present embodiment evaluates the state of sleep abnormality by using the time domain feature value. Therefore, the evaluation unit 18 only describes the abnormal comparison mode, and the rest is no longer used. Narration.

In the abnormal comparison mode, the evaluation unit 18 retrieves the data of the normal group of the database unit 17, and then compares the acceleration rule units 11 to 14, wherein the data of the normal group is no abnormality. , that is, a basic set value, which is measured and recorded in a static state without any limb movement; in the measurement, the evaluation unit 18 captures the acceleration when or before the abnormal movement of the limb occurs. The time domain sensing signal L101 is one of the first sensing signals L1 of the regulation unit 11, wherein the time domain sensing signal L101 is a position corresponding to the acceleration gauge unit 11, and the plurality of time domain features of the time domain sensing signal L101 The value T1 and the amplitude intensity A1 are compared with the basic set value through the evaluation unit 18. Similarly, the accelerometer units 12~14 may respectively be based on the plurality of senses for the basic set value. The plurality of time domain eigenvalues of the plurality of time domain sensing signals L102~L104 of the test signals L2~L4 are compared with the basic set value through a time T2~T4 and an amplitude intensity P2~P4, and then the respective values are respectively evaluated. One of the limbs has abnormal sleep And in this embodiment, the difference between the time T1~T4 and the basic set value is calculated, and is regarded as a first abnormality evaluation value, and the difference between the amplitude intensity A1~A4 and the basic set value is calculated. It is regarded as a second abnormal evaluation value as a basis for the diagnosis of the physician to improve the accuracy of the assessment.

In addition, the reference signal L5 is used as a reference for the time domain sensing signals L101~L104 through the reference signal L5, and the reference signal L5 has a plurality of time domain features, wherein the evaluation unit The time domain feature of the time domain sensing signal L101 of the sensing unit 11 is obtained by the 18 system, and can be regarded as a time domain characteristic difference according to the difference between the time domain features and the time domain features. Thereby, the time domain feature difference values are provided as the basis for the physician evaluation, in order to ensure that the acceleration gauge unit 11 is placed in the correct position during the evaluation process, or the acceleration gauge unit 11 is in a normal operation state, and is not abnormal. The error caused by the state; only the sensing unit 11 is listed in the embodiment, but is not limited thereto.

Moreover, the basic set value may be obtained from the time domain feature values of the abnormal group of the database unit 17, and preferably the base set value is generated through the time domain feature values, and the basic set value is compared. Jiawei sets a plurality of thresholds according to the severity of each limb.

Please refer to the sixth AB diagram, which is a time domain signal diagram of the self-alignment mode of the fourth embodiment of the present invention. As shown in the figure, the setting positions and block diagrams of the acceleration gauges 11 to 14 in this embodiment are shown. The same as the previous embodiment, so it will not be described again; however, the difference is that the evaluation unit 18 of the embodiment has a self-alignment mode.

In the self-alignment mode, the evaluation unit 18 needs to first record the time-domain sensing signals L105 and the time-domain features measured by the first time; when the sleep abnormality occurs or occurs The difference between the time T5 of the time domain sensing signal L105 and the time domain of the time domain characteristic of the time domain sensing signal L106 is calculated by the evaluation unit 18. The value is regarded as a first self-evaluation value, and the difference between the amplitude intensity A5 of the first time and the amplitude intensity A6 of the time domain sensing signal L106 of the second time is calculated and regarded as a The second self-assessment value is used as a basis for the diagnosis of the physician. If the normal average standard is used, it is impossible to know whether the limb measurement area has a significant deterioration of sleep abnormality over a period of time.

Please refer to the seventh AB diagram, which is an abnormal frequency domain signal diagram of the abnormal comparison mode in the fifth embodiment of the present invention. As shown in the figure, the setting positions of the accelerometer units 11 to 14 in this embodiment and The block diagram is the same as the previous embodiment, and therefore is not described in detail. The difference is that in this embodiment, the abnormal motion between the limbs of sleep is evaluated through the accelerometer units 11 to 14, and at least two acceleration gauge units are required. In the embodiment, only the acceleration gauge unit 11 and the accelerometer unit 12 are used to evaluate the degree of harmony between the limbs, but the embodiment is not limited thereto.

The data of the normal ethnic group is no abnormal operation, that is, a basic value set value, which is measured and recorded in the static state without any limb movement, and when the abnormal movement of the limb occurs or occurs, the evaluation is performed. In the abnormal comparison mode, the unit 18 receives the frequency domain sensing signal L17 of the accelerometer unit 11 preset by the database unit 17 and the frequency domain characteristic values M7, and the accelerometer unit 14 The frequency domain sensing signal L18 and the frequency domain features M8, the frequency domain features M7 having the characteristic frequency F7 and the energy intensity P7; the frequency domain features M8 having the characteristic frequency F8 and the energy intensity P8, the evaluation unit 18 compares the frequency domain features of the frequency domain features M7, M8 and the basic set value respectively, and calculates the characteristic frequency F7 of the frequency domain features M7 and the frequency of the basic set value. a difference between the domain features, and a difference between the characteristic frequency F8 of the frequency domain features M8 and the frequency domain features of the basic set value, and is regarded as a first abnormality evaluation value, the first abnormality evaluation value The characteristic frequency of the left part is greater than a side portion; further, calculating a difference between the energy intensity P7 of the plurality of frequency domain features M7 and the energy intensity of the basic set value, and calculating the energy intensity F8 of the plurality of frequency domain features M8 and the basic set value The difference between the energy intensity is regarded as a second abnormality evaluation value, and the second abnormality evaluation value indicates that the energy intensity of the right side portion is greater than the left side portion, and the harmony degree according to the first abnormality evaluation value and the second abnormality evaluation value Evaluation, it can be known that the left side of the abnormal sleep cycle is more rapid, but the right side is a swinging large low frequency, and then push the left limb and the right limb limb sleep abnormal movement as a non-harmonious movement, thereby As a basis for the diagnosis of the physician; in addition, the frequency domain characteristic signals may further include a bandwidth, an average frequency and a frequency distribution, thereby improving the accuracy of the evaluation.

Please refer to the eighth AB diagram, which is an abnormal frequency domain signal diagram of the self-alignment mode of the sixth embodiment of the present invention. As shown in the figure, the setting positions and blocks of the acceleration gauges 11 to 14 in this embodiment are shown. The figure is the same as the previous embodiment, so it will not be described again; however, the difference is that the evaluation unit 18 of the embodiment has a self-alignment mode.

Referring to the seventh AB diagram, in the self-alignment mode, the evaluation unit 18 needs to record the frequency-domain sensing signals L17~L18 measured by the first time quantity, and the frequency frequencies are measured. The domain eigenvalues M7~M8 are used as the second time standard. The frequency domain sensing signal L19 and the frequency domain sensing signal L20 are captured by the evaluation unit 18 when the sleep abnormality occurs or before the occurrence of the sleep abnormality. a plurality of frequency domain characteristic values M9 and M10 of time, and respectively extracting one of the frequency domain sensing characteristic values M9, a characteristic frequency F9 and an energy intensity P9, and extracting one of the frequency domain characteristic values M10 The characteristic frequency F10 and an energy intensity P10; the evaluation unit 18 further calculates the difference between the characteristic frequency F9 and the characteristic frequency F7; the difference between the characteristic frequency F10 and the characteristic frequency F8; the difference between the energy intensity P9 and the energy intensity P7 a difference between the energy intensity P10 and the energy intensity P8, wherein the difference between the energy intensities produces at least a first self-evaluation value, and the difference between the main frequency domains produces at least a second self-evaluation difference That is, the difference between the characteristic frequency F9 and the characteristic frequency F7 approaches 0, However, the difference between the energy intensity P9 and the energy intensity P7 is greater than 0, and the at least one first self-evaluation value is generated, and the tendency of the right limb to deteriorate is observed through the at least one first self-evaluation value; At least a second self-evaluation value, the difference between the characteristic frequency F10 and the characteristic frequency F8 approaches 0, and the difference between the energy intensity P10 and the energy intensity F8 approaches 0, and the at least one second self-evaluation is generated. And observing, by the at least one second self-evaluation value, that there is no significant change in the left limb; and then referring to the at least one first self-evaluation value and the at least one second self-evaluation value to learn the second time Compared with the first time, the right limb has obvious deterioration, while the left limb has no change, that is, during the sleep process, the right limb and the left limb are in a state of disharmony, and the abnormal movement is biased to the right side, thereby As a basis for the diagnosis of the physician; in addition, the frequency domain characteristic signals may further include a bandwidth, an average frequency and a frequency distribution, thereby improving the accuracy of the evaluation.

Please refer to the ninth AB diagram, which is an abnormal frequency domain signal diagram of the abnormal comparison mode in the seventh embodiment of the present invention. As shown in the figure, the setting positions and blocks of the acceleration gauges 11 to 14 in this embodiment are shown. The reference system is the same as the previous embodiment, and the reference unit is also the same as the previous embodiment, and therefore will not be described again. However, the difference is that the evaluation unit 18 of the embodiment transmits the acceleration gauges L11~L14. The time domain characteristics are evaluated.

During the measurement process, the processing unit 16 captures a time domain sensing signal L107 of the accelerometer unit 12 and a time domain sensing signal L108 of the accelerometer unit 14, and records the data in the database unit 17. The unit 18 further extracts the time domain sensing signals L107 of the database unit 17 and the time domain characteristic values of the time domain sensing signal L108.

The time domain sensing signal L107 has a plurality of time domain feature values, and the time domain feature values include a time T7 and an amplitude intensity A7; and the time T7 for calculating the domain features and one of the basic setting values a difference between the preset time and a difference between the amplitude intensity A7 of the time domain features and the preset amplitude intensity of the one of the basic set values, and is regarded as at least a first abnormality evaluation value; the time domain sensing signal L108 has a plurality of time domain feature values, and the time domain feature values include a time T8 and an amplitude intensity A8, and the difference between the time T8 of the time domain features and the time set value is calculated, and The difference between the amplitude intensity A8 of the time domain features and the amplitude intensity of the base set value is calculated and regarded as at least a second abnormality evaluation value.

Please refer to the tenth AB diagram, which is an abnormal frequency domain signal diagram of the self-alignment mode of the eighth embodiment of the present invention. As shown in the figure, the setting positions and blocks of the acceleration gauges 11 to 14 in this embodiment are shown. The figure is the same as the previous embodiment, so it will not be described again; however, the difference is that the evaluation unit 18 of the embodiment has a self-alignment mode.

The evaluation unit 18 receives the time domain features of the time domain sensing signal L107 recorded by the database unit 17 at a first time and the time domain sensing signals L108. And the time domain features of the time domain sensing signal L109 at a second time and the time domain features of the time domain sensing signal L110, according to the second time The time-domain sensing feature values and the first time are respectively calculated from the difference between the time and the amplitude intensity, and at least one self-evaluation value is generated, wherein the two time of the same limb is taken to calculate the difference, and the at least one self is generated. The time domain sensing signal L110 has a time T10 and an amplitude intensity A10, and the time domain sensing signal L108 at the same time and at the same time has the time T8 and The amplitude intensity A8, and then calculating the difference between the time T10 and the time T8, and calculating the difference between the amplitude intensity A10 and the amplitude intensity A8 to generate at least one first self-evaluation value; further, the second time The time domain sensing signal L109 is in the same position The time domain sensing signal L107 of the first time calculates the difference of the time domain features respectively, and the time T9 and the amplitude intensity A9 are calculated in the same manner as described above, thereby generating at least a second self-evaluation value. Therefore, it will not be repeated.

The at least one first self-evaluation value indicates that the left hand strength is maintained at the second time, and the time of the abnormal sleep operation is prolonged, and the abnormality of the left hand is changed according to the first self-evaluation value. Further, the local soreness and discomfort may be aggravated; further, the at least one second self-evaluation value indicates that the left foot has no significant change at the second time and the first time, so according to the at least one first self-evaluation value and The at least one second self-assessment value can be evaluated when the left hand is more aggravated than the left foot at the second time when the sleep abnormality is active, and in the sleep abnormality, the foot is often generated in the foot, and the hand is After a period of foot attack, it may last for several weeks to several months, and then occurs in the upper limbs, that is, the upper limbs are more abnormal than the lower limbs, whereby the physician can rely on the at least one first self-assessment. The value and the at least one second self-assessment value are in turn arranged for treatment.

Please refer to FIG. 11 and the twelfth AC diagram, which are schematic diagrams of a reference unit configuration of a ninth embodiment of the present invention and a reference signal of a reference unit of a ninth embodiment of the present invention, as shown in the figure. The hardware structure of this embodiment is the same as the first figure and the second figure. In this embodiment, the reference unit 15 is in a sleep state, and a plurality of directional acceleration values of the reference signal are recorded.

The reference unit 15 converts vibration or motion changes into acceleration values in the X-axis, the Y-axis, and the Z-axis according to the inertial sensing function, and the reference unit 15 is disposed on the chest measurement area, wherein the X-axis is The head toward the head is positive; the Y axis is positive toward the body side; the Z axis is positive for the normal direction of the chest measurement region; or, the reference unit 15 is disposed in the back measurement region, where the X axis The head is positive toward the head; the Y axis is positive toward the body side; the Z axis is the normal direction of the back measurement area.

When presenting a standing posture, the reference unit 15 generates corresponding acceleration values according to the standing posture, wherein the acceleration values include an X-axis acceleration value L21, a Y-axis acceleration value L22, and a Z-axis acceleration. The value L23, the X-axis acceleration value L21 exhibits a g value, which varies depending on the selected acceleration gauge unit, but the Y-axis acceleration value L22 and the Z-axis acceleration value L23 exhibit a value of 0, and further, The X-axis acceleration value L21 is much larger than the Y-axis acceleration value L22 and the Z-axis acceleration value L23.

Please refer to the thirteenth and fourteenth AC diagrams, which are another reference unit configuration diagram of the ninth embodiment of the present invention and a signal diagram of another reference unit of the ninth embodiment of the present invention, as shown in the figure. As shown, when presenting a positive lying posture, the reference unit 15 generates corresponding acceleration values according to the positive lying posture, wherein the acceleration values include an X-axis acceleration value L24 and a Y-axis acceleration. The value L25 and a Z-axis acceleration value L26, the Z-axis acceleration value L26 exhibits a g value, which is also varied by the selected acceleration gauge unit, but the X-axis acceleration value L24 and the Y-axis acceleration value L25 are A value of 0 is exhibited, and further, the Z-axis acceleration value L26 is much larger than the X-axis acceleration value L24 and the Y-axis acceleration value L25.

The reference unit 15 records the posture as the acceleration values, and the measured posture is not limited to the foregoing standing posture or the positive lying posture, which is only a preferred embodiment, wherein the reference unit 15 The acceleration values are respectively recorded in the positive lying posture, and the first accelerometer unit 11, the second accelerometer unit 12, the third accelerometer unit 13 and the fourth accelerometer unit 14 are driven. Recording is performed, which represents the sleep state; otherwise, the acceleration values of the reference unit 15 exhibit the standing posture without recording or stopping recording.

In summary, the present invention provides a measurement and evaluation device for an abnormal sleep operation, which is provided with an acceleration gauge unit and a processing unit. The acceleration gauge unit is disposed in the limb measurement area and the trunk measurement area, and senses the limb and the trunk measurement. The vibration or movement changes in the region respectively generate the limb and trunk sensing signals, and the processing unit separately extracts the limb and trunk sensing signals to generate the limb and torso frequency domain feature values or/time domain feature values, and can calculate either The difference between the frequency domain characteristic values of the limb and the trunk sensing signal, or / and the difference between the time domain characteristic values of the sensing signals of the two; and the processing unit can also record the limb and torso frequency domain eigenvalues The difference or / and the difference between the time domain feature values. In addition, the sensing signal is obtained by the limb limb and the trunk measurement area captured by the accelerometer unit, and the limb measurement area includes a wrist, an arm, a knee, a tibia or a foot. The trunk measurement area includes a sternum plate and an area between the navel and the diaphragm, and takes time domain eigenvalues of the sensing signals of the two, and calculates a difference between the time domain eigenvalues, wherein the time domain eigenvalues The difference is used to represent the harmony between the left and right upper limbs, the left and right lower limbs or the upper and lower limbs; or/and the frequency domain eigenvalues of the two are calculated, and the difference between the frequency domain eigenvalues is calculated, wherein the time domain eigenvalues are The difference is used to represent the harmony between the left and right upper limbs, the left and right lower limbs, or the upper and lower limbs, and the heartbeat and respiratory rate during sleep can be known; in addition, the present invention further determines the posture by setting a reference unit. The measuring and evaluating device for sleep abnormal operation of the present invention can be used for measuring the movement of a limb, recording the time domain and frequency domain characteristics of the limb, or recording the limbs by measuring the movement of each limb. The time domain and frequency domain characteristic difference are used to evaluate the harmony of the movements between the limbs to assist the physician in diagnosis and to give substantial help to the diagnosis of the condition.

However, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, so that the shapes, structures, features, and spirits described in the claims of the present invention are equally changed. Modifications are intended to be included in the scope of the patent application of the present invention.

1‧‧‧Measurement evaluation device
10‧‧‧Acceleration unit
100‧‧‧Acceleration unit
11‧‧‧Acceleration unit
12‧‧‧Acceleration unit
13‧‧‧Acceleration unit
14‧‧‧Acceleration unit
15‧‧‧reference unit
16‧‧‧Processing unit
17‧‧‧Database unit
18‧‧‧Evaluation unit
19‧‧‧Transportation unit
3‧‧‧ Receiving device
L11, L21, L31, L41‧‧‧ frequency domain sensing signals
L15~L20‧‧‧ frequency domain sensing signal
L101~L110‧‧‧Time domain sensing signal
M1~M10‧‧‧ frequency domain eigenvalue
P1~P10‧‧‧Energy intensity
A1~A10‧‧‧Amplitude intensity
T1~T10‧‧‧Time

1A is a schematic structural view of a first embodiment of the present invention; FIG. 1B is another schematic structural view of a first embodiment of the present invention; and FIG. 2 is a first embodiment of the present invention Block diagram of the third embodiment: a frequency domain signal diagram of the abnormality evaluation mode of the first embodiment of the present invention; and a fourth AB diagram: the frequency of the self-alignment mode of the second embodiment of the present invention Field signal map; fifth AD map: time domain signal map of the abnormality evaluation mode of the third embodiment of the present invention; sixth AB map: time domain of the self-alignment mode of the fourth embodiment of the present invention Signal diagram; seventh AB diagram: an abnormal frequency domain signal diagram of the abnormal comparison mode of the fifth embodiment of the present invention; eighth AB diagram: it is an abnormality of the self-alignment mode of the sixth embodiment of the present invention Frequency domain signal map; ninth AB diagram: an abnormal frequency domain signal diagram of the abnormal comparison mode of the seventh embodiment of the present invention; FIG. 8 AB: it is a self-alignment mode of the eighth embodiment of the present invention Abnormal frequency domain signal diagram; Figure 11: It is the ninth implementation of the present invention A reference unit configuration diagram; a twelfth AC diagram: a signal diagram of a reference unit of a ninth embodiment of the present invention; and a thirteenth diagram: another reference unit of the ninth embodiment of the present invention A configuration diagram; and a fourteenth AC diagram: a signal diagram of another reference unit of the ninth embodiment of the present invention.

Claims (18)

A measurement system for sleep abnormality, comprising: a complex acceleration gauge unit disposed in a plurality of limb measurement areas and a plurality of trunk measurement areas of a human body for measuring and obtaining a plurality of limb sensing signals and a plurality of trunk senses And a processing unit that respectively captures the limb sensing signals and the torso sensing signals, and generates a plurality of limb frequency domain eigenvalues, a plurality of limb time domain eigenvalues, a plurality of trunk frequency domain eigenvalues, and a plurality of torso time domain feature values, and calculating a difference between the limb frequency domain feature values, the limb time domain feature values, the torso frequency domain feature values, and the torso time domain feature values; wherein The processing unit is before or during the sleep state of the human body, and records the frequency domain characteristic values of the limbs, the time domain characteristic values of the limbs, the trunk frequency domain characteristic values, and any of the trunk time domain characteristic values. a difference, the limb time domain feature values and the torso time domain feature values include a first time, a second time, a first amplitude intensity, and a second amplitude intensity, the first time minus the second time time Generating a time difference, the amplitude of the first subtracting the second intensity amplitude intensity to generate an amplitude intensity difference, time difference, and records the amplitude of the intensity difference, to assess the degree of harmony for two of the limb. A measurement system for sleep abnormality according to the first aspect of the patent application, wherein the limb measurement regions are located Right wrist and left leg calf muscle. The measurement system for sleep abnormality according to claim 1, wherein the torso measurement regions are located between the navel and the diaphragm and on the sternum plate. The measurement system for sleep abnormal operation according to claim 1, further comprising: a storage unit, storing the frequency domain characteristic values of the limbs, the time domain characteristic values of the limbs, and the trunk frequency domain characteristic values. And the torso time domain feature values, and record the difference between the limb frequency domain feature values, the limb time domain feature values, the torso frequency domain feature values, and the torso time domain feature values. The measurement system of the sleep abnormality according to the first aspect of the invention, wherein the limb frequency domain characteristic value and the trunk frequency domain characteristic value comprise a first main frequency, a second main frequency, and a first An energy intensity and a second energy intensity, the first main frequency minus the second main frequency, generating a main frequency difference; the first energy intensity minus the second energy intensity, generating an energy intensity difference, recording The main frequency difference and the difference in energy intensity are used to evaluate the harmony of the two limbs. The measuring system for the abnormal operation of sleep according to the first aspect of the patent application, wherein the frequency domain characteristic values of the limbs and the time domain characteristic values of the limbs are calculated to obtain the hand movement of the human body during sleep or Foot movements. As described in the first paragraph of the patent application, the abnormal sleep operation The measurement system, wherein the torso frequency domain characteristic values and the torso time domain characteristic values are calculated to obtain the heartbeat frequency, the respiratory frequency, the number of rises or the number of turns of the human body during sleep. The measurement system for sleep abnormal operation according to claim 1, further comprising: a reference unit disposed on one of the chest or a back measurement area of the human body, and measuring to obtain a reference signal The processing unit receives the reference signal and generates a time domain reference value corresponding to a posture of the human body, and the time domain reference value generates a complex direction acceleration value according to the human body when the posture is changed, and the storage unit is These directional acceleration values are recorded for assessing the harmony of the two limbs. A method for measuring the abnormality of sleep operation includes the steps of: sensing vibration or motion changes of a plurality of limb measurement regions and a plurality of torso measurement regions, and generating a plurality of limb sensing signals and a plurality of trunk sensing signals; The limb sensing signals and the trunk sensing signals are continuously obtained, and a plurality of limb frequency domain eigenvalues, a plurality of limb time domain eigenvalues, a plurality of trunk frequency domain eigenvalues, and a plurality of trunk time domain eigenvalues are respectively obtained. The time domain feature values of the limbs and the torso time domain feature values include a time and an amplitude intensity; when the limb frequency domain feature values are continuously calculated, the limbs are a difference between the domain eigenvalues, the torso frequency domain eigenvalues, and any of the torso time domain eigenvalues; and comparing the limb frequency domain eigenvalues at the different time points, the limb time domain eigenvalues, The difference between the torso frequency domain feature values and any of the torso time domain feature values produces at least one self-evaluation value. The method for measuring the abnormality of sleep according to claim 9 of the patent application scope, wherein the limb measurement regions are located in the right wrist and the left leg calf muscle. A method for measuring a measurement of sleep abnormality according to claim 9 wherein the torso measurement area is located between the navel and the diaphragm and on the sternum. The measurement method for assessing sleep abnormality according to claim 9 is characterized in that the limb sensing signals and the trunk sensing signals are obtained by using a plurality of accelerometer sensings. The method for measuring the abnormality of sleep operation according to claim 9 of the patent application scope, wherein the frequency domain characteristic values of the limbs and the time domain characteristic values of the limbs are calculated to obtain the hand movement of the human body during sleep. Or foot movements. The method for measuring the abnormality of sleep operation according to claim 9 of the patent application scope, wherein the tonal frequency domain characteristic values and the torso time domain characteristic values are calculated to obtain the heartbeat frequency of the human body during sleep, Respiratory rate, number of rises, or number of turns. The amount of sleep abnormality as described in item 9 of the patent application scope An evaluation method, wherein after the step of generating the self-evaluation value after comparison, the frequency domain characteristic value of the limbs, the time domain characteristic values of the limbs, the torso frequency domain characteristic values, and the torso are further compared The difference between the two of the time domain eigenvalues and the plurality of limbs, the trunk frequency domain feature difference value stored in a normal group of a database unit, and the plurality of limbs, trunk time domain feature difference values, and an abnormal group complex number The difference between the frequency of the limbs and the trunk, the difference between the plurality of limbs and the trunk time domain, or the difference between the body and the body of the body, the frequency difference between the body and the body, and the time difference between the plurality of limbs and the trunk, resulting in at least one abnormality. The value is evaluated and the sleep abnormality is determined accordingly. The measurement method for assessing sleep abnormality according to claim 9 , wherein the limb frequency domain characteristic values and the trunk frequency domain characteristic values comprise a characteristic frequency, an energy intensity, a bandwidth, and an average frequency. With a frequency distribution. The method for measuring a measurement of sleep abnormality according to claim 15 of the patent application, wherein the difference in the frequency domain characteristics of the limbs and the trunk of the normal group and the difference in the time domain characteristics of the limbs and the trunk are in a stationary state and are not The limbs are sensed and recorded in the database unit. The method for measuring the abnormality of sleep operation according to claim 15 of the patent application scope, wherein the difference in the frequency characteristics of the limbs and the trunk of the abnormal group and the difference in the time domain characteristics of the limbs and the trunk are sensed Obtained by patients with abnormal sleep disorders.