SG193032A1 - Non-contact vital signal monitoring apparatus and method - Google Patents

Abstract

This invention discloses a non-invasive vital signal monitoring apparatus and method to acquire vital signals of human beings, in particular, heart rate and respiration rate. The core element in this apparatus is a biomedical sensor made from piezoelectric films to form a shape such that the pressure force applied on it can be transformed to the tensile force. This transformation significantly enhances the detection sensitivity of the sensor, and allows to measure extremely weak physical forces. With the characteristic, the sensor is not necessarily directly attached on human body in order to measure the cardiac and respiratory activities. The only perquisite is that there is a medium in between the human body and the sensor that can transport the pressure. The raw data obtained by the sensor is processed in a microprocessor with a dedicated algorithm. This algorithm, with the aim of obtaining the heart and respiration rate, is implemented through three scenarios: (1) the identification of the maximum value and the length of time between the current and next maximum, (2) the identification of the minimum value and the length of time between the current and next minimum, and (3) the combination of the above two. An inexpensive microprocessor is used due to the conciseness of the algorithm, thus the cost of the apparatus is reduced. The apparatus can be used for health care industry for taking care of elderly, disability, and infants in home, nursing home and hospital.Fiq. 5

Description

BACKGROUND AND PRIOR ARTS

Vital signals of human being, such as heart rate and respiration rate are generally used to identify the health condition of a person. For example, during the living hours excluding physical exercise, a person with a heart rate between 50 to 100 beats per minute is in a normal condition, while out of this range may hint some healthy problems and the person needs to have some medical consultants from doctors, and gets treatment if necessary.

Since the vitals signals are directly associated with some medical problems and can reveal health conditions, it is very necessary that we can monitor the signals in real time, especially for those patients with chronic diseases. Moreover, it also can be used as a tool to quantitatively evaluate the sleep quality.

Electrocardiogram (ECG) and Electroencephalography (EEG) are two of the most popular methods to measure the vital signals. However, electrodes are required to directly contact the skin of human being for both of them in order to get precise measurements of the signals. This constraint has largely limited their wide deployment because it forces users under testing circumstances where they feel they are experimental objects. Their responses to the testing environments are destructive to the acquisition of data that is supposed to reveal their real physical conditions. On the other hand, the constraint also limits the sites where the devices are deployed, for example, only in hospitals or clinics.

It is unavoidable that we need to design a method with which the vital signals can be measured in a non-contact manner. This non-contact measurement has the obvious advantages: (1) it removes the psychic pressure of users by completely eliminating the sensors from the body, and allows accurate acquisition of vital signals in a natural way; (2) there is no limitation on the sites where the devices can be deployed, i.e., it can be virtually placed anywhere the person is present, such as home, office, nursing care center, hotel, etc.; (3) the application areas are significantly expanded, from infant monitoring to elderly care.

Recent years have seen the development of different technologies that are used to perform non-contact and non-invasive measurement of the vital signals, such as tube bed, Dopller radar, and UWB radar chip. In this invention, an apparatus that uses piezoelectric films as the biomedical sensor to measure the vital signal and a method to extract the vital signals from the raw data are proposed. This apparatus is easy to deploy, easy to use and cost effective. With the wireless and network communications, the apparatus can work in both tethered and non-tethered modes.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows the non-contact vital signal monitoring apparatus.

FIG. 2 shows a typical heart muscle signal.

FIG. 3 shows the heart beat signal from the piezoelectric sensor unit after filtering.

FIG. 4 shows the respiration signal from the piezoelectric sensor unit after filtering.

FIG. 5 shows the two-step method to calculate the heart rate and respiration rate

DETAILED DESCRIPTION OF THE INVENTION

Reference now will be made in details to various embodiments of the disclosure, one or more examples which are set forth below. Each example is provided in a way of explanation of the disclosure, and it should be mentioned herein that the example is not limited by this disclosure. In fact, the modifications and revisions can be made in the present disclosures without departing from the scope and departure from the disclosure.

For example, features that are illustrated as part of one embodiment in this disclosure can be used on another embodiment to achieve the same function or even a further embodiment. Therefore, it should be clear that the present disclosure covers such medications and modifications as come with the scope of the appended claims and their equivalents.

The present disclosure is generally directed to an apparatus for monitoring vitals signals of a human body, such as heart rate, respiration rate and heart rate variation in a non- contact manner. The values of heart rate, respiration rate and heart rate variation are indicators of healthy conditions of a person. In accord with the present disclosure, it has been well established that those vitals signals are symbols of some diseases and can be used as the reference for pre-treatment diagnoses of those diseases. The apparatus and method of the present disclosure can be used to collect data, analyze the data and extract vital parameters to reveal the health conditions of the person.

In this regard, FIG. 1 illustrates one embodiment of the device and its associative accessories that allows it for data storage, communication, management and sharing through remote or local network. The device is put underneath the sites where the patient lies down, sits on and leans against, or in front of the chest, over the head or beneath the foot.

The electromechanical sensor 10, in particular the piezoelectric films, converts the mechanical force that is applied on it to electrical voltage.

When mechanically deformed by external tensile or bending forces, the charges are generated on the upper and lower electrodes. The electric voltage is subsequently built due to the presence of these charges. The magnitude of the voltage is proportional to the quantities of the charges which are associated with the strength of the external forces. By measuring the voltage, the strength of the force is characterized. The muscle vibrations due to the motions of heart and respiration can generate such a force through a certain medium, such as textiles and closed-air gaps. The vibrations from these physiological activities are so weak that normal sensors are hard to detect. When applying a longitude force on the piezoelectric film, a significantly amplified transverse force is generated. This characteristic allows this material to be able to detect the forces with weak strengths. Moreover, this material is more sensitive to dynamic forces than static forces. Since muscle vibration is continuous and the force it generates is time- variant, the weak physiological signals can be reliably measured. The sensor can tolerate several million times of bending and vibration without significant degradation of sensitivity.

The materials of the sensors include but not limited to naturally occurring crystals, such as berlinite (AIPO4), sucrose, quartz, rochelle salt, topaz, tourmaline-group minerals, etc., other natural materials , such as bone, tendon, silk, wood, enamel, dentin, etc., man-made crystals, such as gallium orthophosphate (GaPO,), langasite (La;GasSiO,), etc., man-made ceramics such as barium titanate (BaTiO), lead titanate (PbTiO;), lead zirconate titanate, potassium niobate (KNbQs), lithium niobate (LiNbO;), lithium tantalate (LiTaOs), sodium tungstate (Na,WO;), zinc oxide (Zn,03), Ba;NaNbs;Os, Pb,KNbsO;5, etc.,

Lead-free piezoceramics such as sodium potassium niobate (NaKNb), bismuth ferrite (BiFeOs), sodium niobate NaNbQO;, bismuth titanate Bi, Ti;O4,, Sodium bismuth titanate

Nao 5 Bios TiOs, etc., and polymers, such as polyvinylidene fluoride (PVDF).

In this disclosure, the sensor is designed in a shape and enclosed in a casing in such a way that the longitude force can be maximized. The device is compact and robust, and the user even does not know its existence. The shape can be but not limited to wave-like, bump-like, cave-like, triangle, square, circle, etc. The length of the sensor is in the range of 1 centimeter to 5 meters, particularly 10 centimeters to 2 meters, more particularly 30 centimeters to 1 meter. The casing can be made from but not limited to materials of plastic, wooden, glass, etc.

The raw signals that sensed by the sensor is amplified, quantized and processed by the combination of amplifiers 20, analog to digital convertors, microprocessors and/or digital signal processors 30. The noisy raw data need to go through extensive processing stages of noise removal, filtering, transformation, peak detection, and period calculation in order to get clean vital data.

FIG. 2 shows an ideal physiology signal from an ECG trace. There are five identifiable features which correspond to different polarization stages that make up a heart beat process. These deflections are denoted by the letters P, Q, R, S and T. The P wave represents the atrium contraction. QRS complex and the T wave represents the ventricles actions. By detecting the R peaks through setting a threshold and measuring the time between them the heart rate can be calculated.

The threshold is not present in operating the disclosed apparatus, because the waveform sensed by the piezoelectric sensor is totally different from the ideal physiology signals. FIG. 3 shows the heart beat signal from the piezoelectric sensor unit after filtering. The waveform appears as a different number of individual waves in a jumping cycle, with their amplitudes varying linearly according to the cycle. Obviously, the period cannot be determined using threshold rectifying or simple Fourier transformation.

Autocorrelation method might be valid but it requires extensive computation, significantly increasing the load on the processor.

In this disclosure, a two-step method is proposed to identify the heart rate and respiration rate directly from the carrier signals, as shown in FIG. 5. To achieve this, four steps are proposed: (1) identifying the maximum value 302; (2) identifying the time period between two consecutive maximums 303; (3) identifying the minimum value 304; (4) identifying the time period between two consecutive minimums 305.

One counter is set up and a value is assigned to this counter before the process 301.

This counter is maintained as an indicator of being not able to larger than. If the counter is surpassed, the value that is maintained is determined as the maximum; another counter is set up and a value is assigned to this counter. This counter is maintained as an indicator of being not able to less than. If the counter is surpassed, the value that is maintained is determined as the minimum. The constants should be determined before the process, thus it has an upper limit for the period that can be identified. This upper limit is actually the reciprocal of the constants.

For instance, the frequency of a person’s heart beat in a normal condition is in a range of 0.7Hz to 1.6Hz, so the time constant during which a maximum value is maintained is set as 0.55 sec, the time constant during which a minimum value is maintained is set as 0.65 sec. When an input is not surpassed in a 0.55 sec time window, the counter starts to count, and the parameter that is being compared is set as the current value; if a new value is input into the comparator, the counter is incremented by one; if the new value is more than the previous one, the parameter that is being compared is updated as the new one, and the value of the counter is accumulated into the accumulator; if the new value is less than or equal to the previous one, the counter is incremented by one with the rest keeping the same; if the value in the counter is equal to the number of data that are generated in a period of 0.55 sec, the value in the accumulator is output. The addition of this value to 0.55 sec is the period of heart beat 306.

With the similar method, the respiration rate can be determined. In fact, with the approach, the heart rate and respiration rate can be determined simultaneously. FIG. 4 shows the respiration signal from the piezoelectric sensor unit after filtering.

This data can be stored locally in any suitable computer-readable medium or media that can be used to implement or practice the presently-disclosed subject matter, including, but not limited to, magnetic storage devices, optical storage devices, semiconductor storage device, and other form of memory devices, and the like.

The data can be accessed and visualized locally, which is a non-tethered type. It also can be accessed remotely, which is a tethered type. For a tethered type, the terminals used to display the data include, but not limited to, a standalone display, a computer monitor, and television through cable connections, or a tablet, a smart phone and PDA through a wireless connections. The wireless connection can use any of a plurality of communication standards, protocols and technologies, including but not limited to Global

System for Mobil Communications (GSM), Enhanced Data GSM Environment (EDGE), wideband code division multiple access (W-CDMA), code division multiple access (CDMA), time division multiple access (TDMA), Bluetooth, Wireless Fidelity (Wi-Fi) (e.g.

IEEE 802.11a, IEEE 802.11b, IEEE 802. 11g and/or IEEE 802.11n), Wi-MAX, Radio- frequency identification (RFID) and any other suitable communication protocols, or any combination thereof, including communications protocols that has not been developed as of the filing date of this document.

For a tethered type, the data, after a certain package process, can be connected to the servers through network communications. This communication compromises sending and/or receiving information over one or more networks of various forms. Besides the networks mentioned above, this networks particularly refer to a dial-in network, a local area network (LAN), wide area network (WAN), public switched telephone network (PSTN), the Internet, intranet or other types of networks. The communication forms include but not limited to real time data streaming, email, instant message, short message service (SMS), and any other forms that can serve the purpose.

The devices that can be used to access the data can be any devices that have network connections, such as desktop computer, server, workstation, handheld computer (such as iPod, iPod touch, or the like), mobile phone, smart phone (iPhone, Blackberry, Galaxy, or the like), or PDA (Palm) or any other suitable devices that are capable of serving the purpose.

Turning again to FIG. 1, the sensor unit 10, e.g. piezoelectric films, is put in a place where the physiology signals can be detected, e.g. underneath a mattress or a blanket on a bed. When the patient lies in the bed, the vibration signals due to the physiological activities are collected through mechanical electrical effects. The data is fed to the signal conditioning unit 20, which contains one or several stages of amplifiers, sample and hold circuits, and filters, for converting the weak physiological signals to the voltage range which can be differentiated by the signal processing unit 30. The signal processing unit, which consists of analog to digital converter, microprocessor or digital signal processor, memories, and clock circuits, serves as the core module in which the data is processed and analyzed. The two-step process that identifies the heart and respiration rate is executed in this unit.

After data extraction, the data can be transmitted by the data transmission unit 40 to the data reception unit 50 of various terminals, including tethered and non-tethered devices, through wired cable and wireless communication. The data can be stored, further processed and managed by the data storage and management unit 60. Through secure authentication, the data can be shared by the authenticated users such as family members, doctors, clinicians, nursed, etc through the data sharing unit 70. Warning signals can be given if some abnormal situations are present after associating the real time data with the pre-defined symptoms.

Vital signals from the apparatus, including heart and respiration rates, can be recorded regularly in home, nursing home, hospital, emergency and clinical situations. Several levels of information can be obtained by measuring the heart and respiration rates. First, the data can be used to verify that the subject is breathing and that the heart is beating.

Respiratory rate and pattern are indicators of respiratory physiology, whereas an irregular pulse rate can indicate cardiac abnormality. The rates can be stored over time and trends can be noted, which can provide a valuable diagnostic tool. For example, the amount of increase in heart rate in response to apneic events indicates the level of tissue hypoxia associated with sleep apnea, and changes in heart and respiratory rates can indicate the sympathetic and parasympathetic responses to trauma. Heart rate variability (HRV) can be analyzed from the heart rate. HRV, which may predict disease states, can be assessed, and heart beat-to-beat times can be assessed to determine the presence of cardiac abnormalities such as an irregular beat-to-beat time, which can indicate atrial fibrillation.

When used in home, this apparatus can allow adults to live independently longer than is currently possible because it provides a method of monitoring the live physiology data.

By keeping older adults healthy, they will maintain function and mobility, indirectly reducing dependence on caregivers and the health care system.

When used in the neonatal intensive care unit, this apparatus can monitor the breathing and heart beat conditions in 24 hours per day, 7 days per week. It can reduce the chance of the infant to develop Sudden Infant Death Syndrome (SIDS) that may pose life threaten. Moreover, it can be used in a home in a tethered mode, the doctor and clinician can remotely observe the conditions of the infants in real time. This can significantly release the load of hospital and also enhance the security level that parents currently are lack of.

These and other modifications and variations to the present disclosure can be practiced by those of ordinary skills in the art, without departing from the spirit and scope of the present disclosure, which is more particularly set forth in the appended claims. In addition, it should be understood that aspects of the various embodiments can be interchanged both in whole and in part. Furthermore, those of ordinary skill in the art will appreciate that the foregoing description is by a way of example only, and is not intended to limit the disclosure so further described in such appended claims.

Claims (18)

CLAIMS What is claimed:

1. An apparatus for monitoring the physiological signals comprising: a sensor unit, a signal condition unit, a signal processing unit, a data transmission unit, a data reception unit, a data storage and management unit and data sharing unit.

2. The apparatus of claim 1, wherein the sensor is an electromechanical sensor comprising a film.

3. The apparatus of claim 2, wherein the film is made from piezoelectric materials.

4. The apparatus of claim 1, wherein the sensor is made from bump-like or strip-like shape.

5. The apparatus of claim 1, wherein the sensor is enclosed in a plastic casing.

6. The apparatus of claim 1, wherein the device is configured as tethered and non- tethered modes.

7. The apparatus of claim 6, wherein the data and alert signals is transmitted via the internet.

8. The apparatus of claim 1, wherein the physiology data can be processed and analyzed and warning is given if abnormal situations are identified.

9. The apparatus of claim 8, wherein the data and warning signals are transferred wirelessly.

10. The apparatus of claim 1, wherein the data transmission and receiving units are not connected to one another by wire.

11. The apparatus of claim 1, wherein the data transmission and receiving units are connected to one another by wire.

12. A method of identifying heart and respiration rate compromising: identification of the maximum value, identification of the minimum value, identification of the time period between two consecutive maximums, and identification of the time period between two consecutive minimums.

13. The method of claim 12, wherein a maximum is compared and a time constant is set and maintained.

14. The method of claim 12, wherein the new identification process is triggered after determining the maximum and the time required to sustain the process is set as the foundation to calculate the period.

15. The method of claim 12, wherein the codes are repeated and the period can be calculated in real time.

16. The method of claim 12, wherein by adjusting the time constant that is not surpassed, the measurement range is adjustable.

17. The method of claim 12, wherein the same scenario is applicable to the minimum value.

18. The method of claim 12, wherein by simultaneously deploying the maximum and minimum values, the period is determined.