Description:FIELD OF INVENTION
[0001] Embodiments of the present disclosure relate to electronic wearable devices and more particularly to a system and a method for a wearable device to monitor and analyze human body vitals.
BACKGROUND
[0002] The development of medical technologies and extension of the average lifespan, there has been an increasing interest in health care. There is a huge jump in awareness and consumption of preventive health care across all over the world in recent times. We are also seeing a growing trend in fitness wearable among a section of population in India and abroad. In particular, athletes and patients, among a number of other consumers, are key individuals who require accurate and up-to-date (real-time and SD cards when the device is offline) body vital data.
[0003] Furthermore, some of the body vitals measuring device, which is a sort of health care device, measures body compositions using a bioelectrical impedance analysis. In this BIA method, an alternating low amplitude current is being applied to the human body and by measuring the electrical impedance of human body, different body compositions can be calculated by using some empirical formulae. However, such BIA devices utilize a typical sensor arrangement which can be bulky and uncomfortable for the typical wearer. In short, these market available BIA devices are neither wearable not affordable.
[0004] With advancement in technology, achieving reliable and high integrity recording however remains a challenge, especially under daily-life activities. Wearable systems have been introduced in an attempt to reduce size, improve comfort and extend the duration for monitoring. Wearable patches might monitor health metrics using a plurality of on-board sensors and detect life threatening health changes. Current technologies for monitoring electrocardiogram (ECG) data and respiratory related data uses a large number of electrodes. To ensure accurate and useful measurements, there are minimum sizes for the electrodes contact area and minimum distances between adjacent electrodes. Thus, current technology limits for a device which would measure both ECG data and respiratory related data accurately in real time.
[0005] Hence, there is a need for an improved system and method in the form of a wearable device to monitor and analyze human body vitals to address the aforementioned issue(s).
BRIEF DISCRIPTION
[0006] In accordance with an embodiment of the present disclosure, a system for wearable device to monitor and analyze human body vitals is provided. The wearable device is coupled with a human body. The wearable device includes an analog front end unit including an electrocardiogram (ECG) sensor and a respiratory sensor configured to sense electrocardiogram (ECG) and respiration analog signals respectively from the human body during at least one of workout, physical activity and rehabilitation. The analog front end unit also includes a converter configured to convert the electrocardiogram (ECG) and respiration analog signals into digital electrocardiogram (ECG) and respiration signals. The wearable device also includes a set of temperature sensors and physical sensors configured to sense temperature signal and one or more physical parameters including at least one of speed, distance, calorie count respectively from the human body during at least one of workout, physical activity and rehabilitation. The wearable device further includes a controlling unit communicably coupled to the analog front end unit and a set of temperature sensors and physical sensors. The controlling unit is configured to receive the digital electrocardiogram (ECG) and respiration signals from the converter and the temperature signal and the one or more physical parameters from the set of temperature sensors and physical sensors. The system also includes a signal processing module, located on a server, and communicably coupled to the controlling unit. The signal processing module is configured to receive the digital electrocardiogram (ECG) signals, the digital respiration signals, the temperature signal and the one or more physical parameters from the controlling unit. The signal processing module is also configured to eliminate a plurality of artifacts from the digital electrocardiogram (ECG), respiration signals, the temperature and the one or more physical parameters using one or more filtration technique to obtain absolute biophysical signals, wherein the plurality of artifacts includes loose lead artifact, wandering baseline artifact, muscle tremor artifact, electromagnetic interference, DC shift and AC noise. The signal processing module is further configured to calculate the human body vitals based on corresponding absolute biophysical signals using a least mean square technique, thereby, analyzing response of the human body during workout, physical activity or rehabilitation, wherein the human body vitals include heart rate, respiration rate, speed, distance covered, and calories burnt.
[0007] In accordance with another embodiment of the present disclosure, a method to operate for a wearable device to monitor and analyze human body vitals is provided. The method includes sensing, by an electrocardiogram (ECG) sensor and a respiratory sensor of an analog front end unit, electrocardiogram (ECG) and respiration analog signals respectively from the human body during at least one of workout, physical activity and rehabilitation. The method also includes converting, by a converter of the analog front end unit, the electrocardiogram (ECG) and respiration analog signals into digital electrocardiogram (ECG) and respiration signals. The method further includes sensing, by a set of temperature sensors and physical sensors, temperature signal and one or more physical parameters including at least one of speed, distance, calorie count respectively from the human body during at least one of workout, physical activity and rehabilitation. The method further includes receiving, by a controlling unit, the digital electrocardiogram (ECG) and respiration signals from the converter and the temperature signal and the one or more physical parameters from the set of temperature sensors and physical sensors, wherein the analog front end unit, the set of temperature sensors and physical sensors and the controlling unit are located inside the wearable device. The method further includes receiving, by a signal processing module, the digital electrocardiogram (ECG) signals, the digital respiration signals, the temperature signal and the one or more physical parameters from the controlling unit. The method further includes eliminating, by the signal processing module, a plurality of artifacts from the digital electrocardiogram (ECG), respiration signals, the temperature and the one or more physical parameters using one or more filtration technique to obtain absolute biophysical signals, wherein the plurality of artifacts includes loose lead artifact, wandering baseline artifact, muscle tremor artifact, electromagnetic interference, DC shift and AC noise. The method further includes calculating, by the signal processing unit, the human body vitals based on corresponding absolute biophysical signals using a least mean square technique, thereby, analyzing response of the human body during workout, physical activity or rehabilitation, wherein the human body vitals include heart rate, respiration rate, speed, distance covered, and calories burnt.
[0008] To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.
BRIEF DESCRIPTION OF THE DRAWINGS
The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which:
[0009] FIG. 1 is a block diagram representation of a system for a wearable device to monitor and analyze human body vitals in accordance with an embodiment of the present disclosure;
[00010] FIG. 2 is a schematic representation of an internal block diagram of the analog front end unit IC of FIG. 1 in accordance with an embodiment of the present disclosure;
[00011] FIG. 3 is a schematic representation of an internal structure of the microcontroller of FIG. 1 in accordance with an embodiment of the present disclosure;
[00012] FIG. 4 is a schematic representation of an exemplary embodiment of the system of FIG. 1 in accordance with an embodiment of the present disclosure;
[00013] FIG. 5(a) and 5(b) is a graphical representation of yet another exemplary embodiment of the system of FIG. 4 in accordance with an embodiment of the present disclosure; and
[00014] FIG. 6(a) and 6(b) illustrates a flow chart representing steps involved in a method for wearable device to calculate human body vitals in accordance with an embodiment of the present disclosure.
[00015] Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.
DETAILED DESCRIPTION
[00016] For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure.
[00017] The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more devices or sub-systems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.
[00018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.
[00019] In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.
[00020] Embodiments of the present disclosure relate to a system and method for wearable device to measure and monitor human body vitals. The human body vital sign monitoring outside the clinical environment based on wearable sensors ensures better support in assessing a patient’s health condition, and in case of health deterioration, appropriate actions might be taken. In everyday life, the users perform different physical activities, and considering that vital sign measurements depend on the intensity of the activity, As used herein, the human body vital signs are measurements of the body's most basic functions. There are few main vital signs routinely monitored by medical professionals and health care providers which includes body temperature, pulse rate, respiration rate (rate of breathing), heart rate or the like. The human body vital signs are useful in detecting or monitoring medical problems. The human body vital signs may be measured in a medical setting, at home, at the site of a medical emergency, or elsewhere using medical devices or wearable devices.
[00021] In recent years, human activity recognition (HAR) has been investigated using various types of sensors, smartphones, body-attached sensors, ambient sensors, video-based information, or the like. Considering the privacy concerns of installing a camera in private spaces, sensor-based activity recognition has dominated the recent research. Furthermore, the advantage of using a smartphone or body-attached sensors for activity recognition is that the person can move freely, at home or at work, while being continuously monitored without dependence on the environment. The wearable devices have limited space available for contact with a patient. The wearable device is most effective when it is as small and unobtrusive as possible to the patient, because the patient will be more likely to wear the device long term and there is a lower likelihood of the wearable device being inadvertently dislodged or otherwise inadvertently disabled. Accordingly, reducing the required surface area of contact with the patient is important to its effective and continuous use. Furthermore, minimizing the weight of a wearable device is important so the method of securing the wearable device to the user may be less harmful to the skin of the user.
[00022] According to certain aspects of the present disclosure, integration of ECG measurement and respiratory rate measurement along with the other vital physical parameters is achieved in the same hardware. Thus, the system may detect ECG electrical activity, while also performing respiration rate analysis and monitors the other important physical parameters related to human body. Various aspects and features of the system to monitor and analyze using a wearable device is further described from FIG. 1 onwards.
[00023] FIG. 1 is a block diagram representation of a system (10) for a wearable device (20) to monitor and analyze human body vitals in accordance with an embodiment of the present disclosure. The system (10) includes the wearable device (20) coupled with a human body. In one embodiment, the wearable device (20) may include a wearable shirt, a wearable snap fit strap or a wearable patch. As used herein, the wearable shirt is a clothing which monitors the wearer's physical condition. The wearable shirts and body suits provide biometric data and physical data, such as pulse rate, temperature, muscle stretch, heart rhythm and physical movement, and the like. Similarly, the wearable snap-fit strap is a wearable around the body part like chest for heart rate monitoring Most of them are made of a long, belt-like elastic band that wraps snugly around the chest, a small electrode pad which sits against skin, and a snap-on transmitter. Such heart-rate monitors work differently than the ubiquitous wrist-bound monitors on new wearables because they use electrocardiography to record the electrical activity of the heart. This process requires electrodes, which live in the shiny, flat pad against the skin. That pad needs moisture water or sweat to pick up any electrical signal. When the user is working out and sweating, the electrodes pick up the electrical signals given off by your heartbeat, and they send that information to the transmitter. Similarly, the wearable patches are a kind of wearable sensor used in the medical industry. They are applied to a patient's skin with adhesive and feature foam part and embedded electronics to monitor the patient's physiological signs such as their pulse.
[00024] Further, the wearable device (20) includes an analog front end unit (30) including an electrocardiogram (ECG) sensor (40) and a respiratory sensor (50) configured to sense electrocardiogram (ECG) and respiration analog signals respectively from the human body during at least one of workout, physical activity and rehabilitation. Also, the analog front end unit (30) includes a converter (35) which is configured to convert the electrocardiogram (ECG) and respiration analog signals into digital electrocardiogram (ECG) and respiration signals. As used herein, ECG is a test that detects and records the strength and timing of the electrical activity in the heart. The electrocardiogram (ECG) sensor (40) records from the body surface and registers the differences in electrical potential generated by the heart. The signal recorded is determined by action potentials generated by millions of individual cells and their sequence of activation. This information is recorded on a graph that shows each phase of the electrical signal as the electrical signal travels through the heart The most vital part of ECG signal processing is analyzing and understanding the QRS complex waveform. In which, 'R'-wave is a very important section of this complex and plays a pivotal role in the interpretation of heart rhythm anomalies. The ECG signal also determines different relevant features of the heart.
[00025] Similarly, the respiratory sensor (50) is used to measure the rate of respiration of a living organism by measuring its rate of exchange of oxygen and/or carbon dioxide. The respiratory sensor (50) allow investigation into how factors such as age, or chemicals affect the rate of respiration. In one embodiment, the respiratory sensor (50) uses a sample of every exhaled breath where carbon dioxide level (CO2) is continually measured and analyzed. In a specific embodiment, the analog front end unit (30) may be a ADS1292R. This IC is meant to specifically capture ECG and respiration analog signals from body and convert the ECG and respiration analog signals to digital form. The R in ADS1292R part number stands for respiration, which means that IC is capable to receive respiration waveforms as well. The resolution of the ADC is 24bit. The internal block diagram for the IC is shown in FIG. 2
[00026] Referring back to FIG. 1, the wearable device (20) further includes a set (60) of temperature sensors (70) and physical sensors (80) which are configured to sense temperature signal and one or more physical parameters respectively from the human body during at least one of workout, physical activity and rehabilitation. The one or more physical parameters includes at least one of speed, distance, calorie count or the like. As used herein, the temperature sensor (70) is an electronic device which measures the temperature of a body or an environment and converts the input data into electronic data to record, monitor, or signal temperature changes. Similarly, as used herein, the physical sensor (80) is a device which measures a physical quantity (such as speed, distance, calorie count or the like) and converts the physical quantity into a signal which may be read by an observer or by an instrument. In one embodiment, the one or more physical sensors (80) may include position sensor, pressure sensor, accelerometer or the like.
[00027] Furthermore, the wearable device (20) includes a controlling unit (90) communicably coupled to the analog front end unit (30) and a set (60) of temperature sensors and physical sensors. The controlling unit (90) is configured to receive the digital electrocardiogram (ECG) and respiration signals from the converter (35) and the temperature signal and the one or more physical parameters from the set (60) of temperature sensors and physical sensors. In one embodiment, the controlling unit (90) receives the digital ECG and respiration signals using a communication module (100) such as wi-fi module. In such an embodiment, the Wi-Fi module as used herein may be a USR-C322 IC. The wi-fi modules convert the serial port or TTL to comply with the wi-fi wireless network communication standard. An IoT wi-fi module may use wi-fi to connect to the Internet directly. In some embodiments, the controlling unit (90) as used herein may be a microcontroller having part number TM4C1294NCPDT. The internal structure of the microcontroller is shown in FIG. 3.
[00028] Returning back to FIG. 1, in one embodiment, the form factor of the wearable device (20) may be 5x8 centimeters. In a preferred embodiment, the wearable device (20) may include a power unit (110) including a plurality of batteries which is configured to provide power to a plurality of units of the wearable device (20). The plurality of units such as the electrocardiogram (ECG) sensor (40) and the respiratory sensor (50), the convertor 30, the temperature sensor (70), the one or more physical sensors (80) and the wi-fi module. In such an embodiment, the power unit (110) may include rechargeable batteries such as Nickel-metal-hybrid (NiMH or Ni-MH) battery or Lithium-ion (Li-ion) and Lithium-ion polymer. In one embodiment, the wearable device (20) may include humidity proof structure using humidity resistive materials and integrate them as per the standard materials. In another embodiment, the elevated heat sinks may also reduce the humidity accumulation without compromising on the signal strength.
[00029] Additionally, the system further includes a signal processing module (120) which is located on a server (130). In one embodiment, the server (130) may be a cloud server. In such an embodiment, the cloud server may be in communication or reside in any computing device (not shown in FIG. 1). In another embodiment, the server (130) may be a local server of any computing device. In such embodiments, the computing devices may include mobile, personal computer laptop, tablet or the like. The signal processing module (120) is communicably coupled to the controlling unit (90) via the communication module (100). The signal processing module (120) is configured to receive the digital electrocardiogram (ECG) signals, the digital respiration signals, the temperature signal and the one or more physical parameters from the controlling unit (90). In one embodiment, the system (10) may include a storage module (140) which is located on the server (130). The storage module (140) is communicably coupled to the controlling unit (90) of the wearable device (20). The storage module (140) is configured to store the digital electrocardiogram (ECG) and respiration signals, the temperature signal and the one or more physical parameters from the controlling unit (90) via the communication module (100).
[00030] The signal processing unit (120) is also configured to eliminate a plurality of artifacts from the digital electrocardiogram (ECG), respiration signals, the temperature and the one or more physical parameters using one or more filtration technique to obtain absolute biophysical signals. The plurality of artifacts includes loose lead artifact, wandering baseline artifact, muscle tremor artifact, electromagnetic interference, DC shift and AC noise. In one embodiment, the one or more filtration technique may include at least one of a low pass filtration technique and a band pass filtration technique. The artifacts on the electrocardiogram may result from a variety of internal and external causes from Parkinsonian muscle tremors to dry electrode gel. For example, the undesirable artifacts, are eliminated when the ECG signal is low pass filtered with a preset cutoff frequency for example 50Hz, since the highest frequency power of the ECG signal is between 0.1 Hz and 45 Hz. As used herein, the loose lead artifact occurs when dealing with patients who are diaphoretic because the electrodes simply will not stick to the patient’s body or placing the electrode over hair. The wandering baseline artifact presents as a slow, undulating baseline on the electrocardiogram. Such artifact may be caused by patient movement, including breathing. The Muscle tremor (or tension) artifact is a type of motion artifact, occurs when patient is cold and shivering. However, it can also happen when patients prop themselves up by their arms. The Electromagnetic interference (EMI) artifact usually results from electrical power lines, electrical equipment in the vicinity. The DC shift occurs when the small impurities within the metal electrode encounters. The ECG signal is corrupted by different noises which include baseline wander (BW), power line interference (PLI), muscle artefact (MA) and instrumentation noise (IN). For example, AC interference in such ECG signals is shown to exhibit two qualities especially relevant to filter design: considerable deviations from a nominal 50 Hz frequency and substantial noise at higher harmonics.
[00031] One of the example, to eliminate the aforementioned plurality of artifacts may include removing the plurality of artifacts using adaptive subtraction method. This method contains QRS detection, formation of electrocardiogram template by averaging the electrocardiogram complexes, using low pass filter to remove undesirable artifacts and subtraction. The QRS detection algorithm is used to identify the position of the ECG artifacts in the signal. This algorithm is applied to ECG signal. The second step is formation of ECG template that contaminated the EMG signal. This could be done by averaging the ECG complexes based on assumption that the EMG has a zero mean Gaussian distribution, so the ECG template set is consisting of QRS detection and a subtraction template, which is selected from the averaged waveform. The subtraction template presented longer duration including the complete ECG waveform (the whole QRS complex as well as P and T waves), which is used to subtract the ECG artifacts from the signal. Further, the low pass filter is used to remove undesirable artifacts, after creating ECG template, this signal was low pass filtered with a preset cutoff frequency. In the subtraction step, the created ECG template is subtracted from contaminated signals in places where there is an R wave.
[00032] Moreover, the signal processing unit (120) is further configured to calculate the human body vitals based on corresponding absolute biophysical signals using a least mean square technique, thereby, analyzing response of the human body during workout, physical activity or rehabilitation. The human body vitals include heart rate, respiration rate, speed, distance covered, and calories burnt. For regular heart rhythms, heart rate may easily be estimated using the large squares (0.2s) on an ECG. Simply identify two consecutive R waves and count the number of large squares between them. By dividing this number into 300 (represents 1 minute) a person’s heart rate is calculated.
Heart Rate = 300 / number of large squares between consecutive R waves.
[00033] Similarly, in one embodiment, respiration rate may be calculated is through the concept of VO2 max, which is the maximum amount of oxygen the body can use during exercise. VO2 max is a function of both heart rate and respiration rate, and can be estimated using the following formula:
VO2 max = (maximum heart rate x stroke volume) x (maximum respiratory rate x tidal volume).
[00034] In this formula, stroke volume refers to the amount of blood pumped by the heart with each beat, and tidal volume refers to the amount of air taken in with each breath.
[00035] In some embodiments, calories may be calculated using below formula
Calories burned per minute = [(heart rate - resting heart rate) / (maximum heart rate - resting heart rate)] x (resting metabolic rate / 60)
[00036] In this formula, the resting metabolic rate refers to the number of calories your body burns at rest, per minute.
[00037] In one embodiment, the distance may be calculated using below formula:
Distance traveled = (calories burned / weight in kilograms) / 1.036
[00038] In this formula, resting heart rate refers to your heart rate when you are at rest, and weight is measured in kilograms. The value 1.036 is a constant that represents the energy cost of running a mile (1.6 kilometers).
[00039] In such an embodiment, the speed may be calculated as:
Speed = distance/time

[00040] FIG. 4 is pictorial representation of an exemplary embodiment (150) of the system (10) of FIG. 1 of the present disclosure. Considering an example where user X (160) is wearing a shirt (170) including the wearable device (20). The user X (160) wears the shirt (170) during an exercise session. The electrocardiogram (ECG) sensor (40) and a respiratory sensor (50) associated with the shirt (170) senses an electrocardiogram (ECG) and respiration analog signals respectively from the body of the user X (160) during the exercise. The analog signals associated with ECG and respiration measurement is converted into digital signals using a converter (35) associated with the shirt for further processing. The set (60) of temperature sensors (70) and physical sensors (80) associated with the shirt senses temperature signal and one or more physical parameters such as speed, distance, calorie count or the like respectively from the body of the user X during the exercise. Such signals sensed by the analog front end unit (30) and a set (60) of temperature sensors and physical sensors is sent to a controlling unit (90) such as a microcontroller via wi-fi module, where the microcontroller sent such signals to a signal processing module (120) of the system. The signal processing unit (120) is located in a mobile phone (180) of the user X (160) as an application. The signal received by the signal processing module is further used to eliminate the artifacts from the signals to obtain absolute value of the signals. Various artifacts such as loose lead artifact, wandering baseline artifact, muscle tremor artifact, electromagnetic interference, DC shift and AC noise are removed using adaptive subtraction method from the digital signals which gives the absolute (error free) biophysical signals. Further, the heart rate, respiration rate, speed, distance covered, and calories burnt during the exercise by the user X is calculated and represented to the user X in his mobile phone application. Such indication makes the user X aware of his current condition as well as alert the user in case of any red flag condition. Exemplary graphical representation of heart rate and respiration rate for user X is shown in FIG 5.
[00041] FIG. 5(a) and 5(b) is a graphical representation (200) of yet another exemplary embodiment of the system (10) of FIG. 4 in accordance with an embodiment of the present disclosure. The waveform 5(a) shows a first scenario where ECG signals looks cleaner without any filtration technique applied. However, the shape of the waveform is not proper. At the same time, the respiration signals look cleaner. Similarly, the waveform 5(b) shows a second scenario where ECG signals are present, however, the ECG signals are not cleaner and need the application of the filtration technique. However, respiration signals look cleaner.
[00042] FIG. 6(a) and 6(b) illustrates a flow chart representing steps involved in a method (300) for wearable device to calculate human body vitals in accordance with an embodiment of the present disclosure. The method (300) includes sensing, by an electrocardiogram (ECG) sensor and a respiratory sensor of an analog front end unit, electrocardiogram (ECG) and respiration analog signals respectively from the human body during at least one of workout, physical activity and rehabilitation in step 310. The method (300) includes converting, by a converter of the analog front end unit, the electrocardiogram (ECG) and respiration analog signals into digital electrocardiogram (ECG) and respiration signals in step 320. The method (300) further includes sensing, by a set of temperature sensors and physical sensors, temperature signal and one or more physical parameters comprising at least one of speed, distance, calorie count respectively from the human body during at least one of workout, physical activity and rehabilitation in step 330. The method (300) also includes receiving, by a controlling unit, the digital electrocardiogram (ECG) and respiration signals from the converter and the temperature signal and the one or more physical parameters from the set of temperature sensors and physical sensors in step 340. The analog front end unit, the set of temperature sensors and physical sensors and the controlling unit are located inside the wearable device. In one embodiment, the wearable device may be a wearable shirt, a wearable snap-fit strap or a wearable patch. In some embodiments, the form factor of the wearable device may be 5x8 centimeters. In a preferred embodiment, the method may include providing power, by a power unit comprising a plurality of batteries, to a plurality of units comprising the electrocardiogram (ECG) sensor and the respiratory sensor, the convertor, the temperature sensor and the one or more physical sensors. In some embodiments, the method may include store, by a storage module, the digital electrocardiogram (ECG) and respiration signals, the temperature signal and the one or more physical parameters. In such an embodiment, the storage unit is located on the server. In one embodiment, the server may be a cloud server. In such an embodiment, the cloud server may be in communication or reside in any computing device. In another embodiment, the server may be a local server of any computing device. In such embodiments, the computing devices may include mobile, personal computer laptop, tablet or the like.
[00043] Subsequently, the method (300) includes receiving, by a signal processing module, the digital electrocardiogram (ECG) signals, the digital respiration signals, the temperature signal and the one or more physical parameters from the controlling unit in step 350. The method (300) further includes eliminating, by the signal processing module, a plurality of artifacts from the digital electrocardiogram (ECG), respiration signals, the temperature and the one or more physical parameters using one or more filtration technique to obtain absolute biophysical signals in step 360. The plurality of artifacts comprises loose lead artifact, wandering baseline artifact, muscle tremor artifact, electromagnetic interference, DC shift and AC noise. In on embodiment, the one or more filtration technique may include at least one of a low pass filtration technique and a band pass filtration technique. Moreover, the method (300) includes calculating, by the signal processing unit, the human body vitals based on corresponding absolute biophysical signals using a least mean square technique, thereby, analyzing response of the human body during workout, physical activity or rehabilitation in step 370. The human body vitals may include heart rate, respiration rate, speed, distance covered and calories burnt.
[00044] Various embodiments of the system and method for a wearable device to monitor and analyze human body vitals as described above enables monitoring bio physical information of an individual such as Heart Rate, Temperature, Respiration rate. The design and arrangement of the sensors and the plurality of units enables the user convenience for measuring body vitals. The system empowers people with the information they need to better manage their health and the health of their loved ones.
[00045] The system may address the data storage requirements for health and wellness management, chronic disease management or patient recovery, medication management, and fitness and workout tracking. For example, a sport or fitness enthusiast may desire to monitor, collect, and/or analyze various aspects of the fitness routine (such as their heart rate, respiration rate, and so forth) to determine how to improve and adjust their fitness routine to increase its efficacy. The parameters are ECG, respiration, Heart Rate, temperature, which are collected/sampled and transmitted to the server for further analysis. This data can be viewed over mobile phones also. The monitoring instrument is a handheld sort of device which gets embedded to smart wearables. This has all the required electrodes/sensors embedded at respective positions. This device is battery operated and should support enough power for the entire exercise episode. This device is humidity proof as well.
[00046] It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the disclosure and are not intended to be restrictive thereof.
[00047] While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.
[00048] The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, the order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples. , Claims:1. A system (10) for a wearable device (20) to monitor and analyze a plurality of human body vitals comprising:
the wearable device (20) coupled with a human body, wherein the wearable device (20) comprises:
an analog front end unit (30) comprising:
an electrocardiogram (ECG) sensor (40) and a respiratory sensor (50) configured to sense electrocardiogram (ECG) and respiration analog signals respectively from the human body during at least one of workout, physical activity and rehabilitation; and
a converter (35) configured to convert the electrocardiogram (ECG) and respiration analog signals into digital electrocardiogram (ECG) and respiration signals;
a set (60) of temperature sensors (70) and physical sensors (80) configured to sense temperature signal and one or more physical parameters comprising at least one of speed, distance, calorie count respectively from the human body during at least one of workout, physical activity and rehabilitation;
a controlling unit (90) communicably coupled to the analog front end unit (30) and a set (60) of temperature sensors (70) and physical sensors (80), wherein the controlling unit (90) is configured to receive the digital electrocardiogram (ECG) and respiration signals from the converter (35) and the temperature signal and the one or more physical parameters from the set (60) of temperature sensors (70) and physical sensors (80); and
a signal processing module (120), located on a server (130), and communicably coupled to the controlling unit (90), wherein the signal processing module (120) is configured to:
receive the digital electrocardiogram (ECG) signals, the digital respiration signals, the temperature signal and the one or more physical parameters from the controlling unit (90);
eliminate a plurality of artifacts from the digital electrocardiogram (ECG), respiration signals, the temperature and the one or more physical parameters using one or more filtration technique to obtain absolute biophysical signals,

wherein the plurality of artifacts comprises loose lead artifact, wandering baseline artifact, muscle tremor artifact, electromagnetic interference, DC shift and AC noise; and
calculate the human body vitals based on corresponding absolute biophysical signals using a least mean square technique, thereby, analyzing response of the human body during workout, physical activity or rehabilitation, wherein the human body vitals comprises heart rate, respiration rate, speed, distance covered and calories burnt.
2. The system (10) as claimed in claim 1, wherein the wearable device (20) comprises a wearable shirt, a wearable snap-fit strap or a wearable patch.
3. The system (10) as claimed in claim 1, wherein the form factor of the wearable device (20) comprises 5x8 centimeters.
4. The system (10) as claimed in claim 1, wherein the wearable device (20) comprises a power unit (110) comprising a plurality of batteries configured to provide power to a plurality of units comprising the electrocardiogram (ECG) sensor (40) and the respiratory sensor (50), the convertor (35), the temperature sensor (70) and the one or more physical sensors (80).
5. The system (10) as claimed in claim 1, wherein the wearable device (20) comprises humidity proof structure using humidity resistive materials integrated with standard materials, wherein the humidity proof structure comprises elevated heat sinks to reduce the humidity accumulation without compromising on the signal strength.
6. The system (10) as claimed in claim 1, comprising a storage module located on the server, wherein the storage module (140) is configured to store the digital electrocardiogram (ECG) and respiration signals, the temperature signal and the one or more physical parameters.
7. The system (10) as claimed in claim 1, wherein the one or more filtration technique comprises at least one of a low pass filtration technique and a band pass filtration technique.
8. A method (300) for operating a wearable device to monitor and analyze human body vitals comprising:
sensing, by an electrocardiogram (ECG) sensor and a respiratory sensor of an analog front end unit, electrocardiogram (ECG) and respiration analog signals respectively from the human body during at least one of workout, physical activity and rehabilitation; (310)
converting, by a converter of the analog front end unit, the electrocardiogram (ECG) and respiration analog signals into digital electrocardiogram (ECG) and respiration signals; (320)
sensing, by a set of temperature sensors and physical sensors, temperature signal and one or more physical parameters comprising at least one of speed, distance, calorie count respectively from the human body during at least one of workout, physical activity and rehabilitation; (330)
receiving, by a controlling unit, the digital electrocardiogram (ECG) and respiration signals from the converter and the temperature signal and the one or more physical parameters from the set of temperature sensors and physical sensors,
wherein the analog front end unit, the set of temperature sensors and physical sensors and the controlling unit are located inside the wearable device; (340)
receiving, by a signal processing module, the digital electrocardiogram (ECG) signals, the digital respiration signals, the temperature signal and the one or more physical parameters from the controlling unit; (350)
eliminating, by the signal processing module, a plurality of artifacts from the digital electrocardiogram (ECG), respiration signals, the temperature and the one or more physical parameters using one or more filtration technique to obtain absolute biophysical signals,
wherein the plurality of artifacts comprises loose lead artifact, wandering baseline artifact, muscle tremor artifact, electromagnetic interference, DC shift and AC noise; and (360)
calculating, by the signal processing unit, the human body vitals based on corresponding absolute biophysical signals using a least mean square technique, thereby, analyzing response of the human body during workout, physical activity or rehabilitation, wherein the human body vitals comprises heart rate, respiration rate, speed, distance covered and calories burnt. (370)
9. The method (300) as claimed in claim 8, wherein eliminating the plurality of artifacts from the digital electrocardiogram (ECG), the respiration signals, the temperature and the one or more physical parameters using the one or more filtration technique comprises an adaptive subtraction method comprising the steps of:
detecting QRS in the digital electrocardiogram (ECG), the respiration signals, the temperature and the one or more physical parameter;
forming electrocardiogram template by averaging the electrocardiogram (ECG) complexes;
removing the plurality of artifacts from averaged electrocardiogram (ECG) complexes using a low pass filter; and
subtracting electrocardiogram template from the digital electrocardiogram (ECG), the respiration signals, the temperature and the one or more physical parameter to obtain the absolute biophysical signals.
Dated this 22nd day of February 2023

Signature

Jinsu Abraham
Patent Agent (IN/PA-3267)
Agent for the Applicant