International Journal of Scientific Research and Engineering Studies (IJSRES) Volume 1 Issue 5, November 2014 ISSN: 2349-8862

Smart Non-Invasive Wearable Health Monitoring System Mayank Gerald Patrick Sajid Husain Arastu Rohit Jain Department of Electrical and Electronic Engineering, Manipal Institute of Technology, Manipal University, Manipal, Karnataka State, India

Abstract: The design and development of a ZigBee based smart non-invasive wearable physiological parameters monitoring device has been developed and reported in this paper. The device is of low cost that can be used to monitor physiological parameters, such as body temperature, pulse rate and body acceleration, of a human subject. The system consists of an electronic device which is worn on the wrist and finger, by an elderly or at-risk person. Using several sensors to measure different vital signs, the person is wirelessly monitored within his own home. The impact sensor is used to detect falls. The device is battery powered for outdoor use. The device can be easily adapted to monitor athletes and infants. A prototype of the device has been fabricated and extensively tested with good results. Keywords: Body temperature measurement, fall detection, heart rate measurement, home monitoring, physiological parameters, sensors, wireless transmission, ZigBee, Arduino.

I.

INTRODUCTION

Health monitoring systems have become a hot topic and important research field today. Research on health monitoring were developed for many applications such as military, homecare unit, hospital, sports training and activity emergency monitoring system. In this project, we are developing a wearable and real-time monitoring system of some critical vital signs for people. That system may help doctor or people in family monitor the emergency alarm from patient or elderly people. The vital signs of health status that are the important parameter in health monitoring system consist of blood pressure, heart rate, oxygen saturation, body temperature, ECG pattern, blood glucose level and respiratory rate. Wireless sensing units integrate wireless communications and mobile computing with transducers to deliver a sensor platform which is inexpensive to install in numerous applications. Indeed, co-locating computational power and radio frequency (RF) communication within the sensor unit itself is a distinct feature of wireless sensing. Today, the www.ijsres.com

progress in science and technology offers miniaturization, speed, intelligence, sophistication, and new materials at lower cost, resulting in the development of various highperformance smart sensing system. Many new research is focused at improving quality of human life in terms of health [1] by designing and fabricating sensors which are either in direct contact with the human body (invasive) or indirectly (non-invasive). One of the reasons for more development in this area is the global population and rise in ageing population [2], one statistic provided by the National Centre for Biotechnology Information is these are the present scenario of India’s overall geriatric healthcare sector:  India has thus acquired the label of “an ageing nation” with 7.7% of its population being more than 60 years old.  About 59% of the geriatric population stated that the nearest government facility was 3 kilometres from their homes.  Since 75% of the elderly reside in rural areas, it is mandatory that geriatric health care services be made a part of the primary health care services. This results in a requirement for medical care, which is expensive for long-term monitoring and long waiting lists for consultations with health professionals. The cost of hospitalization is ever increasing, so is the cost of rehabilitation after a major illness or surgery. Hospitals are looking at sending people back as soon as possible to recoup at home. During this recovery period, several physiological parameters need to be continuously measured. Hence, telemedicine and remote monitoring of patients at home are gaining added importance and urgency [3]–[5]. Patients are being monitored using a network of wireless sensors [6]. Many elderly people dread the idea of being forced to live with their adult children, or in a rest home or in other sheltered living arrangement. They want to live independently and keep control of their own lives. Yet at the same time they know there is a high risk of injury or even death because of a fall or stroke. Such people need to be monitored continuously and provided with immediate medical help and attention when required. We seek to come up with solutions, which help to remove anxiety. As a result, there is a need for an accurate,

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International Journal of Scientific Research and Engineering Studies (IJSRES) Volume 1 Issue 5, November 2014 ISSN: 2349-8862 flexible, non-invasive, comfortable, reliable and low cost monitoring units that unites all these demands. In this paper, a wireless, low-cost system that can be used to monitor physiological parameters, such as temperature, pulse rate of a human subject has been developed. The system cost is around sixty percent lower as compared to the commercially available ones. Also, we noted that the commercially available systems have limited capability on the number of parameters they can monitor and measure. The system developed by us has the capability of transmitting data by wireless means which other systems lack. Hence, a one-toone comparison of our system with other systems is not possible. Albeit each system uses different technology, caters to different need and use. The system which we have developed gives a good framework for productisation; it encompasses different sensors for monitoring and measurement with wireless means. There is an increasing demand for long-term health monitoring which is affordable, continuous, and unobtrusive [7], which will result in considerable impact on annual medical costs [1] and health management [8], [10]. Wearable systems for continuous health monitoring are a key technology in helping the transition to more practical and affordable healthcare. It not only allows the user to closely monitor changes in her or his physiological parameters but also provides feedback to help maintain an optimal health status. Currently, there are monitoring products in the market that are aimed to provide emergency assistance to senior citizens, rehabilitation patients, and medically or physically challenged individuals, but these have limitations. St. John’s and Medic Alert’s Lifelink™ [9] allows the user to set off an alarm manually if they are under medical stress, which will then dial designated contact phone numbers. The fundamental problem with this system is that when medical emergencies happen to the user, they are often unconscious and unable to press an “emergency alert button.” There is no product on the market which does not require manual activation of the alarm and monitors a user’s vital signs smartly, though research is currently undergoing [11]. Major disadvantages with the health monitoring devices are that they are not very easy to use, somewhat intrusive and of course, very expensive. From researching prices of similar devices, they cost anywhere from $500 to $5000 which converts to an exorbitant amount for the Indian population [13]. The reported device consists of a wrist strap and a finger clip (circuitry). This allows the sensors to be mounted around the wrist and finger and the Arduino UNO microcontroller unit connected via single strand wires. In Section II, we present the complete system overview. All the sensors are explained in Section III. The hardware details are in Section IV and the algorithms in Section V. The prototype and test results are discussed in Section VI. This paper ends with a discussion on future developments.

II.

from the three sensors to measure physiological parameters of human (temperature, heart rate and detection of any fall). The inputs from the sensors are integrated and processed. The results are sent through the ZigBee Module located on the device to another receiver ZigBee module near a remote computer, which stores the data into an Access Database. The values can then be displayed on the Graphical User Interface (GUI) running on a computer.

Figure 1: Functional block diagram of system hardware Beat per minute (BPM), body temperature, and impact (in both axes) are given on the display. The design is modular which makes it rather easy and straight forward to add extra sensors for measuring and monitoring other parameters. The hardware blocks are explained in full details in a later section.

III.

DETAILS OF THE SENSING SYSTEM

The current version of the system consists of three sensors: a temperature sensor, heart rate sensor, and an impact sensor. The description of individual sensors follows. A. TEMPERATURE SENSOR The temperature measurement is done using a LM35 precision integrated-circuit temperature sensor. It provides an accuracy of +/- 0.5°C at +25°C. It has a very low current drain of 60 μA. It rated for full −55°C to +150°C range. This sensor is mounted within the wrist strap, positioned in such a way that it is in contact with the skin, allowing it to measure the external temperature of the skin. From the skin temperature, the body temperature is estimated. There can be different methods to estimate the exact body temperature from skin temperature, but with a rough estimation usually the body temperature is 5.1 C higher than skin temperature [14]. Because an exact measurement of body temperature is not required, this method is suitable. Rather, relative changes are monitored within set thresholds, which set off the alarm. This allows the device to detect changes in body temperature that could indicate the patient is undergoing any of the following conditions: trauma, injury, heart attack, stroke, heat exhaustion and burns [12].

SYSTEM OVERVIEW

Fig 1 shows the functional block diagram of the system hardware. The system has been designed to take several inputs www.ijsres.com

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International Journal of Scientific Research and Engineering Studies (IJSRES) Volume 1 Issue 5, November 2014 ISSN: 2349-8862 B. HEART RATE SENSOR Heart rate is the number of heartbeats recorded per minute typically recorded as Beats per Minute (BPM). A custom heart rate sensor is used to read the patient's beats per minute. The sensor is a small and less expensive one. The technique used to measure the heart rate is based on near-infrared (NIR) spectroscopy. NIR spectroscopy involves using light in the wavelength of 700- 900nm to measure blood volume. At these wavelengths most tissues do not absorb light - other than haemoglobin (which is what we are interested in). This allows for designing a non-invasive and low cost method of measuring the pulse. A silicon phototransistor and a Ga-As infrared emitting diode is used in the sensor, mounted side-byside in a single black plastic package in the form of a clip. The amount of light that is detected by the phototransistor varies with the patient’s heart pulse, as the amount of absorbed IR light changes with the flow of blood, which is directly linked to the heart rate. This signal is then amplified, filtered and sent to the GUI to be analysed [14].

Figure 2: IR LED and phototransistor location

Figure 3: The circuit schematic of heart rate measurement circuit The sensor after filtering provided a clean wave that when observed on an oscilloscope confirmed that the sensor was correctly measuring the patients pulse. To get the best and most accurate results with the heart rate sensor, we chose to measure the pulse at the index finger’s tip like commercial device do. Nevertheless, it was checked for working on other fingers too. The sensor after filtering provided a clean wave that when observed on an oscilloscope confirmed that the sensor was correctly measuring the patients pulse. 120k samples at 4 kHz (samples are taken over 30 seconds) was taken and the peaks counted were doubled to get bpm.

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Figure 4: The comparison of heart rate measurement Fig 4 shows the comparison of heart rate measurement with a standard instrument and it is seen that the maximum error is 2 bpm. C. IMPACT SENSOR(ACCELEROMETER) Accelerometer is another important sensor implemented in our system which is used for fall detection of the patient. For this we make use of a low cost, low power 3 axis accelerometer, ADXL 335 from Analog Devices, which can measure the static acceleration in tilt-sensing applications as well as motion, vibration or shock sensing in dynamic applications. It is thin and small in size, has an input voltage around 3.6V and a sensitivity of 300mV/g. It has a wide temperature range of −40°C to +85°C and is supplied in a small, thin, 3 mm × 5 mm × 1 mm, 14-lead, plastic package. This was fitted into the wrist strap. This device provided a digital voltage, the amplitude of which was directly proportional to acceleration. The resultant acceleration was determined by measuring the x-axis and y-axis accelerations. For the corresponding values of XOUT, YOUT pins, the acceleration in g units was given by the equation given below:  Sensor supply voltage: 3.3 V (a typical case)  Zero-g bias output = 1.45 V for X (typically 1.65 V specification from datasheet)  Acceleration Ax (in g units) = [(3.3 – zero-g bias (=1.45V)) * 1000] / 300 Similarly acceleration along y-axis (Ay) was calculated. The resultant acceleration was obtained using the formula: Resultant Acceleration = [15] With the help of TDMS data logging of NI LabView, suitable values were recorded in different scenarios to achieve a precise detection. With the help of MS EXCEL we came to a conclusion for impact detection threshold. The resultant acceleration threshold for peak detection was found to be 3.5.

Figure 5: The typical results of the impact sensor while walking along three axes

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International Journal of Scientific Research and Engineering Studies (IJSRES) Volume 1 Issue 5, November 2014 ISSN: 2349-8862 The purpose of this sensor was to detect sudden impacts that could indicate the patient had fallen over. Fig 5 shows the typical waveform of the impact sensor in LabVIEW, when user is walking in normal position. The impact sensor has been used for different conditions and the Fig 6 shows the typical results. In this project, only two axes (X and Y) are used to analyse movements. The output of the accelerometer was tested with jogging and simulated falling. The output of the accelerometer was tested with walking, everyday movements like sitting, standing, sit-up, etc., and simulated falls. The results showed the difference was simple to detect and proved the accuracy of the algorithm. Fig 6 shows the impact sensor output.

Figure 7: System overview for wireless communication 

Figure 6: Accelerometer output under different situations D. MICROCONTROLLER COMMUNICATION

INTERFACING

AND

The microcontroller used in the wrist strap unit is the Arduino UNO. The Microcontroller is programmed using “C” language for the operation of the above mentioned tasks in this project. This takes inputs from the sensors in the form of analog voltages. Each sensor has a dedicated channel, analog port0 (AN0) for temperature sensor, AN1 for heart rate sensor and AN2, AN3 for impact sensor. 

ZIGBEE MODULE

The system is capable of communicating with the computer wirelessly. The wireless communication is brought by using ZigBee technology. ZigBee is suitable for low rate data and secure networking [16]. It has been widely used for monitoring applications. It has a range of up to 40m. In this project we used ZigBee Series 2 OEM RF modules which operate within the ZigBee protocol and uses 2.4 GHz frequency band. It requires a supply voltage of 3V which is provided by the microcontroller and consumes power as low as 296mA. These modules provide a possibility to build an easy to configure network, with a high data rate up to 230400 Baud/s. They come in a preconfigured mode and establish the communication automatically. In addition, they are powered by 2.7–3.3 V and can be connected to the Arduino UNO without any additional power-supply circuit.

COMMUNICATION

Communication between the wrist units and the receiver unit is wireless. The data measured by the sensors is saved by building a network between the sensors and to set up a computer receiving and storing the values. For the communication ZigBee modules were used, powered by the Arduino UNO microcontroller and transmitted in the unlicensed 2.4GHz frequency band. These provide a wide range and a couple of low-power modes, which could be used to reduce the current consumption of the circuit. In addition, the network-setup is easy and fast, so that an extension of new units is possible without problems. Fig 7 shows the connection overview of various sensor units, wirelessly. The reason this microcontroller was chosen, was because of its low-power consumption and function for serial transmission of data to ZigBee module for wireless transmission. It is powered by a 9V battery, and ports uses 3.3V, from where sensor and ZigBee modules are powered.

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Figure 8: ZigBee Module To connect the ZigBee module to the Microcontroller is done using four wires. The Power-Supply (3.3 V), Ground and TX and RX of the Microcontroller are connected to VCC, GND, DIN and DOUT of the ZigBee module (Fig 9).

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International Journal of Scientific Research and Engineering Studies (IJSRES) Volume 1 Issue 5, November 2014 ISSN: 2349-8862 The other driving factors are low cost, high reliability, high security, low battery usage, simplicity and interoperability with other ZigBee devices. Compared to other wireless protocols, ZigBee wireless protocol offers low complexity. It also offers three frequency bands of operation along with a number of network configurations and optional security capability. It requires a supply voltage in the range of 2.8V to3.3V. ZigBee looks rather like blue tooth but is simpler, has a lower data rate and spends most of its time in snoozing. This characteristic means that a node on a ZigBee network should be able to run for six months to two years on just two AA batteries. Figure 9: ZigBee module electrical connection with microcontroller a) CONFIGURATION AND SETUP: To configure the ZigBee Modules, the provided software X-CTU is used. To set up a network the following conditions have to be fulfilled.  Each network needs one Coordinator and several End- Devices.  All modules have to have the same firmware and PAN-ID. If everything is setup correct, the coordinator establishes a connection to the End-Devices automatically. The Coordinator sends Broadcast Commands, and the End-Devices can send to Coordinator only. b) COMMUNICATION PROTOCOL: To avoid corrupted data and to see which unit was sending the data, an own communication protocol is needed. The transmission of the ZigBee Modules does not provide a checksum or any other possibility to verify the correctness of the received data. The send string for the sensor units contained 27 characters. The first three characters are the name of the user, then each divided by a minus the sensor data. The data is raw, i.e., no processing of data is done here. Each unit sends their data every 2 seconds to the coordinator, where the data has to be collected and tested for correctness.

IV.

Figure 10: Combined Setup of the prototype When in operation, the wrist unit consumes 20 mA of current at 3.3V power supply, supplied from pins of a port of microcontroller. It was also recorded off DC power supply display. The microcontroller is powered by 9V battery. The ZigBee module connected to microcontroller consumes 40 mA during transmission. However, ZigBee modules have the option of going in sleep mode while not transmitting. In sleep modes, ZigBee modules poll ZigBee coordinator (their parent) every 100 ms, while they are awake to retrieve buffered data. Pin sleep of ZigBee allows external microcontroller to determine when the ZigBee should sleep and when it should wake by controlling the Sleep_RQ pin. It saves power when no data is transmitted. By using several power-down modes that could be used to reduce consumption during times when the wrist band is not transmitting, alternatively, the architecture could be altered so that packets are only sent when a value goes outside a preset range. This was noted for future developments.

PROTOTYPE AND EXPERIMENTAL RESULTS

The Arduino UNO microcontroller was used to build and test the prototype design. The sensors were connected individually to the Arduino in its analog pins (AN0-AN3). All the sensors and the Arduino were placed in a box and fixed on the wrist strap. The prototype was powered off a 9V battery. The RF transmission using ZigBee’s has been tested to operate successfully at 30 meters range through obstacles such as concrete walls. ZigBee is a wireless network protocol specifically designed for low data rate sensors and control networks. ZigBee is a consortium of software, hardware and services companies that have developed a common standard for wireless, networking of sensors and controllers. While other wireless standards are concerned with exchanging large amounts of data, ZigBee is for devices that have smaller throughout needs. www.ijsres.com

Figure 11: Output of the prototype As far as the sensors are concerned, they have shown accurate and reliable readings. Also the system is capable of wirelessly communicating with other computer. Fig 11 shows the output for heart beat and temperature readings which are Page 26

International Journal of Scientific Research and Engineering Studies (IJSRES) Volume 1 Issue 5, November 2014 ISSN: 2349-8862 taken from Arduino wirelessly, e.g. the number of heart beat is “77” and body temperature is “37.33 oC” the patient status is normal. This system also warns about the impact, which would be used for fall detection. If the resultant acceleration is greater than 3.5, a message is displayed showing “FALL DETECTED”. Every changing of heart beat reading will update the GUI. As the result, this system is very effective to monitor all patients every minute.

V.

CONCLUSIONS

A low cost personal health monitoring application using wireless sensor network for assisting personal and patientcentric health care management is developed. Critical physiological data from wearable sensors like pulse sensor, temperature sensor and accelerometer sensor are monitored and analyzed in the system. The system is suitable for good and urgent care of emergency victims, the patients in hospitals or at home. It is a network approach for assisting patientcentric health care management. Sensors used in the personal health monitoring system are battery-operated and uses wireless communication, this system can benefit from intelligent sensor management that provides a way to trade-off between power efficiency, data quality and latency. The novel aspect of the design was its low cost and detection of medical distress which does not necessitate pressing any panic button which was achieved successfully. This was an enormous improvement over existing commercial products. Another important aspect of the design was miniaturization, so that the system was as non-intrusive, which was also achieved successfully. The final word would be that medical care will revolve around a patient's needs rather than a doctor's or clinic's schedules through the increased use of information technology.

VI.

ACKNOWLEDGMENT

We acknowledge and are grateful to all the support we received from the Department of Electrical and Electronics Engineering at Manipal Institute of Technology.

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