A Zigbee-Based Human Health Monitoring System

Vaheethabanu S

PG Scholar,Master of Technology, Computer Science and Engineering, Sir Isaac Newton College Of Engineering And Technology, Tamil Nadu, India

IJTCSE Research /ISSN 2349–1582 conference publication

Abstract — For the first time to the best of our knowledge, system architecture for low-power ubiquitously connected multi parametric remote health monitoring system is proposed in this paper. The architecture proposed uses a generic adaptive rule engine for classifying the collected multi parametric data from human being and smartly transmit the data. The on-chip seamless handoff mechanism proposed aids for the ubiquitous connectivity with a very good energy savings by intelligent controlling of the multiple on-chip radios. A health monitoring parameters, such as body temperature, and heart rate with vibration, has been developed. The IEEE802.15.4 and IEEE1451.2 standards-based sensor module has been developed successfully. The Zigbee device and PIC16F877A microcontroller are used in the implementation of sensor module. The real-time monitoring of health and behavioral parameters can be present on the PC. A prototype model is developed and tested with high accuracy results.

Index Terms — Zigbee, sensors, wireless transmission, health parameters, temperature.

INTRODUCTION

Wireless sensor networks (WSN) are used in a huge variety of sectors and industries, one of the important fields of application being expressed by WSN for human health monitoring including temperature, relative humidity but also the concentration of the heart rate such as presented in [1]. Additionally the WSN are used in agriculture related to the irrigation and crop monitoring, and also in healthcare as part of cardiac and respiratory activity monitoring nodes.

The majority of patients in the hospital are ambulatory, and thus, they are well suited to be monitored using wearable sensors for the purposes of predictive care. The goal of such systems is to provide early warning of physiological deterioration such that preventative clinical action may be taken to improve patient outcomes. A WBASN for health monitoring consists of multiple sensor nodes. Each node is typically capable of (i) sensing one or more physiological signals, (ii) processing these signals (e. g. filtering, feature extraction, and feature recognition), (iii) storing the processed data, and (iv)transmitting the data to other nodes and/or a WBASN server. “Intelligent,” online processing of these large datasets is, therefore, required for predictive monitoring, the results of which should then focus the limited resources of human experts to those subsets of patients who are deemed to be most at risk of being physiologically unstable, and who are in need of expert review. In this paper the patient as heart rate, blood pressure, temperature, and respiration contains is measure. The present monitoring system sensor is placed on the wrist of the human, which have care for the patient’s and patient’s attenders. But in modern system we used wireless network and wireless devices which removes the limitation of patient’s. To make human life more comfortable Wireless sensor networks (WSNs) are an emerging technology in existing research and have the potential to transform the way of human life (i.e., make life more comfortable). A wireless sensor is the smallest unit of a network that has unique features, such as, it supports large scale deployment, mobility, reliability; etc Body sensor network systems can help people by providing healthcare services such as medical monitoring, memory enhancement, medical data access, and communication with the healthcare provider in emergency situations through the SMS or GPRS [2]. Also, these systems provide useful methods to remotely acquire and monitor the physiological signals without the need of interruption of the patient’s normal life, thus improving life quality.

Focusing on web based information system that process and publish the data received from air quality WSN the developed system prototype that can be used to help medical researchers to analyze extended amount of experimental data contributing to limit the attenders health issue spreading and attack occurrences based on measurement of the patient and attenders health conditions. Activities such physiotherapy that are commonly performed in indoor with people characterized by limited health can be well organized by personalized air conditions that can contribute to reduce the recovery times.

This article is composed by five sections, wherein the first will focus on the implemented sensor network, referring to the hardware. The second refers the embedded software for the sensor nodes. Elements about the developed software are reported including the WSN data. Finally are presented preliminary experimental results the conclusion produced and the future work.

RELATED WORKS

Wireless health monitoring system (WHMS) has drawn considerable attentions from the research community as well as industry during the last decade. Numerous and yearly increasing research and development efforts have been posted in the literatures. We have limited this effort to include only some of the very recent related works.

Real time mobile healthcare system for monitoring the elderly patients from indoor or outdoor locations has been presented in [4]. A bio-signal sensor and a Smartphone are the main components of the system. The data collected by the bio-signal sensor are transmitted to an intelligent server via GPRS/UMTS network. The system is able to monitor the mobility, location, and vital signs of the elderly patient from a remote location.

A smart shirt has been designed in [5]. The shirt can measure electrocardiogram (ECG) and acceleration signals for continuous and real time health monitoring of a patient. The shirt mainly consists of sensors and conductive fabrics to get the body signal. The measured body signals are transmitted to a base station and server PC via IEEE 802.15.4 network. The wearable devices consume low power and they are small enough to fit into a shirt. To reduce the noise associated with the ECG signal an adaptive filtering method has also been proposed in this work.

Mobile device based healthcare system for monitoring the patients with Alzheimer’s disease has been developed and presented in [6]. The system is able to provide caregivers and medical professional with the ability to be in contact with the patients all the time. This system has been field tested by the Alzheimer’s disease caregivers and the initial results show that the system is very effective for them.

A novel 6LoWPAN based ubiquitous healthcare system has been presented in [7]. The system integrates forwarding nodes and an edge router to provide real time monitoring of the ECG, temperature, and acceleration data of a patient. The user can send instructions to any node where the application running on it. The authors have used LabVIEW program to provide the connectivity. The whole system was tested by using an ECG simulator. The test results show that the received waveforms were found identical to those shown by a high resolution ECG signals.

In this proposed system we minimize the hardware transmitter, receiver, and local monitoring unit in one device. The prime objectives of this system are as follows: (a) it saves the patients’ time and effort by reducing their back and forth travel to health clinics, (b) it provides the patients with an opportunity to save their lives by sending them critical alarm message, and © it also assists the healthcare professionals and relatives to monitor the patients from a remote location. We implement this work by using hardware and software in such a way so that it can be easily accessed by different systems and devices. We made the system flexible enough to accommodate more options as per user demand in future.

WIRELESS SENSOR NETWORK

In order to give a better perception of the implemented architecture for air quality monitoring, in Figure 1 are presented the main hardware and software elements. In Figure 1 represented body sensor network working as the smart coordinator, which transmits frames within IEEE802.15.4 frames and forward them through monitoring server. The smart coordinator architecture expressed by PIC16F877A and Zigbee coordinator of sensor network is expressed.

For this architecture the WSN coordinator data is accessed by the border router through wireless connection. To increase the flexibility and interoperability of the implemented architecture a smart coordinator based on embedded PC expressed by a PIC controller was considered. The embedded PC assures the hardware support for the client side application, and at the same time provides wireless connectivity. The embedded PC to WSN Zigbee coordinator [14] communication is based on a RS232 serial communication protocol.

SENSING NODE

The implemented network characterized by temperature, heart rate and vibration measurement capability through the usage of patients and attenders. The analog inputs of each nodes are used to acquire the values from air quality index sensors. For each wireless sensor node the sampling rate associated with analog channel is programmed in order to assure good accuracy of health parameter calculation, also following guidelines of health monitoring index which defines the minimum number of samples needed to an efficient calculation.

The choice of the sampling rate is performed considering also the general requirements of higher autonomy for WSN nodes. Referring to the communication between sensor nodes and coordinator, in the first approach it is based on 6LoWPAN. Messages are sent between the wireless network of a 6LoWPAN system as packets which are compressed and embedded in IEEE 802.15.4 frames. An important issue is whether the compressed packet is still too large; 6LoWPAN fragments the compressed packet for transportation in two or more frames. The layer also decompresses the packet extracted from a received frame. Alternatively, in the second approach the communication protocol (RS232) uses frames [16].

1) Temperature sensor:

The normal body temperature of a person varies depending on gender, recent activity, food and fluid consumption, time of day, and, in women, the stage of the menstrual cycle. Normal body temperature can range from 97.8 degrees F (or Fahrenheit, equivalent to 36.5 degrees C, or Celsius) to 99 degrees F (37.2 degrees C) for a healthy adult.

2) Heart beat sensor:

For a human aged 18 or more years, a normal resting heart rate can be anything between 60 and 100 beats per minute. Usually the healthier or fitter you are, the lower your rate. A competitive athlete may have a resting heart rate as low as 40 beats per minute. According to the National Health Service, UK, the following are ideal normal pulse rates at rest, in bpm (beats per minute): Newborn baby · Baby aged from 1 to 12 months — 80 to 140 aged from 1 to 2 years — 80 to Toddler/young child aged 2 to 6 years — 75 to · 120 · Child aged 7 to 12 years — 75 to 110 · Adult aged 18+ years — 60 to 100 · Adult athlete — 40 to 60

3) Microcontroller

The Arduino NANO microcontroller is used due to CMOS 8-bit microcontroller and high density non memory technology.The data from the microcontroller is also sent to the Zigbee

4) Zigbee Module

The Zigbee which consist of 2.4 GHz IEEE Std. 802.15.4 RF Transceiver Module. The dimension of the Zigbee is 17.8 mm x 27.9 mm, surface mountable and up to 100m range. This module interfaces with the microcontroller via serial SPI interface. The values of the sensors are noted and the information is broadcasted in the network.

SYSTEM DESIGN

In this process, design and implementation of Health Monitoring Using Wireless Body Area Sensor Network is done with modules of data sensing, data processing and data communication as shown in Fig. 2. Three sensors are contained in data sensing module such as temperature sensor, heart rate sensor and pressure sensor.

Temperature sensor is used to measure the body through external skin. Heartbeat sensor is used to measure the function of heart by blood flow through Finger. Pressure sensor is used to measure the blood pressure of human being. The output of each sensor is interfaced with Analog to Digital circuit (ADC) pins of microcontroller. Data processing module consists of Microcontroller which is a high and needed to communicate the PC data communication module for health information, LCD is used as a display unit in connection with microcontroller displaying the current details of physiological parameters.

RESULTS AND DISCUSSIONS

The heart of the project is micro controller. The project is divided into different block. The heart beat is sensed by the clamp type sensor. Where the signal is achieved from clip type sensor is very low will be in micro volt. The maximum differential signal from the sensor at R wave is up to 1.2mv. Hence the signal should be applied to the instrumentation amplifier for the faithful amplification and S/N level improvement. The suitable gain of the amplifier is decided by the resistance used in the circuit.

The primary objective of This project enables transmission of the system body parameters which is sensed from remote patient to the server PC by using wireless transmission technology

SOFTWARE DESCRIPTION

Software is a basic building block for the every system which designs the processing and operations. Following are the software’s used in designing of the proposed system. For programming of Arduino, embedded c language using Arduino IDE software is used. The new IDE has been designed to enhance developer’s productivity, also enabling faster and more efficient program development. IDE introduces a flexible window management system, enables us to drag and drop individual windows anywhere on the visual surface including support for Multiple Monitors.

To display the data received by Zigbee on servers PC, a PL-2303 driver for USB-to-Serial adapter has installed on that PC. This driver helps to access the data on PC, through USB adapter of Zigbee transceiver. To designing the schematic circuit diagram and PCB Layout, Proteus software is used. This software is less complex, easy to learn and helps to design circuit diagram in professional manner.

CONCLUSION

Thus the system successfully develops a wireless architecture for continuous monitoring the human health. The system to get the solution for collecting sensor values is interfaced with the microcontroller and the data is transmitted wirelessly to the server. This system provides reliability and security for independent-living residents with comfort. In this project used to technology a wide range of benefits to patient, medical personnel, and society through continuous monitor the ambulatory setting and early detection of abnormal conditions. As the future work is mentioned and extension of the wireless sensor network, thus new nodes characterized by new capabilities health concentration measurements as so as new capabilities on respiration activity monitoring Referring to the information system side, in order to provide a more efficient alert system, the warnings can be sent as a SMS to cell phone of users, or by email.

REFERENCES

[1] O. Postolache, J M. D. Pereira, P. Girao, “Smart Sensors Network for Air Quality Monitoring Applications”, IEEE Transactions on Instrumentation and Measurement, Vol.58, Issue 9, pp. 3253–3262, 2009

[2] Prof. Pravin Wararkar, Sawan Mahajan, Ashu Mahajan, Arijit Banerjee, Anchal Madankar, Ashish Sontakke, “Soldier Tracking and Health Monitoring System”, The International Journal of Computer Science & Applications, ISSN: 2278–1080, Volume 2, №02, April 2013, pp: (81–86).

[3] Govindaraj A., Dr. S. Sindhuja Banu, “GPS Based Soldier Tracking and Health Indication System with Environmental Analysis”, International Journal of Enhanced Research in Science Technology & Engineering, ISSN: 2319–7463, Volume 2 Issue 12, December 2013, pp: (46–52).

[4] Bourouis, A., Feham, M., and Bouchachia, A.(2011), “ Ubiquitous Mobile Health Monitoring System for Elderly (UMHMSE)”, International Journal of Computer Science and Information Technology, Vol.2, №3, June, pp. 74–82

[5] Lee, Y.D. and Chung, W.Y. (2009) “Wireless Sensor Network Based Wearable Smart Shirt for Ubiquitous Health and Activity Monitoring”, Sensors and Actuators B: Chameical, Vol. 140, №2, July, pp. 390–395

[6] Moreira, H. ; Oliveira, R. ; Flores, N.(2013), “STAlz: Remotely supporting the diagnosis, tracking and rehabilitation of patients with Alzheimer’s”, In the Proceedings of the 15th IEEE Conference on E-health Networking, Applications, and Services, October 9–12, Lisbob, pp. 580–584

[7] Touati, F. ; Tabish, R. ; and Ben Mnaouer, A.(2013), “Towards u-health: An indoor 6LoWPAN based platform for real-time healthcare monitoring”, In the proceedings of the IFIP International Conference on Wireless and Mobile Networking, April 20–23, 2013,Dubai, pp. 1–4