Ubiquitous Healthcare Monitor System Using Wearable Wireless Sensor Network

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1 Ubiquitous Healthcare Monitor System Using Wearable Wireless Sensor Network Chetan D. Kurjekar 1 and Nikhil M. Palekar 2 Computer Science and Engineering, Jawaharlal Darda College of Engineering and Technology, Yavatmal, Maharashtra, Computer Science and Engineering, Jawaharlal Darda College of Engineering and Technology, Yavatmal, Maharashtra, ABSTRACT Wearable physiological monitoring system consists of a network of sensors embedded onto the cloths or on the body of the wearer to continuously monitor the physiological parameters and transmit wirelessly to a remote monitoring station. At the remote monitoring station the data is collected to study the overall health status of the wearer. In the conventional wearable physiological monitoring system, the sensors are integrated at specific locations on the fabrics and are interconnected to the wearable data acquisition hardware by wires woven into the fabric. The drawbacks associated with these systems are the cables woven in the fabric create noise such as power line interference and signals from nearby radiating sources and thereby corrupting the physiological signals. Also repositioning the sensors in the fabric is difficult once integrated. The problems can be overcome by the use of physiological sensors with miniaturized electronics to condition, process, digitize and wireless transmission integrated into the single module. These sensors are strategically placed at various locations on the vest. Number of sensors integrated into the fabric form a network (Personal Area Network) and interacts with the human system to acquire and transmit the physiological data to a wearable data acquisition system. The wearable data acquisition hardware collects the data from various sensors and transmits the processed data to the remote monitoring station. Also the problems associated with conventional wearable physiological monitoring are discussed. Also introduced priority scheduling and data compression into the system to increase transmission rate of physiological critical signals which improve the bandwidth utilization. It also extends the life time of handheld personal server by reducing power consumption during transmission. Keywords: Wearable Wireless Sensor Network, Zigbee, Smartphone, Architecture. 1. INTRODUCTION Wearable physiological monitoring systems uses an array of sensors integrated into the fabric of the wearer to continuously acquire and transmit the physiological data to a remote monitoring station. The data acquired at the remote monitoring station is correlated to study the overall health status of the wearer. The wearable monitoring systems allow an individual to monitor his/her vital signs remotely and receive feedback to maintain a good health status. These systems alert medical personnel when abnormalities are detected. [3] Wearable sensors with ambient sensor help to solve these problem. Wearable sensors are used to gather physiological and movement data thus enabling patient s status monitoring. Sensors are deployed according to the clinical application of interest. Sensors to monitor vital signs (e.g. heart rate and respiratory rate) would be deployed, Sensors for movement data capturing would be deployed. Fig 1: A Conceptual Representation of A System for Remote Monitoring VOLUME-2, SPECIAL ISSUE-1, MARCH-2015 COPYRIGHT 2015 IJREST, ALL RIGHT RESERVED 293

2 Wireless communication is relied upon to transmit patient s data to a mobile phone or an access point and relay the information to a remote center via the Internet. Emergency situations (e.g. falls) are detected via data processing implemented throughout the system and an alarm message is sent to an emergency service center to provide immediate assistance to patients. Family members and caregivers are alerted in case of an emergency but could also be notified in other situations when the patient requires assistance with, for instance, taking his/her medications. Clinical personnel can remotely monitor patient s status and be alerted in case a medical decision has to be made. 2. HISTORY The wearable physiological monitoring systems consists of three systems namely (a) Vest with the sensors integrated (b) Wearable data acquisition and processing hardware and (c) Remote monitoring station. In the vest sensors for acquiring the physiological parameters are integrated. The sensors outputs and power cables are interconnected to the data acquisition and processing hardware by means of wires routed through the wires woven in the vest. In the wearable data acquisition and processing hardware, the circuits for amplification, filtering and digitization are housed. The digitized and processed data is transmitted wireless to a remote monitoring station. In the remote monitoring station the data is received and displayed in a form suitable for diagnosis. Fig. 2 illustrates the overall architecture of the wearable physiological monitoring system, consisting of a vest with sensors integrated, wearable data acquisition and processing hardware and a remote monitoring station [3]. Fig 2: Overall Architecture of the Wearable Physiological Monitoring System The drawbacks associated with the conventional wearable physiological systems are The cables woven into the fabric to interconnect the sensors to the wearable data acquisition hardware pick up interfering noises (e.g. 50 Hz power line interference). The wires integrated into fabric act like antennas and can easily pick up the noises from nearby radiating sources. The sensors once integrated into the fabric, its location cannot be changed or altered easily. The power required for the sensors to operate is to be drawn from the common battery housed in the wearable data acquisition hardware and are routed through wires woven in the fabric. Typically these systems consist of a centralized processing unit to digitize, process and transmit the data to a remote monitoring system. The processor is loaded heavily to perform multi-channel data acquisition, processing and transmission of data. The cables from the vest interconnecting the sensors can get damaged very easily due to twisting and turning of the cables, while the wearer is performing his routine activity. 3. WEARABLE WIRELESS SENSOR NETWORK To overcome the above issues related to wearable physiological monitoring, the individual sensors integrated into the vest can be housed with electronics and wireless communication system to acquire and transmit the physiological data. The recent advances in the sensors (MEMS and Nanotechnology), low-power microelectronics and miniaturization and wireless networking enable Wireless Sensor Networks (WSN) for human health monitoring. A number of tiny wireless sensors, strategically placed on the human body create a wireless body area network that can monitor various vital signs, providing real-time feedback to the user and medical personnel. Wireless Sensor Networks (WSN) consists of a large number of small nodes, which have built-in computing, power, sensors to acquire physiological data from the wearer and wireless transmission and reception capability. Patient monitoring over the wireless infrastructure oriented ad-hoc network has been investigated. These systems are useful in transmitting the VOLUME-2, SPECIAL ISSUE-1, MARCH-2015 COPYRIGHT 2015 IJREST, ALL RIGHT RESERVED 294

3 medical over larger distances and do not discuss about the applications of wearable physiological monitoring. 4. KEY TECHNOLOGY Wearable systems for patients remote monitoring consist of three main building blocks: 1) the sensing and data collection hardware to collect physiological and movement data, 2) the communication hardware and software to relay data to a remote center, and 3) the data analysis techniques to extract clinically-relevant information from physiological and movement data. Recent advances in sensor technology, microelectronics, telecommunication, and data analysis techniques have enabled the development and deployment of wearable systems for patients remote monitoring. The miniaturization of sensors and electronic circuits based on the use of microelectronics has played a key role in the development of wearable systems. Recent developments in the field of microelectronics have allowed researchers to develop miniature circuits entailing sensing capability, front-end amplification, microcontroller functions, and radio transmission. The flexible circuit shown in Figure 3 is an example of such technology and allows one to gather physiological data as well as transmit the data wirelessly to a data logger using a low-power radio. Fig.3 an Example of Such Technology Particularly relevant to applications in the field of rehabilitation are advances in technology to manufacture microelectromechanical systems (MEMS). MEMS technology has enabled the development of miniaturized inertial sensors that have been used in motor activity and other health status monitoring systems. By using batch fabrication techniques, significant reduction in the size and cost of sensors has been achieved. Microelectronics has also been relied upon to integrate other components, such as microprocessors and radio communication circuits, into a single integrated circuit thus resulting in System-on-Chip implementations. During the last decade we have witnessed tremendous progress in this field and the development of numerous communication standards for low-power wireless communication. These standards have been developed keeping in mind three main requirements: 1) low cost, 2) small size of the transmitters and receivers, and 3) low power consumption. With the development of IEEE /ZigBee and Bluetooth, tethered systems have become obsolete. Most monitoring applications require that data gathered using sensor networks be transmitted to a remote site such as a hospital server for clinical analysis. This can be achieved by transmitting data from the sensor network to an information gateway such as a mobile phone or personal computer. By now most developed countries have achieved almost universal broadband connectivity. For in-home monitoring, sensor data can be aggregated using a personal computer and transmitted to the remote site over the Internet. Also, the availability of mobile telecommunication standards such as 3G means that pervasive continuous health monitoring is possible when the patient is outside the home environment. Mobile phone technology has had a major impact on the development of remote monitoring systems based on wearable sensors. Monitoring applications relying on mobile phones are becoming commonplace. Smart phones are broadly available. Besides being used as information gateways, mobile devices can also function as information processing units. The availability of significant computing power in pocket-sized devices makes it possible to envision ubiquitous health monitoring and intervention applications. In addition, most mobile devices now include an integrated GPS tracking system thus making it possible to locate patients in case of an emergency. Finally, the massive amount of data that one can gather using wearable systems for patient s status monitoring has to be managed and processed to derive clinically relevant information. Data analysis techniques such as signal processing, pattern recognition, data mining and other artificial intelligence-based methodologies have enabled remote monitoring applications that would have been otherwise impossible. VOLUME-2, SPECIAL ISSUE-1, MARCH-2015 COPYRIGHT 2015 IJREST, ALL RIGHT RESERVED 295

4 5. ARCHITECTURE This section describes the system architecture of the proposed wearable sensors for remote healthcare monitoring system. The system is composed of three tiers as shown in Figure 4 below. Fig.4: Architecture of Wearable Sensors for Remote Healthcare Monitoring System The system composed of: 1) Wireless Body Area Network (WBAN); 2) Personal Server (PPS) using IPDA; 3) Medical Server for Healthcare Monitoring (MSHM). Figure 4. Architecture of wearable sensors for remote healthcare monitoring system. 5.1 First Tier The core of this system is the user called the patient. Wearable sensors are attacked to the patient body forming wireless body area network (WBAN) to monitor changes in patient s vital signs closely and provide real time feedback to help maintain an optimal health status. The medical sensors typically consist of five main components: 1) Sensor: it is a sensing chip to sense physiological data from the patient s body. 2) Microcontroller: it is used to perform local data processing such as data compression and it also controls the functionality of other component in sensor node. 3) Memory: it is used to store sensed data temporally. 4) Radio Transceiver: it is responsible for communication between nodes and to send/receive sensed physiological data wirelessly 5) Power supply: the sensor nodes are powered by batteries with a lifetime of several months. Sensor nodes can sense, sample, and process one or more physiological signals. For example, an electro- cardiography (EKG) sensor can be used for monitoring heart activity, a blood pressure sensor can be used for monitoring blood pressure, a breathing sensor for monitoring respiration, an electromyogram (EMG) sensor for monitoring muscle activity, and an electroenphalogram (EEG) sensor for monitoring brain electrical arrive for each sensor. In our design, a sophisticated sensor is integrated into the WBAN called Medical Super Sensor (MSS). This sensor has more memory, processing and communication capabilities than other sensor nodes as shown in Figure 4 above. MSS uses a radio frequency to communicate with other body sensors and ZigBee is used as a communication protocol to communicate with the Personal Server. In this design, we considered Bluetooth and ZigBee technologies. In case of Bluetooth specification, it supports maximum of seven active slaves (i.e. sensors to be controlled by one master, personal server). But the number of sensor nodes we are considering in this system are more than seven therefore Bluetooth technology is not acceptable option. The second technology is ZigBee/IEEE standard. It has a short range, low power consumption, low cost technology, capable of handling large sensor networks up to 65,000 nodes and reliable data transfer. It supports a maximum of 250kbps using Industrial, Scientific and Medical (ISM) free band i.e. 2.4 GHz. There-fore, ZigBee is adopted to transmit physiological signals from WBAN to the patient server. Other reasons why it is used are stated below: Security: Patient information is vital; it must not be changed by unauthorized person. Data transfers from WBAN to the personal server and the medical server must be secured. ZigBee provides a low power hardware encryption solution using Advanced Encryption Standard (AES 128) to encrypt data transmitted between MSS and personal server. VOLUME-2, SPECIAL ISSUE-1, MARCH-2015 COPYRIGHT 2015 IJREST, ALL RIGHT RESERVED 296

5 Scalability: it is highly scalable for many devices. Interoperability between a variety of medical and non-medical devices with data management devices regardless of manufacturer. However, Medical Super-Sensor (MSS) unobtrusively samples, collects multiple sensed vital signs by the body sensors, filtering out all redundant data thereby reducing large volume of data transmitted by BSNs, store them temporarily, process and transfer the relevant patient s data to a personal server through wireless personal im-plemented using ZigBee/IEEE This improves overall bandwidth utilization as well as reducing power consumption of the BSs because each nodes does not need to transmit sensed data to the IPDA but to the col-lector which is MSS and it is closer to the BSs than IP-DA and extending battery life of each sensor node. 5.2 Second Tier Personal Server The personal server interfaces the WBAN nodes through a communication protocol using ZigBee. It is implemented on an Intelligent Personal Digital Assistant (IPDA). It holds patient authentication information and is configured with the medical server IP address in order to interface the medical services. It collects physiological vital signals from WBAN, processes them, and prioritizes the transmission of critical data when there is sudden clinical change in the current patient condition and data content for example changes in cardiovascular signals, temperature, oxygen saturation, and forward it to the medical server. Moreover, the IPDA has the capability to perform the task of analyzing the physiological data intelligently and do a local reasoning to determine user s health status based on data received from MSS and provide feedback through a userfriendly and interactive graphical user interface. 3G communications is used to connect personal server and third tier together but other long range communications protocols can also be used like GPRS, WWAN. In order for IPDA to improve the overall quality of service for data transmission, in terms of latency, band-width and power consumption a differentiated service based on two schemes are presented. They are Priority Scheduling and Data Compression. Priority Scheduling and Data Compression There are different physiological signals that are normally transmitted between the sensor nodes and patient server. The transmission is divided into four types ac-cording to their data rate and latency. They are classified as follow [3]. High data rate and low latency traffic Low data rate and low latency traffic Low data rate and high latency traffic High data rate and high latency traffic High data rate means critical signs that need to be transfer very fast with high reliability while low latency means time delay to the response of transmission of critical signals and should be as much as possible be short. From Table 1 below, each of the physiological signs is given priority weight. It shows the order in which the physiological signs will transmit from IPDA to the medical server via 3G communications for further analysis and diagnosis by the medical staff. Physiological sign that is allocated with priority 1 has the highest priority over other data and will be allowed to transmit first and the vital sign should be transmitted without any delay. It means the present condition of the patient is critical and he/she needs immediate attention of the medical staff while physiological sign with high data rate and high latency means the signal is not critical. It will compress according to a given ratio and stored in the local memory of the IPDA for later transmission after physiological signs with higher priority i.e. priority 1, priority 2 have been allowed to transmit first. Priority scheduling method not only reduces the transmission delay for critical physiological signals, but also decreases traffic congestion. The total number of data sent reduced through data compression method. Therefore, the bandwidth utilization is improved thus, reduces total transmission time. However, IPDA is VOLUME-2, SPECIAL ISSUE-1, MARCH-2015 COPYRIGHT 2015 IJREST, ALL RIGHT RESERVED 297

6 Table 1. Priority of physiological signs. Physiological Signs Data Latency Priority Rate Electrocardiograph High Low 1 (EKG) Heart Rate, Blood Flow, Oxygen Saturation Low Low 2 Respiratory Rate, Blood Pressure, Body Low High 3 Temperature Never Potentials High High 4 using battery for its operation and high amount of energy is consumed during transmission.this method reduces energy consumed by the IPDA during transmission since only the critical vital signs will transmit first while less critical signs are stored and transmit later. The modes consist of Active Mode and Inactive Mode.IPDA is inactive mode when it has no data to receive from MSS or send to the medical server in order to save energy but wake up immediately from inactive to active mode to receive transmitted data and store it. It prioritizes all the received physiological data and send to the medical server based on the priority order so that the medical staff will be adequately prepared before the patient gets to them or send ambulance immediately to pick the patient so as to save his/her life. 5.3 Third Tier The third tier is called Medical Server for Healthcare Monitoring (MSHM). It receives data from the personal server, is the backbone of the entire architecture. It is situated at medical centers where medical services are provided. It is intelligent because it is capable of learning patient specific thresholds and learns from previous treatment records of a patient. MSHM keeps electronic medical records (EMRs) of registered patients, which are accessible by different medical staff, including general practitioners, specialists and doctors from their offices in the hospital over the internet. The present state of the patient can be observed by the medical staff. MSHM is responsible for user authentication, accepting data from personal server, format and insert the received data into corresponding EMRs, analyze the data patterns. The patient s physician can access the data and its patterns from his/her office via the intranet/internet and examine it to ensure the patient is within expected health metrics. If the received data is out of range (i.e. deviation from threshold) or recognize serious health anomalies condition, medical staff in the emergency unit can be notified to take necessary actions. However, if the patient is in the remote area, the specialist doctor will observe the physiological data of the patient diagnose it, prescribe the necessary treatment and drugs for the patient. This information will sent back to the doctor in the remote hospital via the internet. The MSHM also provides feedback instructions to the patient, such as physician s prescribed exercises. 6. SECURITY THREATS Wireless sensor networks for physiological applications vary in size and are deployed over the different regions of body of an individual. There are concerns on security issues in these networks, as the data being monitored is the health status of the individual. Sensor nodes used to form these networks are resource-constrained, which make security applications a challenging problem. To ensure the security of the data being monitoring, the data acquired from each sensor nodes can be encrypted and sent to the sink node, but the encryption and decryption mechanisms has to be very simple and energy efficient. The data are also vulnerable to external attackers, by injecting errors in the routing information, replaying old routing information, distorting routing information or sending malicious information. The data is also subjected to jamming, tampering, Sybil attack, collision etc. The confidentiality requirement is needed to ensure that medical data is well protected from others getting an access to it and not revealed to unauthorized persons while the data is traveling from the sensor nodes to the sink node. The various participants in the network has to be authenticated, by establishing the identity of the user and verifying that the data send is a valid data. Also the integrity of the medical data needs to be ensured as the data being exchanged is medical data. VOLUME-2, SPECIAL ISSUE-1, MARCH-2015 COPYRIGHT 2015 IJREST, ALL RIGHT RESERVED 298

7 7. CONCLUSION It described the architecture of wearable sensors for remote healthcare monitoring system which composed of three tiers. A differentiated services scheme based on priority scheduling and data compression methods were presented in second tier. The method not only reduces transmission delay of physiological vital signs but also improves its bandwidth utilization. The role of wireless technology in healthcare applications is expected to become more important with an increase in deployment of mobile devices and wireless networks. This new technology has potential to provide many advantages to people in rural areas, people with physical disabilities, senior citizens, patients, medical staff, and society at large through continuous monitoring of various physiological vital signs and provide real-time feedback to the user and the medical staff. REFERENCE [1] Shyamal Patel, Hyung Park, Paolo Bonato, Leighton Chan3 and Mary Rodgers A review of wearable sensors and systems with application in rehabilitation Journal of NeuroEngineering and Rehabilitation 2012, 9:21 [2] Ademola Philip Abidoye, Nureni Ayofe Azeez, Ademola Olusola Adesina, Kehinde K. Agbele, Henry O. Nyongesa Using Wearable Sensors for Remote Healthcare Monitoring System Journal of Sensor Technology, 2011, 1, doi: /jst Published Online June 2011 ( [3] P. S. Pandian Wireless Sensor Network for Wearable Physiological Monitoring JOURNAL OF NETWORKS, VOL. 3, NO. 5, MAY 2008 [4] Narendra Kumar, Alok Aggrawal and Nidhi Gupta Wearable Sensors for Remote Healthcare Monitoring System International Journal of Engineering Trends and Technology- Volume3Issue [5] ZigBee Alliance. [ JOURNAL OF NETWORKS, VOL. 3, NO. 5, MAY 2008 [6] Narendra Kumar, Alok Aggrawal and Nidhi Gupta Wearable Sensors for Remote Healthcare Monitoring System International Journal of Engineering Trends and Technology- Volume3Issue [7] ZigBee Alliance. [ VOLUME-2, SPECIAL ISSUE-1, MARCH-2015 COPYRIGHT 2015 IJREST, ALL RIGHT RESERVED 299

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