Wireless sensor networks for healthcare a survey pdf

It is known that generally in multi-hop networks this topology each node simple listens for the data messages and the source node cannot reach the sink directly. So, intermediate is not responsible for retransmitting any messages if any message sensor nodes have to relay their packets. The implementation of is lost, thus the being a passive topology [2]. These contain the lists of node option for any given packet destination.

Routing table is the task of the routing algorithm along with the help of the routing protocol for their construction and maintenance. WSN Routing Protocols can be classified in various ways like according to the network structure, according to the protocol operation etc. BUS Fig. Only one of them will be nominated as the PAN coordinator for identifying the network. This coordinator synchronizes with all other nodes and coordinators in the network.

Network Structure Based Protocol The underlying network structure may play an important role in the operation of routing protocols in WSNs. Flat Protocol This type of protocol is multihop flat routing protocols. In flat networks, each node usually plays the same role and sensor nodes cooperate together to carry out sensing task.

Due to large number of nodes, it is not entitled to set global identifier for each node. This Fig. Since data is being requested through queries, itself as CLuster Head CLH with a cluster identifier CID value attribute-based name is necessary to specify the data attributes.

In of zero. The coordinator then chooses an unused PAN identifier flat routing group, we can find a huge variety of protocols: and broadcasts beacons to all neighboring devices.

Any other devices who receive these beacons may join the network at this device. If in case the requesting 2. Hierarchical Protocol device cannot join the network at the cluster head, it will search Hierarchical or cluster-based routing, originally proposed in for another parent device. For a large-scale wireless network a wireline networks, are well-known techniques with special mesh of multiple neighboring clusters can be formed [2].

As such, the concept of hierarchical routing is also utilized to perform energy-efficient routing in WSNs. In a hierarchical architecture, higher energy nodes can be used to process and w w w. Multipath Routing Protocols [3] perform the sensing in the proximity of the target. This means Multiple paths are used to enhance the network performance. When that creation of clusters and assigning special tasks to cluster the crucial path fails between the source and the destination an heads can greatly contribute to overall system scalability, lifetime, alternate path exists that measured the fault tolerance resilience and energy efficiency.

Hierarchical routing is an efficient way to of a protocol. This can be increased, by maintaining multiple paths lower energy consumption within a cluster and by performing between the source and the destination. This increases the cost of data aggregation and fusion in order to decrease the number of energy consumption and traffic generation.

The alternate paths transmitted messages to the BS. Hierarchical routing is mainly are kept alive by sending periodic messages. Due to this, network two-layer routing where one layer is used to select cluster heads reliability can be increased. Also the overhead of maintaining the and the other layer is used for routing.

However, most techniques alternate paths increases. Query Based Routing Protocols [3] etc. Location Based Protocol In this kind of routing, sensor nodes are addressed by means of 5. Coherent and Non-Coherent Processing [3] their locations. The distance between neighbouring nodes can Data processing is a major component in the operation of wireless be estimated on the basis of incoming signal strengths. Relative sensor networks. Hence, routing techniques employ different data coordinates of neighbouring nodes can be obtained by exchanging processing techniques.

There are two ways of data processing such information between neighbours. Alternatively, the location based routing before being sent to other nodes for further of nodes may be available directly by communicating with a processing. As the system is used in ICU room, the room size considered for maximum of 8 beds in any hospital is nearly sq.

Wi-Fi provides very high-speed access to internet compared to any other technology already established in the market.

Excluding Li-Fi which is not commercially available. In tier III, data from server is made available to authorized users from outside world using internet. Block diagram of proposed system is shown in Fig 2. Inbuilt signal conditioning circuit is used for interfacing sensor with A to D converter of Arduino Nano. Signals are then send to cloud storage using Thing Speak. Using Internet this medical data is made available to caregivers and doctors for reference. Existing Internet from home or hospital is used for this communication.

An alert message is sent to caregivers and relatives when readings cross threshold values, considering an emergency. For increased complexity and accuracy ECG sensor AD is used which states the condition of heart correctly.

Data collected from sensors is sent over Thing Speak channels. Authorised users like caregivers and doctors with login and password can monitor this data. Fig 5 and Fig 6 shows the sample of results displayed on Thing Speak channels and Fig 7 shows results on monitor. Sample ECG signals are plotted in Fig. Fig 10 shows the histogram of communication range of Wi-Fi with respect to size of ICU room during 3 different experiments. Nearly equal sized ICU units at different locations and at different time are considered for above experimentations.

Feedback of the system on rating scale of is obtained from patients who voluntarily participated in the survey is shown in Fig All responses below 50 rating are considered as rejected. The response time of our system is found 10 seconds for ECG readings and 5 seconds for other body parameters. In this paper healthcare monitoring system for cardiac patients is proposed which monitors body parameters of heart patient like Heart rate, Temperature and SPO2.

On any abnormality, it gives alert to caregivers. Using Internet, data can be made available for remote use and only to authorized users like remote specialist doctors for special advice. Thus designing parameters like availability, security, correctness and efficiency are achieved successfully. Thus the system can found helpful for the continuous monitoring of the cardiac patients in ICU of hospitals.

The use of this system can be extended to care and monitor elderly people staying all alone at their homes and also for baby care. Skip to search form Skip to main content Skip to account menu You are currently offline. Some features of the site may not work correctly. DOI: Networks Becoming mature enough to be used for improving the quality of life, wireless sensor network technologies are considered as one of the key research areas in computer science and healthcare application industries.

The pervasive healthcare systems provide rich contextual information and alerting mechanisms against odd conditions with continuous monitoring. This minimizes the need for caregivers and helps the chronically ill and elderly to survive an independent life, besides provides quality care… Expand. View via Publisher. Save to Library Save. Create Alert Alert. Share This Paper. Background Citations. The system is able to determine when and which bottle is removed or replaced by the patient and the amount of medicine taken.

The Base Station software tasks include simulating a display and its GUI for the patient; determining when medicine is required; and maintaining various interactions between the Medicine Mote and the Patient Mote. The system is capable of monitoring the drugs that are bought by the user and when the presence at home is detected the smart appliances, such as TV, can be used to inform the patient about the usage and dosage. Furthermore, an interactive TV application can also be integrated with the system that allows the purchase of the new packet of the drugs when the supply is decreased.

As an alternative scenario, the iCabiNET system can be integrated with the cellular network or ordinary telephone network in order to remind the patients to take their medication correctly.

Another intelligent packaging prototype is proposed and developed by Pang et al. The system is capable of both remote medication intake monitoring and vital signs monitoring. The intelligent package prototype, called the iPackage, is different from RFID attached intelligent packages in that it uses an array of Controlled Delamination Material CDM films and its control circuits are added.

The CDM film is a 3-layer foil composed of aluminum bottom and top layers and an adhesive middle layer made of electrochemical epoxy. When a voltage higher than a particular threshold is applied on the bottom layer and top layer, an electrochemical reaction occurs in the middle layer. When the voltage is applied for a certain amount of time, the epoxy layer is destroyed and delaminated. The identification of the correct pill is accomplished by RFID.

The prototype design of CDM and tagged capsule package is depicted in Fig 6. Figure 6: A Prototype of iPackage [81] 3. Medical Status Monitoring Applications Monitoring the medical status of the people is the most widely studied application type of pervasive healthcare systems. The commonly used vital signs are ECG, pulse oximetry, body temperature, heart rate, blood pressure. The acceleration data is also used together with these vital signs in some studies.

Most of the studies focus on capturing and sending the data to a remote site for further evaluation. The sensors continuously measure and trans- mit physiological data together with the audio and video recordings to health service providers in order to provide fast and reliable remote assistance in case of accidents.

CodeBlue [83] is a hardware and software platform developed at Harvard University. The hardware design part includes the design and development of a mote-base pulse oximeter, two-lead ECG, and a motion analysis sen- sor board. CodeBlue aims to provide coordination and communication among wireless medical devices in an ad-hoc manner. Moreover, when publishers and subscribers are not within radio range, multi-hop routing is used. Since the publishers and subscribers are mobile, mobility must be taken into account when establishing routing paths.

Also, a discovery protocol is used for Code- Blue nodes to discover each other and determine the capabilities of their sensor devices. Moreover, the system integrates a localization system called MoteTrack [98] which is an RF-based localization system used for locating the patients and healthcare professionals. CodeBlue project is one of the most comprehensive projects in the literature which includes mote design, software architecture design, ad-hoc network design and multi-hop commu- nication together with location tracking.

AlarmNet [84] is a wireless medical sensor network system prototype com- posed of five components. The mobile body sensor network is responsible for the physiological monitoring and the location tracking functions.

The mo- bile body sensors include heart rate, oxygen saturation, and ECG that are developed in CodeBlue project. The emplaced sensor network provides a spatial context and environmental information such as temperature, motion, humidity. The designers use indoor temperature and luminosity sensors for this purpose.

The AlarmGate connects the wireless sensor and IP networks and also responsible for privacy, power management, query management, and security. It acts as a gateway between the data accumulation and storage parts.

The data is stored in the back-end for long-term analysis and mining. The graphical user interface that runs on a PDA displays accelerometer data, patient pulse-rate, and environmental temperature and allows caregivers to query sensor data.

The PDA devices are carried by healthcare professionals and they are able to remotely monitor the vital signs of the patients. The LifeGuard [85], which was developed for astronauts in the first place, can also be used for general vital signs monitoring. The system is comprised of three components. The sensors part can support different types of sensors such as ECG, respiration, pulse oximeter, blood pressure. It has 3-axis accelerometers and skin temperature sensors internally.

The base station part is a Blue- tooth capable Tablet PC. It can display and also store the data streaming from CPOD for further evaluation. Zhou et al. The medical sensors form a star schema network with a gateway node elected by either a self-organizing protocol or manual configuration. The second layer provides reliable transmission. If the patient is at home, the physiological data is transferred to one of the nearest wireless nodes that are emplaced in the house. When the patient is outside, the relay mission is accomplished by a mobile phone or a PDA device.

The third layer of the system is responsible for the aggregation of physiological data in a remote medical center for analysis and providing feedback data back to the patient through a mobile phone, a PDA or web services.

The mentioned projects are sophisticated and comprehensive research studies. There are also simpler prototype designs in the literature worth mentioning for addressing different types of users.

In [87], for instance, sev- eral prototypes are presented by a group of researchers. As an example, FireLine is designed for monitoring cardiac measurements of firefighters for being able to take the necessary actions in the case of abnormality. The heart rate measurements are transmitted to a base station mote attached to a portable laptop where the data are stored and processed. The device is comprised of two motes.

The first mote collects the vital sign information coming from the sensors and transmits them wirelessly to the second mote which is connected to the base station computer for processing. If the vital signs are over the limits, the caregivers are alerted.

LISTENse is a prototype that enables the hearing impaired to perceive the critical sound information like doorbell or smoke alarm. It is comprised of at least two wireless sensor network motes. The Transmitter periodically samples the microphone sig- nal and compares the sample with a reference user-defined value. When the measured signal is over the reference value, an encrypted message is sent to the Base Station to prevent the false alarms caused by any similar existing wireless devices in the environment.

Upon receiving the encrypted activa- tion message, the Base Station extracts the Transmitter address and turns on the vibrator and corresponding LEDs. Alternatively, it may display an appropriate text message on its LCD screen. There is a significant research effort on cardiac monitoring. Especially the mobile ECG measurement systems are gaining importance since their extended usability.

When a WLAN is not present, a cell phone with a prototype wireless dongle that is capable of performing a simple electrocardiogram diagnosis algorithm is used. The dongle collects the physiological data coming from the sensor and an appli- cation running on the cell phone analyzes this data locally. The proposed work is important in its effort on providing continuous roaming; however the limitations of cell phone re- sources prevent ECG analysis algorithm to work appropriately. Yang et al.

The mobile ECG recording de- vice sends the data to the mobile phone via Bluetooth. The mobile phone records and analyzes the received data. If any abnormality is detected the ECG data is sent to a server for further analysis by the healthcare profes- sionals.

If requested, the mobile phone is able to display the ECG signal and the heart rate on the screen. A similar work using a PDA as the base station is also represented in []. The wearable unit has a Secure Digital Memory Card SD Card interface and a high speed USB port; therefore, it can also record physiological data to be transmitted to the hand-held device for further use or can transmit raw ECG data to a monitor for real-time display.

Furthermore, the hand-held device can relay data and abnormality alarms to the Internet for the use of healthcare professionals. With these features, it behaves both as a real-time and as an offline physical activities monitor. There are also some studies for identification of complications of some diseases such as epilepsy seizure. In a neurological body area network prototype, the ECG data captures an epilepsy seizure; however, without the context information the change in the heart rate cannot be reliably attributed to an epilepsy seizure since it may be due to motion.

Therefore, the contextual information on the location of the patient and the location of the healthcare professionals are combined with the availability of the healthcare professionals and the most appropriate professional is routed to the patient having an epilepsy seizure in AWARENESS.

In order to enable context-awareness, a rule language and an engine are designed as well as an infrastructure for discovering and dy- namically binding sources with the application. Challenges and Open Research Problems of the WSN Solutions for Healthcare In this section, we present the challenges observed while designing perva- sive healthcare systems and state the open research problems of the surveyed systems. There are numerous challenges of wireless sensor networks in all lay- ers.

In this survey, we approach these challenges with a healthcare specific perspective. The stated challenges are selected must be studied for fully enjoying the benefits of pervasive healthcare systems using wireless sensor networks. Hardware Level Challenges 4. Unobtrusiveness The design and development of wearable sensor devices without violating unobtrusiveness is still a significant challenge. When the patients have to carry sensors attached on their bodies as fall detection systems described in [70] and FireLine [87], unobtrusiveness becomes a major challenge amongst many others.

These body-worn sensor devices are heavy and highly obtrusive devices, whereas the bandage type ECG sensors described in [21] and watch-shaped activity recorder in [22] are much more easy-to-bear devices.

The integration of the sensor devices with the fabric is studied in several publications [, , ]. Sensitivity and calibration Sensitivity of the sensor devices is important especially when the users wear the sensors under harsh environments like in a fire situation or exercis- ing. The sweat can affect the transducers of the sensor devices negatively, causing the reduction in the sensitivity of the body-worn sensors or requiring recalibration of the sensors.

Gietzelt et al. Yet, the self-calibration and sensitivity enhancement algorithms are still needed for sensor devices differ- ent than accelerometers. Low-maintenance and highly sensitive vital-signs monitoring sensors will attain importance as pervasive healthcare systems evolve. Energy One of the bottlenecks of sensor devices is the batteries. Con- sidering the likelihood of forgetting to recharge the batteries of several sen- sors, this is a significant issue to be solved.

Although there is much effort on designing low-power sensors to minimize this bottleneck [21], we still need energy scavenging techniques. Therefore, motion [] and body heat [, ] based energy scavenging techniques should be studied for healthcare systems.

Data Acquisition Efficiency The data collection rate in pervasive healthcare systems is high. The development of efficient data processing techniques are of great importance.

In some cases 3-lead ECG may not be sufficient for identifying a cardiac disease or a single 3-axes accelerometer may not be capable of classifying all activities of the people. In these cases, more sensors will be needed and the gathered data will increase. The real-time acquisition and analysis of the physiological data is essential. Besides, time-stamping and ordering of the events, synchronization of different sensors are open research problems [6].

Finally, integrating different types of sensors, like RFID tags, implantable body sensors and wireless sensors necessitates the development of modular architectures. Physical Layer Challenges 4. Error resilience and reliability Low transmission power and small antenna sizes of wireless sensor devices causes reduced Signal-to-Noise Ratios SNR thus causing higher bit error rates and reducing the reliable coverage area.

However, the reliable trans- fer of data in medical monitoring systems is vital. Therefore, error resilient network coding schemes for medical data transmission should be developed for increasing network reliability.

It lets every sensor to transfer data through two relays and the relay nodes XOR the packets before sending. Although they have showed the improvements in the packet loss rate through simulations, the real deployments for measuring physio- logical signals, such as ECG and EEG and improving the proposed system accordingly are left as future works.

The reliable data transmission should be studied thoroughly for low power body area sensor networks. Interoperability The integration of several sensing devices operating at different frequen- cies raises an interoperability problem. Communication between different devices occupies multiple bands and use different protocols.

This situation may cause interferences among different devices especially in the unlicensed Industrial, Scientific and Medical ISM radio bands. The pervasive health- care systems must be designed with interoperability provisioning between different devices [6]. Bandwidth The bandwidth available for data communication for wireless body area networks is relatively low. Although, new sensor nodes can operate at Kbps, due to duty cycling mechanisms for lowering the power consumption lowers the actual available bandwidth.

For this reason efficient compression algorithms should be developed for multimedia data transmission. These compression techniques should also be lightweight enough for running on a sensor node which does not have high performance processing units and memory. To begin with, Quality of Service QoS requirements of emergency traffic are needed to be studied for healthcare monitoring applications.

In [], Benhaddou et al. In most cases, we can safely assume that there will be a nearby access point base station since these systems are generally connected to a gate- way before sending data over the WAN. These are also of great importance since their ability of extending the boundaries of the service.

For real pervasive healthcare monitoring, we will need multi-hop wireless communications between the sensor nodes even- tually. Therefore, delay optimizing MAC design will be essential. Demirkol et al. Healthcare monitoring applications require emergency event reporting be- sides periodic physiological data reporting.

Under emergency conditions, the emergency data should be guaranteed to be delivered with a reasonable delay. For this purpose, emergency data prioritization mechanisms should be de- veloped.

Moreover, the fairness among different emergent situations should be considered. The event based fairness scheme proposed by Durmus et al. The prioritization and fairness mechanisms for vital signs monitoring applications are open research issues. Network Layer Challenges Delay optimizing and energy-aware routing protocols are the most impor- tant open research challenges for applications of wireless sensor networks for healthcare monitoring.

The convergent traffic inherent in wireless sensor net- works may cause choke effect at the nodes closer to the base station. For this reason, load balancing routing protocols need to be developed.

Moreover, when multimedia traffic is encountered with the emergence of multi-modal sensor networks for healthcare monitoring applications, congestion avoidance and rate control issues become significant []. These techniques should also be integrated with data compression techniques for better utilization.

For addressing this challenge Tang et al [] propose a thermal-aware routing protocol TARA for implanted biosensor networks. Yet, these protocols should avoid the degradation on delay performance. Moreover, for reliable data delivery, multipath routing protocols for medical sensor networks should be studied. Transport Layer Challenges Since healthcare applications deal with life-critical data, a lost frame or packet can cause an alarm situation to be missed totally or misinterpreted.

Although there are reliabil- ity mechanisms at different layers such as automatic repeat request ARQ at MAC layer, critical WSN applications such as healthcare monitoring require total end-to-end reliability mechanisms []. The reliability for medical ap- plication may require either packet level or event level solutions. For periodic traffic, packet level reliability is essential whereas for emergency event report- ing such as a sudden fall detection then event reporting is more important than individual packet reporting.

Designing cross-layer protocols for ensuring reliable delivery for different type of traffic is also essential.

The congestion and flow control mechanisms at the transport layer are also rare. In that sense, ESRT may be suitable for event reporting applications. On the other hand, for periodic physiological data reporting such as ECG, or heart rate, every single packet has to be delivered reliably; therefore transport protocols addressing this issue are still needed to be developed. Application Layer Challenges We have already addressed some of the challenging issues in Sec.

On the other hand, organizing the data and producing meaningful information that evolve into knowledge is one of the hardest challenges at the application layer. The application layer being at the top surface is expected to have a coordinating mission also. In this context, the organization of ambient sensor data, medical data and other contextual data must be held by this layer. The organization of data is crucial and should be studied deeply. Moreover, robust machine learning algorithms are needed for self-learning, autonomous systems replacing rule-based and static systems.

Layer Independent Challenges There are some challenges that are not directly related with a specific layer or directly related with all. These challenges and related hints for their solutions are provided in the following subsections.

Security The fundamental security requirements of the overall system are confi- dentiality, data integrity, accountability, availability, and access control. In [], an elliptic curve cryptography for key distribution, in order to decrease energy consumption is proposed.

Another challenging issue with the security requirements arises when the patients are unconscious. Since obtaining pass- words may not be possible in those cases, biometric methods may be used for accountability []. The physiological signal based authentication scheme proposed in [31] is an example. It generates identity information for mu- tual authentication from an ECG-like measure called photoplethysmogram PPG captured simultaneously at two different parts of the body. Finding unique biometric features to be used for identification purposes is a further challenge in this context.

Privacy Authorization of the users in the system should not be overlooked and the users should have autonomy and control over their data of any type [50]. Besides, especially in image processing applications which are becoming more available from day to day, the privacy-preserving methods should be devel- oped for the comfort of the monitored people.

On-node processing of images can be a solution in which no images are transferred, only the information about the image is sent over the network. Srinivasan et al. This privacy flaw enables the attacker to monitor the ADL of the people only with two pieces of information, namely the timestamp and the fingerprint of each radio message. Although, the authors propose a hybrid scheme for thwarting this kind of attack they also note that there may be many potential physical-layer privacy attacks on wireless ubiquitous systems to be studied.

User-friendliness The users should embrace the system for full satisfaction. Casas et al. The development of natural interfaces between a diverse group of people and pervasive systems are crucial. In [], the authors surveyed their level of user-friendliness among a small elderly group and concluded that their inter- face should be revisited. The needs for different groups should be identified clearly, which is not a trivial task.

For instance, the user interface for the handicapped and the elderly must be based on voice, gesture, and visual animation, and must avoid any kind of particular skills. The interface for healthcare profes- sionals should output medical data such as emergency situation indicators and behavioral patterns of the people under observation in a domain-specific notation.

The healthcare professionals and caregivers should also have user- friendly and natural interfaces with immediate response capabilities. Ease of deployment and scalability Similar to user-friendliness, developing easily deployable pervasive sys- tems is also an essential and nontrivial challenge. When the number of pa- tients and caregivers increase, the scalable and easily deployable applications that can also support multiple receivers will attain much importance.

Perva- sive healthcare monitoring systems generally require the simultaneous use of several sensor devices, communication devices and software. With these di- verse components, ease of deployment becomes a challenge to be considered.

For this purpose, a software as a service approach could be used for both scal- ability and ease of deployment, together with small and easily configurable sensor devices. The system must support addition of new components at runtime, in order to adapt the system to changing disabilities over time. The software platforms and distributed services will be needed for seamless integration of the hardware and the application levels and interoperability among these will be essential [, ].

Mobility The aim of health monitoring is to let people to survive an independent life with high-quality healthcare services. The use of sensors and sensor networks for this purpose is not new [, ] however, the emergence of wireless sen- sor networks has enabled the development of applications which ensure and encourage the mobility of the users.

In this way, the wireless sensor network technologies enable the ubiquity of healthcare systems. Providing mobil- ity necessitate the design of multi-hop, multi-modal, ad-hoc sensor networks which brings the challenges mentioned in the previous subsections along with the location-awareness challenges. In this study, we have evaluated the examples of how people could benefit from living in homes that have wireless sensor technologies for improved quality of life and outlined issues to keep in mind during their development.

We have surveyed systems for acquiring and interpreting context information for the ubiquitous deployment of wire- less sensor networks. Results from these works suggest a strong potential for wireless sensor networks to open new research perspectives for low-cost, energy-efficient ad-hoc deployment of multi-modal sensors for an improved quality of medical care. In future smart home environments, there will be multi-modal sensor solutions that incorporate the benefits described, how- ever, there are still challenges to overcome to achieve these context-aware, pervasive healthcare applications.

We have provided an analysis of these chal- lenges from a healthcare perspective of WSNs. A combination of different sensing modalities like video sensing, RFID, medical sensors together with smart appliances and remote monitoring ability will lead context-aware, per- vasive healthcare applications to become within the reach of ordinary users.

References [1] D. Cook, J. Augusto, and V. Kinsella and D. Schmidt and K. Mcfadden and J. Stankovic, Q. Cao, T. Doan, L. Fang, Z. He, R. Kiran, S. Lin, S. Son, R. Stoleru, and A. Ng, M.

Sim, C. Tan, and C. Meyer and A. Orwat, A. Graefe, and T. Chan, D. Escriba, and E.