Movement based time division multiplexing for near real time feedback body area network applications

2014

IEEE Sensors J.

Self Cite

Health and sport applications have been a flourishing area for deploying Wireless Body Area Networks (WBAN) as this technology can provide a real time feedback which is important for the user, coaches, doctors and the viewing public. A wireless accelerometer sensor module was used to determine the link performance by recording the data and traffic lost on different runners and for different transmitter locations around the human body (foot, leg and arm). An approximate swing time calculation algorithm was employed to find the swing time effect on these losses. Experimental measurements showed 98% reliability at 250kbps while 62% resulted when using a data rate of 2Mbps. The results also showed that the sensor on the wrist gives the best outcome from the locations tested.

Section: Introductionmentioning

confidence: 91%

Node Position Effect on Link Reliability for Body Centric Wireless Network Running Applications

2014

IEEE Sensors J.

Self Cite

“…The authors previous work was carried out to determine the best node locations on a human body and to achieve a maximum connectivity to a receiving unit located on the chest, in order to sustain good wireless communications between the nodes while the athletes are moving [10][11][12][13]. In [10] a wireless accelerometer sensor module was used to determine the link performance by recording the data and traffic loss on different runners and for different transmitter locations around the human body (foot, leg and arm).…”

Section: Previous Workmentioning

confidence: 99%

Self-Calibrating Body Sensor Network Based on Periodic Human Movements

2015

IEEE Sensors J.

Body sensor networks with a central gateway node can control wireless transmission and optimize the network lifetime. The central node should be placed within communication reach of other nodes spread out around the human body, such as on the chest. This paper reports a novel energy-efficient time multiplexing transmission method based on the human rhythmic movement of running for on-body wireless communication. The running style of each individual allows the network to selfcalibrate the communication scheme so that transmissions occur only when high link reliability is predicted. This technique takes advantage of the periodic running actions to implement a dynamic time division multiple access (TDMA) strategy for a five node body network with very little communication overhead, long sleep times for the sensor transceivers and robustness to communication errors. The results showed all wireless communications were successful, except when two nodes attempt to use the transmission medium simultaneously. An aggregated network reliability of 90% was achieved compared to 63% when employing traditional time multiplexing algorithms.

“…1). The nodes sense body movements, store and send information [8]. In the tests, acceleration samples from the axis parallel to the forearm were recorded every 20ms at both nodes and sent to the Hub on the chest.…”

Section: Measurement Settingmentioning

confidence: 99%

“…One important problem associated with BSN is the effect of body movement on the wireless connection. For example, the absorption [7] and obstruction [8] of wireless signals through the body, and data collision [9] are common difficulties to be overcome.…”

Section: Introductionmentioning

confidence: 99%

High Reliability Body Sensor Network Using Gesture Triggered Burst Transmission

2015

Procedia Engineering

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Body Sensor Networks (BSN) is a developing area of research that allows wireless sensors to collect important parameters and monitor the human body. The wrist movement of a test subject running at moderate speed was monitored using accelerometer sensors. The sensor nodes were programmed to follow a gesture transmission technique to collect acceleration data and to predict the best limb position for communications while the athlete is moving. This paper reports a high reliability wireless network to acquire 50Hz movement acceleration during running. This reduces transmission power and increases the reliability. A result of 30% data loss was reduced to around 1% compared to continuous communications. This technology is important for a wide range of monitoring applications including measuring movement symmetry, physiology and athlete rehabilitation.