A survey on wearable sensor-based systems for health monitoring and prognosis
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Information Technology in Biomedicine
A novel solution approach and protocol design for bio-telemetry applications
Advances in Engineering Software
Implementation of web based biotelemetry applications on WiMAX networks
Advances in Engineering Software
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Wireless-enabled processor modules intended for communicating low-frequency phenomena (i.e., temperature, humidity, and ambient light) have been enabled to acquire and transmit multiple biological signals in real time, which has been achieved by using computationally efficient data acquisition, filtering, and compression algorithms, and interfacing the modules with biological interface hardware. The sensor modules can acquire and transmit raw biological signals at a rate of 32 kb/s, which is near the hardware limit of the modules. Furthermore, onboard signal processing enables one channel, sampled at a rate of 4000 samples/s at 12-bit resolution, to be compressed via adaptive differential-pulse-code modulation (ADPCM) and transmitted in real time. In addition, the sensors can be configured to filter and transmit individual time-referenced ldquospikerdquo waveforms, or to transmit the spike height and width for alleviating network traffic and increasing battery life. The system is capable of acquiring eight channels of analog signals as well as data via an asynchronous serial connection. A back-end server archives the biological data received via networked gateway sensors, and hosts them to a client application that enables users to browse recorded data. The system also acquires, filters, and transmits oxygen saturation and pulse rate via a commercial-off-the-shelf interface board. The system architecture can be configured for performing real-time nonobtrusive biological monitoring of humans or rodents. This paper demonstrates that low-power, computational, and bandwidth-constrained wireless-enabled platforms can indeed be leveraged for wireless biosignal monitoring.