DocumentCode :
941174
Title :
Bi-Fi: An Embedded Sensor/System Architecture for Remote Biological Monitoring
Author :
Farshchi, Shahin ; Pesterev, Aleksey ; Nuyujukian, Paul H. ; Mody, Istvan ; Judy, Jack W.
Author_Institution :
Univ. of California at Los Angeles, Los Angeles
Volume :
11
Issue :
6
fYear :
2007
Firstpage :
611
Lastpage :
618
Abstract :
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.
Keywords :
adaptive modulation; biomedical telemetry; data compression; differential pulse code modulation; filtering theory; intelligent sensors; medical signal processing; microprocessor chips; network servers; patient monitoring; real-time systems; wireless sensor networks; Bi-Fi system; adaptive differential-pulse-code modulation; asynchronous serial connection; back-end server; biological interface hardware; bit rate 32 kbit/s; commercial-off-the-shelf interface board; data acquisition; data compression algorithms; data filtering; embedded sensor; low-frequency phenomena; multiple biological signals; network traffic; networked gateway sensors; onboard signal processing; oxygen saturation; real-time nonobtrusive biological monitoring; remote biological monitoring; time-referenced spike waveforms; wireless-enabled processor modules; Biology computing; Biosensors; Computer architecture; Filters; Hardware; Humidity; Remote monitoring; Sensor phenomena and characterization; Sensor systems; Temperature sensors; Brain–Machine interface; TinyOS; mote; neural recording; smart dust; spike compression; spike filtering; stimulation; telemetry; wireless; Analog-Digital Conversion; Computer Communication Networks; Diagnosis, Computer-Assisted; Equipment Design; Equipment Failure Analysis; Monitoring, Ambulatory; Signal Processing, Computer-Assisted; Telemetry; Transducers;
fLanguage :
English
Journal_Title :
Information Technology in Biomedicine, IEEE Transactions on
Publisher :
ieee
ISSN :
1089-7771
Type :
jour
DOI :
10.1109/TITB.2007.897600
Filename :
4358283
Link To Document :
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