Research Article
Comparison of Power-Efficiency of Asthmatic Wheezing Wearable Sensor Architectures
@INPROCEEDINGS{10.1007/978-3-319-61563-9_13, author={Dinko Oletic and Vedran Bilas}, title={Comparison of Power-Efficiency of Asthmatic Wheezing Wearable Sensor Architectures}, proceedings={Sensor Systems and Software. 7th International Conference, S-Cube 2016, Sophia Antipolis, Nice, France, December 1-2, 2016, Revised Selected Papers}, proceedings_a={S-CUBE}, year={2017}, month={7}, keywords={m-health Body sensor networks Asthmatic wheeze detection Digital signal processing Compressed sensing Power-analysis}, doi={10.1007/978-3-319-61563-9_13} }- Dinko Oletic
Vedran Bilas
Year: 2017
Comparison of Power-Efficiency of Asthmatic Wheezing Wearable Sensor Architectures
S-CUBE
Springer
DOI: 10.1007/978-3-319-61563-9_13
Abstract
Power-requirements of a wireless wearable sensor for quantification of asthmatic wheezing in respiratory sounds, a typical symptom of chronic asthma, are analysed. Two converse sensor architectures are compared. One featuring processing-intensive on-board respiratory sound classification, and the other performing communication-intensive signal streaming, employing compressive sensing (CS) encoding for data-rate reduction, with signal reconstruction and classification performed on the peer mobile device. It is shown that lower total sensor power, ranging from 216 to 357 µW, may be obtained on the sensor streaming the CS encoded signal, operating at the compression rate higher than 2x. Total power-budget of 328 to 428 µW is shown required in the architecture with on-board processing.