Naslov
Low- power wearable system for asthmatic wheeze detection

Autori
Oletić, Dinko

Vrsta, podvrsta i kategorija rada
Ocjenski radovi, doktorska disertacija

Fakultet
Fakultet elektrotehnike i računarstva

Mjesto
Zagreb

Datum
16.11

Godina
2016

Stranica
178

Mentor
Bilas, Vedran

Ključne riječi
biomedical sensors; wireless sensor networks; electronic auscultation; asthmatic wheeze detection; short-term Fourier transform (STFT); compressed sensing (CS); hidden Markov model (HMM); low-power electronic design

Sažetak
Area of this research is minimization of energy consumption of electronic systems for longterm monitoring of common symptom of chronic asthma - asthmatic wheezing. The proposed electronic sensor system consists of a wearable sensor measuring the mechanical vibrations on skin surface originating from respiration, and a wireless mobile device (smartphone). The system conducts automatic recognition of respiratory sounds. The essential design requirement is energy consumption at which the sensor system is able to quantify symptoms. In this context, research compared two system architectures: with asthmatic wheeze detection on the sensor node, and the architecture in which information capture on occurrence of wheeze is distributed between a sensor node and a mobile device. Firstly, the problem of power-efficient asthmatic wheeze detection on-board sensor node was addressed. Building up on the literature state-of-the-art, four algorithms based on features drawn from STFT time-frequency decomposition have been compared on an low-power audio processing DSP. Best trade-off between classification performance and execution speed was obtained by STFT spectral crest shapes tracking algorithm yielding 87.51% sensitivity (SE), 93.42% specificity (SP), and 92.53% accuracy (ACC) at less than 3% of DSP’s active time. Secondly, application of compressed sensing (CS) was evaluated in a distributed sensing system as a mean of simultaneous reduction of power consumption of sensor node, and the data-rate reduction in wireless communication. A prototype was demonstrated, implementing a combination of a time-domain subsampling CS encoder on the sensor node, and the real-time DFT/DCT spectra CS reconstruction OMP algorithm on smartphone. Compression ratios of 4x to 5.33x were proved feasible. A robust algorithm for wheeze detection from CS reconstructed spectra, based on HMM, was proposed. It enabled for up to SE of 89.99%, SP of 94.03%, and 93.45% ACC at the CS compression rate of 4x, at the processing cost comparable to spectral crest shapes tracking algorithm. Finally, system-level power analysis confirmed that lowest system-level power, estimated from 328 to 428 μW, may be achieved in architecture with wheeze detection on-board sensor node. However, in the distributed architecture, CS enables for the lowest sensor node power (216 - 357 μW), while simultaneously keeping the total system power (775 - 2605 μW) lower or equal to streaming of the uncompressed signal.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika

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