Pregled bibliografske jedinice broj: 823563
Energy-Efficient Respiratory Sounds Sensing for Personal Mobile Asthma Monitoring
Energy-Efficient Respiratory Sounds Sensing for Personal Mobile Asthma Monitoring // Ieee sensors journal, 16 (2016), 23; 8295-8303 doi:10.1109/JSEN.2016.2585039 (međunarodna recenzija, članak, znanstveni)
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Naslov
Energy-Efficient Respiratory Sounds Sensing for Personal Mobile Asthma Monitoring
Autori
Oletić, Dinko ; Bilas, Vedran
Izvornik
Ieee sensors journal (1530-437X) 16
(2016), 23;
8295-8303
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
M-health ; asthmatic wheezing ; compressive sensing ; non-uniform sampling ; orthogonal matching pursuit
Sažetak
Current medical practice of long-term chronic respiratory diseases treatment lacks a convenient method of empowering the patients and caregivers to continuously quantitatively track the intensity of respiratory symptoms. Such is ”asthmatic wheezing”, occurring in respiratory sounds. We envision a mobile, personalized asthma monitoring system comprising of a wearable, energy-constrained acoustic sensor and smartphone. In this article we address the energy-burden of acquisition and streaming of acoustic respiratory signal, and lessen it by applying the concept of compressed sensing (CS). First we analyse the adherence of normal and pathologic respiratory sounds frequency representations (DFT, DCT) to the sparse signal model. Given the pseudo-random non-uniform subsampling encoder implemented on MSP430 microcontroller, we review tradeoffs of accuracy and execution time of different CS algorithms, suitable for real-time respiratory spectrum recovery on smartphone. Working CS respiratory spectrum acquisition prototype is demonstrated, and evaluated. Prototype enables for real-time reconstruction of spectra dominated by approximately 8 frequency components with more than 80% accuracy, on Android smartphone using OMP algorithm, from only 25% signal samples (w.r.t. Nyquist rate) acquired and streamed by sensor at 8 kbit/s.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus