Literature DB >> 32050716

Validation of a Body-Conducted Sound Sensor for Respiratory Sound Monitoring and a Comparison with Several Sensors.

Takeshi Joyashiki1,2, Chikamune Wada1.   

Abstract

The ideal respiratory sound sensor exhibits high sensitivity, wide-band frequency characteristics, and excellent anti-noise properties. We investigated the body-conducted sound sensor (BCS) and verified its usefulness in respiratory sound monitoring through comparison with an air-coupled microphone (ACM) and acceleration sensor (B & K: 8001). We conducted four experiments for comparison: 1) estimation by equivalent circuit model of sensors and measurement by a sensitivity evaluation system; 2) measurement of tissue-borne sensitivity-to-air-noise sensitivity ratio (SRTA); 3) respiratory sound measurement through a simulator; and 4) actual respiratory sound measurement using human subjects. For 1), the simulation and measured values of all the sensors showed good agreement; BCS demonstrated sensitivity ~10 dB higher than ACM and higher sensitivity in the high-frequency segments compared with 8001. In 2), BCS showed high SRTA in the 600-1000 and 1200-2000-Hz frequency segments. In 3), BCS detected wheezes in the high-frequency segments of the respiratory sound. Finally, in 4), the sensors showed similar characteristics and features in the high-frequency segments as the simulators, where typical breathing sound detection was possible. BCS displayed a higher sensitivity and anti-noise property in high-frequency segments compared with the other sensors and is a useful respiratory sound sensor.

Entities:  

Keywords:  bioacoustics; body-conducted sound sensor; respiratory sound simulator; sensitivity evaluation system

Year:  2020        PMID: 32050716     DOI: 10.3390/s20030942

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  2 in total

1.  Polymeric piezoresistive airflow sensor to monitor respiratory patterns.

Authors:  Sajad Abolpour Moshizi; Abolfazl Abedi; Majid Sanaeepur; Christopher J Pastras; Zhao Jun Han; Shuying Wu; Mohsen Asadnia
Journal:  J R Soc Interface       Date:  2021-12-08       Impact factor: 4.118

2.  Fiber-Optic Based Smart Textiles for Real-Time Monitoring of Breathing Rate.

Authors:  Aizhan Issatayeva; Aidana Beisenova; Daniele Tosi; Carlo Molardi
Journal:  Sensors (Basel)       Date:  2020-06-17       Impact factor: 3.576

  2 in total

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