Bluetooth Breathing Sound Detection Device Based on Time and Frequency Domain Analyze

dc.contributor.authorChunhakam, Puripak
dc.contributor.authorPanpho, Phakakorn
dc.contributor.authorWardkein, Paramote
dc.date.accessioned2026-08-06T10:36:53Z
dc.date.available2026-08-06T10:36:53Z
dc.date.issued2022-04-20
dc.description.abstractIn this paper, a wearable and simple system for breathing sounds detection from the left and right External Auditory Canal (EAC) was proposed. This system consists of two main parts: 1) Hardware design for detecting input breathing sound signal and 2) software design for processing and displaying the output results. Two condenser microphones are used to detect breathing sound and the detected signal is transmitted to the main processor by a Bluetooth channel. Two main proposed algorithms to detect breathing sounds and evaluate the number of respirations were presented: the first algorithm employs sound signals in the time domain to detect breathing sound with power window threshold scanning and count breathing pulses. For the second one, Fast Fourier transforms (FFT) along with detecting the maximum magnitude of its low-frequency elements in the breathing frequency band is presented and it is interpreted as respiration rate. The results of both algorithms show that the system can accurately monitor breathing. The percentage of error for the 1st and 2nd algorithms was 6.77% and 5.00%, respectively. The experimental results presented that this breathing detection system can measure and provide the breathing and respiration rate as expected.
dc.identifier.citationACM International Conference Proceeding Series, 94-100, 2022
dc.identifier.doi10.1145/3535694.3535711
dc.identifier.other2-s2.0-85134606208
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/13188
dc.sourceACM International Conference Proceeding Series
dc.subjectBluetooth
dc.subjectbreathing
dc.subjectcondenser microphone
dc.subjectrespiration rate
dc.subjectsleep apnea
dc.titleBluetooth Breathing Sound Detection Device Based on Time and Frequency Domain Analyze
dc.typeConference Paper

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