Aged people who live alone are in particular need of a daily health check, medication, and of warm communication with family and friends. The authors have been developing a life-support computer system with such functions. Among them, a daily health check function with the capability of measuring blood pressure, detecting diseases from coughing, and so on would in particular be very powerful for primary care. As a first step to achieving quick services for a daily health check with a personal computer, utilization of cough information is considered. Features of cough data are analyzed aiming at developing an automatic cough data detection method. This paper proposes a novel method for extracting cough signals from other types of signals. The differential coefficient of a low-pass filtered waveform is first shown to be an effective parameter for discriminating between vowel and cough signals, and the relationship between cut-off frequency and cough detection rate is clarified. This parameter is then applied to cough signals mixed with vowel signals or white noises to evaluate robustness. The evaluation tests show that the cough feature can be perfectly detected for a 20 dB S/N ratio when the cut-off frequency is set to 24 [Hz]. The experimental results suggest that the proposed cough detection method can be a useful tool as a primary care for aged people with a bronchitis like an asthmatic bronchitis and a bronchopneumonia.
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Shoichi TAKEDA, Shuichi KATO, Koki TORIUMI, "A Basic Study of Cough Signal Detection for a Life-Support System" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 12, pp. 2640-2648, December 2000, doi: .
Abstract: Aged people who live alone are in particular need of a daily health check, medication, and of warm communication with family and friends. The authors have been developing a life-support computer system with such functions. Among them, a daily health check function with the capability of measuring blood pressure, detecting diseases from coughing, and so on would in particular be very powerful for primary care. As a first step to achieving quick services for a daily health check with a personal computer, utilization of cough information is considered. Features of cough data are analyzed aiming at developing an automatic cough data detection method. This paper proposes a novel method for extracting cough signals from other types of signals. The differential coefficient of a low-pass filtered waveform is first shown to be an effective parameter for discriminating between vowel and cough signals, and the relationship between cut-off frequency and cough detection rate is clarified. This parameter is then applied to cough signals mixed with vowel signals or white noises to evaluate robustness. The evaluation tests show that the cough feature can be perfectly detected for a 20 dB S/N ratio when the cut-off frequency is set to 24 [Hz]. The experimental results suggest that the proposed cough detection method can be a useful tool as a primary care for aged people with a bronchitis like an asthmatic bronchitis and a bronchopneumonia.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_12_2640/_p
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@ARTICLE{e83-a_12_2640,
author={Shoichi TAKEDA, Shuichi KATO, Koki TORIUMI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Basic Study of Cough Signal Detection for a Life-Support System},
year={2000},
volume={E83-A},
number={12},
pages={2640-2648},
abstract={Aged people who live alone are in particular need of a daily health check, medication, and of warm communication with family and friends. The authors have been developing a life-support computer system with such functions. Among them, a daily health check function with the capability of measuring blood pressure, detecting diseases from coughing, and so on would in particular be very powerful for primary care. As a first step to achieving quick services for a daily health check with a personal computer, utilization of cough information is considered. Features of cough data are analyzed aiming at developing an automatic cough data detection method. This paper proposes a novel method for extracting cough signals from other types of signals. The differential coefficient of a low-pass filtered waveform is first shown to be an effective parameter for discriminating between vowel and cough signals, and the relationship between cut-off frequency and cough detection rate is clarified. This parameter is then applied to cough signals mixed with vowel signals or white noises to evaluate robustness. The evaluation tests show that the cough feature can be perfectly detected for a 20 dB S/N ratio when the cut-off frequency is set to 24 [Hz]. The experimental results suggest that the proposed cough detection method can be a useful tool as a primary care for aged people with a bronchitis like an asthmatic bronchitis and a bronchopneumonia.},
keywords={},
doi={},
ISSN={},
month={December},}
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TY - JOUR
TI - A Basic Study of Cough Signal Detection for a Life-Support System
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2640
EP - 2648
AU - Shoichi TAKEDA
AU - Shuichi KATO
AU - Koki TORIUMI
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E83-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2000
AB - Aged people who live alone are in particular need of a daily health check, medication, and of warm communication with family and friends. The authors have been developing a life-support computer system with such functions. Among them, a daily health check function with the capability of measuring blood pressure, detecting diseases from coughing, and so on would in particular be very powerful for primary care. As a first step to achieving quick services for a daily health check with a personal computer, utilization of cough information is considered. Features of cough data are analyzed aiming at developing an automatic cough data detection method. This paper proposes a novel method for extracting cough signals from other types of signals. The differential coefficient of a low-pass filtered waveform is first shown to be an effective parameter for discriminating between vowel and cough signals, and the relationship between cut-off frequency and cough detection rate is clarified. This parameter is then applied to cough signals mixed with vowel signals or white noises to evaluate robustness. The evaluation tests show that the cough feature can be perfectly detected for a 20 dB S/N ratio when the cut-off frequency is set to 24 [Hz]. The experimental results suggest that the proposed cough detection method can be a useful tool as a primary care for aged people with a bronchitis like an asthmatic bronchitis and a bronchopneumonia.
ER -