TY - GEN
T1 - Development of an AI-based non-invasive Pulse AudioGram monitoring device for arrhythmia screening
AU - Lin, Che Wei
AU - Chang, Yung
AU - Lin, Chou Ching K.
AU - Tsai, Liang Miin
AU - Chen, Ju Yi
N1 - Funding Information:
ACKNOWLEDGMENT The work is supported by Ministry of Health and Welfare, Taiwan (R.O.C), under grant MOHW106-TDU-B-211-113003. The authors want to express their sincere gratitude to Prof. Chih-Han Chang, Prof. Fang-Ming Yu, and Prof. Yang-Kun Ou for their constructive feedback and great help on the research findings reported in this study.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/19
Y1 - 2017/12/19
N2 - An artificial intelligence-based (AI-based) noninvasive Pulse AudioGram (PAG) monitoring device with arrhythmia screening algorithm has been developed in this research study. The PAG monitoring device consists of four components, including an audiogram sensor, an analog-digital converter, a microprocessor, and a data storage unit. The main function of the proposed AI-based non-invasive PAG is to measure the audio signal in radial artery generated by hemodynamics. Hemodynamics under arrhythmia and sinus rhythm (SR) conditions might exhibit different patterns as the heart rhythm becomes irregular under arrhythmia condition. PAG signals of SR and other arrhythmia symptoms such as atrial fibrillation (AF), aortic regurgitation (AR), and congestive heart failure (CHF) were collected during this research. In the experiment results, the proposed method can achieve accuracy of 99.29% when discriminating SR and AF; the proposed method can achieve accuracy of 98.92% when discriminating SR, AF, AR, and CHF. In this study, we have successfully developed an AI-based non-invasive PAG monitoring device for arrhythmia screening, and have plan to use it in on large-scale screening for arrhythmia in the near future.
AB - An artificial intelligence-based (AI-based) noninvasive Pulse AudioGram (PAG) monitoring device with arrhythmia screening algorithm has been developed in this research study. The PAG monitoring device consists of four components, including an audiogram sensor, an analog-digital converter, a microprocessor, and a data storage unit. The main function of the proposed AI-based non-invasive PAG is to measure the audio signal in radial artery generated by hemodynamics. Hemodynamics under arrhythmia and sinus rhythm (SR) conditions might exhibit different patterns as the heart rhythm becomes irregular under arrhythmia condition. PAG signals of SR and other arrhythmia symptoms such as atrial fibrillation (AF), aortic regurgitation (AR), and congestive heart failure (CHF) were collected during this research. In the experiment results, the proposed method can achieve accuracy of 99.29% when discriminating SR and AF; the proposed method can achieve accuracy of 98.92% when discriminating SR, AF, AR, and CHF. In this study, we have successfully developed an AI-based non-invasive PAG monitoring device for arrhythmia screening, and have plan to use it in on large-scale screening for arrhythmia in the near future.
UR - http://www.scopus.com/inward/record.url?scp=85048480294&partnerID=8YFLogxK
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U2 - 10.1109/HIC.2017.8227579
DO - 10.1109/HIC.2017.8227579
M3 - Conference contribution
AN - SCOPUS:85048480294
T3 - 2017 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2017
SP - 40
EP - 43
BT - 2017 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2017
Y2 - 6 November 2017 through 8 November 2017
ER -