TY - GEN
T1 - EarHealth
T2 - 20th ACM International Conference on Mobile Systems, Applications and Services, MobiSys 2022
AU - Jin, Yincheng
AU - Gao, Yang
AU - Guo, Xiaotao
AU - Wen, Jun
AU - Li, Zhengxiong
AU - Jin, Zhanpeng
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/6/27
Y1 - 2022/6/27
N2 - With the aging of the population and the long-time wearing of earphones, hearing health has gradually emerged as a worldwide health issue. Early detection of hearing health conditions would greatly reduce potential risks with timely medical intervention. This study proposes an earphone-based ear condition monitoring system, named EarHealth, which is low-cost, non-invasive, and easily usable in daily life. It can detect three major hearing health conditions: ruptured eardrum, earwax buildup and blockage, and otitis media. By analyzing the recorded echoes evoked by a chirp sound stimulus, EarHealth recognizes the distinguishable characteristics from ear canal structure and eardrum mobility. EarHealth achieves an accuracy of 82.6% in 92 human subjects, including 27 normal subjects, 22 patients with ruptured eardrum, 25 patients with otitis media, and 18 patients with earwax blockage. EarHealth is the first earphone-based system capable of monitoring hearing health conditions by utilizing the ear canal geometry and eardrum mobility. It is anticipated that EarHealth would provide pervasive and proactive protection for hearing health.
AB - With the aging of the population and the long-time wearing of earphones, hearing health has gradually emerged as a worldwide health issue. Early detection of hearing health conditions would greatly reduce potential risks with timely medical intervention. This study proposes an earphone-based ear condition monitoring system, named EarHealth, which is low-cost, non-invasive, and easily usable in daily life. It can detect three major hearing health conditions: ruptured eardrum, earwax buildup and blockage, and otitis media. By analyzing the recorded echoes evoked by a chirp sound stimulus, EarHealth recognizes the distinguishable characteristics from ear canal structure and eardrum mobility. EarHealth achieves an accuracy of 82.6% in 92 human subjects, including 27 normal subjects, 22 patients with ruptured eardrum, 25 patients with otitis media, and 18 patients with earwax blockage. EarHealth is the first earphone-based system capable of monitoring hearing health conditions by utilizing the ear canal geometry and eardrum mobility. It is anticipated that EarHealth would provide pervasive and proactive protection for hearing health.
KW - acoustic sensing
KW - ear canal
KW - ear disease
KW - eardrum mobility
KW - earphone
UR - https://www.scopus.com/pages/publications/85134081190
U2 - 10.1145/3498361.3538935
DO - 10.1145/3498361.3538935
M3 - Conference contribution
AN - SCOPUS:85134081190
T3 - MobiSys 2022 - Proceedings of the 2022 20th Annual International Conference on Mobile Systems, Applications and Services
SP - 397
EP - 408
BT - MobiSys 2022 - Proceedings of the 2022 20th Annual International Conference on Mobile Systems, Applications and Services
PB - Association for Computing Machinery, Inc
Y2 - 27 June 2022 through 1 July 2022
ER -