Paper Info
Title
Coughtrigger: Earbuds IMU Based Cough Detection Activator Using An Energy-Efficient Sensitivity-Prioritized Time Series Classifier
Abstract
Persistent coughs are a major symptom of respiratory-related diseases. Increasing research attention has been paid to detecting coughs using wearables, especially during the COVID-19 pandemic. Microphone is most widely used sensor to detect coughs. However, the intense power consumption needed to process audio hinders continuous audio-based cough detection on battery-limited commercial wearables, such as earbuds. We present CoughTrigger, which utilizes a lower-power sensor, inertial measurement unit (IMU), in earbuds as a cough detection activator to trigger a higher-power sensor for audio processing and classification. It runs all-the-time as a standby service with minimal battery consumption and triggers the audio-based cough detection when a candidate cough is detected from IMU. Besides, the use of IMU brings the benefit of improved specificity of cough detection. Experiments are conducted on 45 subjects and CoughTrigger achieved 0.77 AUC score. We also validated its effectiveness on free-living data and through on-device implementation.
Year
DOI
Venue
2022
10.1109/ICASSP43922.2022.9746334
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Keywords
DocType
ISSN
Cough Detection Activation,Sensitivity-prioritized Classification,Multi-Center Classifier,Template Matching,Earbuds
Conference
1520-6149
ISBN
Citations 
PageRank 
978-1-6654-0541-6
0
0.34
References 
Authors
8
9
Name
Order
Citations
PageRank
Shibo Zhang196.00
Ebrahim Nemati28415.30
Minh Dinh301.01
Nathan Folkman400.34
Tousif Ahmed5326.26
Mahbubur Rahman600.34
Jilong Kuang73817.00
Nabil Alshurafa813419.65
Alex Gao913.08