Real-Time True Wireless Stereo Wearing Detection Using a PPG Sensor with Edge AI

Kim, Raehyeong; Park, Joungmin; Kim, Jaeseong; Oh, Jongwon; Lee, Seung Eun

doi:10.3390/electronics14193911

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Open AccessArticle

Real-Time True Wireless Stereo Wearing Detection Using a PPG Sensor with Edge AI

by

Raehyeong Kim

,

Joungmin Park

,

Jaeseong Kim

,

Jongwon Oh

and

Seung Eun Lee

^*

Department of Electronic Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea

^*

Author to whom correspondence should be addressed.

Electronics 2025, 14(19), 3911; https://doi.org/10.3390/electronics14193911

Submission received: 30 August 2025 / Revised: 28 September 2025 / Accepted: 29 September 2025 / Published: 30 September 2025

(This article belongs to the Special Issue Machine Learning in Electronic and Biomedical Engineering, 3rd Edition)

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Abstract

True wireless stereo (TWS) earbuds are evolving into multifunctional wearable devices, offering opportunities not only for audio streaming but also for health-related applications. A fundamental requirement for such devices is the ability to accurately detect whether they are being worn, yet conventional proximity sensors remain limited in both reliability and functionality. This work explores the use of photoplethysmography (PPG) sensors, which are widely applied in heart rate and blood oxygen monitoring, as an alternative solution for wearing detection. A PPG sensor was embedded into a TWS prototype to capture blood flow changes, and the wearing status was classified in real time using a lightweight k-nearest neighbor (k-NN) algorithm on an edge AI processor. Experimental evaluation showed that incorporating a validity check enhanced classification performance, achieving F1 scores above 0.95 across all wearing conditions. These results indicate that PPG-based sensing can serve as a robust alternative to proximity sensors and expand the capabilities of TWS devices.

Keywords: true wireless stereo (TWS); photoplethysmography (PPG); real-time; edge AI

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MDPI and ACS Style

Kim, R.; Park, J.; Kim, J.; Oh, J.; Lee, S.E. Real-Time True Wireless Stereo Wearing Detection Using a PPG Sensor with Edge AI. Electronics 2025, 14, 3911. https://doi.org/10.3390/electronics14193911

AMA Style

Kim R, Park J, Kim J, Oh J, Lee SE. Real-Time True Wireless Stereo Wearing Detection Using a PPG Sensor with Edge AI. Electronics. 2025; 14(19):3911. https://doi.org/10.3390/electronics14193911

Chicago/Turabian Style

Kim, Raehyeong, Joungmin Park, Jaeseong Kim, Jongwon Oh, and Seung Eun Lee. 2025. "Real-Time True Wireless Stereo Wearing Detection Using a PPG Sensor with Edge AI" Electronics 14, no. 19: 3911. https://doi.org/10.3390/electronics14193911

APA Style

Kim, R., Park, J., Kim, J., Oh, J., & Lee, S. E. (2025). Real-Time True Wireless Stereo Wearing Detection Using a PPG Sensor with Edge AI. Electronics, 14(19), 3911. https://doi.org/10.3390/electronics14193911

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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Real-Time True Wireless Stereo Wearing Detection Using a PPG Sensor with Edge AI

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