Jeong, Hyoyoung Yoo, Jae-Young Ouyang, Wei Greane, Aurora Lee Jean Xue Wiebe, Alexandra Jane Huang, Ivy Lee, Young Joong Lee, Jong Yoon Kim, Joohee Ni, Xinchen Kim, Suyeon Huynh, Huong Le-Thien Zhong, Isabel Chin, Yu Xuan Gu, Jianyu Johnson, Aaron M. Brancaccio, Theresa Rogers, John A. 2024-01-12T02:32:03Z 2024-01-12T02:32:03Z 2023-11-27 2023-02 0027-8424 https://pubs.kist.re.kr/handle/201004/75795 Vocal fatigue is a measurable form of performance fatigue resulting from overuse of the voice and is characterized by negative vocal adaptation. Vocal dose refers to cumulative exposure of the vocal fold tissue to vibration. Professionals with high vocal demands, such as singers and teachers, are especially prone to vocal fatigue. Failure to adjust habits can lead to compensatory lapses in vocal technique and an increased risk of vocal fold injury. Quantifying and recording vocal dose to inform individuals about potential overuse is an important step toward mitigating vocal fatigue. Previous work establishes vocal dosimetry methods, that is, processes to quantify vocal fold vibration dose but with bulky, wired devices that are not amenable to continuous use during natural daily activities; these previously reported systems also provide limited mechanisms for real-time user feedback. This study introduces a soft, wireless, skin-conformal technology that gently mounts on the upper chest to capture vibratory responses associated with vocalization in a manner that is immune to ambient noises. Pairing with a separate, wirelessly linked device supports haptic feedback to the user based on quantitative thresholds in vocal usage. A machine learning-based approach enables precise vocal dosimetry from the recorded data, to support personalized, real-time quantitation and feedback. These systems have strong potential to guide healthy behaviors in vocal use. English National Academy of Sciences Closed-loop network of skin-interfaced wireless devices for quantifying vocal fatigue and providing user feedback Article 10.1073/pnas.2219394120 1 Proceedings of the National Academy of Sciences of the United States of America, v.120, no.9 Proceedings of the National Academy of Sciences of the United States of America 120 9 N scie scopus 001167153100005 Multidisciplinary Sciences Science & Technology - Other Topics Article AUTOMATIC SPEECH DOSE MEASURES POPULATION PREVALENCE closed network quantifying vocal fatigue wearable electronics haptic feedback real-time machine learning