ScholarWorks Community:https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/3952026-07-25T11:50:20Z2026-07-25T11:50:20ZSmartwatch-Based Unobtrusive Continuous Anxiety Tracker for Evaluating Post-Stroke Patients’ Quality of LifeChoi, SanghoonSeo, Woo-KeunJung, Jin-ManPark, SeonghoSeo, Hyo-Changhttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/2193692026-07-21T02:30:12Z2026-07-01T00:00:00ZTitle: Smartwatch-Based Unobtrusive Continuous Anxiety Tracker for Evaluating Post-Stroke Patients’ Quality of Life
Authors: Choi, Sanghoon; Seo, Woo-Keun; Jung, Jin-Man; Park, Seongho; Seo, Hyo-Chang
Abstract: Post-stroke anxiety (PSA) affects 20–30% of stroke survivors and significantly impacts quality of life (QoL) and rehabilitation outcomes. Traditional emotion assessment relies on subjective self-reports, limiting to capture real-time fluctuations in emotional states. This study proposes a self-supervised learning (SSL) framework combined with a transformer-based emotion classifier to enable continuous anxiety tracking in patients with stroke using smartwatch-derived photoplethysmography (PPG). The SSL model was pretrained on the VitalDB dataset using R-peak-to-peak intervals (RRIs) extracted from electrocardiography (ECG) signals. The pretrained encoder is then integrated into a transformer-based classifier trained on the Psychophysiology of Positive and Negative Emotions (POPANE) dataset with labeled emotional responses. The trained model was applied to smartwatch-derived pulse peak intervals (PPI) from patients with stroke, and evaluated against Generalized Anxiety Disorder-7 (GAD-7) scores and we evaluated it against GAD-7 scores using both group-level and 90-day longitudinal analyses, along with on-device feasibility on a Galaxy Watch6. Over the 30 days preceding the second survey, between-group differences were significant by Welch’s t-test (p = 0.0086), and discrimination reached an AUC of 0.859 with a 95% confidence interval of 0.664–0.992. In 90-day monitoring, generalized estimating equations showed persistent divergence when groups were defined by the second survey, with significant differences across multiple weeks preceding the survey, consistent with the retrospective GAD-7 window. These findings indicate that ECG-pretrained cardiac representations can be translated to smartwatch PPG for unobtrusive, continuous anxiety tracking in stroke. The results provide feasibility-level evidence and motivate larger, multi-site prospective validation toward clinical deployment.2026-07-01T00:00:00Z저강도 집속초음파/GluN2B-NMDAR PAM기반 혈광성 치매 치료기술 개발고성호https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/2182442026-07-21T08:33:39Z2026-06-24T00:00:00ZTitle: 저강도 집속초음파/GluN2B-NMDAR PAM기반 혈광성 치매 치료기술 개발
Authors: 고성호2026-06-24T00:00:00Z혈액바이오마커 연구 소개 및 혈액검체 수집상황고성호https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/2182432026-07-21T08:33:38Z2026-06-12T00:00:00ZTitle: 혈액바이오마커 연구 소개 및 혈액검체 수집상황
Authors: 고성호2026-06-12T00:00:00ZTegoStroke고성호https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/2182422026-07-21T08:33:36Z2026-06-05T00:00:00ZTitle: TegoStroke
Authors: 고성호2026-06-05T00:00:00Z