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    <dc:date>2026-07-24T04:48:22Z</dc:date>
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  <item rdf:about="https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/219369">
    <title>Smartwatch-Based Unobtrusive Continuous Anxiety Tracker for Evaluating Post-Stroke Patients’ Quality of Life</title>
    <link>https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/219369</link>
    <description>Title: 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.</description>
    <dc:date>2026-07-01T00:00:00Z</dc:date>
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  <item rdf:about="https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/218244">
    <title>저강도 집속초음파/GluN2B-NMDAR PAM기반 혈광성 치매 치료기술 개발</title>
    <link>https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/218244</link>
    <description>Title: 저강도 집속초음파/GluN2B-NMDAR PAM기반 혈광성 치매 치료기술 개발
Authors: 고성호</description>
    <dc:date>2026-06-24T00:00:00Z</dc:date>
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  <item rdf:about="https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/218243">
    <title>혈액바이오마커 연구 소개 및 혈액검체 수집상황</title>
    <link>https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/218243</link>
    <description>Title: 혈액바이오마커 연구 소개 및 혈액검체 수집상황
Authors: 고성호</description>
    <dc:date>2026-06-12T00:00:00Z</dc:date>
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  <item rdf:about="https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/218242">
    <title>TegoStroke</title>
    <link>https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/218242</link>
    <description>Title: TegoStroke
Authors: 고성호</description>
    <dc:date>2026-06-05T00:00:00Z</dc:date>
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