{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T13:34:54Z","timestamp":1777988094997,"version":"3.51.4"},"reference-count":47,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2025,12,13]],"date-time":"2025-12-13T00:00:00Z","timestamp":1765584000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Zhejiang health information association research program","award":["2023XHSZ-Z01"],"award-info":[{"award-number":["2023XHSZ-Z01"]}]},{"name":"The medical and health research project of Zhejiang province","award":["2025KY1028"],"award-info":[{"award-number":["2025KY1028"]}]},{"name":"The general research project of Zhejiang provincial department of education","award":["Y202352673"],"award-info":[{"award-number":["Y202352673"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Parkinson\u2019s disease (PD) is a progressive neurodegenerative disorder whose early symptoms, especially mild tremor, are often clinically imperceptible. Early detection is crucial for initiating neuroprotective interventions to slow dopaminergic neuronal degeneration. Current PD diagnosis relies predominantly on subjective clinical assessments due to the absence of definitive biomarkers. This study proposes a novel approach for the early detection of PD through a custom-developed smart wristband equipped with an inertial measurement unit (IMU). Unlike previous paper-based or resting-tremor approaches, this study introduces a mid-air Archimedean spiral task combined with an attention-enhanced Long Short-Term Memory (LSTM) architecture, enabling substantially more sensitive detection of subtle early-stage Parkinsonian motor abnormalities. We propose LAFNet, a model based on an attention-enhanced LSTM network, which processes motion data that has been filtered using a Kalman algorithm for noise reduction, enabling rapid and accurate diagnosis. Clinical data evaluation demonstrated exceptional performance, with an accuracy of 99.02%. The proposed system shows significant potential for clinical translation as a non-invasive screening tool for early-stage Parkinson\u2019s disease (PD).<\/jats:p>","DOI":"10.3390\/s25247579","type":"journal-article","created":{"date-parts":[[2025,12,16]],"date-time":"2025-12-16T08:46:52Z","timestamp":1765874812000},"page":"7579","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Wearable-Sensor-Based Analysis of Aerial Archimedean Spirals for Early Detection of Parkinson\u2019s Disease"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-7251-8227","authenticated-orcid":false,"given":"Hao","family":"Shi","sequence":"first","affiliation":[{"name":"School of Information Engineering, Hangzhou Medical College, Hangzhou 311399, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sanyun","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Hangzhou Medical College, Hangzhou 311399, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhuoying","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Public Health, Hangzhou Medical College, Hangzhou 311399, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuting","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Hangzhou Medical College, Hangzhou 311399, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e080952","DOI":"10.1136\/bmj-2024-080952","article-title":"Projections for Prevalence of Parkinson\u2019s Disease and Its Driving Factors in 195 Countries and Territories to 2050: Modelling Study of Global Burden of Disease Study 2021","volume":"388","author":"Su","year":"2025","journal-title":"BMJ"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Al-Worafi, Y.M. 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