{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T04:49:22Z","timestamp":1793335762597,"version":"4.5.0"},"reference-count":30,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010318","name":"University of Manitoba","doi-asserted-by":"publisher","award":["328120-352400-2000"],"award-info":[{"award-number":["328120-352400-2000"]}],"id":[{"id":"10.13039\/100010318","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Parkinson\u2019s disease (PD), a progressive neurodegenerative disorder affecting over 10 million people worldwide, necessitates continuous symptom monitoring to optimize treatment and enhance quality of life. Effective communication between patients and healthcare providers (HCPs) is vital but often hindered by fragmented data and cognitive impairments. PARKA AI, a novel iOS application, leverages Apple Watch HealthKit data (e.g., tremor detection, mobility metrics, heart rate, and sleep patterns) and integrates it with self-reported logs (e.g., mood, medication adherence) to empower PD self-management and improve patient\u2013HCP interactions. Employing a human-centered design approach, we developed a high-fidelity prototype using a large language model (LLM)\u2014 Google Gemini 1.5 Flash\u2014to process and analyze self-reports and objective sensor-derived data from Apple Healthkit to generate patient-friendly summaries and concise HCP reports. PARKA AI provides accessible data visualizations, personalized self-management tools, and streamlined HCP reports to foster engagement and communication. This paper outlines the derived design requirements, prototype features, and illustrative use cases to show how LLMs can be used in digital health tools. Future work will focus on real-world usability testing to validate the application\u2019s efficacy and accessibility.<\/jats:p>","DOI":"10.3390\/bioengineering12101059","type":"journal-article","created":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T10:54:48Z","timestamp":1759229688000},"page":"1059","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["PARKA AI: A Sensor-Integrated Mobile Application for Parkinson\u2019s Disease Monitoring and Self-Management"],"prefix":"10.3390","volume":"12","author":[{"given":"Krisha Sanjay","family":"Bhalala","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-0147-5423","authenticated-orcid":false,"given":"Hamid","family":"Mansoor","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1212\/01.wnl.0000247740.47667.03","article-title":"Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030","volume":"68","author":"Dorsey","year":"2007","journal-title":"Neurology"},{"key":"ref_2","first-page":"S3","article-title":"The Emerging Evidence of the Parkinson Pandemic","volume":"8","author":"Dorsey","year":"2018","journal-title":"J. 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