{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T14:48:52Z","timestamp":1791902932842,"version":"4.3.4"},"reference-count":34,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T00:00:00Z","timestamp":1790294400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T00:00:00Z","timestamp":1790294400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"JSPS","award":["JPJS00420240013"],"award-info":[{"award-number":["JPJS00420240013"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Digital phenotyping requires continuous, real-world collection of multimodal behavioral and physiological data. Although several smartphone-based sensing frameworks have been developed and used, open-source platforms for long-term smartwatch sensor data acquisition remain limited. To bridge this gap, SensorW was developed, an open-source Wear operating system (OS)-based framework for direct lifelog data collection from smartwatches without requiring a paired smartphone or manufacturer cloud service. SensorW includes a front-end Wear OS application for sensor data collection and a back-end server for application initiation, secure data submission, and storage. The front-end application uses battery-management strategies, such as hybrid Global Positioning System sampling and wake-lock management, to continuously collect multimodal sensor outputs, including location data, physical activity\u2013related metrics, barometric pressure, and device wear status, and submit data to the back-end server. A preliminary technical evaluation of SensorW was conducted with seven participants who wore SensorW-enabled devices continuously for at least seven consecutive days. The technical evaluation demonstrated multimodal data collection during 17\u201342 days of monitoring, with operational data availability ranging from 0.73 to 1.00 across participants. These findings support the technical feasibility of SensorW as a practical and extensible platform for continuous digital phenotyping using consumer-grade smartwatches.<\/jats:p>","DOI":"10.3390\/s26196093","type":"journal-article","created":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T14:36:34Z","timestamp":1790346994000},"page":"6093","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SensorW: Open-Source Wear Operating System Platform for Continuous Global Positioning System and Multimodal Sensor Data Collection in Real-World Settings"],"prefix":"10.3390","volume":"26","author":[{"given":"Yichi","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Social Medicine, Graduate School of Medicine, Hirosaki University, Hirosaki 036-8562, 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