Evidence map›Paper›PMID 42884293›Full record

ArticleSensors (Basel, Switzerland)2026

SensorW: Open-Source Wear Operating System Platform for Continuous Global Positioning System and Multimodal Sensor Data Collection in Real-World Settings.

Yichi Yang, Kazushige Ihara, Felipe Alfonso Sandoval Garrido, Koki Hirata, Tao Jiang, Hua Lan, Han Wu, Hongyue Yu, Yoshinori Tamada, Koichi Murashita and 2 more

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Yichi YangDepartment of Social Medicine, Graduate School of Medicine, Hirosaki University, Hirosaki 036-8562, Japan.
Kazushige IharaDepartment of Social Medicine, Graduate School of Medicine, Hirosaki University, Hirosaki 036-8562, Japan.
Felipe Alfonso Sandoval GarridoSection of Global Health and Preventive Medicine, Global Well-being Research Institute, Hirosaki University, Hirosaki 036-8562, Japan.
Koki HirataDepartment of Social Medicine, Graduate School of Medicine, Hirosaki University, Hirosaki 036-8562, Japan.
Tao JiangDepartment of Social Medicine, Graduate School of Medicine, Hirosaki University, Hirosaki 036-8562, Japan.ORCID 0009-0004-6284-9162
Hua LanDepartment of Social Medicine, Graduate School of Medicine, Hirosaki University, Hirosaki 036-8562, Japan.
Han WuDepartment of Social Medicine, Graduate School of Medicine, Hirosaki University, Hirosaki 036-8562, Japan.
Hongyue YuDepartment of Social Medicine, Graduate School of Medicine, Hirosaki University, Hirosaki 036-8562, Japan.
Yoshinori TamadaResearch Institute of Health Innovation, Hirosaki University, Hirosaki 036-8562, Japan.ORCID 0000-0003-3483-9712
Koichi MurashitaResearch Institute of Health Innovation, Hirosaki University, Hirosaki 036-8562, Japan.
Ken ItohDepartment of Stress Response Science, Biomedical Research Center, Graduate School of Medicine, Hirosaki University, Hirosaki 036-8562, Japan.ORCID 0000-0002-5518-0729
Kazutaka YoshidaInstitute of Global Well-being Science, Hirosaki University, Hirosaki 036-8562, Japan.

Funding

Japan's Peak Research Universities (J-PEAKS)
6 · The paper itself

Abstract

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-related 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 17-42 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.

Indexed as

Data CollectionGeographic Information SystemsDigital HealthHumansSmartphoneWearable Electronic Deviceslifelog datamobile healthwearable sensing

Identifiers

PMID42884293
PMCPMC13667565

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.