OpenHealth: Open-Source Platform for Wearable Health Monitoring
Abstract
This article presents an open-source platform for wearable health monitoring. It aims to design a standard set of hardware/software and wearable devices that can enable autonomous collection of clinically relevant data. It provides reference implementations of human activity and gesture recognition applications within this platform.
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OpenHealth achieves greater than 90% accuracy for all actions, such as stand, jump, walk and sit.
“Experiment results demonstrate that the system achieves greater than 90% accuracy for all actions, such as stand, jump, walk and sit.”
From Review of Wearable Devices and Data Collection Considerations for Connected Health (2021) · cites this paper as [161]
OpenHealth wearable device can identify movements, such as up, down, left and right, with an accuracy of 98.6% in trials with seven users.
“Trials with seven users show that the wearable device can identify these movements with an accuracy of 98.6% [161].”
From Review of Wearable Devices and Data Collection Considerations for Connected Health (2021) · cites this paper as [161]
Cites
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Self-citationTelehealth Management of Parkinson’s Disease Using Wearable Sensors: An Exploratory Study
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Self-citationNear-optimal energy allocation for self-powered wearable systems
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Review of Wearable Devices and Data Collection Considerations for Connected Health
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- Authors
- Bhat, G., Deb, R., & Ogras, U. Y.
- Affiliations
- Arizona State University (US)
- Venue
- IEEE Design & Test
- Published
- 2019-10
- Volume
- 36
- Issue
- 5
- Pages
- 27-34
- ISSN
- 2168-2356 (ISSN-L)
- 2168-2364
- OpenAlex
- W2921296709
- Cited by
- 36
- References
- 16
- Citations by year
- 2026: 1 · 2024: 5 · 2023: 6 · 2022: 7 · 2021: 8 · 2020: 5 · 2019: 4
- FWCI
- 2.69
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Design and Test (publishedVersion)
- Funders
- National Science Foundation
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
- Keywords
- wearable health monitoring, open-source platform, wearable devices, human activity recognition, gesture recognition, clinical data collection, reference implementation
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