The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Wearable feedback systems for rehabilitation
Open accessAbstract
In this paper we describe LiveNet, a flexible wearable platform intended for long-term ambulatory health monitoring with real-time data streaming and context classification. Based on the MIT Wearable Computing Group's distributed mobile system architecture, LiveNet is a stable, accessible system that combines inexpensive, commodity hardware; a flexible sensor/peripheral interconnection bus; and a powerful, light-weight distributed sensing, classification, and inter-process communications software architecture to facilitate the development of distributed real-time multi-modal and context-aware applications. LiveNet is able to continuously monitor a wide range of physiological signals together with the user's activity and context, to develop a personalized, data-rich health profile of a user over time. We demonstrate the power and functionality of this platform by describing a number of health monitoring applications using the LiveNet system in a variety of clinical studies that are underway. Initial evaluations of these pilot experiments demonstrate the potential of using the LiveNet system for real-world applications in rehabilitation medicine.
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Kessler, R. C., Berglund, P., Demler, O., Jin, R., Koretz, D., Merikangas, K. R., Rush, A. J., Walters, E. E., & Wang, P. S. (2003) · JAMA · doi:10.1001/jama.289.23.3095 · Cited by 7,988
Cited by
A review of wearable sensors and systems with application in rehabilitation
Patel, S., Park, H., Bonato, P., Chan, L., & Rodgers, M. (2012) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-9-21 · Cited by 2,396
A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis
Pantelopoulos, A., & Bourbakis, N. G. (2010) · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · doi:10.1109/tsmcc.2009.2032660 · Cited by 2,296
A tutorial on human activity recognition using body-worn inertial sensors
Bulling, A., Blanke, U., & Schiele, B. (2014) · ACM Computing Surveys · doi:10.1145/2499621 · Cited by 1,668
Wireless sensor networks for healthcare: A survey
Alemdar, H., & Ersoy, C. (2010) · Computer Networks · doi:10.1016/j.comnet.2010.05.003 · Cited by 1,427
Smart wearable systems: Current status and future challenges
Chan, M., Estève, D., Fourniols, J.-Y., Escriba, C., & Campo, E. (2012) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2012.09.003 · Cited by 953
Metadata
- Authors
- Sung, M., Marci, C., & Pentland, A.
- Venue
- Journal of NeuroEngineering and Rehabilitation
- Published
- 2005-06-29
- Volume
- 2
- Issue
- 1
- ISSN
- 1743-0003
- OpenAlex
- W2135233422
- Cited by
- 227
- References
- 1
- FWCI
- 15.56
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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