Wearable feedback systems for rehabilitation

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.

[1]  Holter Nj,et al.  Remote recording of physiological data by radio. , 1949 .

[2]  Simon Kay,et al.  Telemedicine Theory and Practice , 1997 .

[3]  R. Elford.  Telemedicine: Theory and Practice , 1997 .

[4]  C. Tavormina.  Embracing the Eden Alternative in long-term care environments. , 1999, Geriatric nursing.

[5]  M. Gabe.  Mental health: a report of the Surgeon General. , 2000, Home care provider.

[6]  Xiaoyi Ma,et al.  Eliciting user preferences using image-based experience sampling and reflection , 2002, CHI Extended Abstracts.

[7]  Albrecht Schmidt,et al.  Multi-sensor context aware clothing , 2002, Proceedings. Sixth International Symposium on Wearable Computers,.

[8]  Sumit Basu,et al.  Conversational scene analysis , 2002 .

[9]  Olga V. Demler,et al.  The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). , 2003, JAMA.

[10]  Alex Pentland,et al.  MIThril 2003: applications and architecture , 2003, Seventh IEEE International Symposium on Wearable Computers, 2003. Proceedings..

[11]  Joshua Weaver.  A wearable health monitor to aid Parkinson disease treatment , 2003 .

[12]  Medical devices: cardiovascular devices: reclassification of the arrhythmia detector and alarm. Final rule. , 2003, Federal register.

[13]  W. Flemons,et al.  Comparison of home oximetry monitoring with laboratory polysomnography in children. , 2003, Chest.

[14]  Walter Bender,et al.  Every sign of life , 2003 .

[15]  Alex Pentland,et al.  Social Network Computing , 2003, UbiComp.

[16]  David A. Klapper.  Use of wearable ambulatory monitor in the classification of movement states in Parkinson's disease , 2003 .

[17]  Ling Bao,et al.  Physical activity recognition from acceleration data under semi-naturalistic conditions , 2003 .

[18]  Kent Larson,et al.  MITes: Wireless Portable Sensors for Studying Behavior , 2004 .

[19]  Natalia Marmasse,et al.  Providing lightweight telepresence in mobile communication to enhance collaborative living , 2004 .