Literature DB >> 17270775

An unobtrusive in-home monitoring system for detection of key motor changes preceding cognitive decline.

T L Hayes1, M Pavel, J A Kaye.   

Abstract

The existing paradigm of ongoing or posttreatment monitoring of patients through periodic but infrequent office visits has many limitations. Relying on self-report by the patient or their family is equally unreliable. We propose an alternative paradigm in which continuous, unobtrusive monitoring is used to observe changes in physical behavior over time. We highlight the use of this technique for monitoring motor activity that may be predictive of early cognitive changes in the elderly. Initial results using a system of low-cost wireless sensors are presented, together with a discussion of appropriate analyses and interpretation of such data. Using low-cost wireless sensor network coupled with algorithms to detect changes in relevant patterns of behavior, we are able to detect both acute and gradual changes that may indicate a need for medical intervention.

Entities:  

Year:  2004        PMID: 17270775     DOI: 10.1109/IEMBS.2004.1403715

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  6 in total

1.  Automated activity-aware prompting for activity initiation.

Authors:  Lawrence B Holder; Diane J Cook
Journal:  Gerontechnology       Date:  2013-01-01

2.  Naturalistic assessment of everyday activities and prompting technologies in mild cognitive impairment.

Authors:  Adriana M Seelye; Maureen Schmitter-Edgecombe; Diane J Cook; Aaron Crandall
Journal:  J Int Neuropsychol Soc       Date:  2013-01-25       Impact factor: 2.892

3.  Unobtrusive assessment of activity patterns associated with mild cognitive impairment.

Authors:  Tamara L Hayes; Francena Abendroth; Andre Adami; Misha Pavel; Tracy A Zitzelberger; Jeffrey A Kaye
Journal:  Alzheimers Dement       Date:  2008-11       Impact factor: 21.566

Review 4.  Application of cognitive rehabilitation theory to the development of smart prompting technologies.

Authors:  Adriana M Seelye; Maureen Schmitter-Edgecombe; Barnan Das; Diane J Cook
Journal:  IEEE Rev Biomed Eng       Date:  2012

Review 5.  Ambient Sensors for Elderly Care and Independent Living: A Survey.

Authors:  Md Zia Uddin; Weria Khaksar; Jim Torresen
Journal:  Sensors (Basel)       Date:  2018-06-25       Impact factor: 3.576

6.  Prediction of Mild Cognitive Impairment Using Movement Complexity.

Authors:  Taha Khan; Peter G Jacobs
Journal:  IEEE J Biomed Health Inform       Date:  2021-01-05       Impact factor: 5.772

  6 in total

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