Journal ArticleDOI
Fast track article: Assessing everyday life behavioral rhythms for the older generation
TLDR
A pattern recognition model for assessing behavioral rhythms in the framework of aging and technologies is presented and a customized software embedding the model shows the potential of the system tool to detect baseline behaviors and changes, which could be related to particular chronic disease symptoms.About:
This article is published in Pervasive and Mobile Computing.The article was published on 2009-10-01. It has received 37 citations till now.read more
Citations
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Journal ArticleDOI
Literature review on monitoring technologies and their outcomes in independently living elderly people.
TL;DR: Monitoring technology is a promising field, with applications to the long-term care of elderly persons, however, monitoring technologies have to be brought to the next level, with longitudinal studies that evaluate their (cost-) effectiveness to demonstrate the potential to prolong independent living of elderly people.
Journal ArticleDOI
Monitoring human health behaviour in one's living environment: A technological review
Shane A. Lowe,Gearóid ÓLaighin +1 more
TL;DR: The range of technologies that have been used in isolation for behaviour monitoring both in research and commercial devices are reviewed and discussed and Filtering, range, sensitivity, usability and other considerations of different technologies are discussed.
Journal ArticleDOI
Progress in ambient assisted systems for independent living by the elderly
TL;DR: Findings from the work suggest that most frameworks focused on activity monitoring for assessing immediate risks, while the opportunities for integrating environmental factors for analytics and decision-making, in particular for the long-term care were often overlooked.
Journal ArticleDOI
Ambient Sensors for Elderly Care and Independent Living: A Survey.
TL;DR: A comprehensive survey of non-wearable (i.e., ambient) sensors for various elderly care systems with insight into different types of ambient-sensor-based elderly monitoring technologies in the home is obtained.
Proceedings ArticleDOI
AALO: Activity recognition in smart homes using Active Learning in the presence of Overlapped activities
Enamul Hoque,John A. Stankovic +1 more
TL;DR: The evaluation of activity recognition performance on a 26-day dataset shows that the active learning based approach performs as good as the state of the art supervised techniques (HMM and HSMM).
References
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Journal ArticleDOI
Assessing Self‐maintenance: Activities of Daily Living, Mobility, and Instrumental Activities of Daily Living
TL;DR: There is documented evidence that measures of self-maintaining function can be reliably used in clinical evaluations as well as in program evaluations and in planning and that evaluation by these measures helps to identify problems that require treatment or care.
Proceedings ArticleDOI
Recognizing human action in time-sequential images using hidden Markov model
Junji Yamato,J. Ohya,K. Ishii +2 more
TL;DR: The recognition rate is improved by increasing the number of people used to generate the training data, indicating the possibility of establishing a person-independent action recognizer.
Journal ArticleDOI
Recent developments in human motion analysis
Liang Wang,Weiming Hu,Tieniu Tan +2 more
TL;DR: This paper provides a comprehensive survey of research on computer-vision-based human motion analysis, namely human detection, tracking and activity understanding, and various methods for each issue are discussed in order to examine the state of the art.
Journal ArticleDOI
Older adults' attitudes towards and perceptions of ‘smart home’ technologies: a pilot study
George Demiris,Marilyn Rantz,Myra A. Aud,Karen Dorman Marek,Harry W. Tyrer,Marjorie Skubic,Ali Hussam +6 more
TL;DR: The perceptions and expectations of seniors in regard to ‘smart home’ technology installed and operated in their homes with the purpose of improving their quality of life and/or monitoring their health status are explored.
Proceedings ArticleDOI
Real-Time Recognition of Physical Activities and Their Intensities Using Wireless Accelerometers and a Heart Rate Monitor
Emmanuel Munguia Tapia,Stephen S. Intille,William L. Haskell,Kent Larson,Julie A. Wright,Abby C. King,Robert H. Friedman +6 more
TL;DR: A real-time algorithm for automatic recognition of not only physical activities, but also, in some cases, their intensities, using five triaxial wireless accelerometers and a wireless heart rate monitor is presented.