Health-status monitoring through analysis of behavioral patterns

By Tracy Barger, Donald E. Brown, Majd Alwan. IEEE transactions on systems, man and cybernetics. Part A. Systems and humans, 2005

314 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Transportation, Signal Processing

View Paper: https://www.semanticscholar.org/paper/d1be79d04ff875ee2e6a10ec7bd4d70ab2243f88

How researchers see this paper

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In Computer Vision and Pattern Recognition

In Transportation

In Signal Processing

Citations in the corpus

Simultaneous Tracking and Activity Recognition (STAR) Using Many Anonymous, Binary Sensors (2005, unknown): “Like other researchers in academia and industry, we envision an off-the-shelf system installed and configured by a consumer [1, 6, 7, 28].”
A Survey on Ambient-Assisted Living Tools for Older Adults (2013, background): “cluding decision trees [67], neural networks [68], case-based reasoning [69], mixture models [70], and the popular graphical models [71].”
Wireless Architectures for Heterogeneous Sensing in Smart Home Applications: Concepts and Real Implementation (2013, background): “During that time, researchers began to recognize the importance of applying and improving methodologies for behavior monitoring and decision making also in the fields of assistance services [72], [73] and power management [64].”
How smart are our environments? An updated look at the state of the art (2007, background): “At University of Virginia’s MARC project [5], these sensors were able to actually categorize individual’s days into vacation (at home) and work days.”
Emotion Recognition From EEG Using Higher Order Crossings (2010, methodology): “…signals to emotions and synthesizing the patient's affective information for the healthcare provider [6]; enhancement of behavioral patterns of daily activity using ontological models that embed the emotional factor, assisting diagnosis in conjunction to a person's health condition [7].”
A Survey on Ambient Intelligence in Health Care (2013, unknown): “Methods for activity discovery build on a rich history of discovery research, including methods for mining frequent sequences [1,17], mining frequent patterns using regular expressions [47], constraint-based mining [90], and frequent-periodic pattern mining [91], [92].”