Mining Periodic Patterns and Accuracy Calculation for Activity Monitoring Using RF Tag Arrays

Proceedings of International Joint Conference on Computational Intelligence - Algorithms for Intelligent Systems ◽

10.1007/978-981-13-7564-4_8 ◽

2019 ◽

pp. 85-95

Author(s):

Md. Amirul Islam ◽

Uzzal Kumar Acharjee

Keyword(s):

Activity Monitoring ◽

Periodic Patterns ◽

Rf Tag

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Wavelet analysis of EEG for theta activity monitoring as an alternative to fast fourier transform-based analysis

Electroencephalography and Clinical Neurophysiology ◽

10.1016/s0013-4694(97)88508-6 ◽

1997 ◽

Vol 103 (1) ◽

pp. 116

Author(s):

S Angioni

Keyword(s):

Fourier Transform ◽

Wavelet Analysis ◽

Fast Fourier Transform ◽

Activity Monitoring ◽

Theta Activity

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Ambulatory Activity Monitoring

European Psychologist ◽

10.1027/1016-9040.14.2.142 ◽

2009 ◽

Vol 14 (2) ◽

pp. 142-152 ◽

Cited By ~ 54

Author(s):

Johannes B.J. Bussmann ◽

Ulrich W. Ebner-Priemer ◽

Jochen Fahrenberg

Keyword(s):

Physical Activity ◽

Activity Monitoring ◽

Main Stream ◽

Computer Algorithms ◽

Ambulatory Activity ◽

Physiological Variables ◽

Piezoresistive Sensors ◽

Self Reports ◽

Recent Developments ◽

Objectively Measured

Behavior is central to psychology in almost any definition. Although observable activity is a core aspect of behavior, assessment strategies have tended to focus on emotional, cognitive, or physiological responses. When physical activity is assessed, it is done so mostly with questionnaires. Converging evidence of only a moderate association between self-reports of physical activity and objectively measured physical activity does raise questions about the validity of these self-reports. Ambulatory activity monitoring, defined as the measurement strategy to assess physical activity, posture, and movement patterns continuously in everyday life, has made major advances over the last decade and has considerable potential for further application in the assessment of observable activity, a core aspect of behavior. With new piezoresistive sensors and advanced computer algorithms, the objective measurement of physical activity, posture, and movement is much more easily achieved and measurement precision has improved tremendously. With this overview, we introduce to the reader some recent developments in ambulatory activity monitoring. We will elucidate the discrepancies between objective and subjective reports of activity, outline recent methodological developments, and offer the reader a framework for developing insight into the state of the art in ambulatory activity-monitoring technology, discuss methodological aspects of time-based design and psychometric properties, and demonstrate recent applications. Although not yet main stream, ambulatory activity monitoring – especially in combination with the simultaneous assessment of emotions, mood, or physiological variables – provides a comprehensive methodology for psychology because of its suitability for explaining behavior in context.

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