Ahmed et al., 2013 - Google Patents
Physical activity identification using supervised machine learning and based on pulse rateAhmed et al., 2013
View PDF- Document ID
- 2952790554624116580
- Author
- Ahmed M
- Loutfi A
- Publication year
- Publication venue
- International Journal of Advanced Computer Sciences and Applications
External Links
Snippet
Physical activity is one of the key components for elderly in order to be actively ageing. Pulse rate is a convenient physiological parameter to identify elderly's physical activity since it increases with activity and decreases with rest. However, analysis and classification of …
- 230000000704 physical effect 0 title abstract description 43
Classifications
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- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
- A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
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- G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
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- A—HUMAN NECESSITIES
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- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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