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The Research Of Energy Expenditure Detection Based On Tri-axial Acelerometer

Posted on:2012-07-02Degree:MasterType:Thesis
Country:ChinaCandidate:G Z ZhuFull Text:PDF
GTID:2178330332484633Subject:Biomedical engineering
Abstract/Summary:PDF Full Text Request
The physical activity energy expenditure mainly refers to the part of the body energy which is used for muscle contraction to mechanical work. People's diet structure has changed enormously with the improvement of living standards.Many chronic diseases,such as hypertension and diabetes mellitus,have happened more and more common.One reason leading to this result is that people take too little sports so that their energy expenditure is reduced.The detection of the physical activity energy expenditure is extremely important to forecast physical activity and improve movement way.In clinical medicine,some diseases,such as hyperthyroidism,need to monitor the patients'energy expenditure. In the athletic training,physical activity is also needed to measured to improve athletes'training effect.Besides,the research of the physical activity energy expenditure is also very important in In nutrition and labor physiology fields.Human daily actions are protean.Monitoring the daily actions is significant to personal health(such as keeping from falling) and social security(illegal activities).Considering two points mentioned above,we developed a monitoring system of three-dimensional acceleration to monitor the physical activity energy expenditure and daily actions.The system is based on three-dimensional acceleration transducer (MMA7260) and microprocessor (MSP430F149).The research includes two parts.The first is the recognition of daily action.We will recognize six actions(stand,upstairs,downstairs,walk,run and jump).We will choose the best scheme and realize the recognition of six actions by comparing two algorithms and three positions for wearing device.The second is monitoring the physical activity energy expenditure. We will choose the best scheme and realize the measurement accuracy up to 94% by comparing two algorithms and three positions for wearing device.
Keywords/Search Tags:Physical Activity Energy Expenditure Monitoring, Gesture Recognition, Tri-axial Acceleration, Sensor
PDF Full Text Request
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