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The standard method for the analysis of body accelerations cannot accurately estimate the energy expenditure (EE) of uphill or downhill walking. The ability to recognize the grade of the walking surface will most likely improve upon the accuracy of the EE estimates for daily physical activities. This paper investigates the benefits of automatic gait analysis approaches including step-by-step gait...
This paper describes classification of gait patterns from a waist-mounted triaxial accelerometer. A feature extraction technique using empirical mode decomposition (EMD) and an amplitude/frequency modulation (AM-FM) model is proposed for the classification of walking activities from accelerometry data. A set of novel features, including AM, instantaneous frequency (IF) and instantaneous amplitude...
This paper describes accelerometry based classification of walking patterns. A feature extraction technique based on empirical mode decomposition (EMD) is proposed for the classification of unsupervised walking activities from accelerometry data. The front-end 20 dimensional features representing the gait patterns were obtained from the first three modes of decomposition of the acceleration data in...
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