DocumentCode :
2937172
Title :
Recognizing short duration hand movements from accelerometer data
Author :
Krishnan, Narayanan C. ; Pradhan, Gaurav N. ; Panchanathan, Sethuraman
Author_Institution :
Dept. of Comput. Sci. & Eng., Arizona State Univ., Tempe, AZ, USA
fYear :
2009
fDate :
June 28 2009-July 3 2009
Firstpage :
1700
Lastpage :
1703
Abstract :
Processing of accelerometer data for recognizing short duration hand movements is a challenging problem. This paper focuses on characterization of acceleration data corresponding to hand movements (lift to mouth, scoop, stir, pour, unscrew cap) using aggregate statistical features and histograms computed from raw acceleration and derivative of the acceleration data. Data collected from an accelerometer placed on the wrist of subjects was used to perform the analysis. Supplementing the statistical features with raw acceleration histograms had a very marginal effect on the classification performance. However, the addition of derivative histograms resulted in a considerable improvement in the classification accuracy by nearly 8%. The effect of bin size of the derivative histograms was also conducted. It was observed that having a small number of bins decreased the classification accuracy by 3%. We thus show that adding features that capture the distribution of the changes in the acceleration data improve the classification performance.
Keywords :
accelerometers; feature extraction; image motion analysis; statistical analysis; acceleration histogram; accelerometer data processing; aggregate statistical features; feature extraction; short duration hand movement recognition; Acceleration; Accelerometers; Biomedical monitoring; Biosensors; Feature extraction; Histograms; Mouth; Sensor phenomena and characterization; Wearable sensors; Wrist; accelerometer; feature extraction; histograms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo, 2009. ICME 2009. IEEE International Conference on
Conference_Location :
New York, NY
ISSN :
1945-7871
Print_ISBN :
978-1-4244-4290-4
Electronic_ISBN :
1945-7871
Type :
conf
DOI :
10.1109/ICME.2009.5202848
Filename :
5202848
Link To Document :
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