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ACTIVITY MONITORING SYSTEM USING DYNAMIC TIME WARPING FOR THE ELDERLY AND DISABLED PERSONS

Platform : EMBEDDED

IEEE Projects Years : 2012-13

ACTIVITY MONITORING SYSTEM USING DYNAMIC TIME WARPING FOR THE ELDERLY AND DISABLED PERSONS

AIM:

 

                                                          Our system applied DTW method to recognize human activities of daily living. We used two feature sets to the classifier such as database and test data. We kept signals to the reference databases from two healthy subjects, male is 24 years old and female is 23 years old. Train data were recorded from different human activities.. By the way, test data were the test signals inputs. These test signals were recorded every two seconds (sampling time 70ms). Each test signal was computed in DTW method with ten activities reference database as follow DTW method computed two signals per time: test signal and reference database signal. So, DTW was used for ten times per each test signal. In this method, we got ten optimal warp paths as above-mentioned. After that, we found the minimal value from these ten optimal warp paths.



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