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dc.contributor.authorYurtman, A.en_US
dc.contributor.authorBarshan, B.en_US
dc.date.accessioned2016-02-08T11:47:33Z
dc.date.available2016-02-08T11:47:33Z
dc.date.issued2014en_US
dc.identifier.urihttp://hdl.handle.net/11693/27208
dc.description.abstractWe develop an autonomous system to detect and evaluate physical therapy exercises using wearable motion sensor units. We propose an algorithm based on the dynamic time warping (DTW) dissimilarity measure to detect the occurrences of one or more exercise types in the recording of a physical therapy session. The algorithm evaluates the exercises as correctly/incorrectly performed, identifying the error type, if any. To evaluate the algorithm's performance, we record a data set consisting of one template execution and 10 test executions of each of the three execution types of eight exercises performed by five subjects. We thus obtain a total of 120 and 1,200 exercise executions in the training and test sets, respectively. The test signals also contain idle time intervals. The proposed algorithm detects 1,125 executions in the whole test set, where 8.58% of the 1,200 executions are missed and 4.91% of the idle time intervals are incorrectly detected as executions. The accuracy is 93.46 % for exercise classification only and 88.65 % for simultaneous exercise and execution type classification. To test the behavior of the system in case of unknown movements, the algorithm is executed for each exercise by leaving out the templates of that exercise, resulting in only 10 false alarms out of 1,200 executions. This demonstrates the robustness of the system against unknown movements. The proposed system may be used both for estimating the intensity of a physical therapy session and for evaluating executions of an exercise to provide feedback to the patient and the physical therapy specialist. © 2014 IEEE.en_US
dc.language.isoTurkishen_US
dc.source.title2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedingsen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2014.6830523en_US
dc.subjectaccelerometeren_US
dc.subjectautomated physical therapyen_US
dc.subjectdynamic programmingen_US
dc.subjectdynamic time warpingen_US
dc.subjectgyroscopeen_US
dc.subjectinertial sensorsen_US
dc.subjectmagnetometeren_US
dc.subjectmotion detectionen_US
dc.subjectmotion sensorsen_US
dc.subjectpattern recognitionen_US
dc.subjectpattern searchen_US
dc.subjectphysiotherapyen_US
dc.subjectsubsequence dynamic time warpingen_US
dc.subjectAccelerometersen_US
dc.subjectDynamic programmingen_US
dc.subjectGyroscopesen_US
dc.subjectMagnetometersen_US
dc.subjectPattern recognitionen_US
dc.subjectPhysical therapyen_US
dc.subjectSensorsen_US
dc.subjectSignal detectionen_US
dc.subjectStatistical testsen_US
dc.subjectTestingen_US
dc.subjectDynamic time warpingen_US
dc.subjectInertial sensoren_US
dc.subjectMotion detectionen_US
dc.subjectMotion sensorsen_US
dc.subjectPattern searchen_US
dc.subjectAlgorithmsen_US
dc.titleDetection and evaluation of physical therapy exercises from wearable motion sensor signals by dynamic time warpingen_US
dc.title.alternativeFizik tedavi egzersizlerinin giyilebilir hareket algilayicilari i şaretlerinden dinamik zaman bükmesiyle sezimi ve değerlendirilmesien_US
dc.typeConference Paperen_US
dc.departmentDepartment of Electrical and Electronics Engineering
dc.citation.spage1491en_US
dc.citation.epage1494en_US
dc.identifier.doi10.1109/SIU.2014.6830523en_US
dc.publisherIEEE Computer Societyen_US


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