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<t>WIS</t> <t>module</t> pictorially represented on a human model in T-pose
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WIS module pictorially represented on a human model in T-pose

Journal: IEEE sensors journal

Article Title: Wearable Inertial Sensors for Range of Motion Assessment

doi: 10.1109/JSEN.2019.2960320

Figure Lengend Snippet: WIS module pictorially represented on a human model in T-pose

Article Snippet: The results indicate that the EGM approach, requiring four quaternion products, is computationally efficient compared to the EG approach, requiring eight quaternion products. table ft1 table-wrap mode="anchored" t5 TABLE III caption a7 Technique Computation time for one WIS module ( μ s) Computation time for five WIS modules ( μ s) EG approach 65.01 325.05 EGM approach 18.50 92.50 Open in a separate window C omputation T ime for D ifferent M isalignment T echniques A MATLAB routine was developed to obtain the positive and negative peaks of the time series WIS module data using findpeaks command.

Techniques:

C omputation T ime for D ifferent M isalignment T echniques

Journal: IEEE sensors journal

Article Title: Wearable Inertial Sensors for Range of Motion Assessment

doi: 10.1109/JSEN.2019.2960320

Figure Lengend Snippet: C omputation T ime for D ifferent M isalignment T echniques

Article Snippet: The results indicate that the EGM approach, requiring four quaternion products, is computationally efficient compared to the EG approach, requiring eight quaternion products. table ft1 table-wrap mode="anchored" t5 TABLE III caption a7 Technique Computation time for one WIS module ( μ s) Computation time for five WIS modules ( μ s) EG approach 65.01 325.05 EGM approach 18.50 92.50 Open in a separate window C omputation T ime for D ifferent M isalignment T echniques A MATLAB routine was developed to obtain the positive and negative peaks of the time series WIS module data using findpeaks command.

Techniques: