Key result
Integrating contextual factors like activity type and sensor location into regression models improved the R2 value for MET calculation of exergaming movements from 0.71 to up to 0.89.
Integrating contextual information such as activity type and sensor location improves the accuracy of MET calculations from wearable motion sensors during exergaming.
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May refine wearable MET estimates during exergaming; hypothesis-generating and requires clinical validation before practice change.
Mortazavi et al. (2014) studied this question. Context-aware data processing (activity type and sensor location) vs. Generalized model was evaluated on R2 value for MET calculation and mean absolute error. Integrating contextual factors like activity type and sensor location into regression models improved the R2 value for MET calculation of exergaming movements from 0.71 to up to 0.89.
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