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Human Activity Recognition Using Self-Supervised Representations of Wearable Data
Our model is based on a frozen self-supervised representation learned on a large unlabeled dataset, combined with a shallow multi-layer perceptron with temporal smoothing.
Human Activity Recognition on wrist-worn accelerometers using self-supervised neural networks
Measures of Activity of Daily Living (ADL) are an important indicator of overall health but difficult to measure in-clinic.
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