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Decision-tree-based human activity classification algorithm using single-channel foot-mounted gyroscope
Wearable devices that measure and recognise human activity in realtime require classification algorithms that are both fast and accurate when implemented on limited hardware. This paper presents a decision-tree based method for differentiating between individual walking, running, stair climbing and stair descent strides using a single channel of a foot mounted gyroscope suitable for implementation on embedded hardware. Temporal features unique to each activity were extracted using an initialdoi:10.1049/el.2015.0436 fatcat:wjnoeoy3c5hzzo6kn6clpb7umy