Sub-transfer Learning in Human Activity Recognition: Boosting the Outlier User Accuracy

In this human activity recognition dataset, there are a total of 53 participants, consisting of 33 adults and 20 youths. In a laboratory experiment, individuals were given a set of synchronized sensors that were attached to their wrist and ankle using customized Velcro bands. These sensors, which were called Triaxial Wocket accelerometers, were lightweight, small, and thin. While wearing these sensors, the participants performed everyday tasks, and the raw acceleration data was collected at a rate of 90 Hz and transmitted wirelessly to a smartphone via Bluetooth.