PUB - Publikationen an der Universität Bielefeld

Biosensors measure signals from the human body, and usually process them with a small ML model on simple hardware. When a new person starts using such a device, a domain adaptation problem arises. We consider the case where no labels are known for the new person, but data (including labels) from several other people are available (unsupervised, multi-source). As an application scenario, we look at a shoe insole with 3-8 pressure sensors that estimates how much weight/force is put on the foot (regression problem). We propose a distance measure between a source and target domain, and a combination of all source models. Experiments on real world data from 13 persons show that our method outperforms all other tested methods by a good margin.