Transferring Knowledge of Daily Life Routines with Wearable Accessory

Creative Commons license.

Project description

Benefits from characterization of the patient’s routines goes into medical diagnosis and care of elderly people to assess individual’s physical and mental conditions. Annotation techniques to collect reference data are expensive, time-consuming and error-prone.

This project aims to implement an energy-efficient daily routine recognition algorithm able to learn activities and to transfer available knowledge to new activities. Daily life activity dataset from wrist-worn inertial sensors is provided.

Project type Bachelor/Master Thesis
Work distribution 100% Data Analysis
Useful knowledge Machine learning
Starting date Immediate


Giovanni Schiboni

Friedrich-Alexander-Universität Erlangen-Nürnberg