Research Article
Non-intrusive and Privacy Preserving Activity Recognition System for Infants Exploiting Smart Toys
@INPROCEEDINGS{10.1007/978-3-030-99197-5_1, author={Niko Bonomi and Michela Papandrea}, title={Non-intrusive and Privacy Preserving Activity Recognition System for Infants Exploiting Smart Toys}, proceedings={IoT Technologies for Health Care. 8th EAI International Conference, HealthyIoT 2021, Virtual Event, November 24-26, 2021, Proceedings}, proceedings_a={HEALTHYIOT}, year={2022}, month={3}, keywords={Activity Motricity Infants Neurodevelopment Toys HAR Infants activity recognition}, doi={10.1007/978-3-030-99197-5_1} }- Niko Bonomi
Michela Papandrea
Year: 2022
Non-intrusive and Privacy Preserving Activity Recognition System for Infants Exploiting Smart Toys
HEALTHYIOT
Springer
DOI: 10.1007/978-3-030-99197-5_1
Abstract
The Human Activity Recognition (HAR) research area showed great advances in the last decade, achieving excellent prediction performances and great applicability, which is reflected on the wearable sensors market adoption. However, most of the research effort concentrated on an adult target population. When considering a younger population of infants or children, currently available HAR solution based on wearable devices are not applicable anymore. In this paper we present an HAR based solution targeting infants, based on a non-intrusive and privacy-preserving measurement methodology which allows the preservation of children behaviour and the collection of objective data (particularly important for clinical observation purposes). The proposed solution, based on the usage of a set of smart toys (AutoPlay toys-set) achieves great performances in the recognition of a set of 12 toy-activity pairs, reaching accuracy values up to(96\%). These results pave the way to a broad application of the presented methodology on objective analysis of humans motor skills.
