Convolutional Neural Network for Elderly Wandering Prediction in Indoor Scenarios

Rafael Oliveira, Fabio Barreto, Raphael Abreu

Abstract

This work proposes a way to detect wandering activity of Alzheimer’s patients from path data collected from non-intrusive indoor sensors around the house. Due to the lack of adequate data, we’ve manually generated a dataset of 220 paths using our own developed application. Wandering patterns in the literature are normally identified by visual features (such as loops or random movement), thus our dataset was transformed into images and augmented. Convolutional layers were used on the neural network model since they tend to have good results finding patterns specially on images. The Convolutional Neural Network model was trained with the generated data and achieved an f1 score (relation between precision and recall) of 75%, recall of 60%, and precision of 100% on our 10 sample validation slice.

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Paper Citation


in Harvard Style

Oliveira R., Barreto F. and Abreu R. (2021). Convolutional Neural Network for Elderly Wandering Prediction in Indoor Scenarios.In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: HEALTHINF, ISBN 978-989-758-490-9, pages 253-260. DOI: 10.5220/0010379902530260


in Bibtex Style

@conference{healthinf21,
author={Rafael Oliveira and Fabio Barreto and Raphael Abreu},
title={Convolutional Neural Network for Elderly Wandering Prediction in Indoor Scenarios},
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: HEALTHINF,},
year={2021},
pages={253-260},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010379902530260},
isbn={978-989-758-490-9},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: HEALTHINF,
TI - Convolutional Neural Network for Elderly Wandering Prediction in Indoor Scenarios
SN - 978-989-758-490-9
AU - Oliveira R.
AU - Barreto F.
AU - Abreu R.
PY - 2021
SP - 253
EP - 260
DO - 10.5220/0010379902530260