A Hybrid Model based on Convolutional Neural Networks and Long Short-term Memory for Rest Tremor Classification

Jihen Fourati, Jihen Fourati, Mohamed Othmani, Hela Ltifi, Hela Ltifi

2022

Abstract

Parkinson’s disease is a neurodegenerative disease, in which tremor is the main symptom. Deep brain stimulation can help manage a broad range of neurological ailments such as Parkinson’s disease. It involves electrical impulses delivered to specific targets in the brain, with the purpose of altering or modulating neural functioning. Security is playing a vital role in protecting healthcare gadgets from unauthorized access or modification. Our purpose is to adopt deep learning methodologies to classify resting tremors. To achieve this purpose, a novel approach for resting tremor classification in patients with Parkinson’s disease using a hybrid model based on convolutional neural networks and long short-term memory is proposed. This research exploits the high-level feature extraction of the convolutional neural network model and the potential capacity to capture long-term dependencies of the long short-term memory model. The performed experiments demonstrate that our proposed approach outperforms the best result for other state-of-the-art methods.

Paper Citation

in Harvard Style

Fourati J., Othmani M. and Ltifi H. (2022). A Hybrid Model based on Convolutional Neural Networks and Long Short-term Memory for Rest Tremor Classification. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-547-0, pages 75-82. DOI: 10.5220/0010773600003116

in Bibtex Style

@conference{icaart22,
author={Jihen Fourati and Mohamed Othmani and Hela Ltifi},
title={A Hybrid Model based on Convolutional Neural Networks and Long Short-term Memory for Rest Tremor Classification},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2022},
pages={75-82},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010773600003116},
isbn={978-989-758-547-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - A Hybrid Model based on Convolutional Neural Networks and Long Short-term Memory for Rest Tremor Classification
SN - 978-989-758-547-0
AU - Fourati J.
AU - Othmani M.
AU - Ltifi H.
PY - 2022
SP - 75
EP - 82
DO - 10.5220/0010773600003116