Characterization of Upper Limb Functionality Caused by Neuromuscular Disorders using Novel Motion Features from a Specialized Gaming Platform

A. Chytas, D. Fotopoulos, V. Kilintzis, E. Koutsiana, I. Ladakis, E. Kiana, T. Loizidis, I. Chouvarda

2021

Abstract

This paper describes the methodology for analyzing upper limb motion data derived from a novel Gamified Motion Control Assessment platform that is based on a virtual 3D game environment. The gamified approach targets patients experiencing upper-limb movement hindrances, typically caused by neuromuscular disorders. The leap motion controller is used for interaction. The game guides the avatar to move along the X and Y axis following specific paths. The avatar mimics the movement of the user's hand that performs these movements for rehabilitation. In order to use this method for the training and assessment patient’s motion, a quantified approach that uses the game-based motion for patient assessment is required. Besides simple game scores that are often used, the proposed data analysis aims to elaborate on the discrimination between pathological and healthy movement with a machine learning approach, as well as the quantification of the patient’s progress over time. For this purpose, movement and performance-related features were extracted from the leap sensor recordings and their value was explored towards characterizing the patient state and progress in detail. A dataset with multiple recordings from patients and healthy individuals was used for this purpose. All patients suffered from neuromuscular disorders. The features with the highest discriminatory value between the two groups were subsequently used to develop a set of classifiers for different sets of movements (e.g., horizontal, diagonal, vertical). A patient was left out of the classifier creation procedure and used for external validation. The models achieved high accuracy (92.13%). These results are deemed promising for the quantification of a patient’s progress.

Paper Citation

in Harvard Style

Chytas A., Fotopoulos D., Kilintzis V., Koutsiana E., Ladakis I., Kiana E., Loizidis T. and Chouvarda I. (2021). Characterization of Upper Limb Functionality Caused by Neuromuscular Disorders using Novel Motion Features from a Specialized Gaming Platform. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 4: BIOSIGNALS; ISBN 978-989-758-490-9, SciTePress, pages 60-68. DOI: 10.5220/0010244400002865

in Bibtex Style

@conference{biosignals21,
author={A. Chytas and D. Fotopoulos and V. Kilintzis and E. Koutsiana and I. Ladakis and E. Kiana and T. Loizidis and I. Chouvarda},
title={Characterization of Upper Limb Functionality Caused by Neuromuscular Disorders using Novel Motion Features from a Specialized Gaming Platform},
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 4: BIOSIGNALS},
year={2021},
pages={60-68},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010244400002865},
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 (BIOSTEC 2021) - Volume 4: BIOSIGNALS
TI - Characterization of Upper Limb Functionality Caused by Neuromuscular Disorders using Novel Motion Features from a Specialized Gaming Platform
SN - 978-989-758-490-9
AU - Chytas A.
AU - Fotopoulos D.
AU - Kilintzis V.
AU - Koutsiana E.
AU - Ladakis I.
AU - Kiana E.
AU - Loizidis T.
AU - Chouvarda I.
PY - 2021
SP - 60
EP - 68
DO - 10.5220/0010244400002865
PB - SciTePress