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Mobile Applications for Stroke: A Survey and a Speech Classification Approach

Topics: Assistive Technology and Adaptive Systems; Data Analytics and Health; Diagnostic Support; Emergency and Alerts Handling; Home Care Monitoring Systems; Mobile Health Monitoring; Speech and Tactile Interfaces; Web and Mobile Interaction

Authors: Ariella Richardson 1 ; Shani Ben Ari 1 ; Maayan Sinai 1 ; Aviya Atsmon 1 ; Ehud Conley 1 ; Yohai Gat 1 and Gil Segev 2

Affiliations: 1 Lev Academic Center, Jerusalem and Israel ; 2 BGSegev Ltd. (segevlabs.org), Jerusalem and Israel

ISBN: 978-989-758-368-1

Keyword(s): Digital Health, m-Health, Mobile, Stroke, Speech, Cardiovascular, Machine Learning, Data Mining.

Abstract: Strokes are a cause of serious long-term disability and create an immense burden on healthcare. Among the sea of mobile applications for health, some target stroke patients, and most require active user cooperation. Our proposed application, collects data, without user intervention. We apply data mining methods to create personal feedback to the patient or doctor. We provide a survey of applications for mobile or wearables, specifically for stroke. We also survey papers that apply data mining to stroke. In addition to the survey, we present a feasibility study on using speech for classification of stroke patients. We created a new data set of unstructured speech recordings, increasing applicability. We present experimental results on classification of stroke patients. Our study provides promising insight to detecting stroke patients using a mobile application without requiring active user participation.

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Paper citation in several formats:
Richardson, A.; Ben Ari, S.; Sinai, M.; Atsmon, A.; Conley, E.; Gat, Y. and Segev, G. (2019). Mobile Applications for Stroke: A Survey and a Speech Classification Approach.In Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE, ISBN 978-989-758-368-1, pages 159-166. DOI: 10.5220/0007586901590166

@conference{ict4awe19,
author={Ariella Richardson. and Shani Ben Ari. and Maayan Sinai. and Aviya Atsmon. and Ehud S. Conley. and Yohai Gat. and Gil Segev.},
title={Mobile Applications for Stroke: A Survey and a Speech Classification Approach},
booktitle={Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE,},
year={2019},
pages={159-166},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007586901590166},
isbn={978-989-758-368-1},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE,
TI - Mobile Applications for Stroke: A Survey and a Speech Classification Approach
SN - 978-989-758-368-1
AU - Richardson, A.
AU - Ben Ari, S.
AU - Sinai, M.
AU - Atsmon, A.
AU - Conley, E.
AU - Gat, Y.
AU - Segev, G.
PY - 2019
SP - 159
EP - 166
DO - 10.5220/0007586901590166

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