Mobile applications for stroke: A survey and a speech classification approach

Ariella Richardson; Shani Ben Ari; Maayan Sinai; Aviya Atsmon; Ehud S. Conley; Yohai Gat; Gil Segev

doi:10.5220/0007586901590166

Mobile applications for stroke: A survey and a speech classification approach

Ariella Richardson, Shani Ben Ari, Maayan Sinai, Aviya Atsmon, Ehud S. Conley, Yohai Gat, Gil Segev

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health
Editors	Martina Ziefle, Leszek Maciaszek
Pages	159-166
Number of pages	8
ISBN (Electronic)	9789897583681
DOIs	https://doi.org/10.5220/0007586901590166
State	Published - 2019
Externally published	Yes
Event	5th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2019 - Heraklion, Crete, Greece Duration: 2 May 2019 → 4 May 2019

Publication series

Name	ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health

Conference

Conference	5th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2019
Country/Territory	Greece
City	Heraklion, Crete
Period	2/05/19 → 4/05/19

Keywords

Cardiovascular
Data Mining
Digital Health
M-Health
Machine Learning
Mobile
Speech
Stroke

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Computer Science Applications
Health Informatics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.5220/0007586901590166

Cite this

Richardson, A., Ari, S. B., Sinai, M., Atsmon, A., Conley, E. S., Gat, Y., & Segev, G. (2019). Mobile applications for stroke: A survey and a speech classification approach. In M. Ziefle, & L. Maciaszek (Eds.), ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health (pp. 159-166). (ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health). https://doi.org/10.5220/0007586901590166

Richardson, Ariella ; Ari, Shani Ben ; Sinai, Maayan et al. / Mobile applications for stroke : A survey and a speech classification approach. ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health. editor / Martina Ziefle ; Leszek Maciaszek. 2019. pp. 159-166 (ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health).

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title = "Mobile applications for stroke: A survey and a speech classification approach",

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.",

keywords = "Cardiovascular, Data Mining, Digital Health, M-Health, Machine Learning, Mobile, Speech, Stroke",

author = "Ariella Richardson and Ari, \{Shani Ben\} and Maayan Sinai and Aviya Atsmon and Conley, \{Ehud S.\} and Yohai Gat and Gil Segev",

note = "Publisher Copyright: Copyright {\textcopyright} 2019 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved; 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2019 ; Conference date: 02-05-2019 Through 04-05-2019",

year = "2019",

doi = "10.5220/0007586901590166",

language = "الإنجليزيّة",

series = "ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health",

pages = "159--166",

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booktitle = "ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health",

}

Richardson, A, Ari, SB, Sinai, M, Atsmon, A, Conley, ES, Gat, Y & Segev, G 2019, Mobile applications for stroke: A survey and a speech classification approach. in M Ziefle & L Maciaszek (eds), ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health. ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health, pp. 159-166, 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2019, Heraklion, Crete, Greece, 2/05/19. https://doi.org/10.5220/0007586901590166

Mobile applications for stroke: A survey and a speech classification approach. / Richardson, Ariella; Ari, Shani Ben; Sinai, Maayan et al.
ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health. ed. / Martina Ziefle; Leszek Maciaszek. 2019. p. 159-166 (ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Mobile applications for stroke

T2 - 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2019

AU - Richardson, Ariella

AU - Ari, Shani Ben

AU - Sinai, Maayan

AU - Atsmon, Aviya

AU - Conley, Ehud S.

AU - Gat, Yohai

AU - Segev, Gil

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Cardiovascular

KW - Data Mining

KW - Digital Health

KW - M-Health

KW - Machine Learning

KW - Mobile

KW - Speech

KW - Stroke

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DO - 10.5220/0007586901590166

M3 - منشور من مؤتمر

T3 - ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health

SP - 159

EP - 166

BT - ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health

A2 - Ziefle, Martina

A2 - Maciaszek, Leszek

Y2 - 2 May 2019 through 4 May 2019

ER -

Richardson A, Ari SB, Sinai M, Atsmon A, Conley ES, Gat Y et al. Mobile applications for stroke: A survey and a speech classification approach. In Ziefle M, Maciaszek L, editors, ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health. 2019. p. 159-166. (ICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health). doi: 10.5220/0007586901590166

Mobile applications for stroke: A survey and a speech classification approach

Abstract

Publication series

Conference

Keywords

All Science Journal Classification (ASJC) codes

UN SDGs

Access to Document

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