A Smartphone-Based Clinical Decision Support System for Tremor Assessment

Guillaume Zamora; Caro E.M. Fuchs; Aurelie Degeneffe; Pieter Kubben; Uzay Kaymak

doi:10.1007/978-3-030-63061-4_1

A Smartphone-Based Clinical Decision Support System for Tremor Assessment

Guillaume Zamora, Caro E.M. Fuchs, Aurelie Degeneffe, Pieter Kubben, Uzay Kaymak

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

3 Citations (Scopus)

Abstract

Tremor severity assessment is an important element for the diagnosis and treatment decision-making process of patients suffering from Essential Tremor (ET). Classically, questionnaires like the ETRS and QUEST surveys have been used to assess tremor severity. Recently, attention around computerized tremor analysis has grown. In this study, we use regression trees to map the relationship between tremor data that is collected using the TREMOR12 smartphone application with ETRS and QUEST scores. We aim to develop a model that is able to automatically assess tremor severity of patients suffering from Essential Tremor without the use of more subjective questionnaires. This study shows that tremor data gathered using the TREMOR12 application is useful for constructing machine learning models that can be used to support the diagnosis and monitoring of patients who suffer from Essential Tremor.

Original language	English
Title of host publication	Computational Intelligence Methods for Bioinformatics and Biostatistics - 16th International Meeting, CIBB 2019, Revised Selected Papers
Subtitle of host publication	16th International Meeting, CIBB 2019, Bergamo, Italy, September 4–6, 2019, Revised Selected Papers
Editors	Paolo Cazzaniga, Daniela Besozzi, Ivan Merelli, Luca Manzoni
Place of Publication	Cham
Publisher	Springer
Chapter	1
Pages	3-12
Number of pages	10
ISBN (Electronic)	978-3-030-63061-4
ISBN (Print)	978-3-030-63060-7
DOIs	https://doi.org/10.1007/978-3-030-63061-4_1
Publication status	Published - 2020
Event	16th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics, CIBB 2019 - Bergamo, Italy Duration: 4 Sept 2019 → 6 Sept 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12313 LNBI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics, CIBB 2019
Abbreviated title	CIBB 2019
Country/Territory	Italy
City	Bergamo
Period	4/09/19 → 6/09/19

Funding

Grenoble Institute of Technology

Keywords

Clinical decision support
Essential Tremor
Smartphone application
Tremor severity

Access to Document

10.1007/978-3-030-63061-4_1

Cite this

Zamora, G., Fuchs, C. E. M., Degeneffe, A., Kubben, P., & Kaymak, U. (2020). A Smartphone-Based Clinical Decision Support System for Tremor Assessment. In P. Cazzaniga, D. Besozzi, I. Merelli, & L. Manzoni (Eds.), Computational Intelligence Methods for Bioinformatics and Biostatistics - 16th International Meeting, CIBB 2019, Revised Selected Papers: 16th International Meeting, CIBB 2019, Bergamo, Italy, September 4–6, 2019, Revised Selected Papers (pp. 3-12). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12313 LNBI). Springer. https://doi.org/10.1007/978-3-030-63061-4_1

Zamora, Guillaume ; Fuchs, Caro E.M. ; Degeneffe, Aurelie et al. / A Smartphone-Based Clinical Decision Support System for Tremor Assessment. Computational Intelligence Methods for Bioinformatics and Biostatistics - 16th International Meeting, CIBB 2019, Revised Selected Papers: 16th International Meeting, CIBB 2019, Bergamo, Italy, September 4–6, 2019, Revised Selected Papers. editor / Paolo Cazzaniga ; Daniela Besozzi ; Ivan Merelli ; Luca Manzoni. Cham : Springer, 2020. pp. 3-12 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{b1881ec628dd499faf56965b19fab9bf,

title = "A Smartphone-Based Clinical Decision Support System for Tremor Assessment",

abstract = "Tremor severity assessment is an important element for the diagnosis and treatment decision-making process of patients suffering from Essential Tremor (ET). Classically, questionnaires like the ETRS and QUEST surveys have been used to assess tremor severity. Recently, attention around computerized tremor analysis has grown. In this study, we use regression trees to map the relationship between tremor data that is collected using the TREMOR12 smartphone application with ETRS and QUEST scores. We aim to develop a model that is able to automatically assess tremor severity of patients suffering from Essential Tremor without the use of more subjective questionnaires. This study shows that tremor data gathered using the TREMOR12 application is useful for constructing machine learning models that can be used to support the diagnosis and monitoring of patients who suffer from Essential Tremor.",

keywords = "Clinical decision support, Essential Tremor, Smartphone application, Tremor severity",

author = "Guillaume Zamora and Fuchs, {Caro E.M.} and Aurelie Degeneffe and Pieter Kubben and Uzay Kaymak",

year = "2020",

doi = "10.1007/978-3-030-63061-4_1",

language = "English",

isbn = "978-3-030-63060-7",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "3--12",

editor = "Paolo Cazzaniga and Daniela Besozzi and Merelli, {Ivan } and Luca Manzoni",

booktitle = "Computational Intelligence Methods for Bioinformatics and Biostatistics - 16th International Meeting, CIBB 2019, Revised Selected Papers",

address = "Germany",

note = "16th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics, CIBB 2019, CIBB 2019 ; Conference date: 04-09-2019 Through 06-09-2019",

}

Zamora, G, Fuchs, CEM, Degeneffe, A, Kubben, P & Kaymak, U 2020, A Smartphone-Based Clinical Decision Support System for Tremor Assessment. in P Cazzaniga, D Besozzi, I Merelli & L Manzoni (eds), Computational Intelligence Methods for Bioinformatics and Biostatistics - 16th International Meeting, CIBB 2019, Revised Selected Papers: 16th International Meeting, CIBB 2019, Bergamo, Italy, September 4–6, 2019, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12313 LNBI, Springer, Cham, pp. 3-12, 16th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics, CIBB 2019, Bergamo, Italy, 4/09/19. https://doi.org/10.1007/978-3-030-63061-4_1

A Smartphone-Based Clinical Decision Support System for Tremor Assessment. / Zamora, Guillaume; Fuchs, Caro E.M.; Degeneffe, Aurelie et al.
Computational Intelligence Methods for Bioinformatics and Biostatistics - 16th International Meeting, CIBB 2019, Revised Selected Papers: 16th International Meeting, CIBB 2019, Bergamo, Italy, September 4–6, 2019, Revised Selected Papers. ed. / Paolo Cazzaniga; Daniela Besozzi; Ivan Merelli; Luca Manzoni. Cham: Springer, 2020. p. 3-12 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12313 LNBI).

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

TY - GEN

T1 - A Smartphone-Based Clinical Decision Support System for Tremor Assessment

AU - Zamora, Guillaume

AU - Fuchs, Caro E.M.

AU - Degeneffe, Aurelie

AU - Kubben, Pieter

AU - Kaymak, Uzay

PY - 2020

Y1 - 2020

N2 - Tremor severity assessment is an important element for the diagnosis and treatment decision-making process of patients suffering from Essential Tremor (ET). Classically, questionnaires like the ETRS and QUEST surveys have been used to assess tremor severity. Recently, attention around computerized tremor analysis has grown. In this study, we use regression trees to map the relationship between tremor data that is collected using the TREMOR12 smartphone application with ETRS and QUEST scores. We aim to develop a model that is able to automatically assess tremor severity of patients suffering from Essential Tremor without the use of more subjective questionnaires. This study shows that tremor data gathered using the TREMOR12 application is useful for constructing machine learning models that can be used to support the diagnosis and monitoring of patients who suffer from Essential Tremor.

AB - Tremor severity assessment is an important element for the diagnosis and treatment decision-making process of patients suffering from Essential Tremor (ET). Classically, questionnaires like the ETRS and QUEST surveys have been used to assess tremor severity. Recently, attention around computerized tremor analysis has grown. In this study, we use regression trees to map the relationship between tremor data that is collected using the TREMOR12 smartphone application with ETRS and QUEST scores. We aim to develop a model that is able to automatically assess tremor severity of patients suffering from Essential Tremor without the use of more subjective questionnaires. This study shows that tremor data gathered using the TREMOR12 application is useful for constructing machine learning models that can be used to support the diagnosis and monitoring of patients who suffer from Essential Tremor.

KW - Clinical decision support

KW - Essential Tremor

KW - Smartphone application

KW - Tremor severity

UR - http://www.scopus.com/inward/record.url?scp=85098288485&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-63061-4_1

DO - 10.1007/978-3-030-63061-4_1

M3 - Conference contribution

SN - 978-3-030-63060-7

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 3

EP - 12

BT - Computational Intelligence Methods for Bioinformatics and Biostatistics - 16th International Meeting, CIBB 2019, Revised Selected Papers

A2 - Cazzaniga, Paolo

A2 - Besozzi, Daniela

A2 - Merelli, Ivan

A2 - Manzoni, Luca

PB - Springer

CY - Cham

T2 - 16th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics, CIBB 2019

Y2 - 4 September 2019 through 6 September 2019

ER -

Zamora G, Fuchs CEM, Degeneffe A, Kubben P, Kaymak U. A Smartphone-Based Clinical Decision Support System for Tremor Assessment. In Cazzaniga P, Besozzi D, Merelli I, Manzoni L, editors, Computational Intelligence Methods for Bioinformatics and Biostatistics - 16th International Meeting, CIBB 2019, Revised Selected Papers: 16th International Meeting, CIBB 2019, Bergamo, Italy, September 4–6, 2019, Revised Selected Papers. Cham: Springer. 2020. p. 3-12. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-63061-4_1

A Smartphone-Based Clinical Decision Support System for Tremor Assessment

Abstract

Publication series

Conference

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Cite this