Multimodal signal acquisition for pain assessment in physiotherapy

Aleksandra Badura; Maria Bieńkowska; Aleksandra Masłowska; Robert Czarlewski; Andrzej Myśliwiec; Ewa Pietka

doi:10.1007/978-3-030-49666-1_18

Multimodal signal acquisition for pain assessment in physiotherapy

Aleksandra Badura
, Maria Bieńkowska
, Aleksandra Masłowska
, Robert Czarlewski
, Andrzej Myśliwiec
, Ewa Pietka

Department of Medical Informatics and Artificial Intelligence (RIB/RIB1)

The Jerzy Kukuczka Academy of Physical Education in Katowice
APA Sp. z o.o.

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

6 Citations (Scopus)

Abstract

Pain monitoring during physiotherapy is an important factor determining the course of therapy. However, current pain scales are subjective and do not feature a unified level of pain that indicates the required interruption of the therapy. Hence, in this study a multimodal platform with wearable devices for monitoring and objective assessment of pain is presented. In the case study, six patients with neck pain underwent fascial therapy with simultaneous recording of signals. For classification we used electrodermal activity, electromyography, and respiration signals. The decision relies on the occurrence of signal distortion surrounding the onset of the pain in a specified time period.

Original language	English
Title of host publication	Advances in Intelligent Systems and Computing
Publisher	Springer
Pages	227-237
Number of pages	11
DOIs	https://doi.org/10.1007/978-3-030-49666-1_18
Publication status	Published - 2021

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1186
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Keywords

Manual therapy
Pain assessment
Pain in physiotherapy
Pain monitoring
Physiotherapy

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-3-030-49666-1_18

Cite this

@inbook{acd952161b6e40099ebd84c6bfbbf4dc,

title = "Multimodal signal acquisition for pain assessment in physiotherapy",

abstract = "Pain monitoring during physiotherapy is an important factor determining the course of therapy. However, current pain scales are subjective and do not feature a unified level of pain that indicates the required interruption of the therapy. Hence, in this study a multimodal platform with wearable devices for monitoring and objective assessment of pain is presented. In the case study, six patients with neck pain underwent fascial therapy with simultaneous recording of signals. For classification we used electrodermal activity, electromyography, and respiration signals. The decision relies on the occurrence of signal distortion surrounding the onset of the pain in a specified time period.",

keywords = "Manual therapy, Pain assessment, Pain in physiotherapy, Pain monitoring, Physiotherapy",

author = "Aleksandra Badura and Maria Bie{\'n}kowska and Aleksandra Mas{\l}owska and Robert Czarlewski and Andrzej My{\'s}liwiec and Ewa Pietka",

note = "Publisher Copyright: {\textcopyright} The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.",

year = "2021",

doi = "10.1007/978-3-030-49666-1\_18",

language = "English",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer",

pages = "227--237",

booktitle = "Advances in Intelligent Systems and Computing",

address = "Germany",

}

TY - CHAP

T1 - Multimodal signal acquisition for pain assessment in physiotherapy

AU - Badura, Aleksandra

AU - Bieńkowska, Maria

AU - Masłowska, Aleksandra

AU - Czarlewski, Robert

AU - Myśliwiec, Andrzej

AU - Pietka, Ewa

N1 - Publisher Copyright: © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

PY - 2021

Y1 - 2021

N2 - Pain monitoring during physiotherapy is an important factor determining the course of therapy. However, current pain scales are subjective and do not feature a unified level of pain that indicates the required interruption of the therapy. Hence, in this study a multimodal platform with wearable devices for monitoring and objective assessment of pain is presented. In the case study, six patients with neck pain underwent fascial therapy with simultaneous recording of signals. For classification we used electrodermal activity, electromyography, and respiration signals. The decision relies on the occurrence of signal distortion surrounding the onset of the pain in a specified time period.

AB - Pain monitoring during physiotherapy is an important factor determining the course of therapy. However, current pain scales are subjective and do not feature a unified level of pain that indicates the required interruption of the therapy. Hence, in this study a multimodal platform with wearable devices for monitoring and objective assessment of pain is presented. In the case study, six patients with neck pain underwent fascial therapy with simultaneous recording of signals. For classification we used electrodermal activity, electromyography, and respiration signals. The decision relies on the occurrence of signal distortion surrounding the onset of the pain in a specified time period.

KW - Manual therapy

KW - Pain assessment

KW - Pain in physiotherapy

KW - Pain monitoring

KW - Physiotherapy

UR - https://www.scopus.com/pages/publications/85091020662

U2 - 10.1007/978-3-030-49666-1_18

DO - 10.1007/978-3-030-49666-1_18

M3 - Chapter

AN - SCOPUS:85091020662

T3 - Advances in Intelligent Systems and Computing

SP - 227

EP - 237

BT - Advances in Intelligent Systems and Computing

PB - Springer

ER -

Multimodal signal acquisition for pain assessment in physiotherapy

Abstract

Publication series

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this