Mapping Data Mining Technique and Gamification Approach for Studying PostStroke Rehabilitation Training: A systematic literature review
Data mining has been widely used in healthcare to provide treatment and care recommendations based on a collective prediction of individual conditions. For rehabilitation, various data mining techniques have been applied to predict and recommend suitable recovery paths and training. Also, the gamifi...
Saved in:
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English English |
Published: |
ResearchGate
2023
|
Subjects: | |
Online Access: | https://eprints.ums.edu.my/id/eprint/37695/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/37695/2/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/37695/ http://dx.doi.org/10.1109/ACCESS.2023.3262260 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.ums.eprints.37695 |
---|---|
record_format |
eprints |
spelling |
my.ums.eprints.376952023-11-29T02:12:38Z https://eprints.ums.edu.my/id/eprint/37695/ Mapping Data Mining Technique and Gamification Approach for Studying PostStroke Rehabilitation Training: A systematic literature review Nooralisa M. Tuah Daphne L. Goh Syed Nasirin Syed Zainol Abidin Fatimah Ahmedy Mohammad Hossin QA101-(145) Elementary mathematics. Arithmetic RM930-931 Rehabilitation therapy Data mining has been widely used in healthcare to provide treatment and care recommendations based on a collective prediction of individual conditions. For rehabilitation, various data mining techniques have been applied to predict and recommend suitable recovery paths and training. Also, the gamification concept was applied to rehabilitation training to motivate the patient to follow the training until the end. Researchers have conducted considerable research to investigate the validity and effectiveness of those techniques on massive patient data on specific conditions and treatment contexts. However, it is still unclear how to effectively offer customized rehabilitation training to stroke patients using gamification and data mining approaches. Thus, to understand how researchers studied them, we examined 34 peer-reviewed articles published in computer science and medical proceedings and journals between 2012 and 2022. We systematically reviewed the data mining and gamification techniques researchers had applied for post-stroke rehabilitation and related prediction models resulting from the data mining processes. As a result of the analyses, three significant contributions are identified. This article 1) identifies trends in data mining and gamification used in personalized post-stroke rehabilitation training; 2) maps trends in the study of data mining and gamification in post-stroke rehabilitation; and 3) identifies underexplored studiesfor future work. There is a definite need to continue developing and researching intervention strategies related to rehabilitation to address recovery problems by providing accuracy and protection of healthcare, as well as incorporating components that promote patients' motivation and engagement. ResearchGate 2023 Article NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/37695/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/37695/2/FULL%20TEXT.pdf Nooralisa M. Tuah and Daphne L. Goh and Syed Nasirin Syed Zainol Abidin and Fatimah Ahmedy and Mohammad Hossin (2023) Mapping Data Mining Technique and Gamification Approach for Studying PostStroke Rehabilitation Training: A systematic literature review. IEEE Access. pp. 1-19. ISSN 2169-3536 http://dx.doi.org/10.1109/ACCESS.2023.3262260 |
institution |
Universiti Malaysia Sabah |
building |
UMS Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Malaysia Sabah |
content_source |
UMS Institutional Repository |
url_provider |
http://eprints.ums.edu.my/ |
language |
English English |
topic |
QA101-(145) Elementary mathematics. Arithmetic RM930-931 Rehabilitation therapy |
spellingShingle |
QA101-(145) Elementary mathematics. Arithmetic RM930-931 Rehabilitation therapy Nooralisa M. Tuah Daphne L. Goh Syed Nasirin Syed Zainol Abidin Fatimah Ahmedy Mohammad Hossin Mapping Data Mining Technique and Gamification Approach for Studying PostStroke Rehabilitation Training: A systematic literature review |
description |
Data mining has been widely used in healthcare to provide treatment and care recommendations based on a collective prediction of individual conditions. For rehabilitation, various data mining techniques have been applied to predict and recommend suitable recovery paths and training. Also, the gamification concept was applied to rehabilitation training to motivate the patient to follow the training until the end. Researchers have conducted considerable research to investigate the validity and effectiveness of those techniques on massive patient data on specific conditions and treatment contexts. However, it is still unclear how to effectively offer customized rehabilitation training to stroke patients using gamification and data mining approaches. Thus, to understand how researchers studied them, we examined 34 peer-reviewed articles published in computer science and medical proceedings and journals between 2012 and 2022. We systematically reviewed the data mining and gamification techniques researchers had applied for post-stroke rehabilitation and related prediction models resulting from the data mining processes. As a result of the analyses, three significant contributions are identified. This article 1) identifies trends in data mining and gamification used in personalized post-stroke rehabilitation training; 2) maps trends in the study of data mining and gamification in post-stroke rehabilitation; and 3) identifies underexplored studiesfor future work. There is a definite need to continue developing and researching intervention strategies related to rehabilitation to address recovery problems by providing accuracy and protection of healthcare, as well as incorporating components that promote patients' motivation and engagement. |
format |
Article |
author |
Nooralisa M. Tuah Daphne L. Goh Syed Nasirin Syed Zainol Abidin Fatimah Ahmedy Mohammad Hossin |
author_facet |
Nooralisa M. Tuah Daphne L. Goh Syed Nasirin Syed Zainol Abidin Fatimah Ahmedy Mohammad Hossin |
author_sort |
Nooralisa M. Tuah |
title |
Mapping Data Mining Technique and Gamification Approach for Studying PostStroke Rehabilitation Training: A systematic literature review |
title_short |
Mapping Data Mining Technique and Gamification Approach for Studying PostStroke Rehabilitation Training: A systematic literature review |
title_full |
Mapping Data Mining Technique and Gamification Approach for Studying PostStroke Rehabilitation Training: A systematic literature review |
title_fullStr |
Mapping Data Mining Technique and Gamification Approach for Studying PostStroke Rehabilitation Training: A systematic literature review |
title_full_unstemmed |
Mapping Data Mining Technique and Gamification Approach for Studying PostStroke Rehabilitation Training: A systematic literature review |
title_sort |
mapping data mining technique and gamification approach for studying poststroke rehabilitation training: a systematic literature review |
publisher |
ResearchGate |
publishDate |
2023 |
url |
https://eprints.ums.edu.my/id/eprint/37695/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/37695/2/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/37695/ http://dx.doi.org/10.1109/ACCESS.2023.3262260 |
_version_ |
1783877960704458752 |
score |
13.160551 |