Mapping Data Mining Technique and Gamification Approach for Studying Post- Stroke Rehabilitation Training: A systematic literature review

I see nothing here that will get survivors recovered. Why don't you use data mining techniques to analyze why stroke researchers do not solve stroke recovery. That would be more useful than this crapola.

Mapping Data Mining Technique and Gamification Approach for Studying Post- Stroke Rehabilitation Training: A systematic literature review 

VOLUME XX, 2017 1
Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000.
Digital Object Identifier 10.1109/ACCESS.2017.Doi Number
Mapping Data Mining Technique and
Gamification Approach for Studying Post-
Stroke Rehabilitation Training: A systematic
literature review
Nooralisa M. Tuah1,2 , Daphne L. Goh1,2 , Syed Nasirin1,3 , Fatimah Ahmedy4 , and Mohammad
Hossin5
1 Faculty of Computing and Informatics, Universiti Malaysia Sabah, Labuan International Campus, 87008 Labuan F.T., Malaysia
2 Creative Computing Research Group, Universiti Malaysia Sabah, Labuan International Campus, 87008 Labuan F.T., Malaysia
3 Decision Support System Research Group, Universiti Malaysia Sabah, Labuan International Campus, 87008 Labuan F.T., Malaysia
4 Faculty of Medicine & Health Sciences, Universiti Malaysia Sabah, 88400 Kota Kinabalu, Sabah, Malaysia
5 Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia
Corresponding author: Nooralisa M. Tuah (e-mail: alisa.tuah@ums.edu.my).
This work was supported in part by the Univeristi Malaysia Sabah under Grant GKP0043.

ABSTRACT

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 under explored studies for 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.