Sat, May 17, 2025
[Archive]
Volume 5, Issue 1 (2-2025)
APM 2025, 5(1): 114-122 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Salamati S, Ebrahimi E, Rashidy P, Alavi M. Efficacy of AI-Based Pilates on Motor Performance and Fear of Falling in Older Adults. APM 2025; 5 (1) :114-122
URL: http://apssjournal.com/article-1-102-en.html
URL: http://apssjournal.com/article-1-102-en.html
1- Department of Physical Activity and Health Promotion, Faculty of Medicine and Surgery, Tor Vergata University of Rome, Rome, Italy
2- Department of Corrective Exercise & Sport Injury, Faculty of Physical Education and Sport Sciences, Allameh Tabataba'i University, Tehran, Iran ,ebrahimeebrahimi703@gmail.com
3- Department of Corrective Exercise & Sport Injury, Faculty of Physical Education and Sport Sciences, University of Isfahan, Isfahan, Iran
4- Department of Corrective Exercise & Sport Injury, Faculty of Physical Education and Sport Sciences, Allameh Tabataba'i University, Tehran, Iran
2- Department of Corrective Exercise & Sport Injury, Faculty of Physical Education and Sport Sciences, Allameh Tabataba'i University, Tehran, Iran ,
3- Department of Corrective Exercise & Sport Injury, Faculty of Physical Education and Sport Sciences, University of Isfahan, Isfahan, Iran
4- Department of Corrective Exercise & Sport Injury, Faculty of Physical Education and Sport Sciences, Allameh Tabataba'i University, Tehran, Iran
Abstract: (93 Views)
Over the past decade, research on artificial intelligence (AI) has expanded significantly, exploring its potential to enhance the quality of life for older adults. Therefore, the study aims to investigate the effect of a 4-week AI-generated Pilates training program on motor performance and fear of falling in older adults. This quasi-experimental study selected 30 female older adults aged 65 years and older, dividing them into two groups: one for experimental (N = 15) and another for control (N = 15). The experimental groups had four weeks of AI-based intervention with three sessions per week. During this period, the control group engaged in the routine activities. The Timed Up and Go and the Falls Efficacy Scale-International (FES-I) questionnaire were done as pre-posttest, respectively. The independent t-test was used for inferential statistics. Data analysis was conducted at a significance level of 95% with an alpha level less than or equal to 0.05. The findings showed that there was a significant difference between the two groups in the scores of the TUG test (p<0.03) and the FES-I questionnaire (p<0.001). By utilizing AI to develop personalized exercise programs, healthcare practitioners can improve motor performance and reduce the fear of falling in older adults. These findings highlight the potential of AI-driven rehabilitation strategies in geriatric care, emphasizing the need for further research to refine program parameters and extend their benefits to a broader aging population.
Type of Study: Original Article |
Subject:
Sports Biomechanics
Received: 2025/03/22 | Accepted: 2025/04/23 | Published: 2025/02/28
Received: 2025/03/22 | Accepted: 2025/04/23 | Published: 2025/02/28
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
