000			05131nam a22003257a 4500
001			T002916
003			PILC
005			20241106080646.0
008			241106b |||||||| |||| 00| 0 eng d
040			_beng _cFEU-NRMF MEDICAL LIBRARY _drda
050			_aPT 2024 0013
100	1		_aArcenal, Lyka Shayne P. _eauthor
245	0	1	_aRoles of artificial intelligence in the physical therapy practice: a scoping review / _b[author]: Arcenal, Lyka Shayne P. Arroyo, Denise Emmanuelle V. Bias, Dan Amiel D. Llosala, Raphael A. Medina, Hannah Danielle B. Mostacho, Nissos Ardel A [co author]: Marc Edward Garrido
260			_aQuezon City, Philippines; _bFEU-Dr. Nicanor Reyes Medical Foundation Institute of Medicine, _c2024
300			_a95pages _c28cm
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
504			_aIncludes Appendix
520			_aABSTRACT: Introduction. Technological advances have now sprouted in different fields and continue its advancement in the healthcare system, including Artificial Intelligence (Al). Despite fear of job replacement, the technology, nowadays, undeniably makes all the work efficient and accessible. Artificial Intelligence are devices made to replicate human intelligence with the goal of alleviating quality of life. As part of healthcare innovation, Al is now starting to be integrated in the physical therapy practice. Physical therapy is a health specialty focused on re attainment and improvement of the function and well-being of people with disabilities. It generally involves examinations, assessments, evaluations, and exercises that vary from different physiotherapist’s approaches to another. The lack of consistency and objectivity in the practice may undermine the overall patient care and outcomes. Thus, this study seeks to conduct a comprehensive research of the available literature on the roles of Artificial Intelligence (Al) in the Physical Therapy practice. Methods. This study follows a Scoping Review Design according to the frameworks by Arksey and O’Malley (2005) and Joanna Briggs Institute (JBI) Approach to Conducting Scoping Review. In this review, 1,379 literatures were gathered from online databases, with specific search terms, such as: PubMed Cochrane, Embase, UpToDate, ClinicalTrials.gov, PEDro. The screening for eligibility has 2 levels: 1st is the screening for relevance to pass the inclusion criteria, specifically the titles, abstracts, and keywords, leaving 220 studies to undergo the 2nd screening. Next is the screening for relevance, where full text copies of the studies are scanned, leaving only 10 literatures to be appraised. Specific details collected from each of the 10 studies were gathered using a tablethe obtained data are as follows: (1) Authors, Year, Country, (2) Title, (3) Artificial Intelligence Technology, (4) Research Design, (5) Research Methods, (6) Application to PT Practice, (7) Results. The collected data was further examined and segregated based on their use in the (1) Assessment, (2) Treatment Part, and their (3) Limitations and Gaps. Results and Discussion. Majority of the ten (10) obtained studies were (6) Randomized Controlled Trials, followed by (2) Meta Analysis, (1) Systematic Review and (1) Systematic Review and Meta Analysis. Al tools and equipment that were used in the clinic were OptiTrack, Al exercise mobile application, Al machine learning, Robot-Assisted Gait Training (RAGT) with Hybrid-Assistive Locomotion/Limb (HAL), Smart digital wristband, Overground (OG) Robotic Exoskeleton, wearable activity tracker, Honda Walking Assist (HWA), and mobile application. All Al devices were found to be helpful in the assessment and exercise implementation in physical therapy, but should still be thoroughly studied to solve the problem in its applicability. Conclusion. This study was able to obtain more knowledge about the clinical usage of Artificial Intelligence (Al) in the physical therapy practice, proving how its clinical use can improve efficiency in conducting assessments, monitoring status and progress of patients during their rehabilitation journey, and in the application of enhanced techniques in treating patients. Hence, resulting in better patient care. Despite the benefits Al could provide, it also has its disadvantages as it could not adapt to immediate changes unlike in conventional practice. The study came to a conclusion that this emerging technology still could not replace the modern physical therapy practice, but could only be a catalyst in amplifying overall competence of physical therapy rehabilitation.
521			_aKoakh _aTHPT
700			_aArroyo, Denise Emmanuelle V. _eauthor
700			_aBias, Dan Amiel D. _eauthor
700			_aLlosala, Raphael A. _eauthor
700			_aMedina, Hannah Danielle B _eauthor
700			_aMostacho, Nissos Ardel A _eauthor
700			_aMarc Edward Garrido _eco-author
856			_21 _30 _qpdf _uhttps://library.feu-nrmf.ph/cgi-bin/koha/opac-retrieve-file.pl?id=4ff7a20975558b1935fec6ab51a32c28 _yClick here for FULL TEXT _1ALL
942			_2lcc _cTH
999			_c13186 _d13186