Description

• Title:
  Review Of The Application Of Artificial Intelligence (AI) Exercise Training In Improving Cognitive Function In The Elderly Population
• Creator:
  Zhang, Tingran;
  Zhang, mufan;
  Luo, Jiong
• Description:
  With the increasing cognitive dysfunction of the elderly and the incidence rate of dementia caused by aging, in recent years, many countries have studied and applied artificial intelligence (AI) to reduce the pressure on caregivers and improve the quality of life of dementia patients. This study comprehensively summarizes the impact of AI cognitive training on the mental symptoms of dementia patients from 2010 to 2024 through literature review. The results show that AI training has been used in multiple fields, breaking through many limitations of traditional action recognition technology. Through virtual cyberspace, real-time interaction of multiple senses can be achieved, allowing people to feel reality in the virtual network and accurately capture participants' actions; Through AI games, elderly people can improve their physical and cognitive functions, reduce depression and anxiety, meet the psychological and social needs of dementia patients, enhance their independence and dignity in life, and make objective assessments of cognitive function, which may help prevent dementia.
• Object availability:
  free access
• Rights: https://creativecommons.org/licenses/by-nc-sa/4.0 ;
  Prawa autorskie (c) 2025 Tingran Zhang, Mufan Zhang, Jiong Luo
• Date:
  2025.02.10
• Type:
  info:eu-repo/semantics/article;
  info:eu-repo/semantics/publishedVersion
• Language:
  English
• Source:
  Quality in Sport; Tom 38 (2025); 58019;
  Quality in Sport; Vol. 38 (2025); 58019;
  2450-3118
• Format:
  application/pdf
• Publisher:
  University Center for Sports Research, Nicolaus Copernicus University, Torun, Poland
• Relation: https://apcz.umk.pl/QS/article/view/58019/41472
• Subject:
  AI cognitive training;
  Cognitive function;
  Intelligent technology;
  Dementia;
  Taking care of the load
• Identifier: https://apcz.umk.pl/QS/article/view/58019
• Data provider:
  Akademicka Platforma Czasopism
• Can I use it?:
  seek permission
• Type:
  text