| dc.description.abstract | Elderly individuals often face challenges staying physically active due to age-related
issues such as mobility problems, balance difficulties, and stiff joints, which increase
the risk of injuries and reduce the effectiveness of workouts. This research focuses
on identifying the most effective technologies and methodologies to address these
challenges by providing safe and personalized exercise guidance, particularly for home based routines. The proposed solution integrates an expert system for personalized
recommendations and health warnings, along with a computer vision framework
to monitor posture and provide real-time corrective feedback. Using the PRISMA
framework, a systematic literature review was conducted to explore existing technologies
and methodologies. This process identified over 100 relevant studies, of which 30 were
selected for detailed review. The analysis revealed that 40% of the studies highlighted
the high accuracy of motion detection devices, such as Kinect cameras, while 30%
emphasized the importance of expert systems for tailored exercise guidance. The
findings suggest that combining expert systems with computer vision technologies is
the optimal approach for enhancing safety, posture accuracy, and the effectiveness of
exercises for elderly users. This research contributes to addressing the current gaps in
fitness technology by providing a practical framework for supporting elderly individuals
through guided, interactive home workouts. | en_US |
