PHAROS 2.0-A PHysical Assistant RObot System Improved

Area of Science:

• Gerontology
• Robotics
• Computer Science

Background:

• Active aging offers significant physical and cognitive benefits for older adults.
• Previous PHAROS system used a social robot for exercise monitoring and recommendations.
• Limitations included basic exercise analysis and a recommendation system lacking temporal and preference considerations.

Purpose of the Study:

• To introduce PHAROS 2.0, an improved system for active aging in older adults.
• To enhance motion capture with detailed exercise completeness and real-time correction.
• To develop a more accurate recommender system incorporating performance, temporal evolution, and preferences.

Main Methods:

• Utilized computer vision for motion analysis and exercise correctness evaluation.
• Implemented a refined motion capture system to assess exercise completeness and provide real-time corrective feedback.
• Developed a novel algorithm for the recommender system, weighing performance, temporal data, and user preferences.

Main Results:

• PHAROS 2.0 provides detailed feedback on exercise execution, identifying specific errors.
• The enhanced recommender system offers more accurate exercise suggestions based on a comprehensive data analysis.
• Recommendations are now provided as a batch of exercises, allowing for more tailored programs.

Conclusions:

• PHAROS 2.0 significantly advances the capabilities of robotic systems for supporting active aging.
• The system's improved feedback and personalized recommendations can lead to better adherence and outcomes in older adults.
• This evolution represents a step towards more intelligent and adaptive assistive technologies for elderly care.