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Updated: Aug 5, 2026

Exergaming in Older People Living with HIV Improves Balance, Mobility and Ameliorates Some Aspects of Frailty
Published on: October 6, 2016
Exergaming for Healthy Aging: Associations with Functional Capacity, Social Participation, Self-Efficacy for
João Quatorze1,2, Magda Reis1,3, Guilherme Alvarez1
1Coimbra Health School, Polytechnic University of Coimbra, Rua 5 de Outubro, 3045-043 Coimbra, Portugal.
Abstract:
This study explores current applications of exergaming in healthcare, with a focus on how the Otago Exercise Program-a structured, evidence-based program designed to improve strength and balance in older adults-integrated into the FallSensing exergames, contributes to improving older adults' functioning. It also aims to generate evidence to support the optimization of sensor-based technologies for more personalized and adaptable exercise interventions. Community-dwelling older adults (≥60 years) were recruited from facilities in Coimbra, Portugal, and allocated into an exergames group (IG; n = 27) and a control group (CG; n = 34). The CG maintained usual daily activities, while the IG completed an 8-week (16-session) exergame-based program. After completing the program, the CG showed a decline in functional ability, whereas the IG demonstrated significant improvements in the Step Test (p = 0.001), Four-Stage Balance Modified Test (p = 0.001), Self-Efficacy for Exercise Scale (p = 0.009), and Activities and Participation Profile Related to Mobility questionnaire (p < 0.001). Exergaming was safe and effective in enhancing functional ability, participation, and self-efficacy in older adults. However, careful consideration of exercise frequency, intensity, and participants' age is recommended when prescribing exergame-based interventions. These results also highlight another interesting topic among physiotherapists who prescribe and monitor exergames, that technology developers should consider exercise-time monitoring systems that integrate physical (e.g., eye, facial, and mouth features) and physiological signals to enhance fatigue detection accuracy.
