Med Sci Sports Exerc. 2026 Aug 6. doi: 10.1249/MSS.0000000000004101. Online ahead of print.
ABSTRACT
INTRODUCTION: Aging is associated with decreased aerobic fitness and increased adiposity, independent predictors of all-cause mortality. Endurance exercise is recommended to improve adiposity and aerobic fitness, but weight-bearing limitations and lack of access to exercise facilities are common barriers to exercise among older adults. In the present study, we developed a home-based remotely supervised high intensity interval training (HIIT) intervention on an all-extremity non-weight-bearing exercise (ANE) ergometer and investigated in older adults: (a) safety and feasibility; and (b) its effects on aerobic fitness and adiposity.
METHODS: Twenty older adults (61-74 years; 11/9 females/males), free of major clinical disease, completed assessments at baseline, after 8 weeks of their usual lifestyle (i.e., control period) and after 8 weeks of home-based remotely supervised HIIT. HIIT was performed on an ANE ergometer at home, 4 days/week, under synchronous remote supervision using video conferencing and real-time heart rate monitoring via cloud-based technology. Aerobic fitness and body composition were assessed using maximal oxygen consumption via open circuit spirometry during a maximal exercise test and dual-energy X-ray absorptiometry, respectively.
RESULTS: There were no adverse events related to home-based HIIT, and participants completed 96% of scheduled HIIT sessions. Aerobic fitness decreased by 1.2 ± 0.4 ml·kg -1·min -1 over the 8-week control period (P=0.04) and increased by 4.5 ± 0.7 ml·kg -1·min -1 over the 8-week HIIT (P<0.001). Fat mass did not change over the control period (P=1.0) but decreased by 1.4 ± 0.35 kg in response to HIIT (P=0.003).
CONCLUSIONS: This novel home-based remotely supervised HIIT intervention, is safe, feasible, and results in improvements in aerobic fitness and adiposity in older adults. Our findings form the foundation for investigating home-based remotely supervised HIIT in clinical populations.
PMID:42561157 | DOI:10.1249/MSS.0000000000004101