Objectives: Heart rate variability (HRV) can be a simple, non-invasive method of gauging cardiac autonomic nervous system fluctuations across periodised training workloads and taper in elite athlete populations. Th...Objectives: Heart rate variability (HRV) can be a simple, non-invasive method of gauging cardiac autonomic nervous system fluctuations across periodised training workloads and taper in elite athlete populations. The purpose of these three case studies was to examine daily cardiac autonomic variations in Paralympic athletes leading in to the Paralympic games. Methods: Three Paralympie gold medallist swimmers were monitored daily for their resting HRV over a 17-week monitoring period leading up to the Paralympic games. Specific time- and frequency-domain measures, along with non-linear indices of HRV were calculated for all analyses. All HRV data were analysed individually using daily values, weekly average values, and average values for rest and training phases. Results: A significant difference in HRV was seen for all variables between athlete 1 and athletes 2 and 3 (amputee disabilities) during the entire monitoring period. Conclusion: Despite minimal long-term changes, both swimming classification and disability type significantly influence HRV during athlete monitoring. An increased understanding of individual responses to training, travel, and other outside influences affecting Paralympic athletes could potentially lead to improved management and monitoring of training workloads for enhanced nerformance.展开更多
文摘Objectives: Heart rate variability (HRV) can be a simple, non-invasive method of gauging cardiac autonomic nervous system fluctuations across periodised training workloads and taper in elite athlete populations. The purpose of these three case studies was to examine daily cardiac autonomic variations in Paralympic athletes leading in to the Paralympic games. Methods: Three Paralympie gold medallist swimmers were monitored daily for their resting HRV over a 17-week monitoring period leading up to the Paralympic games. Specific time- and frequency-domain measures, along with non-linear indices of HRV were calculated for all analyses. All HRV data were analysed individually using daily values, weekly average values, and average values for rest and training phases. Results: A significant difference in HRV was seen for all variables between athlete 1 and athletes 2 and 3 (amputee disabilities) during the entire monitoring period. Conclusion: Despite minimal long-term changes, both swimming classification and disability type significantly influence HRV during athlete monitoring. An increased understanding of individual responses to training, travel, and other outside influences affecting Paralympic athletes could potentially lead to improved management and monitoring of training workloads for enhanced nerformance.