Objective: To determine the effects of a wearable plus personalized biometric-based coaching on heart rate variability (HRV) and health-related quality of life (HRQoL). Participants: Student athletes on NCAA Division I Eastern Washington University football team. Methods: A mixed study design including randomization of participants into a wearable without coaching group (WO) and a wearable with coaching group (WC). HRV data were recorded via WHOOP® strap for 14 weeks. WC group received personalized coaching based on HRV data via smart phone application. Student athletes completed a HRQoL survey at start and end of study. Results: A significant effect of time was present for both HRV and HRQoL. A slightly larger increase was seen in both variables for the WC group; however, group means were not significantly different. Conclusions: Access to biometric data alone may imbue an increase in HRV and HRQoL. Such increases may be compounded by a reduction in both training and academic stressors during the summer term off-season.
Objective: To determine if sleep metrics and group assignment between wearable plus coaching (WC) and wearable without coaching (WO) are predictive of HRV in NCAA DI football players. Participants: Collegiate student athletes on NCAA Division I football team. Methods: Participants were randomized into WC and WO groups. HRV and restorative sleep stages were recorded via WHOOP® 4.0 strap for 14 weeks. The percentage of sleep duration dubbed restorative sleep (%RESTOR) was calculated. Linear forced entry regression analysis was performed to determine the association between %RESTOR, group assignment, and HRV. Results: %RESTOR and group assignment accounted for 59.3% of the variance seen in HRV. A significant, negative association between %RESTOR and HRV was present. Group assignment was not associated with HRV. Conclusions: Lower %RESTOR was indicative of higher HRV. Less time spent in restorative sleep may indicate less stress and less need for recovery.
","abstract_html":"<p>Objective: To determine the effects of a wearable plus personalized biometric-based coaching on heart rate variability (HRV) and health-related quality of life (HRQoL). Participants: Student athletes on NCAA Division I Eastern Washington University football team. Methods: A mixed study design including randomization of participants into a wearable without coaching group (WO) and a wearable with coaching group (WC). HRV data were recorded via WHOOP® strap for 14 weeks. WC group received personalized coaching based on HRV data via smart phone application. Student athletes completed a HRQoL survey at start and end of study. Results: A significant effect of time was present for both HRV and HRQoL. A slightly larger increase was seen in both variables for the WC group; however, group means were not significantly different. Conclusions: Access to biometric data alone may imbue an increase in HRV and HRQoL. Such increases may be compounded by a reduction in both training and academic stressors during the summer term off-season.</p> <p>Objective: To determine if sleep metrics and group assignment between wearable plus coaching (WC) and wearable without coaching (WO) are predictive of HRV in NCAA DI football players. Participants: Collegiate student athletes on NCAA Division I football team. Methods: Participants were randomized into WC and WO groups. HRV and restorative sleep stages were recorded via WHOOP® 4.0 strap for 14 weeks. The percentage of sleep duration dubbed restorative sleep (%RESTOR) was calculated. Linear forced entry regression analysis was performed to determine the association between %RESTOR, group assignment, and HRV. Results: %RESTOR and group assignment accounted for 59.3% of the variance seen in HRV. A significant, negative association between %RESTOR and HRV was present. Group assignment was not associated with HRV. Conclusions: Lower %RESTOR was indicative of higher HRV. Less time spent in restorative sleep may indicate less stress and less need for recovery.</p>","abstract_has_math":false,"creators":["Henson, Perla Millan"],"institution":null,"degree_name":"Master of Science (MS) in Wellness and Movement Sciences","degree_level":"Thesis: EWU Only","degree_discipline":"Wellness and Movement Sciences","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-01-01T08:00:00Z","date_published":"2025-01-01T08:00:00Z","updated_at":"2026-07-24T02:13:16Z","subjects":["Exercise Physiology","Exercise Science","Health Psychology","Sports Sciences"],"languages":[],"rights":["Access perpetually restricted to EWU users with an active EWU NetID"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dc.ewu.edu/theses/969","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Henson, Perla Millan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Wellness and Movement Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis: EWU Only"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS) in Wellness and Movement Sciences"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Exercise Physiology","Exercise Science","Health Psychology","Sports Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Access perpetually restricted to EWU users with an active EWU NetID"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dc.ewu.edu/theses/969"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Objective: To determine the effects of a wearable plus personalized biometric-based coaching on heart rate variability (HRV) and health-related quality of life (HRQoL). Participants: Student athletes on NCAA Division I Eastern Washington University football team. Methods: A mixed study design including randomization of participants into a wearable without coaching group (WO) and a wearable with coaching group (WC). HRV data were recorded via WHOOP® strap for 14 weeks. WC group received personalized coaching based on HRV data via smart phone application. Student athletes completed a HRQoL survey at start and end of study. Results: A significant effect of time was present for both HRV and HRQoL. A slightly larger increase was seen in both variables for the WC group; however, group means were not significantly different. Conclusions: Access to biometric data alone may imbue an increase in HRV and HRQoL. Such increases may be compounded by a reduction in both training and academic stressors during the summer term off-season.
Objective: To determine if sleep metrics and group assignment between wearable plus coaching (WC) and wearable without coaching (WO) are predictive of HRV in NCAA DI football players. Participants: Collegiate student athletes on NCAA Division I football team. Methods: Participants were randomized into WC and WO groups. HRV and restorative sleep stages were recorded via WHOOP® 4.0 strap for 14 weeks. The percentage of sleep duration dubbed restorative sleep (%RESTOR) was calculated. Linear forced entry regression analysis was performed to determine the association between %RESTOR, group assignment, and HRV. Results: %RESTOR and group assignment accounted for 59.3% of the variance seen in HRV. A significant, negative association between %RESTOR and HRV was present. Group assignment was not associated with HRV. Conclusions: Lower %RESTOR was indicative of higher HRV. Less time spent in restorative sleep may indicate less stress and less need for recovery.
"]},{"key":"dc:title","label":"Title","values":["Examining the effects of wearable technology and biometric coaching on heart rate variability, health related quality of life, and predictors of heart rate variability in collegiate athletes"]}]}],"canonical_facts":{"dc:creator":["Henson, Perla Millan"],"dc:description.abstract":["Objective: To determine the effects of a wearable plus personalized biometric-based coaching on heart rate variability (HRV) and health-related quality of life (HRQoL). Participants: Student athletes on NCAA Division I Eastern Washington University football team. Methods: A mixed study design including randomization of participants into a wearable without coaching group (WO) and a wearable with coaching group (WC). HRV data were recorded via WHOOP® strap for 14 weeks. WC group received personalized coaching based on HRV data via smart phone application. Student athletes completed a HRQoL survey at start and end of study. Results: A significant effect of time was present for both HRV and HRQoL. A slightly larger increase was seen in both variables for the WC group; however, group means were not significantly different. Conclusions: Access to biometric data alone may imbue an increase in HRV and HRQoL. Such increases may be compounded by a reduction in both training and academic stressors during the summer term off-season.
Objective: To determine if sleep metrics and group assignment between wearable plus coaching (WC) and wearable without coaching (WO) are predictive of HRV in NCAA DI football players. Participants: Collegiate student athletes on NCAA Division I football team. Methods: Participants were randomized into WC and WO groups. HRV and restorative sleep stages were recorded via WHOOP® 4.0 strap for 14 weeks. The percentage of sleep duration dubbed restorative sleep (%RESTOR) was calculated. Linear forced entry regression analysis was performed to determine the association between %RESTOR, group assignment, and HRV. Results: %RESTOR and group assignment accounted for 59.3% of the variance seen in HRV. A significant, negative association between %RESTOR and HRV was present. Group assignment was not associated with HRV. Conclusions: Lower %RESTOR was indicative of higher HRV. Less time spent in restorative sleep may indicate less stress and less need for recovery.
"],"dc:identifier":["https://dc.ewu.edu/theses/969"],"dc:rights":["Access perpetually restricted to EWU users with an active EWU NetID"],"dc:subject":["Exercise Physiology","Exercise Science","Health Psychology","Sports Sciences"],"dc:title":["Examining the effects of wearable technology and biometric coaching on heart rate variability, health related quality of life, and predictors of heart rate variability in collegiate athletes"],"thesis:degree_discipline":["Wellness and Movement Sciences"],"thesis:degree_level":["Thesis: EWU Only"],"thesis:degree_name":["Master of Science (MS) in Wellness and Movement Sciences"]},"updated_at":"2026-07-24T02:13:16Z"}