PURPOSE: To determine the accuracy of predicted Energy Expenditure (EE) reported by a wrist-worn activity monitor compared to measured EE during both a long- and short-duration exercise. METHODS: In addition to a VO2max treadmill test, a running speed at approximately 70 - 75% of that VO2max was found during the first visit. The second and third visit was comprised of either a 30-minute or 10-minute run at the speed previously determined. A wrist activity monitor was worn and VO2 and EE were recorded by a metabolic cart. Pearson correlation, paired samples t-test, and repeated measures ANOVAs compared predicted and measured EE. An independent samples t-test determined significant differences in characteristics between fitness groups (p < 0.05). RESULTS: N = 25 (60% male). A significant correlation was found between predicted EE and measured EE for both short and long duration (p < 0.001). The repeated measures ANOVA determined the interactive effect of measurement mode and fitness level was significant. CONCLUSIONS: Overall, there is a strong correlation between criterion and predictive measurement, however, consumers should exercise caution when using predicted measures.
","abstract_html":"<p>PURPOSE: To determine the accuracy of predicted Energy Expenditure (EE) reported by a wrist-worn activity monitor compared to measured EE during both a long- and short-duration exercise. METHODS: In addition to a VO<sub>2max</sub> treadmill test, a running speed at approximately 70 - 75% of that VO<sub>2max</sub> was found during the first visit. The second and third visit was comprised of either a 30-minute or 10-minute run at the speed previously determined. A wrist activity monitor was worn and VO2 and EE were recorded by a metabolic cart. Pearson correlation, paired samples t-test, and repeated measures ANOVAs compared predicted and measured EE. An independent samples t-test determined significant differences in characteristics between fitness groups (<em>p</em> < 0.05). RESULTS:<em> N = 25 (60% male)</em>. A significant correlation was found between predicted EE and measured EE for both short and long duration (<em>p</em> < 0.001). The repeated measures ANOVA determined the interactive effect of measurement mode and fitness level was significant. CONCLUSIONS: Overall, there is a strong correlation between criterion and predictive measurement, however, consumers should exercise caution when using predicted measures.</p>","abstract_has_math":false,"creators":["Van Camp, Cailyn"],"institution":null,"degree_name":"Master of Science (MS)","degree_level":"Open Access Thesis","degree_discipline":"Health Promotion and Human Performance","degree_department":null,"school":null,"contributors":["Rebecca Moore, Ph.D.","Catherine Gammon, Ph.D.","Anthony Moreno, Ph.D."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-01-01T08:00:00Z","date_published":"2020-01-01T08:00:00Z","updated_at":"2026-07-24T02:17:40Z","subjects":["energy expenditure","validation","wearable fitness tracker","Kinesiology"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.emich.edu/theses/1027","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Rebecca Moore, Ph.D.","Catherine Gammon, Ph.D.","Anthony Moreno, Ph.D."]},{"key":"dc:creator","label":"Author","values":["Van Camp, Cailyn"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2020-09-22T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Health Promotion and Human Performance"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["energy expenditure","validation","wearable fitness tracker","Kinesiology"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.emich.edu/theses/1027"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["PURPOSE: To determine the accuracy of predicted Energy Expenditure (EE) reported by a wrist-worn activity monitor compared to measured EE during both a long- and short-duration exercise. METHODS: In addition to a VO2max treadmill test, a running speed at approximately 70 - 75% of that VO2max was found during the first visit. The second and third visit was comprised of either a 30-minute or 10-minute run at the speed previously determined. A wrist activity monitor was worn and VO2 and EE were recorded by a metabolic cart. Pearson correlation, paired samples t-test, and repeated measures ANOVAs compared predicted and measured EE. An independent samples t-test determined significant differences in characteristics between fitness groups (p < 0.05). RESULTS: N = 25 (60% male). A significant correlation was found between predicted EE and measured EE for both short and long duration (p < 0.001). The repeated measures ANOVA determined the interactive effect of measurement mode and fitness level was significant. CONCLUSIONS: Overall, there is a strong correlation between criterion and predictive measurement, however, consumers should exercise caution when using predicted measures.
"]},{"key":"dc:title","label":"Title","values":["Accuracy of predicted energy expenditure from a Fitbit Inspire HR activity monitor during short- and long-duration exercise"]}]}],"canonical_facts":{"dc:contributor":["Rebecca Moore, Ph.D.","Catherine Gammon, Ph.D.","Anthony Moreno, Ph.D."],"dc:creator":["Van Camp, Cailyn"],"dc:date.available":["2020-09-22T07:00:00Z"],"dc:description.abstract":["PURPOSE: To determine the accuracy of predicted Energy Expenditure (EE) reported by a wrist-worn activity monitor compared to measured EE during both a long- and short-duration exercise. METHODS: In addition to a VO2max treadmill test, a running speed at approximately 70 - 75% of that VO2max was found during the first visit. The second and third visit was comprised of either a 30-minute or 10-minute run at the speed previously determined. A wrist activity monitor was worn and VO2 and EE were recorded by a metabolic cart. Pearson correlation, paired samples t-test, and repeated measures ANOVAs compared predicted and measured EE. An independent samples t-test determined significant differences in characteristics between fitness groups (p < 0.05). RESULTS: N = 25 (60% male). A significant correlation was found between predicted EE and measured EE for both short and long duration (p < 0.001). The repeated measures ANOVA determined the interactive effect of measurement mode and fitness level was significant. CONCLUSIONS: Overall, there is a strong correlation between criterion and predictive measurement, however, consumers should exercise caution when using predicted measures.
"],"dc:identifier":["https://commons.emich.edu/theses/1027"],"dc:subject":["energy expenditure","validation","wearable fitness tracker","Kinesiology"],"dc:title":["Accuracy of predicted energy expenditure from a Fitbit Inspire HR activity monitor during short- and long-duration exercise"],"thesis:degree_discipline":["Health Promotion and Human Performance"],"thesis:degree_level":["Open Access Thesis"],"thesis:degree_name":["Master of Science (MS)"]},"updated_at":"2026-07-24T02:17:40Z"}