Nicholas Rémillard, Marisa Mulvey, Greg J. Petrucci, J. Sirard
{"title":"基于加速度计的高强度间歇训练能量消耗估算的验证","authors":"Nicholas Rémillard, Marisa Mulvey, Greg J. Petrucci, J. Sirard","doi":"10.33697/ajur.2022.057","DOIUrl":null,"url":null,"abstract":"Accelerometers are used to assess free-living physical activity (PA) and energy expenditure (EE). Energy expenditure estimation algorithms have been calibrated using steady-state exercise. However, most free-living PA is not steady-state. Objective: The purpose of this study was to discern the differences between criterion-measured and accelerometer-estimated EE (kCals) during a non-steady-state High-Intensity Interval Training (HIIT) session. Methods: Recreationally active adults (N=29, 18-30 years) completed one of two HIIT protocols. Each participant wore ActiGraph GT3X+ accelerometers on the right hip and non-dominant wrist while EE was measured using portable indirect calorimetry. Data analysis was conducted using custom R scripts and bias [95% CIs] to determine significant differences between indirect calorimetry and EE estimates using previously developed algorithms. Results: All accelerometer algorithms underestimated EE during recovery intervals (range; -4.31 to -6.55 kCals) and overestimated EE during work intervals (0.57 to 5.70 kcals). Over the whole HIIT session, only the Hildebrand wrist method was not significantly different from the criterion measured EE. Conclusion: Current ActiGraph EE estimations based on steady-state activities underestimate EE during recovery periods of treadmill HIIT sessions. Future studies should investigate accelerometer signals immediately after high-intensity bouts to more accurately predict EE of the subsequent recovery period.\n\nKEYWORDS: ActiGraph; Accelerometer; HIIT; Indirect calorimetry; EPOC; Energy expenditure; Non-steady state; Calories","PeriodicalId":72177,"journal":{"name":"American journal of undergraduate research","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Validation of Accelerometer-Based Estimations of Energy Expenditure During High-Intensity Interval Training\",\"authors\":\"Nicholas Rémillard, Marisa Mulvey, Greg J. Petrucci, J. Sirard\",\"doi\":\"10.33697/ajur.2022.057\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Accelerometers are used to assess free-living physical activity (PA) and energy expenditure (EE). Energy expenditure estimation algorithms have been calibrated using steady-state exercise. However, most free-living PA is not steady-state. Objective: The purpose of this study was to discern the differences between criterion-measured and accelerometer-estimated EE (kCals) during a non-steady-state High-Intensity Interval Training (HIIT) session. Methods: Recreationally active adults (N=29, 18-30 years) completed one of two HIIT protocols. Each participant wore ActiGraph GT3X+ accelerometers on the right hip and non-dominant wrist while EE was measured using portable indirect calorimetry. Data analysis was conducted using custom R scripts and bias [95% CIs] to determine significant differences between indirect calorimetry and EE estimates using previously developed algorithms. Results: All accelerometer algorithms underestimated EE during recovery intervals (range; -4.31 to -6.55 kCals) and overestimated EE during work intervals (0.57 to 5.70 kcals). Over the whole HIIT session, only the Hildebrand wrist method was not significantly different from the criterion measured EE. Conclusion: Current ActiGraph EE estimations based on steady-state activities underestimate EE during recovery periods of treadmill HIIT sessions. Future studies should investigate accelerometer signals immediately after high-intensity bouts to more accurately predict EE of the subsequent recovery period.\\n\\nKEYWORDS: ActiGraph; Accelerometer; HIIT; Indirect calorimetry; EPOC; Energy expenditure; Non-steady state; Calories\",\"PeriodicalId\":72177,\"journal\":{\"name\":\"American journal of undergraduate research\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American journal of undergraduate research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33697/ajur.2022.057\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of undergraduate research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33697/ajur.2022.057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Validation of Accelerometer-Based Estimations of Energy Expenditure During High-Intensity Interval Training
Accelerometers are used to assess free-living physical activity (PA) and energy expenditure (EE). Energy expenditure estimation algorithms have been calibrated using steady-state exercise. However, most free-living PA is not steady-state. Objective: The purpose of this study was to discern the differences between criterion-measured and accelerometer-estimated EE (kCals) during a non-steady-state High-Intensity Interval Training (HIIT) session. Methods: Recreationally active adults (N=29, 18-30 years) completed one of two HIIT protocols. Each participant wore ActiGraph GT3X+ accelerometers on the right hip and non-dominant wrist while EE was measured using portable indirect calorimetry. Data analysis was conducted using custom R scripts and bias [95% CIs] to determine significant differences between indirect calorimetry and EE estimates using previously developed algorithms. Results: All accelerometer algorithms underestimated EE during recovery intervals (range; -4.31 to -6.55 kCals) and overestimated EE during work intervals (0.57 to 5.70 kcals). Over the whole HIIT session, only the Hildebrand wrist method was not significantly different from the criterion measured EE. Conclusion: Current ActiGraph EE estimations based on steady-state activities underestimate EE during recovery periods of treadmill HIIT sessions. Future studies should investigate accelerometer signals immediately after high-intensity bouts to more accurately predict EE of the subsequent recovery period.
KEYWORDS: ActiGraph; Accelerometer; HIIT; Indirect calorimetry; EPOC; Energy expenditure; Non-steady state; Calories