Use of Cross-Correlation Analysis to Determine Heart Rate Kinetics During Non-Steady State, Fatiguing Exercise in Collegiate Female Soccer Athletes
| dc.contributor.author | Williams, Brian Orbreyn | en |
| dc.contributor.committeechair | Williams, Jay H. | en |
| dc.contributor.committeemember | Hulver, Matthew W. | en |
| dc.contributor.committeemember | Tegarden, David P. | en |
| dc.contributor.committeemember | Rankin, Janet W. | en |
| dc.contributor.committeemember | Frisard, Madlyn I. | en |
| dc.contributor.department | Human Nutrition, Foods and Exercise | en |
| dc.date.accessioned | 2021-12-24T07:00:15Z | en |
| dc.date.available | 2021-12-24T07:00:15Z | en |
| dc.date.issued | 2020-07-01 | en |
| dc.description.abstract | For years, heart rate (HR) kinetics have been used as an indicator of training status and fatigue. Slowed kinetics indicate poor fitness and/or fatigue. In this study it was determined that HR kinetics can be reliably estimated during modeled, quasi-binary, and dynamic exercise using cross-correlation analysis of HR and external work rate. Heart rate and running speed were cross-correlated yielding a cross-correlation function (CCF) and analyzed for its peak (CCFmax) and time delay (CCFlag). Modeled exercise data where the time constants for HR (τ) increased from 2-120 sec. yielded linear decreases in CCFmax (r2 = 0.9949) and linear increases in CCFlag (r2=0.9996). A strong linear relationship existed between CCFmax and CCFlag (r2=0.9989). Steady-state exercise data produced strong relationships between the calculated τ and CCFmax (r2=0.8736) and CCFlag (r2=0.9061), and CCFmax and CCFlag showed a positive relationship (r2=0.7753). CCFmax between repeated sprint trials (R2=0.9123) and super set trails (R2=0.9227) were very similar. These results suggest good repeatability for both quasi-binary activity and random activity. To assess validity, CCFmax values during the sprint trials were compared to two standard field tests of fitness (Beep and Man U tests). There were strong relationships between CCFmax and distances covered during the Beep (r2=0.7911) and Mann U tests (r2=0.7770). Lastly, the applicability of the CCF method was applied to dynamic exercise, using data collected from competitive soccer matches. For the field players, significant reductions in CCFmax occurred during the first and second periods of the match. There was a significant relationship between the total distance covered during the match and the decline in CCFmax (r=-0.4297, p<0.05). Larger declines in CCFmax during the last 15 min of the match were also seen in the second match of a multiple match week compared to the first match. Tis later finding suggests that CCFmax may be a use tool to evaluate "fatigue" during dynamic exercise. Overall, cross-correlation of HR and running speed appears to be a reliable, valid and applicable approach to evaluate HR kinetics during exercise. As such, it may be beneficial for evaluating player fitness and readiness for competition. | en |
| dc.description.abstractgeneral | Exercise physiologists and sports professionals are continually in search of novel techniques which would assess training effectiveness and performance on the field. However, it is of paramount importance that any field-based data collection method must be noninvasive as to not interfere with the athlete's ability to perform in sport. Currently, heart rate (HR) is the most readily accessible and commonly used variable to estimate cardiovascular response to exercise. Heart rate kinetics have proven to be a powerful indicator of training status as HR responses to changes in exercise intensity are accelerated following exercise training. In this study we were able to determine that HR kinetics can be reliably estimated during modeled, quasi-binary, and dynamic exercise using cross-correlation analysis of HR and external work rate. Heart Rate and running speed were cross-correlated yielding a cross-correlation function (CCF). That function was then analyzed for its peak (CCFmax) and time delay (CCFlag). Modeled exercise data yielded linear decreases in CCFmax and linear increases in CCFlag. Also, CCFmax and CCFlag were correlated to each other. Steady-state exercise data produced the same linear relationships observed for the modeled data for CCFmax and CCFlag. CCFmax between repeated sprint trials were found to be highly reliable which suggest good repeatability for both quasi-binary activity and random activity. CCFmax was also found to be highly valid when comparing sprint values to validated fitness test values. Additionally, good relationships were found between CCFmax derived during fitness tests and distances covered on the fitness tests. As HR kinetics are linked to fitness, these results suggest that CCFmax values are valid. There was a significant relationship between the total distance covered during a full soccer match and the decline in CCFmax in field players that were not seen in the goalkeeper. Lastly, CCFmax declined during the last 15 minutes of the match compared to the start of the match. These results demonstrate CCF derived HR kinetics appear to be reliable and valid metrics for evaluating soccer fitness and "fatigue". This method may prove to be a strong indicator of fitness in other high activity sports as well. | en |
| dc.description.degree | Doctor of Philosophy | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:26099 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/107262 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Exercise | en |
| dc.subject | Soccer | en |
| dc.subject | Fatigue | en |
| dc.subject | Aerobic Capacity | en |
| dc.subject | Heart Rate Kinetics | en |
| dc.title | Use of Cross-Correlation Analysis to Determine Heart Rate Kinetics During Non-Steady State, Fatiguing Exercise in Collegiate Female Soccer Athletes | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Human Nutrition, Foods, and Exercise | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |
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