| Autor: |
Seshadri DR; Department of Bioengineering, Lehigh University, Bethlehem, PA 18015, USA.; Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA., VanBibber HD; Sports Medicine Institute, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA.; Department of Orthopaedic Surgery, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA.; Department of Cognitive Science, Case Western Reserve University, Cleveland, OH 44106, USA.; Department of Psychology, Case Western Reserve University, Cleveland, OH 44106, USA., Sethi MP; Department of Cognitive Science, Case Western Reserve University, Cleveland, OH 44106, USA.; Department of Psychology, Case Western Reserve University, Cleveland, OH 44106, USA., Harlow ER; Sports Medicine Institute, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA.; Department of Orthopaedic Surgery, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA., Voos JE; Sports Medicine Institute, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA.; Department of Orthopaedic Surgery, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA. |
| Abstrakt: |
Wearable devices in sports have been used at the professional and higher collegiate levels, but not much research has been conducted at lower collegiate division levels. The objective of this retrospective study was to gather big data using the Catapult wearable technology, develop an algorithm for musculoskeletal modeling, and longitudinally determine the workloads of male college soccer (football) athletes at the Division III (DIII) level over the course of a 12-week season. The results showed that over the course of a season, (1) the average match workload (432 ± 47.7) was 1.5× greater than the average training workload (252.9 ± 23.3) for all positions, (2) the forward position showed the lowest workloads throughout the season, and (3) the highest mean workload was in week 8 (370.1 ± 177.2), while the lowest was in week 4 (219.1 ± 26.4). These results provide the impetus to enable the interoperability of data gathered from wearable devices into data management systems for optimizing performance and health. |
