| dc.contributor.advisor | Hosoi, Anette (Peko) | |
| dc.contributor.author | Nielan, Maya Katherine | |
| dc.date.accessioned | 2022-08-29T16:33:22Z | |
| dc.date.available | 2022-08-29T16:33:22Z | |
| dc.date.issued | 2022-05 | |
| dc.date.submitted | 2022-05-27T16:19:20.246Z | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/145107 | |
| dc.description.abstract | Understanding exertion during exercise helps athletes prevent injuries and train at an optimal level. Currently, there exist metrics to determine exertion levels that are specific to individual activities that are mostly dynamic in nature. American football linemen spend most of their energy maintaining static loads; thus, they are in need of a new exertion metric. To design this metric, acceleration, force, and heart rate data is recorded over different weight lifting, running, and football-specific activities. From this data, a dimensionless external load value is calculated as [equation] and an internal load or exertion value is calculated as [equation]. These external and internal load values are compared within the football specific activity experiments and across all experiments of different activities. The relationship between these values is represented through this power fit [equation], suggesting that the relative change in external load gives rise to a proportional relative change in the body’s exertion levels. | |
| dc.publisher | Massachusetts Institute of Technology | |
| dc.rights | In Copyright - Educational Use Permitted | |
| dc.rights | Copyright MIT | |
| dc.rights.uri | http://rightsstatements.org/page/InC-EDU/1.0/ | |
| dc.title | Quantifying Exertion for American Football Linemen via Force, Acceleration, and Heart Rate Measurements | |
| dc.type | Thesis | |
| dc.description.degree | M.Eng. | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
| mit.thesis.degree | Master | |
| thesis.degree.name | Master of Engineering in Electrical Engineering and Computer Science | |