Assessing the bias in estimations of vertical, jump height with smartphones
Reference persons TAIAN MARTINS
External reference persons Dr Alessio Gallina, School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham (UK)
Research Groups Laboratory for Engineering of the Neuromuscular System (LISiN)
Thesis type EXPERIMENTAL APPLIED
Description Different methods have been proposed for estimating the height of vertical jumps, all based on the vertical component of the velocity of the body centre of gravity at take-off. Vertical speed at take-off can be estimated using the flight-time, impulse-momentum, and work-energy approaches. The first approach is the simplest, requiring the measurement of the time subjects take to land after take-off. The simplicity of the method opens for the use of different instruments, from contact mats to smartphones. However, regardless of how flight time is computed, implicit in this method is the assumption that the speed of the body centre of mass at take-off and landing is the same. Rarely, though, speed is the same when taking off and landing. Violation of this assumption introduces a bias on the estimated jump height, which magnitude depends on the uncertainty with which take-off and landing instants are measured.
In this proposal, the student is expected to conduct experiments with the goal of addressing the question: how large is the bias of jump height values estimated with the flight-time method, as computed with smartphones and force plates?
The activities proposed will be conducted in collaboration with Dr Alessio Gallina, School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham (UK).
Required skills Good understanding of neuromuscular physiology
Advanced Matlab (or other coding languages) skills
High English proficiency
Notes Students willing to undertake this proposal are requested to contact the supervisor and submit:
1. A letter of interest for the proposed project
2. Elements motivating the decision to pursue this thesis (5-10 lines of text)
Deadline 31/12/2023 PROPONI LA TUA CANDIDATURA