Optimal control of long-term feedback during periodic and continuous movements

Movement variability is inherent in human movement, which during periodic and continuous movement may accumulation over time to cause significant deviations away from the planned movement pattern. To prevent such drastic errors in movement the CNS employs a feedback mechanism which detects deviations from the planned movement and triggers the appropriate response to correct the motions. A feedback control mechanism such as this would produce further variability in the executed movement patterns, which can be mistaken for other forms of movement variability. Errors within this long-term feedback control mechanism would result in poor postural control in prolonged gait and balance tasks, increasing the chance that the individual will fall or a sports performance will be threatened.

Aims
1) determine the changes in movement coordination due to internal feedback mechanisms
2) create a model of the feedback processes
3) determine the sensitivity of these processes and parameters to control movement over time and examine implications for limitations for human performance.

The proposed project could use a combination of EMG, kinematic (motion capture) and kinetic (force plates, instrumented treadmill) data collection to examine and isolate the changes in movement coordination due to internal feedback mechanisms during continuous and periodic movement patterns (such as gait, tumbling, or high-bar giant swings). Subsequently, a computer simulation model could be used to create the predicted feedback processes and recreate the action under investigation during multiple cycles using a long-term feedback control strategy (such as a central pattern generator with PID controller).

Find out more
http://www.lboro.ac.uk/departments/ssehs/staff/blenkinsopglen/

http://www.lboro.ac.uk/departments/ssehs/staff/michael-hiley/

Entry requirements
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Sport Science, Mathematics, Engineering, or related areas.

A relevant Master's degree and / or experience in one or more of the following will be an advantage: Biomechanics, Motor Control, Mathematics, Engineering, or related areas.