Timing Accuracy in Human Throwing
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This study examines the precision required in the timing of muscle activations and projectile release to hit a target of 20 cm in diameter oriented horizontally either 6 or 8 m away. Over-arm throws, constrained to the sagittal plane, were simulated using a muscle-actuated, two-segment model representing the forearm and hand plus projectile. The parameters defining the modeled muscles and the anthropometry were specific to two male subjects. An objective function specified that throws must be both fast and accurate. Once an optimal solution had been found, the sensitivity of these timings was investigated. The times of activation or release were changed and the simulation model re-run with the new timings, and it was determined whether the projectile would still have struck the target. For one set of simulations, to hit the target at 8 m, the optimal throw was achieved with a time delay between the onset of wrist activation and elbow extensor activation [Proximal-distal (PD) delay] of 49 ms and a release time of 83.4 ms. At this optimal point in the solution space, the launch window was 1.2 ms (assuming the original PD delay). The launch window was the time available within which the projectile must be released and still strike the target. The window during which the wrist flexors could be activated was 10. 41 ms (assuming the projectile was released at the pre-planned optimal time). The control scheme which required the least timing precision had a PD delay of 56 ms and a release time of 89.4 ms. Errors in timing could occur in activation and release simultaneously under this scheme, the timing windows were 4 ms in PD delay and 2.4 ms in release. Similar results were found for a second set of simulations. These simulations revealed the precise timings required in muscle activations and release required for fast accurate throws.
Neural Encoding and Representation of Time for Sensorimotor Control and Learning.
Balasubramaniam R, Haegens S, Jazayeri M, Merchant H, Sternad D, Song J J Neurosci. 2020; 41(5):866-872.
PMID: 33380468 PMC: 7880297. DOI: 10.1523/JNEUROSCI.1652-20.2020.
Back to reality: differences in learning strategy in a simplified virtual and a real throwing task.
Zhang Z, Sternad D J Neurophysiol. 2020; 125(1):43-62.
PMID: 33146063 PMC: 8087380. DOI: 10.1152/jn.00197.2020.
Exploiting the geometry of the solution space to reduce sensitivity to neuromotor noise.
Zhang Z, Guo D, Huber M, Park S, Sternad D PLoS Comput Biol. 2018; 14(2):e1006013.
PMID: 29462147 PMC: 5834204. DOI: 10.1371/journal.pcbi.1006013.
Analysis of timing variability in human movements by aligning parameter curves in time.
Maurer L, Maurer H, Muller H Behav Res Methods. 2017; 50(5):1841-1852.
PMID: 28791601 DOI: 10.3758/s13428-017-0952-0.
Stirn I, Carruthers J, Sibila M, Pori P J Hum Kinet. 2017; 56:197-205.
PMID: 28469758 PMC: 5384067. DOI: 10.1515/hukin-2017-0037.