Control of force during rapid visuomotor force-matching tasks can be described by discrete time PID control algorithms

Force trajectories during isometric force-matching tasks involving isometric contractions vary substantially across individuals. In this study, we investigated if this variability can be explained by discrete time proportional, integral, derivative (PID) control algorithms with varying model paramet...

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Vydané v:	Experimental brain research Ročník 235; číslo 8; s. 2561 - 2573
Hlavní autori:	Dideriksen, Jakob Lund, Feeney, Daniel F., Almuklass, Awad M., Enoka, Roger M.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2017 Springer Springer Nature B.V
Predmet:	Action Adult Algorithms Analysis Biomedical and Life Sciences Biomedicine Control algorithms Discrete time Electromyography Feedback Feedback, Sensory - physiology Female Humans Imperative sentences Isometric Contraction - physiology Male Matching Matching tasks Models, Theoretical Movement (Physiology) Muscle contraction Neurology Neurosciences Psychomotor Performance - physiology Reduction (Phonological or Phonetic) Research Article Sensorimotor integration Signal Processing, Computer-Assisted Time Factors Trajectories (Physics) Visual feedback Visual perception Young Adult Denmark Visuomotor tasks Isometric force Computational models Motor control
ISSN:	0014-4819, 1432-1106, 1432-1106
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Abstract	Force trajectories during isometric force-matching tasks involving isometric contractions vary substantially across individuals. In this study, we investigated if this variability can be explained by discrete time proportional, integral, derivative (PID) control algorithms with varying model parameters. To this end, we analyzed the pinch force trajectories of 24 subjects performing two rapid force-matching tasks with visual feedback. Both tasks involved isometric contractions to a target force of 10% maximal voluntary contraction. One task involved a single action (pinch) and the other required a double action (concurrent pinch and wrist extension). 50,000 force trajectories were simulated with a computational neuromuscular model whose input was determined by a PID controller with different PID gains and frequencies at which the controller adjusted muscle commands. The goal was to find the best match between each experimental force trajectory and all simulated trajectories. It was possible to identify one realization of the PID controller that matched the experimental force produced during each task for most subjects (average index of similarity: 0.87 ± 0.12; 1 = perfect similarity). The similarities for both tasks were significantly greater than that would be expected by chance (single action: p = 0.01; double action: p = 0.04). Furthermore, the identified control frequencies in the simulated PID controller with the greatest similarities decreased as task difficulty increased (single action: 4.0 ± 1.8 Hz; double action: 3.1 ± 1.3 Hz). Overall, the results indicate that discrete time PID controllers are realistic models for the neural control of force in rapid force-matching tasks involving isometric contractions.
AbstractList	Force trajectories during isometric force-matching tasks involving isometric contractions vary substantially across individuals. In this study, we investigated if this variability can be explained by discrete time proportional, integral, derivative (PID) control algorithms with varying model parameters. To this end, we analyzed the pinch force trajectories of 24 subjects performing two rapid force-matching tasks with visual feedback. Both tasks involved isometric contractions to a target force of 10% maximal voluntary contraction. One task involved a single action (pinch) and the other required a double action (concurrent pinch and wrist extension). 50,000 force trajectories were simulated with a computational neuromuscular model whose input was determined by a PID controller with different PID gains and frequencies at which the controller adjusted muscle commands. The goal was to find the best match between each experimental force trajectory and all simulated trajectories. It was possible to identify one realization of the PID controller that matched the experimental force produced during each task for most subjects (average index of similarity: 0.87 ± 0.12; 1 = perfect similarity). The similarities for both tasks were significantly greater than that would be expected by chance (single action: p = 0.01; double action: p = 0.04). Furthermore, the identified control frequencies in the simulated PID controller with the greatest similarities decreased as task difficulty increased (single action: 4.0 ± 1.8 Hz; double action: 3.1 ± 1.3 Hz). Overall, the results indicate that discrete time PID controllers are realistic models for the neural control of force in rapid force-matching tasks involving isometric contractions.Force trajectories during isometric force-matching tasks involving isometric contractions vary substantially across individuals. In this study, we investigated if this variability can be explained by discrete time proportional, integral, derivative (PID) control algorithms with varying model parameters. To this end, we analyzed the pinch force trajectories of 24 subjects performing two rapid force-matching tasks with visual feedback. Both tasks involved isometric contractions to a target force of 10% maximal voluntary contraction. One task involved a single action (pinch) and the other required a double action (concurrent pinch and wrist extension). 50,000 force trajectories were simulated with a computational neuromuscular model whose input was determined by a PID controller with different PID gains and frequencies at which the controller adjusted muscle commands. The goal was to find the best match between each experimental force trajectory and all simulated trajectories. It was possible to identify one realization of the PID controller that matched the experimental force produced during each task for most subjects (average index of similarity: 0.87 ± 0.12; 1 = perfect similarity). The similarities for both tasks were significantly greater than that would be expected by chance (single action: p = 0.01; double action: p = 0.04). Furthermore, the identified control frequencies in the simulated PID controller with the greatest similarities decreased as task difficulty increased (single action: 4.0 ± 1.8 Hz; double action: 3.1 ± 1.3 Hz). Overall, the results indicate that discrete time PID controllers are realistic models for the neural control of force in rapid force-matching tasks involving isometric contractions. Force trajectories during isometric force-matching tasks involving isometric contractions vary substantially across individuals. In this study, we investigated if this variability can be explained by discrete time proportional, integral, derivative (PID) control algorithms with varying model parameters. To this end, we analyzed the pinch force trajectories of 24 subjects performing two rapid force-matching tasks with visual feedback. Both tasks involved isometric contractions to a target force of 10% maximal voluntary contraction. One task involved a single action (pinch) and the other required a double action (concurrent pinch and wrist extension). 50,000 force trajectories were simulated with a computational neuromuscular model whose input was determined by a PID controller with different PID gains and frequencies at which the controller adjusted muscle commands. The goal was to find the best match between each experimental force trajectory and all simulated trajectories. It was possible to identify one realization of the PID controller that matched the experimental force produced during each task for most subjects (average index of similarity: 0.87 ± 0.12; 1 = perfect similarity). The similarities for both tasks were significantly greater than that would be expected by chance (single action: p = 0.01; double action: p = 0.04). Furthermore, the identified control frequencies in the simulated PID controller with the greatest similarities decreased as task difficulty increased (single action: 4.0 ± 1.8 Hz; double action: 3.1 ± 1.3 Hz). Overall, the results indicate that discrete time PID controllers are realistic models for the neural control of force in rapid force-matching tasks involving isometric contractions. Force trajectories during isometric force-matching tasks involving isometric contractions vary substantially across individuals. In this study, we investigated if this variability can be explained by discrete time proportional, integral, derivative (PID) control algorithms with varying model parameters. To this end, we analyzed the pinch force trajectories of 24 subjects performing two rapid force-matching tasks with visual feedback. Both tasks involved isometric contractions to a target force of 10% maximal voluntary contraction. One task involved a single action (pinch) and the other required a double action (concurrent pinch and wrist extension). 50,000 force trajectories were simulated with a computational neuromuscular model whose input was determined by a PID controller with different PID gains and frequencies at which the controller adjusted muscle commands. The goal was to find the best match between each experimental force trajectory and all simulated trajectories. It was possible to identify one realization of the PID controller that matched the experimental force produced during each task for most subjects (average index of similarity: 0.87 ± 0.12; 1 = perfect similarity). The similarities for both tasks were significantly greater than that would be expected by chance (single action: p = 0.01; double action: p = 0.04). Furthermore, the identified control frequencies in the simulated PID controller with the greatest similarities decreased as task difficulty increased (single action: 4.0 ± 1.8 Hz; double action: 3.1 ± 1.3 Hz). Overall, the results indicate that discrete time PID controllers are realistic models for the neural control of force in rapid force-matching tasks involving isometric contractions. Force trajectories during isometric force-matching tasks involving isometric contractions vary substantially across individuals. In this study, we investigated if this variability can be explained by discrete time proportional, integral, derivative (PID) control algorithms with varying model parameters. To this end, we analyzed the pinch force trajectories of 24 subjects performing two rapid force-matching tasks with visual feedback. Both tasks involved isometric contractions to a target force of 10% maximal voluntary contraction. One task involved a single action (pinch) and the other required a double action (concurrent pinch and wrist extension). 50,000 force trajectories were simulated with a computational neuromuscular model whose input was determined by a PID controller with different PID gains and frequencies at which the controller adjusted muscle commands. The goal was to find the best match between each experimental force trajectory and all simulated trajectories. It was possible to identify one realization of the PID controller that matched the experimental force produced during each task for most subjects (average index of similarity: 0.87 ± 0.12; 1 = perfect similarity). The similarities for both tasks were significantly greater than that would be expected by chance (single action: p = 0.01; double action: p = 0.04). Furthermore, the identified control frequencies in the simulated PID controller with the greatest similarities decreased as task difficulty increased (single action: 4.0 ± 1.8 Hz; double action: 3.1 ± 1.3 Hz). Overall, the results indicate that discrete time PID controllers are realistic models for the neural control of force in rapid force-matching tasks involving isometric contractions.
Audience	Academic
Author	Almuklass, Awad M. Enoka, Roger M. Feeney, Daniel F. Dideriksen, Jakob Lund
Author_xml	– sequence: 1 givenname: Jakob Lund surname: Dideriksen fullname: Dideriksen, Jakob Lund email: jldi@hst.aau.dk organization: SMI, Department of Health Science and Technology, Aalborg University – sequence: 2 givenname: Daniel F. surname: Feeney fullname: Feeney, Daniel F. organization: Department of Integrative Physiology, University of Colorado Boulder – sequence: 3 givenname: Awad M. surname: Almuklass fullname: Almuklass, Awad M. organization: Department of Integrative Physiology, University of Colorado Boulder, College of Medicine, King Saud bin Abdulaziz University for Health Sciences – sequence: 4 givenname: Roger M. surname: Enoka fullname: Enoka, Roger M. organization: Department of Integrative Physiology, University of Colorado Boulder
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/28555275$$D View this record in MEDLINE/PubMed
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CitedBy_id	crossref_primary_10_1016_j_humov_2019_102516 crossref_primary_10_1007_s00221_019_05524_z crossref_primary_10_1109_TNSRE_2025_3576669 crossref_primary_10_1177_17531934231211254 crossref_primary_10_3389_fphys_2019_00176 crossref_primary_10_1152_jn_00222_2022 crossref_primary_10_1113_JP275658 crossref_primary_10_1155_2018_9324623
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Snippet	Force trajectories during isometric force-matching tasks involving isometric contractions vary substantially across individuals. In this study, we investigated...
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SubjectTerms	Action Adult Algorithms Analysis Biomedical and Life Sciences Biomedicine Control algorithms Discrete time Electromyography Feedback Feedback, Sensory - physiology Female Humans Imperative sentences Isometric Contraction - physiology Male Matching Matching tasks Models, Theoretical Movement (Physiology) Muscle contraction Neurology Neurosciences Psychomotor Performance - physiology Reduction (Phonological or Phonetic) Research Article Sensorimotor integration Signal Processing, Computer-Assisted Time Factors Trajectories (Physics) Visual feedback Visual perception Young Adult
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Title	Control of force during rapid visuomotor force-matching tasks can be described by discrete time PID control algorithms
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