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Kunavar T, Jamšek M, Avila-Mireles EJ, Rueckert E, Peternel L, Babič J. The Effects of Different Motor Teaching Strategies on Learning a Complex Motor Task. SENSORS (BASEL, SWITZERLAND) 2024; 24:1231. [PMID: 38400387 PMCID: PMC10892071 DOI: 10.3390/s24041231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 02/25/2024]
Abstract
During the learning of a new sensorimotor task, individuals are usually provided with instructional stimuli and relevant information about the target task. The inclusion of haptic devices in the study of this kind of learning has greatly helped in the understanding of how an individual can improve or acquire new skills. However, the way in which the information and stimuli are delivered has not been extensively explored. We have designed a challenging task with nonintuitive visuomotor perturbation that allows us to apply and compare different motor strategies to study the teaching process and to avoid the interference of previous knowledge present in the naïve subjects. Three subject groups participated in our experiment, where the learning by repetition without assistance, learning by repetition with assistance, and task Segmentation Learning techniques were performed with a haptic robot. Our results show that all the groups were able to successfully complete the task and that the subjects' performance during training and evaluation was not affected by modifying the teaching strategy. Nevertheless, our results indicate that the presented task design is useful for the study of sensorimotor teaching and that the presented metrics are suitable for exploring the evolution of the accuracy and precision during learning.
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Affiliation(s)
- Tjasa Kunavar
- Laboratory for Neromechanics and Biorobotics, Department of Automatics and Biocybernetics, Jožef Stefan Institute, 1000 Ljubljana, Slovenia
- Jožef Stefan International Postgraduate School, Jamova cesta 39, 1000 Ljubljana, Slovenia
| | - Marko Jamšek
- Laboratory for Neromechanics and Biorobotics, Department of Automatics and Biocybernetics, Jožef Stefan Institute, 1000 Ljubljana, Slovenia
| | - Edwin Johnatan Avila-Mireles
- Laboratory for Neromechanics and Biorobotics, Department of Automatics and Biocybernetics, Jožef Stefan Institute, 1000 Ljubljana, Slovenia
| | - Elmar Rueckert
- Chair of Cyber-Physical-Systems, Montauniversität Leoben, 8700 Leoben, Austria
| | - Luka Peternel
- Department of Cognitive Robotics, Delft University of Technology, 2628 CD Delft, The Netherlands
| | - Jan Babič
- Laboratory for Neromechanics and Biorobotics, Department of Automatics and Biocybernetics, Jožef Stefan Institute, 1000 Ljubljana, Slovenia
- Faculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, Slovenia
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Bucklin MA, Deol J, Brown G, Perreault EJ, Gordon KE. Optimism persists when walking in unpredictable environments. Sci Rep 2023; 13:6853. [PMID: 37100839 PMCID: PMC10133317 DOI: 10.1038/s41598-023-33662-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 04/17/2023] [Indexed: 04/28/2023] Open
Abstract
Humans continuously modulate their control strategies during walking based on their ability to anticipate disturbances. However, how people adapt and use motor plans to create stable walking in unpredictable environments is not well understood. Our purpose was to investigate how people adapt motor plans when walking in a novel and unpredictable environment. We evaluated the whole-body center of mass (COM) trajectory of participants as they performed repetitions of a discrete goal-directed walking task during which a laterally-directed force field was applied to the COM. The force field was proportional in magnitude to forward walking velocity and randomly directed towards either the right or left each trial. We hypothesized that people would adapt a control strategy to reduce the COM lateral deviations created by the unpredictable force field. In support of our hypothesis, we found that with practice the magnitude of COM lateral deviation was reduced by 28% (force field left) and 44% (force field right). Participants adapted two distinct unilateral strategies, implemented regardless of if the force field was applied to the right or to the left, that collectively created a bilateral resistance to the unpredictable force field. These strategies included an anticipatory postural adjustment to resist against forces applied to the left, and a more lateral first step to resist against forces applied to the right. In addition, during catch trials when the force field was unexpectedly removed, participants exhibited trajectories similar to baseline trials. These findings were consistent with an impedance control strategy that provides a robust resistance to unpredictable perturbations. However, we also found evidence that participants made predictive adaptations in response to their immediate experience that persisted for three trials. Due to the unpredictable nature of the force field, this predictive strategy would sometimes result in greater lateral deviations when the prediction was incorrect. The presence of these competing control strategies may have long term benefits by allowing the nervous system to identify the best overall control strategy to use in a novel environment.
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Affiliation(s)
- Mary A Bucklin
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, 645 N. Michigan Ave, Suite 1100, Chicago, IL, 60611, USA.
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA.
| | - Jasjit Deol
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, 645 N. Michigan Ave, Suite 1100, Chicago, IL, 60611, USA
| | - Geoffrey Brown
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, 645 N. Michigan Ave, Suite 1100, Chicago, IL, 60611, USA
| | - Eric J Perreault
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA
- Shirley Ryan Ability Lab, Chicago, IL, USA
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, USA
| | - Keith E Gordon
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, 645 N. Michigan Ave, Suite 1100, Chicago, IL, 60611, USA
- Research Service, Edward Hines Jr. VA Hospital, Hines, IL, USA
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Bucklin MA, Brown G, Gordon KE. People adapt a consistent center-of-mass trajectory in a novel force field. J Neurophysiol 2023; 129:298-306. [PMID: 36542421 PMCID: PMC9886345 DOI: 10.1152/jn.00391.2021] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 12/19/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022] Open
Abstract
During human walking the whole body center-of-mass (COM) trajectory may be a control objective, a goal the central nervous system uses to plan and regulate movement. Our previous observation, that after practice walking in a novel laterally directed force field people adapt a COM trajectory similar to their normal trajectory, supports this idea. However, our prior work only presented data demonstrating changes in COM trajectory in response to a single force field. To evaluate whether this phenomena is robust, in the present study we present new data demonstrating that people adapt their COM trajectory in a similar manner when the direction of the external force field is changed resulting in drastically different lower limb joint dynamics. Specifically, we applied a continuous, left-directed force field (in the previous experiment the force field was applied to the right) to the COM as participants performed repeated trials of a discrete walking task. We again hypothesized that with practice walking in the force field people would adapt a COM trajectory that was similar to their baseline performance and exhibit aftereffects, deviation of their COM trajectory in the opposite direction of force field, when the field was unexpectedly removed. These hypotheses were supported and suggest that participants formed an internal model to control their COM trajectory. Collectively these findings demonstrate that people adapt their gait patterns to anticipate consistent aspects of the external environment. These findings suggest that this response is robust to force fields applied in multiple directions that may require substantially different neural control.NEW & NOTEWORTHY With experience people adapted a predictive internal model to control their whole body center-of-mass walking trajectory that anticipated the disruptive laterally directed forces of a novel and consistent external environment. Collectively these findings demonstrate that adaptation of gait to anticipate consistent aspects of the external environment is a response that is robust to force fields in multiple directions that require substantially different lower limb dynamics and neural control.
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Affiliation(s)
- Mary A Bucklin
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
- Department of Biomedical Engineering, Northwestern University, Evanston, Illinois
| | - Geoffrey Brown
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Keith E Gordon
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
- Research Service, Edward Hines, Jr. Department of Veterans Affairs Hospital, Hines, Illinois
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Takahashi C, Azad M, Rajasekaran V, Babič J, Mistry M. Human Stiffness Perception and Learning in Interacting With Compliant Environments. Front Neurosci 2022; 16:841901. [PMID: 35757537 PMCID: PMC9215212 DOI: 10.3389/fnins.2022.841901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 04/19/2022] [Indexed: 11/19/2022] Open
Abstract
Humans are capable of adjusting their posture stably when interacting with a compliant surface. Their whole-body motion can be modulated in order to respond to the environment and reach to a stable state. In perceiving an uncertain external force, humans repetitively push it and learn how to produce a stable state. Research in human motor control has led to the hypothesis that the central nervous system integrates an internal model with sensory feedback in order to generate accurate movements. However, how the brain understands external force through exploration movements, and how humans accurately estimate a force from their experience of the force, is yet to be fully understood. To address these questions, we tested human behaviour in different stiffness profiles even though the force at the goal was the same. We generated one linear and two non-linear stiffness profiles, which required the same force at the target but different forces half-way to the target; we then measured the differences in the learning performance at the target and the differences in perception at the half-way point. Human subjects learned the stiffness profile through repetitive movements in reaching the target, and then indicated their estimation of half of the target value (position and force separately). This experimental design enabled us to probe how perception of the force experienced in different profiles affects the participants' estimations. We observed that the early parts of the learning curves were different for the three stiffness profiles. Secondly, the position estimates were accurate independent of the stiffness profile. The estimation in position was most likely influenced by the external environment rather than the profile itself. Interestingly, although visual information about the target had a large influence, we observed significant differences in accuracy of force estimation according to the stiffness profile.
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Affiliation(s)
- Chie Takahashi
- School of Computer Science, University of Birmingham, Birmingham, United Kingdom
- Edinburgh Centre for Robotics, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
- School of Metallurgy and Materials, University of Birmingham, Birmingham, United Kingdom
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Morteza Azad
- School of Computer Science, University of Birmingham, Birmingham, United Kingdom
| | - Vijaykumar Rajasekaran
- School of Computer Science, University of Birmingham, Birmingham, United Kingdom
- School of Metallurgy and Materials, University of Birmingham, Birmingham, United Kingdom
| | - Jan Babič
- Laboratory for Neuromechanics and Biorobotics, Department for Automation, Biocybernetics and Robotics, Jožef Stefan Institute, Ljubljana, Slovenia
- Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia
| | - Michael Mistry
- School of Computer Science, University of Birmingham, Birmingham, United Kingdom
- Edinburgh Centre for Robotics, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
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Xue H, Herzog R, Berger TM, Bäumer T, Weissbach A, Rueckert E. Using Probabilistic Movement Primitives in Analyzing Human Motion Differences Under Transcranial Current Stimulation. Front Robot AI 2021; 8:721890. [PMID: 34595209 PMCID: PMC8476753 DOI: 10.3389/frobt.2021.721890] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 08/19/2021] [Indexed: 11/13/2022] Open
Abstract
In medical tasks such as human motion analysis, computer-aided auxiliary systems have become the preferred choice for human experts for their high efficiency. However, conventional approaches are typically based on user-defined features such as movement onset times, peak velocities, motion vectors, or frequency domain analyses. Such approaches entail careful data post-processing or specific domain knowledge to achieve a meaningful feature extraction. Besides, they are prone to noise and the manual-defined features could hardly be re-used for other analyses. In this paper, we proposed probabilistic movement primitives (ProMPs), a widely-used approach in robot skill learning, to model human motions. The benefit of ProMPs is that the features are directly learned from the data and ProMPs can capture important features describing the trajectory shape, which can easily be extended to other tasks. Distinct from previous research, where classification tasks are mostly investigated, we applied ProMPs together with a variant of Kullback-Leibler (KL) divergence to quantify the effect of different transcranial current stimulation methods on human motions. We presented an initial result with 10 participants. The results validate ProMPs as a robust and effective feature extractor for human motions.
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Affiliation(s)
- Honghu Xue
- Institute for Robotics and Cognitive Systems, University of Luebeck, Luebeck, Germany
| | - Rebecca Herzog
- Institute of Systems Motor Science, University of Luebeck, Luebeck, Germany.,Department of Neurology, University Medical Center Schleswig-Holstein, Luebeck, Germany
| | - Till M Berger
- Institute of Systems Motor Science, University of Luebeck, Luebeck, Germany
| | - Tobias Bäumer
- Department of Neurology, University Medical Center Schleswig-Holstein, Luebeck, Germany
| | - Anne Weissbach
- Institute of Systems Motor Science, University of Luebeck, Luebeck, Germany.,Institute of Neurogenetics, University of Luebeck, Luebeck, Germany
| | - Elmar Rueckert
- Chair of Cyber-Physical-Systems, Montanuniversität Leoben, Leoben, Austria
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Jamsek M, Kunavar T, Bobek U, Rueckert E, Babic J. Predictive Exoskeleton Control for Arm-Motion Augmentation Based on Probabilistic Movement Primitives Combined With a Flow Controller. IEEE Robot Autom Lett 2021. [DOI: 10.1109/lra.2021.3068892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Bucklin MA, Wu M, Brown G, Gordon KE. American Society of Biomechanics Journal of Biomechanics Award 2018: Adaptive motor planning of center-of-mass trajectory during goal-directed walking in novel environments. J Biomech 2019; 94:5-12. [PMID: 31416592 DOI: 10.1016/j.jbiomech.2019.07.030] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 07/11/2019] [Accepted: 07/26/2019] [Indexed: 11/27/2022]
Abstract
To aid in the successful execution of goal-directed walking (discrete movement from a start location to an end target) the central nervous system forms a predictive motor plan. For the motor plan to be effective, it must be adapted in response to environmental changes. Despite motor planning being inherent to goal-directed walking, it is not understood how the nervous system adapts these plans to interact with changing environments. Our objective was to understand how people adapt motor plans of center of mass (COM) trajectory during goal-directed walking in response to a consistent change in environmental dynamics. Participants preformed a series of goal-directed walking trials in a novel environment created by a cable robot that applied a lateral force field to their COM. We hypothesized that participants would adapt to the environment by forming an internal model of their COM trajectory within the force field. Our findings support this hypothesis. Initially, we found COM trajectory significantly deviated in the same direction as the applied field, relative to baseline (no field) (p = 0.002). However, with practice in the field, COM trajectory adapted back to the baseline (p = 0.6). When we unexpectedly removed the field, participants demonstrated after-effects, COM trajectory deviated in the direction opposite of the field relative to baseline (p < 0.001). Our findings suggest that when performing a goal-directed walking task, people adapt a motor plan that predicts the COM trajectory that will emerge from the interaction between a specific set of motor commands and the external environment.
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Affiliation(s)
- Mary A Bucklin
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA.
| | - Mengnan/Mary Wu
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Geoffrey Brown
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Keith E Gordon
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Research Service, Edward Hines Jr. VA Hospital, Hines, IL, USA
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Babič J, Oztop E, Kawato M. Human motor adaptation in whole body motion. Sci Rep 2016; 6:32868. [PMID: 27608652 PMCID: PMC5016968 DOI: 10.1038/srep32868] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2016] [Accepted: 08/16/2016] [Indexed: 11/18/2022] Open
Abstract
The main role of the sensorimotor system of an organism is to increase the survival of the species. Therefore, to understand the adaptation and optimality mechanisms of motor control, it is necessary to study the sensorimotor system in terms of ecological fitness. We designed an experimental paradigm that exposed sensorimotor system to risk of injury. We studied human subjects performing uncon- strained squat-to-stand movements that were systematically subjected to non-trivial perturbation. We found that subjects adapted by actively compensating the perturbations, converging to movements that were different from their normal unperturbed squat-to-stand movements. Furthermore, the adapted movements had clear intrinsic inter-subject differences which could be explained by different adapta- tion strategies employed by the subjects. These results suggest that classical optimality measures of physical energy and task satisfaction should be seen as part of a hierarchical organization of optimality with safety being at the highest level. Therefore, in addition to physical energy and task fulfillment, the risk of injury and other possible costs such as neural computational overhead have to be considered when analyzing human movement.
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Affiliation(s)
- Jan Babič
- Jožef Stefan Institute, Ljubljana, Slovenia
| | | | - Mitsuo Kawato
- ATR Brain Information Communication Research Laboratory Group, Kyoto, Japan
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