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Nayeem R, Sohn WJ, DiCarlo JA, Gochyyev P, Lin DJ, Sternad D. Novel Platform for Quantitative Assessment of Functional Object Interactions After Stroke. IEEE Trans Neural Syst Rehabil Eng 2022; 31:426-436. [PMID: 36455078 PMCID: PMC10079607 DOI: 10.1109/tnsre.2022.3226067] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Many persons with stroke exhibit upper extremity motor impairments. These impairments often lead to dysfunction and affect performance in activities of daily living, where successful manipulation of objects is essential. Hence, understanding how upper extremity motor deficits manifest in functional interactions with objects is critical for rehabilitation. However, quantifying skill in these tasks has been a challenge. Traditional rehabilitation assessments require highly trained clinicians, are time-consuming, and yield subjective scores. This paper introduces a custom-designed device, the "MAGIC Table", that can record real-time kinematics of persons with stroke during interaction with objects, specifically a 'cup of coffee'. The task and its quantitative assessments were derived from previous basic-science studies. Six participants after stroke and six able-bodied participants moved a 3D-printed cup with a rolling ball inside, representing sloshing coffee, with 3 levels of difficulty. Movements were captured via a high-resolution camera above the table. Conventional kinematic metrics (movement time and smoothness) and novel kinematic metrics accounting for object interaction (risk and predictability) evaluated performance. Expectedly, persons with stroke moved more slowly and less smoothly than able-bodied participants, in both simple reaches and during transport of the cup-and-ball system. However, the more sensitive metric was mutual information, which captured the predictability of interactions, essential in cup transport as shown in previous theoretical research. Predictability sensitively measured differences in performance with increasing levels of difficulty. It also showed the best intraclass consistency, promising sensitive differentiation between different levels of impairment. This first study highlights the feasibility of this new device and indicates that examining dynamic object interaction may provide valuable insights into upper extremity function after stroke useful for assessment and rehabilitation.
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Affiliation(s)
- Rashida Nayeem
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
| | - Won Joon Sohn
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
| | - Julie A. DiCarlo
- Department of Neurology, Massachusetts General Hospital, Center for Neurotechnology and Neurorecovery, Harvard Medical School, Boston, MA, USA
| | - Perman Gochyyev
- Department of Neurology, Massachusetts General Hospital, Center for Neurotechnology and Neurorecovery, Harvard Medical School, Boston, MA, USA
| | - David J. Lin
- Department of Neurology, Massachusetts General Hospital, Center for Neurotechnology and Neurorecovery, Harvard Medical School, Boston, MA, USA
| | - Dagmar Sternad
- Department of Electrical and Computer Engineering and the Department of Biology and Physics, Northeastern University, Boston, MA, USA
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Arlati S, Di Santo SG, Franchini F, Mondellini M, Filiputti B, Luchi M, Ratto F, Ferrigno G, Sacco M, Greci L. Acceptance and Usability of Immersive Virtual Reality in Older Adults with Objective and Subjective Cognitive Decline. J Alzheimers Dis 2021; 80:1025-1038. [DOI: 10.3233/jad-201431] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Virtual reality (VR) has recently emerged as a promising means for the administration of cognitive training of seniors at risk of dementia. Immersive VR could result in increased engagement and performances; however, its acceptance in older adults with cognitive deficits still has to be assessed. Objective: To assess acceptance and usability of an immersive VR environment requiring real walking and active participants’ interaction. Methods: 58 seniors with mild cognitive impairment (MCI, n = 24) or subjective cognitive decline (SCD, n = 31) performed a shopping task in a virtual supermarket displayed through a head-mounted display. Subjective and objective outcomes were evaluated. Results: Immersive VR was well-accepted by all but one participant (TAM3 positive subscales > 5.33), irrespective of the extent of cognitive decline. Participants enjoyed the experience (spatial presence 3.51±0.50, engagement 3.85±0.68, naturalness 3.85±0.82) and reported negligible side-effects (SSQ: 3.74; q1-q3:0–16.83). The environment was considered extremely realistic, such as to induce potentially harmful behaviors: one participant fell while trying to lean on a virtual shelf. Older participants needed more time to conclude trials. Participants with MCI committed more errors in grocery items’ selection and experienced less “perceived control” over the environment. Conclusion: Immersive VR was acceptable and enjoyable for older adults in both groups. Cognitive deficits could induce risky behaviors, and cause issues in the interactions with virtual items. Further studies are needed to confirm acceptance of immersive VR in individuals at risk of dementia, and to extend the results to people with more severe symptoms.
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Affiliation(s)
- Sara Arlati
- Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato, Consiglio Nazionale delle Ricerche, Lecco, Italy
- Dipartimento di Elettronica, Informatica e Bioingegneria, Politecnico di Milano, Milano, Italy
| | - Simona Gabriella Di Santo
- Laboratorio-servizio di Epidemiologia e Ricerca Clinica, IRCCS Fondazione Santa Lucia, Roma, Italy
- Dipartimento di Medicina dei Sistemi, Universitá degli Studi di Roma ‘Tor Vergata’, Facoltá di Medicina e Chirurgia, Roma, Italy
| | - Flaminia Franchini
- Laboratorio-servizio di Epidemiologia e Ricerca Clinica, IRCCS Fondazione Santa Lucia, Roma, Italy
- Dipartimento di Medicina dei Sistemi, Universitá degli Studi di Roma ‘Tor Vergata’, Facoltá di Medicina e Chirurgia, Roma, Italy
| | - Marta Mondellini
- Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato, Consiglio Nazionale delle Ricerche, Lecco, Italy
| | - Beatrice Filiputti
- Laboratorio-servizio di Epidemiologia e Ricerca Clinica, IRCCS Fondazione Santa Lucia, Roma, Italy
| | - Matilde Luchi
- Laboratorio-servizio di Epidemiologia e Ricerca Clinica, IRCCS Fondazione Santa Lucia, Roma, Italy
| | - Federica Ratto
- Laboratorio-servizio di Epidemiologia e Ricerca Clinica, IRCCS Fondazione Santa Lucia, Roma, Italy
| | - Giancarlo Ferrigno
- Dipartimento di Elettronica, Informatica e Bioingegneria, Politecnico di Milano, Milano, Italy
| | - Marco Sacco
- Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato, Consiglio Nazionale delle Ricerche, Lecco, Italy
| | - Luca Greci
- Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato, Consiglio Nazionale delle Ricerche, Milano, Italy
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Levac DE, Huber ME, Sternad D. Learning and transfer of complex motor skills in virtual reality: a perspective review. J Neuroeng Rehabil 2019; 16:121. [PMID: 31627755 PMCID: PMC6798491 DOI: 10.1186/s12984-019-0587-8] [Citation(s) in RCA: 82] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2018] [Accepted: 09/05/2019] [Indexed: 12/11/2022] Open
Abstract
The development of more effective rehabilitative interventions requires a better understanding of how humans learn and transfer motor skills in real-world contexts. Presently, clinicians design interventions to promote skill learning by relying on evidence from experimental paradigms involving simple tasks, such as reaching for a target. While these tasks facilitate stringent hypothesis testing in laboratory settings, the results may not shed light on performance of more complex real-world skills. In this perspective, we argue that virtual environments (VEs) are flexible, novel platforms to evaluate learning and transfer of complex skills without sacrificing experimental control. Specifically, VEs use models of real-life tasks that afford controlled experimental manipulations to measure and guide behavior with a precision that exceeds the capabilities of physical environments. This paper reviews recent insights from VE paradigms on motor learning into two pressing challenges in rehabilitation research: 1) Which training strategies in VEs promote complex skill learning? and 2) How can transfer of learning from virtual to real environments be enhanced? Defining complex skills by having nested redundancies, we outline findings on the role of movement variability in complex skill acquisition and discuss how VEs can provide novel forms of guidance to enhance learning. We review the evidence for skill transfer from virtual to real environments in typically developing and neurologically-impaired populations with a view to understanding how differences in sensory-motor information may influence learning strategies. We provide actionable suggestions for practicing clinicians and outline broad areas where more research is required. Finally, we conclude that VEs present distinctive experimental platforms to understand complex skill learning that should enable transfer from therapeutic practice to the real world.
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Affiliation(s)
- Danielle E Levac
- Department of Physical Therapy, Movement and Rehabilitation Sciences, Northeastern University, 407c Robinson Hall, 360 Huntington Ave, Boston, MA, 02115, USA.
| | - Meghan E Huber
- Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave, Bldg 3, Rm 143, Cambridge, MA, 02139, USA
| | - Dagmar Sternad
- Biology, Electrical and Computer Engineering, and Physics, Northeastern University, 503 Richards Hall, 360 Huntington Avenue, Boston, MA, 02118, USA
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Hasson CJ, Goodman SE. Learning to shape virtual patient locomotor patterns: internal representations adapt to exploit interactive dynamics. J Neurophysiol 2019; 121:321-335. [PMID: 30403561 PMCID: PMC6383669 DOI: 10.1152/jn.00408.2018] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 10/19/2018] [Accepted: 11/01/2018] [Indexed: 11/22/2022] Open
Abstract
This work aimed to understand the sensorimotor processes used by humans when learning how to manipulate a virtual model of locomotor dynamics. Prior research shows that when interacting with novel dynamics humans develop internal models that map neural commands to limb motion and vice versa. Whether this can be extrapolated to locomotor rehabilitation, a continuous and rhythmic activity that involves dynamically complex interactions, is unknown. In this case, humans could default to model-free strategies. These competing hypotheses were tested with a novel interactive locomotor simulator that reproduced the dynamics of hemiparetic gait. A group of 16 healthy subjects practiced using a small robotic manipulandum to alter the gait of a virtual patient (VP) that had an asymmetric locomotor pattern modeled after stroke survivors. The point of interaction was the ankle of the VP's affected leg, and the goal was to make the VP's gait symmetric. Internal model formation was probed with unexpected force channels and null force fields. Generalization was assessed by changing the target locomotor pattern and comparing outcomes with a second group of 10 naive subjects who did not practice the initial symmetric target pattern. Results supported the internal model hypothesis with aftereffects and generalization of manipulation skill. Internal models demonstrated refinements that capitalized on the natural pendular dynamics of human locomotion. This work shows that despite the complex interactive dynamics involved in shaping locomotor patterns, humans nevertheless develop and use internal models that are refined with experience. NEW & NOTEWORTHY This study aimed to understand how humans manipulate the physics of locomotion, a common task for physical therapists during locomotor rehabilitation. To achieve this aim, a novel locomotor simulator was developed that allowed participants to feel like they were manipulating the leg of a miniature virtual stroke survivor walking on a treadmill. As participants practiced improving the simulated patient's gait, they developed generalizable internal models that capitalized on the natural pendular dynamics of locomotion.
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Affiliation(s)
- Christopher J Hasson
- Neuromotor Systems Laboratory, Department of Physical Therapy, Movement, and Rehabilitation Sciences, Northeastern University , Boston, Massachusetts
- Department of Bioengineering, Northeastern University , Boston, Massachusetts
- Department of Biology, Northeastern University , Boston, Massachusetts
| | - Sarah E Goodman
- Department of Bioengineering, Northeastern University , Boston, Massachusetts
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Bazzi S, Ebert J, Hogan N, Sternad D. Stability and predictability in human control of complex objects. CHAOS (WOODBURY, N.Y.) 2018; 28:103103. [PMID: 30384626 PMCID: PMC6170195 DOI: 10.1063/1.5042090] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Previous research on movement control suggested that humans exploit stability to reduce vulnerability to internal noise and external perturbations. For interactions with complex objects, predictive control based on an internal model of body and environment is needed to preempt perturbations and instabilities due to delays. We hypothesize that stability can serve as means to render the complex dynamics of the body and the task more predictable and thereby simplify control. However, the assessment of stability in complex interactions with nonlinear and underactuated objects is challenging, as for existent stability analyses the system needs to be close to a (known) attractor. After reviewing existing methods for stability analysis of human movement, we argue that contraction theory provides a suitable approach to quantify stability or convergence in complex transient behaviors. To test its usefulness, we examined the task of carrying a cup of coffee, an object with internal degrees of freedom. A simplified model of the task, a cart with a suspended pendulum, was implemented in a virtual environment to study human control strategies. The experimental task was to transport this cart-and-pendulum on a horizontal line from rest to a target position as fast as possible. Each block of trials presented a visible perturbation, which either could be in the direction of motion or opposite to it. To test the hypothesis that humans exploit stability to overcome perturbations, the dynamic model of the free, unforced system was analyzed using contraction theory. A contraction metric was obtained by numerically solving a partial differential equation, and the contraction regions with respect to that metric were computed. Experimental results showed that subjects indeed moved through the contraction regions of the free, unforced system. This strategy attenuated the perturbations, obviated error corrections, and made the dynamics more predictable. The advantages and shortcomings of contraction analysis are discussed in the context of other stability analyses.
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Affiliation(s)
- Salah Bazzi
- Department of Biology, Northeastern University, Boston, Massachusetts 02115, USA
| | - Julia Ebert
- Department of Computer Science, Harvard University, Cambridge, Massachusetts 02138, USA
| | - Neville Hogan
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Dagmar Sternad
- Department of Biology, Northeastern University, Boston, Massachusetts 02115, USA
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6
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Shah AK, Sharp I, Hajissa E, Patton JL. Reshaping Movement Distributions With Limit-Push Robotic Training. IEEE Trans Neural Syst Rehabil Eng 2018; 26:2134-2144. [PMID: 29994313 DOI: 10.1109/tnsre.2018.2839565] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
High-cost situations need to be avoided. However, occasionally, cost may only be learned by experience. Here, we tested whether an artificially induced unstable and invisible high-cost region, a "limit-push" force field, might reshape people's motion distributions. Healthy and neurologically impaired (chronic stroke) populations attempted 600 interceptions of a projectile while holding a robot handle that could render forces to the hand. The "limit-push," in the middle of the study, pushed the hand outward unless the hand stayed within a box-shaped region. Both healthy and some stroke survivors adapted through selection of safer actions, avoiding the high-cost regions (outside the box); they stayed more inside and even kept a greater distance from the box's boundaries. This was supported by other measures that showed subjects distributed their hand movements within the box more uniformly. These effects lasted a very short time after returning to the no-force condition. Although most robotic teaching approaches focus on shifting the mean, this limit-push treatment demonstrates how both mean and variance might be reshaped in motor training and neurorehabilitation.
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7
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He K, Liang Y, Abdollahi F, Fisher Bittmann M, Kording K, Wei K. The Statistical Determinants of the Speed of Motor Learning. PLoS Comput Biol 2016; 12:e1005023. [PMID: 27606808 PMCID: PMC5015831 DOI: 10.1371/journal.pcbi.1005023] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Accepted: 06/17/2016] [Indexed: 11/18/2022] Open
Abstract
It has recently been suggested that movement variability directly increases the speed of motor learning. Here we use computational modeling of motor adaptation to show that variability can have a broad range of effects on learning, both negative and positive. Experimentally, we also find contributing and decelerating effects. Lastly, through a meta-analysis of published papers, we verify that across a wide range of experiments, movement variability has no statistical relation with learning rate. While motor learning is a complex process that can be modeled, further research is needed to understand the relative importance of the involved factors.
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Affiliation(s)
- Kang He
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
- Beijing Key Laboratory of Behavior and Mental Health, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Beijing, China
| | - You Liang
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
| | - Farnaz Abdollahi
- Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America
| | | | - Konrad Kording
- Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America
- Northwestern University, Chicago, Illinois, United States of America
| | - Kunlin Wei
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
- Beijing Key Laboratory of Behavior and Mental Health, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Beijing, China
- * E-mail:
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8
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Predictability and Robustness in the Manipulation of Dynamically Complex Objects. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2016; 957:55-77. [PMID: 28035560 DOI: 10.1007/978-3-319-47313-0_4] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Manipulation of complex objects and tools is a hallmark of many activities of daily living, but how the human neuromotor control system interacts with such objects is not well understood. Even the seemingly simple task of transporting a cup of coffee without spilling creates complex interaction forces that humans need to compensate for. Predicting the behavior of an underactuated object with nonlinear fluid dynamics based on an internal model appears daunting. Hence, this research tests the hypothesis that humans learn strategies that make interactions predictable and robust to inaccuracies in neural representations of object dynamics. The task of moving a cup of coffee is modeled with a cart-and-pendulum system that is rendered in a virtual environment, where subjects interact with a virtual cup with a rolling ball inside using a robotic manipulandum. To gain insight into human control strategies, we operationalize predictability and robustness to permit quantitative theory-based assessment. Predictability is quantified by the mutual information between the applied force and the object dynamics; robustness is quantified by the energy margin away from failure. Three studies are reviewed that show how with practice subjects develop movement strategies that are predictable and robust. Alternative criteria, common for free movement, such as maximization of smoothness and minimization of force, do not account for the observed data. As manual dexterity is compromised in many individuals with neurological disorders, the experimental paradigm and its analyses are a promising platform to gain insights into neurological diseases, such as dystonia and multiple sclerosis, as well as healthy aging.
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Clark BC, Law TD, Hong SL. Editorial: "From brain to body: the impact of nervous system declines on muscle performance in aging". Front Aging Neurosci 2015; 7:66. [PMID: 25983692 PMCID: PMC4415401 DOI: 10.3389/fnagi.2015.00066] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2015] [Accepted: 04/14/2015] [Indexed: 11/13/2022] Open
Affiliation(s)
- Brian C Clark
- Ohio Musculoskeletal and Neurological Institute, Ohio University Athens, OH, USA ; Department of Biomedical Sciences, Ohio University Athens, OH, USA ; Department of Geriatric Medicine, Ohio University Athens, OH, USA
| | - Timothy D Law
- Ohio Musculoskeletal and Neurological Institute, Ohio University Athens, OH, USA ; Department of Geriatric Medicine, Ohio University Athens, OH, USA ; Department of Family Medicine, Ohio University Athens, OH, USA
| | - S Lee Hong
- Ohio Musculoskeletal and Neurological Institute, Ohio University Athens, OH, USA ; Department of Biomedical Sciences, Ohio University Athens, OH, USA
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10
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Nasseroleslami B, Hasson CJ, Sternad D. Rhythmic manipulation of objects with complex dynamics: predictability over chaos. PLoS Comput Biol 2014; 10:e1003900. [PMID: 25340581 PMCID: PMC4207605 DOI: 10.1371/journal.pcbi.1003900] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2014] [Accepted: 09/11/2014] [Indexed: 11/19/2022] Open
Abstract
The study of object manipulation has been largely confined to discrete tasks, where accuracy, mechanical effort, or smoothness were examined to explain subjects' preferred movements. This study investigated a rhythmic manipulation task, which involved continuous interaction with a nonlinear object that led to unpredictable object behavior. Using a simplified virtual version of the task of carrying a cup of coffee, we studied how this unpredictable object behavior affected the selected strategies. The experiment was conducted in a virtual set-up, where subjects moved a cup with a ball inside, modeled by cart-and-pendulum dynamics. Inverse dynamics calculations of the system showed that performing the task with different amplitudes and relative phases required different force profiles and rendered the object's dynamics with different degrees of predictability (quantified by Mutual Information between the applied force and the cup kinematics and its sensitivity). Subjects (n = 8) oscillated the virtual cup between two targets via a robotic manipulandum, paced by a metronome at 1 Hz for 50 trials, each lasting 45 s. They were free to choose their movement amplitude and relative phase between the ball and cup. Experimental results showed that subjects increased their movement amplitudes, which rendered the interactions with the object more predictable and with lower sensitivity to the execution variables. These solutions were associated with higher average exerted force and lower object smoothness, contradicting common expectations from studies on discrete object manipulation and unrestrained movements. Instead, the findings showed that humans selected strategies with higher predictability of interaction dynamics. This finding expressed that humans seek movement strategies where force and kinematics synchronize to repeatable patterns that may require less sensorimotor information processing.
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Affiliation(s)
- Bahman Nasseroleslami
- Department of Biology, Northeastern University, Boston, Massachusetts, United States of America
- * E-mail: ,
| | - Christopher J. Hasson
- Department of Physical Therapy, Movement and Rehabilitation Sciences, Northeastern University, Boston, Massachusetts, United States of America
| | - Dagmar Sternad
- Department of Biology, Northeastern University, Boston, Massachusetts, United States of America
- Department of Electrical and Computer Engineering, Northeastern University, Boston, Massachusetts, United States of America
- Department of Physics, Northeastern University, Boston, Massachusetts, United States of America
- Center for the Interdisciplinary Research on Complex Systems, Northeastern University, Boston, Massachusetts, United States of America
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Acquisition of novel and complex motor skills: stable solutions where intrinsic noise matters less. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2014; 826:101-24. [PMID: 25330888 DOI: 10.1007/978-1-4939-1338-1_8] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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