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Villalba MM, Silva NRS, Fujita RA, Fogagnolo C, Gomes MM, Pacheco MM. Muscle Recruitment Strategies in a Redundant Task: Age Differences Through Network Analyses. J Mot Behav 2024:1-15. [PMID: 38565202 DOI: 10.1080/00222895.2024.2332767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 03/12/2024] [Indexed: 04/04/2024]
Abstract
There are numerous studies comparing young and old adults in terms of muscle coordination in standard tasks (e.g., walking, reaching) and small variations of them. These tasks might hide differences: individuals would converge to similar behavior as they practice these throughout life. Also, we are unaware of studies that considered the muscle recruitment nested dynamics. For this reason, our study evaluated how young and old women coordinate and control the movement system while performing an unusual redundant motor control task through the network physiology approach. We acquired electromyographic signals from nine leg muscles of the dominant and non-dominant limbs during maximum voluntary isometric contractions (knee extension and flexion) and co-contraction bouts. Our results showed that young participants presented higher peak torque output, with similar EMG variability, compared to older participants. Considering firing rate frequencies, old and young women demonstrated different traits for network clustering and efficiency for the task. Age seems to affect muscle coordination at higher frequencies, even with a similar number of muscle synergies, indicating that younger women might have more integrated synergies than older women. The findings also point to differential muscle coordination adaptability.
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Affiliation(s)
- Marina M Villalba
- Biomechanics and Motor Control Laboratory, School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
- Ribeirão Preto College of Nursing, University of São Paulo, Ribeirão Preto, Brazil
| | - Nilson R S Silva
- Biomechanics and Motor Control Laboratory, School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
- Department of Mechanical and Biomedical Engineering, Mechanical Adaptations Laboratory, Boise State University, Boise, USA
| | - Rafael A Fujita
- Biomechanics and Motor Control Laboratory, School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
- Ribeirão Preto College of Nursing, University of São Paulo, Ribeirão Preto, Brazil
| | - Carol Fogagnolo
- Biomechanics and Motor Control Laboratory, School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Matheus M Gomes
- Biomechanics and Motor Control Laboratory, School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
- Ribeirão Preto College of Nursing, University of São Paulo, Ribeirão Preto, Brazil
| | - Matheus M Pacheco
- Biomechanics and Motor Control Laboratory, School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
- Faculty of Sport, LABIOMEP, CIFI2D, University of Porto, Porto, Portugal
- Department of Physical Education, GEDEM, Federal University of Rondônia, Porto Velho, Brazil
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Development of a Vision-Guided Shared-Control System for Assistive Robotic Manipulators. SENSORS 2022; 22:s22124351. [PMID: 35746131 PMCID: PMC9228253 DOI: 10.3390/s22124351] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 05/26/2022] [Accepted: 06/01/2022] [Indexed: 02/04/2023]
Abstract
Assistive robotic manipulators (ARMs) provide a potential solution to mitigating the difficulties and lost independence associated with manipulation deficits in individuals with upper-limb impairments. However, achieving efficient control of an ARM can be a challenge due to the multiple degrees of freedom (DoFs) of an ARM that need to be controlled. This study describes the development of a vision-guided shared-control (VGS) system and how it is applied to a multi-step drinking task. The VGS control allows the user to control the gross motion of the ARM via teleoperation and commands the ARM to autonomously perform fine manipulation. A bench-top test of the autonomous actions showed that success rates for different subtasks ranged from 80% to 100%. An evaluation with three test pilots showed that the overall task performance, in terms of success rate, task completion time, and joystick mode-switch frequency, was better with VGS than with teleoperation. Similar trends were observed with a case participant with a spinal cord injury. While his performance was better and he perceived a smaller workload with VGS, his perceived usability for VGS and teleoperation was similar. More work is needed to further improve and test VGS on participants with disabilities.
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Lee MH, Patel P, Ranganathan R. Children are suboptimal in adapting motor exploration to task dimensionality during motor learning. Neurosci Lett 2021; 770:136355. [PMID: 34808270 DOI: 10.1016/j.neulet.2021.136355] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 10/19/2021] [Accepted: 11/15/2021] [Indexed: 11/19/2022]
Abstract
Motor learning in novel tasks requires exploration to find the appropriate coordination patterns to perform the task. Prior work has shown that compared to adults, children show limited exploration when learning a task that required using upper body movements to control a 2D cursor on a screen. Here, by changing the task dimensionality to 1D, we examined two competing hypotheses: whether children show limited exploration as a general strategy, or whether children are suboptimal in adapting their exploration to task dimensionality. Two groups of children (9- and 12-year olds), and one group of adults learned a virtual task that involved learning to control a cursor on the screen using movements of the upper body. Participants practiced the task for a single session with a total of 232 reaching movements. Results showed that 9-year olds show worse task performance relative to adults, as indicated by higher movement times and path lengths. Analysis of the coordination strategies indicated that both groups of children showed lower variance along the first principal component, suggesting that they had greater exploration than adults which was suboptimal for the 1D task. These results suggest that motor learning in children is characterized not by limited exploration per se, but by a limited adaptability in matching motor exploration to task dimensionality.
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Affiliation(s)
- Mei-Hua Lee
- Department of Kinesiology, Michigan State University, East Lansing, MI, USA.
| | - Priya Patel
- Department of Kinesiology, Michigan State University, East Lansing, MI, USA
| | - Rajiv Ranganathan
- Department of Kinesiology, Michigan State University, East Lansing, MI, USA
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Pierella C, Galofaro E, De Luca A, Losio L, Gamba S, Massone A, Mussa-Ivaldi FA, Casadio M. Recovery of Distal Arm Movements in Spinal Cord Injured Patients with a Body-Machine Interface: A Proof-of-Concept Study. SENSORS (BASEL, SWITZERLAND) 2021; 21:2243. [PMID: 33807007 PMCID: PMC8004832 DOI: 10.3390/s21062243] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 03/18/2021] [Accepted: 03/19/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND The recovery of upper limb mobility and functions is essential for people with cervical spinal cord injuries (cSCI) to maximize independence in daily activities and ensure a successful return to normality. The rehabilitative path should include a thorough neuromotor evaluation and personalized treatments aimed at recovering motor functions. Body-machine interfaces (BoMI) have been proven to be capable of harnessing residual joint motions to control objects like computer cursors and virtual or physical wheelchairs and to promote motor recovery. However, their therapeutic application has still been limited to shoulder movements. Here, we expanded the use of BoMI to promote the whole arm's mobility, with a special focus on elbow movements. We also developed an instrumented evaluation test and a set of kinematic indicators for assessing residual abilities and recovery. METHODS Five inpatient cSCI subjects (four acute, one chronic) participated in a BoMI treatment complementary to their standard rehabilitative routine. The subjects wore a BoMI with sensors placed on both proximal and distal arm districts and practiced for 5 weeks. The BoMI was programmed to promote symmetry between right and left arms use and the forearms' mobility while playing games. To evaluate the effectiveness of the treatment, the subjects' kinematics were recorded while performing an evaluation test that involved functional bilateral arms movements, before, at the end, and three months after training. RESULTS At the end of the training, all subjects learned to efficiently use the interface despite being compelled by it to engage their most impaired movements. The subjects completed the training with bilateral symmetry in body recruitment, already present at the end of the familiarization, and they increased the forearm activity. The instrumental evaluation confirmed this. The elbow motion's angular amplitude improved for all subjects, and other kinematic parameters showed a trend towards the normality range. CONCLUSION The outcomes are preliminary evidence supporting the efficacy of the proposed BoMI as a rehabilitation tool to be considered for clinical practice. It also suggests an instrumental evaluation protocol and a set of indicators to assess and evaluate motor impairment and recovery in cSCI.
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Affiliation(s)
- Camilla Pierella
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genova, 16132 Genoa, Italy
- Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genoa, 16145 Genoa, Italy; (E.G.); (A.D.L.)
- Department of Physiology, Northwestern University, Chicago, IL 60611, USA;
- Shirley Ryan Ability Lab, Chicago, IL 60611, USA
| | - Elisa Galofaro
- Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genoa, 16145 Genoa, Italy; (E.G.); (A.D.L.)
- Assistive Robotics and Interactive Exosuits (ARIES) Lab, Institute of Computer Engineering (ZITI), University of Heidelberg, 69117 Heidelberg, Germany
| | - Alice De Luca
- Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genoa, 16145 Genoa, Italy; (E.G.); (A.D.L.)
- Movendo Technology, 16128 Genoa, Italy
- Recovery and Functional Reeducation Unit, Santa Corona Hospital, ASL2 Savonese, 17027 Pietra Ligure, Italy
| | - Luca Losio
- S.C. Unità Spinale Unipolare, Santa Corona Hospital, ASL2 Savonese, 17027 Pietra Ligure, Italy; (L.L.); (S.G.); (A.M.)
- Italian Spinal Cord Laboratory (SCIL), 17027 Pietra Ligure, Italy
| | - Simona Gamba
- S.C. Unità Spinale Unipolare, Santa Corona Hospital, ASL2 Savonese, 17027 Pietra Ligure, Italy; (L.L.); (S.G.); (A.M.)
- Italian Spinal Cord Laboratory (SCIL), 17027 Pietra Ligure, Italy
| | - Antonino Massone
- S.C. Unità Spinale Unipolare, Santa Corona Hospital, ASL2 Savonese, 17027 Pietra Ligure, Italy; (L.L.); (S.G.); (A.M.)
- Italian Spinal Cord Laboratory (SCIL), 17027 Pietra Ligure, Italy
| | - Ferdinando A. Mussa-Ivaldi
- Department of Physiology, Northwestern University, Chicago, IL 60611, USA;
- Shirley Ryan Ability Lab, Chicago, IL 60611, USA
- Department of Physical Medicine and Rehabilitation, Northwestern University, Evanston, IL 60208, USA
- Department of Biomedical Engineering, Northwestern University, Evanston, IL 60208, USA
| | - Maura Casadio
- Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genoa, 16145 Genoa, Italy; (E.G.); (A.D.L.)
- Department of Physiology, Northwestern University, Chicago, IL 60611, USA;
- Italian Spinal Cord Laboratory (SCIL), 17027 Pietra Ligure, Italy
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Controlling a robotic arm for functional tasks using a wireless head-joystick: A case study of a child with congenital absence of upper and lower limbs. PLoS One 2020; 15:e0226052. [PMID: 32756553 PMCID: PMC7406178 DOI: 10.1371/journal.pone.0226052] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 06/29/2020] [Indexed: 11/19/2022] Open
Abstract
Children with movement impairments needing assistive devices for activities of daily living often require novel methods for controlling these devices. Body-machine interfaces, which rely on body movements, are particularly well-suited for children as they are non-invasive and have high signal-to-noise ratios. Here, we examined the use of a head-joystick to enable a child with congenital absence of all four limbs to control a seven degree-of-freedom robotic arm. Head movements were measured with a wireless inertial measurement unit and used to control a robotic arm to perform two functional tasks-a drinking task and a block stacking task. The child practiced these tasks over multiple sessions; a control participant performed the same tasks with a manual joystick. Our results showed that the child was able to successfully perform both tasks, with movement times decreasing by ~40-50% over 6-8 sessions of training. The child's performance with the head-joystick was also comparable to the control participant using a manual joystick. These results demonstrate the potential of using head movements for the control of high degree-of-freedom tasks in children with limited movement repertoire.
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Day KA, Bastian AJ. Providing low-dimensional feedback of a high-dimensional movement allows for improved performance of a skilled walking task. Sci Rep 2019; 9:19814. [PMID: 31875040 PMCID: PMC6930294 DOI: 10.1038/s41598-019-56319-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 11/30/2019] [Indexed: 12/28/2022] Open
Abstract
Learning a skilled movement often requires changing multiple dimensions of movement in a coordinated manner. Serial training is one common approach to learning a new movement pattern, where each feature is learned in isolation from the others. Once one feature is learned, we move on to the next. However, when learning a complex movement pattern, serial training is not only laborious but can also be ineffective. Often, movement features are linked such that they cannot simply be added together as we progress through training. Thus, the ability to learn multiple features in parallel could make training faster and more effective. When using visual feedback as the tool for changing movement, however, such parallel training may increase the attentional load of training and impair performance. Here, we developed a novel visual feedback system that uses principal component analysis to weight four features of movement to create a simple one-dimensional 'summary' of performance. We used this feedback to teach healthy, young participants a modified walking pattern and compared their performance to those who received four concurrent streams of visual information to learn the same goal walking pattern. We demonstrated that those who used the principal component-based visual feedback improved their performance faster and to a greater extent compared to those who received concurrent feedback of all features. These results suggest that our novel principal component-based visual feedback provides a method for altering multiple features of movement toward a prescribed goal in an intuitive, low-dimensional manner.
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Affiliation(s)
- Kevin A Day
- Center for Movement Studies, Kennedy Krieger Institute, Baltimore, MD, 21205, USA
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Amy J Bastian
- Center for Movement Studies, Kennedy Krieger Institute, Baltimore, MD, 21205, USA.
- Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
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Online and offline contributions to motor learning change with practice, but are similar across development. Exp Brain Res 2019; 237:2865-2873. [PMID: 31468063 DOI: 10.1007/s00221-019-05639-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2019] [Accepted: 08/23/2019] [Indexed: 10/26/2022]
Abstract
Children show motor learning deficits relative to adults across a diverse range of tasks. One mechanism that has been proposed to underlie these differences is the contribution of online and offline components to overall learning; however, these tasks have almost focused exclusively on sequence learning paradigms which are characterized by performance gains in the offline phase. Here, we examined the role of online and offline learning in a novel motor task which was characterized by warm-up decrement, i.e., a performance loss, during the offline phase. In particular, using a relatively extended practice period, we examined if differences between children and adults persist across relatively long practice periods, and if the contribution of online and offline learning is affected by age and by practice itself. Two groups of children, 8-10 years and 11-13 years old, and one group of young adults (N = 30, n = 10/group) learned a novel task that required control of upper body movements to control a cursor on a screen. Participants learned the task over 5 days and we measured movement time as the primary task performance variable. Consistent with prior results, we found that 8-10 year olds had longer movement times compared to both 11-13 year olds and adults. We also found distinct changes in online and offline learning with practice; the amount of online learning decreased with practice, whereas offline learning was relatively stable across practice. However, there was no detectable effect of age group on either online or offline learning. These results suggest that age-related differences in learning among children 8-10 years old are persistent even after extended practice but are not necessarily accounted for by differences in online and offline learning.
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