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De Miguel-Rubio A, Gallego-Aguayo I, De Miguel-Rubio MD, Arias-Avila M, Lucena-Anton D, Alba-Rueda A. Effectiveness of the Combined Use of a Brain-Machine Interface System and Virtual Reality as a Therapeutic Approach in Patients with Spinal Cord Injury: A Systematic Review. Healthcare (Basel) 2023; 11:3189. [PMID: 38132079 PMCID: PMC10742447 DOI: 10.3390/healthcare11243189] [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: 10/26/2023] [Revised: 11/30/2023] [Accepted: 12/14/2023] [Indexed: 12/23/2023] Open
Abstract
Spinal cord injury has a major impact on both the individual and society. This damage can cause permanent loss of sensorimotor functions, leading to structural and functional changes in somatotopic regions of the spinal cord. The combined use of a brain-machine interface and virtual reality offers a therapeutic alternative to be considered in the treatment of this pathology. This systematic review aimed to evaluate the effectiveness of the combined use of virtual reality and the brain-machine interface in the treatment of spinal cord injuries. A search was performed in PubMed, Web of Science, PEDro, Cochrane Central Register of Controlled Trials, CINAHL, Scopus, and Medline, including articles published from the beginning of each database until January 2023. Articles were selected based on strict inclusion and exclusion criteria. The Cochrane Collaboration's tool was used to assess the risk of bias and the PEDro scale and SCIRE systems were used to evaluate the methodological quality of the studies. Eleven articles were selected from a total of eighty-two. Statistically significant changes were found in the upper limb, involving improvements in shoulder and upper arm mobility, and weaker muscles were strengthened. In conclusion, most of the articles analyzed used the electroencephalogram as a measurement instrument for the assessment of various parameters, and most studies have shown improvements. Nonetheless, further research is needed with a larger sample size and long-term follow-up to establish conclusive results regarding the effect size of these interventions.
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Affiliation(s)
- Amaranta De Miguel-Rubio
- Department of Nursing, Pharmacology and Physiotherapy, University of Cordoba, 14004 Cordoba, Spain; (I.G.-A.); (A.A.-R.)
| | - Ignacio Gallego-Aguayo
- Department of Nursing, Pharmacology and Physiotherapy, University of Cordoba, 14004 Cordoba, Spain; (I.G.-A.); (A.A.-R.)
| | | | - Mariana Arias-Avila
- Physical Therapy Department, Universidade Federal de São Carlos, São Paulo 13565-905, Brazil;
| | - David Lucena-Anton
- Department of Nursing and Physiotherapy, University of Cadiz, 11009 Cadiz, Spain;
| | - Alvaro Alba-Rueda
- Department of Nursing, Pharmacology and Physiotherapy, University of Cordoba, 14004 Cordoba, Spain; (I.G.-A.); (A.A.-R.)
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Bisson JA, Dupre JR, DeJong SL. Training of isometric force tracking to improve motor control of the wrist after incomplete spinal cord injury: a case study. Physiother Theory Pract 2022:1-12. [PMID: 35287525 DOI: 10.1080/09593985.2022.2049405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
OBJECTIVE Upper limb function is a high priority for people with cervical spinal cord injury (SCI). This case report describes an application of technology to activate spared neural pathways and improve wrist motor control. CASE DESCRIPTION A 73-year-old man with chronic incomplete C5 SCI completed 24 training sessions over 92 days. Each session included 2 maximal contractions, 6 test trials, and 10 training trials of a visuomotor force tracking task. The participant attempted to match a sinusoidal target force curve, using isometric wrist flexor and extensor contractions. Electromyography (EMG) and force signals were recorded. OUTCOMES Errors were elevated initially and improved with training, similarly during extension and flexion phases of the force tracking task. Improvement in both phases was associated with greater flexor activation in flexion phases and greater extensor relaxation in flexion phases. Errors were not related to EMG modulation during the extensor phases. Small improvements in active range of motion, grip force, spasticity, touch sensation, and corticospinal excitability were also observed. CONCLUSIONS Motor skill training improved motor control after incomplete SCI, within the range of residual force production capacity. Performance gains were associated with specific adjustments in muscle activation and relaxation, and increased corticospinal excitability.
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Affiliation(s)
- Jayden A Bisson
- Department of Physical Therapy and Rehabilitation Science, Roy J. And Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA, USA
| | - Jacob R Dupre
- Department of Physical Therapy and Rehabilitation Science, Roy J. And Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA, USA
| | - Stacey L DeJong
- Department of Physical Therapy and Rehabilitation Science, Roy J. And Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA, 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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Rizzoglio F, Pierella C, De Santis D, Mussa-Ivaldi F, Casadio M. A hybrid Body-Machine Interface integrating signals from muscles and motions. J Neural Eng 2020; 17:046004. [PMID: 32521522 DOI: 10.1088/1741-2552/ab9b6c] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
OBJECTIVE Body-Machine Interfaces (BoMIs) establish a way to operate a variety of devices, allowing their users to extend the limits of their motor abilities by exploiting the redundancy of muscles and motions that remain available after spinal cord injury or stroke. Here, we considered the integration of two types of signals, motion signals derived from inertial measurement units (IMUs) and muscle activities recorded with electromyography (EMG), both contributing to the operation of the BoMI. APPROACH A direct combination of IMU and EMG signals might result in inefficient control due to the differences in their nature. Accordingly, we used a nonlinear-regression-based approach to predict IMU from EMG signals, after which the predicted and actual IMU signals were combined into a hybrid control signal. The goal of this approach was to provide users with the possibility to switch seamlessly between movement and EMG control, using the BoMI as a tool for promoting the engagement of selected muscles. We tested the interface in three control modalities, EMG-only, IMU-only and hybrid, in a cohort of 15 unimpaired participants. Participants practiced reaching movements by guiding a computer cursor over a set of targets. MAIN RESULTS We found that the proposed hybrid control led to comparable performance to IMU-based control and significantly outperformed the EMG-only control. Results also indicated that hybrid cursor control was predominantly influenced by EMG signals. SIGNIFICANCE We concluded that combining EMG with IMU signals could be an efficient way to target muscle activations while overcoming the limitations of an EMG-only control.
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Affiliation(s)
- Fabio Rizzoglio
- Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145, Genoa, Italy. Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, United States of America. Shirley Ryan Ability Lab, Chicago, IL 60611, United States of America. Author to whom any correspondence should be addressed
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De Santis D, Mussa-Ivaldi FA. Guiding functional reorganization of motor redundancy using a body-machine interface. J Neuroeng Rehabil 2020; 17:61. [PMID: 32393288 PMCID: PMC7216597 DOI: 10.1186/s12984-020-00681-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Accepted: 04/01/2020] [Indexed: 01/01/2023] Open
Abstract
Background Body-machine interfaces map movements onto commands to external devices. Redundant motion signals derived from inertial sensors are mapped onto lower-dimensional device commands. Then, the device users face two problems, a) the structural problem of understanding the operation of the interface and b) the performance problem of controlling the external device with high efficiency. We hypothesize that these problems, while being distinct are connected in that aligning the space of body movements with the space encoded by the interface, i.e. solving the structural problem, facilitates redundancy resolution towards increasing efficiency, i.e. solving the performance problem. Methods Twenty unimpaired volunteers practiced controlling the movement of a computer cursor by moving their arms. Eight signals from four inertial sensors were mapped onto the two cursor’s coordinates on a screen. The mapping matrix was initialized by asking each user to perform free-form spontaneous upper-limb motions and deriving the two main principal components of the motion signals. Participants engaged in a reaching task for 18 min, followed by a tracking task. One group of 10 participants practiced with the same mapping throughout the experiment, while the other 10 with an adaptive mapping that was iteratively updated by recalculating the principal components based on ongoing movements. Results Participants quickly reduced reaching time while also learning to distribute most movement variance over two dimensions. Participants with the fixed mapping distributed movement variance over a subspace that did not match the potent subspace defined by the interface map. In contrast, participant with the adaptive map reduced the difference between the two subspaces, resulting in a smaller amount of arm motions distributed over the null space of the interface map. This, in turn, enhanced movement efficiency without impairing generalization from reaching to tracking. Conclusions Aligning the potent subspace encoded by the interface map to the user’s movement subspace guides redundancy resolution towards increasing movement efficiency, with implications for controlling assistive devices. In contrast, in the pursuit of rehabilitative goals, results would suggest that the interface must change to drive the statistics of user’s motions away from the established pattern and toward the engagement of movements to be recovered. Trial registration ClinicalTrials.gov, NCT01608438, Registered 16 April 2012.
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Affiliation(s)
- Dalia De Santis
- Northwestern University and the Shirley Ryan AbilityLab, Chicago, IL, USA. .,Fondazione Istituto Italiano di Tecnologia, Genoa, Italy.
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Heald E, Kilgore K, Hart R, Moss C, Peckham PH. Myoelectric signal from below the level of spinal cord injury as a command source for an implanted upper extremity neuroprosthesis - a case report. J Neuroeng Rehabil 2019; 16:100. [PMID: 31375143 PMCID: PMC6679451 DOI: 10.1186/s12984-019-0571-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Accepted: 07/29/2019] [Indexed: 12/04/2022] Open
Abstract
Implanted motor neuroprostheses offer significant restoration of function for individuals with spinal cord injury. Providing adequate user control for these devices is a challenge but is crucial for successful performance. Electromyographic (EMG) signals can serve as effective control sources, but the number of above-injury muscles suitable to provide EMG-based control signals is very limited. Previous work has shown the presence of below-injury volitional myoelectric signals even in subjects diagnosed with motor complete spinal cord injury. In this case report, we present a demonstration of a hand grasp neuroprosthesis being controlled by a user with a C6 level, motor complete injury through EMG signals from their toe flexor. These signals were successfully translated into a functional grasp output, which performed similarly to the participant’s usual shoulder position control in a grasp-release functional test. This proof-of-concept demonstrates the potential for below-injury myoelectric activity to serve as a novel form of neuroprosthesis control.
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Affiliation(s)
- Elizabeth Heald
- Dept. of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Wickenden Building, Cleveland, OH, 44106, USA
| | - Kevin Kilgore
- Dept. of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Wickenden Building, Cleveland, OH, 44106, USA.,Louis Stokes Veterans Affairs Medical Center, Cleveland, OH, USA.,MetroHealth Medical Center, Cleveland, OH, USA
| | - Ronald Hart
- Louis Stokes Veterans Affairs Medical Center, Cleveland, OH, USA
| | - Christa Moss
- Dept. of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Wickenden Building, Cleveland, OH, 44106, USA
| | - P Hunter Peckham
- Dept. of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Wickenden Building, Cleveland, OH, 44106, USA. .,MetroHealth Medical Center, Cleveland, OH, USA.
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Beckerle P, Castellini C, Lenggenhager B. Robotic interfaces for cognitive psychology and embodiment research: A research roadmap. WILEY INTERDISCIPLINARY REVIEWS. COGNITIVE SCIENCE 2018; 10:e1486. [PMID: 30485732 DOI: 10.1002/wcs.1486] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Revised: 10/03/2018] [Accepted: 10/20/2018] [Indexed: 11/09/2022]
Abstract
Advanced human-machine interfaces render robotic devices applicable to study and enhance human cognition. This turns robots into formidable neuroscientific tools to study processes such as the adaptation between a human operator and the operated robotic device and how this adaptation modulates human embodiment and embodied cognition. We analyze bidirectional human-machine interface (bHMI) technologies for transparent information transfer between a human and a robot via efferent and afferent channels. Even if such interfaces have a tremendous positive impact on feedback loops and embodiment, advanced bHMIs face immense technological challenges. We critically discuss existing technical approaches, mainly focusing on haptics, and suggest extensions thereof, which include other aspects of touch. Moreover, we point out other potential constraints such as limited functionality, semi-autonomy, intent-detection, and feedback methods. From this, we develop a research roadmap to guide understanding and development of bidirectional human-machine interfaces that enable robotic experiments to empirically study the human mind and embodiment. We conclude the integration of dexterous control and multisensory feedback to be a promising roadmap towards future robotic interfaces, especially regarding applications in the cognitive sciences. This article is categorized under: Computer Science > Robotics Psychology > Motor Skill and Performance Neuroscience > Plasticity.
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Affiliation(s)
- Philipp Beckerle
- Elastic Lightweight Robotics Group, Robotics Research Institute, Technische Universität Dortmund, Dortmund, Germany.,Institute for Mechatronic Systems in Mechanical Engineering, Technische Universität Darmstadt, Darmstadt, Germany
| | - Claudio Castellini
- Institut of Robotics and Mechatronics, DLR German Aerospace Center, Oberpfaffenhofen, Germany
| | - Bigna Lenggenhager
- Cognitive Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland
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