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Allen JR, Karri SR, Yang C, Stoykov ME. Spinal Cord Stimulation for Poststroke Hemiparesis: A Scoping Review. Am J Occup Ther 2024; 78:7802180220. [PMID: 38477681 PMCID: PMC11017736 DOI: 10.5014/ajot.2024.050533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2024] Open
Abstract
IMPORTANCE Spinal cord stimulation (SCS) is a neuromodulation technique that can improve paresis in individuals with spinal cord injury. SCS is emerging as a technique that can address upper and lower limb hemiparesis. Little is understood about its effectiveness with the poststroke population. OBJECTIVE To summarize the evidence for SCS after stroke and any changes in upper extremity and lower extremity motor function. DATA SOURCES PubMed, Web of Science, Embase, and CINAHL. The reviewers used hand searches and reference searches of retrieved articles. There were no limitations regarding publication year. STUDY SELECTION AND DATA COLLECTION This review followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. The inclusion and exclusion criteria included a broad range of study characteristics. Studies were excluded if the intervention did not meet the definition of SCS intervention, used only animals or healthy participants, did not address upper or lower limb motor function, or examined neurological conditions other than stroke. FINDINGS Fourteen articles met the criteria for this review. Seven studies found a significant improvement in motor function in groups receiving SCS. CONCLUSIONS AND RELEVANCE Results indicate that SCS may provide an alternative means to improve motor function in the poststroke population. Plain-Language Summary: The results of this study show that spinal cord stimulation may provide an alternative way to improve motor function after stroke. Previous neuromodulation methods have targeted the impaired supraspinal circuitry after stroke. Although downregulated, spinal cord circuitry is largely intact and offers new possibilities for motor recovery.
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Affiliation(s)
- Jonathan R Allen
- Jonathan R. Allen, OTD, OTR/L, is Occupational Therapist, Corewell Health, Grand Rapids, MI. At the time of the study, Allen was Doctoral Student, Department of Occupational Therapy, College of Health Sciences, University of Michigan-Flint;
| | - Swathi R Karri
- Swathi R. Karri, is Osteopathic Medical Student II, Chicago College of Osteopathic Medicine, Midwestern University, Downers Grove, IL
| | - Chen Yang
- Chen Yang, PhD, is Postdoctoral Fellow, Max Näder Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, IL, and Postdoctoral Fellow, Physical Medicine & Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Mary Ellen Stoykov
- Mary Ellen Stoykov, PhD, OTR/L, is Research Scientist, Arms + Hands Lab, Shirley Ryan AbilityLab, Chicago, IL, and Research Associate Professor, Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, IL
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Rizvi A, Parveen S, Bazigha F, Noohu MM. Effect of transcranial direct current stimulation in combination with robotic therapy in upper limb impairments in people with stroke: a systematic review. THE EGYPTIAN JOURNAL OF NEUROLOGY, PSYCHIATRY AND NEUROSURGERY 2023. [DOI: 10.1186/s41983-023-00640-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/30/2023] Open
Abstract
Abstract
Background
Stroke is a devastating condition, which not only affects patients’ activity, but also is a primary reason for the psychosocial impact on them, their caregivers, and the healthcare system. Transcranial direct current stimulation (tDCS) modulates cortical activity, encouraging neuro-modulation and motor recovery in stroke rehabilitation. Robotic therapy (RT) provides repetitive, high-intensity, interactive, task-specific intervention and can measure changes while providing feedback to people with stroke.
Objectives
This study aimed to evaluate and summarize the scientific literature systematically to investigate the combined effect of tDCS and RT in patients with stroke.
Methods
Four databases (MEDLINE, Web of Science, ScienceDirect, & PEDro) were searched for clinical trials investigating the effect of RT and tDCS in stroke patients with upper limb impairment. PEDro scale was used for the quality assessment of included studies.
Results
The search yielded 208 articles. A total of 213 patients with stroke who had upper limb impairment were studied. In the majority of the trials, RT combined with tDCS lead to positive improvement in various measures of upper limb function and spasticity.
Conclusions
RT along with tDCS is an effective mode of rehabilitation, although no additional effects of tDCS plus RT in comparison with RT alone were reported. Large, robust studies are needed, so that health care providers and researchers can make better decisions about merging tDCS and RT in stroke rehabilitation settings in the future.
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Belkacem AN, Jamil N, Khalid S, Alnajjar F. On closed-loop brain stimulation systems for improving the quality of life of patients with neurological disorders. Front Hum Neurosci 2023; 17:1085173. [PMID: 37033911 PMCID: PMC10076878 DOI: 10.3389/fnhum.2023.1085173] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 03/06/2023] [Indexed: 04/11/2023] Open
Abstract
Emerging brain technologies have significantly transformed human life in recent decades. For instance, the closed-loop brain-computer interface (BCI) is an advanced software-hardware system that interprets electrical signals from neurons, allowing communication with and control of the environment. The system then transmits these signals as controlled commands and provides feedback to the brain to execute specific tasks. This paper analyzes and presents the latest research on closed-loop BCI that utilizes electric/magnetic stimulation, optogenetic, and sonogenetic techniques. These techniques have demonstrated great potential in improving the quality of life for patients suffering from neurodegenerative or psychiatric diseases. We provide a comprehensive and systematic review of research on the modalities of closed-loop BCI in recent decades. To achieve this, the authors used a set of defined criteria to shortlist studies from well-known research databases into categories of brain stimulation techniques. These categories include deep brain stimulation, transcranial magnetic stimulation, transcranial direct-current stimulation, transcranial alternating-current stimulation, and optogenetics. These techniques have been useful in treating a wide range of disorders, such as Alzheimer's and Parkinson's disease, dementia, and depression. In total, 76 studies were shortlisted and analyzed to illustrate how closed-loop BCI can considerably improve, enhance, and restore specific brain functions. The analysis revealed that literature in the area has not adequately covered closed-loop BCI in the context of cognitive neural prosthetics and implanted neural devices. However, the authors demonstrate that the applications of closed-loop BCI are highly beneficial, and the technology is continually evolving to improve the lives of individuals with various ailments, including those with sensory-motor issues or cognitive deficiencies. By utilizing emerging techniques of stimulation, closed-loop BCI can safely improve patients' cognitive and affective skills, resulting in better healthcare outcomes.
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Affiliation(s)
- Abdelkader Nasreddine Belkacem
- Department of Computer and Network Engineering, College of Information Technology, UAE University, Al-Ain, United Arab Emirates
- *Correspondence: Abdelkader Nasreddine Belkacem
| | - Nuraini Jamil
- Department of Computer Science and Software Engineering, College of Information Technology, UAE University, Al-Ain, United Arab Emirates
| | - Sumayya Khalid
- Department of Computer Science and Software Engineering, College of Information Technology, UAE University, Al-Ain, United Arab Emirates
| | - Fady Alnajjar
- Department of Computer Science and Software Engineering, College of Information Technology, UAE University, Al-Ain, United Arab Emirates
- Center for Brain Science, RIKEN, Saitama, Japan
- Fady Alnajjar
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Selamat SNS, Che Me R, Ahmad Ainuddin H, Salim MSF, Ramli HR, Romli MH. The Application of Technological Intervention for Stroke Rehabilitation in Southeast Asia: A Scoping Review With Stakeholders' Consultation. Front Public Health 2022; 9:783565. [PMID: 35198531 PMCID: PMC8858807 DOI: 10.3389/fpubh.2021.783565] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Accepted: 12/31/2021] [Indexed: 01/03/2023] Open
Abstract
Background The technological intervention is considered as an adjunct to the conventional therapies applied in the rehabilitation session. In most high-income countries, technology has been widely used in assisting stroke survivors to undergo their treatments. However, technology use is still lacking in Southeast Asia, especially in middle- and low-income countries. This scoping review identifies and summarizes the technologies and related gaps available in Southeast Asia pertaining to stroke rehabilitation. Methods The JBI manual for evidence synthesis was used to conduct a scoping study. Until September 2021, an electronic search was performed using four databases (Medline, CINAHL, Scopus, ASEAN Citation Index). Only the studies that were carried out in Southeast Asia were chosen. Results Forty-one articles were chosen in the final review from 6,873 articles found during the initial search. Most of the studies reported the implementation of technological intervention combined with conventional therapies in stroke rehabilitation. Advanced and simple technologies were found such as robotics, virtual reality, telerehabilitation, motion capture, assistive devices, and mobility training from Singapore, Thailand, Malaysia, and Indonesia. The majority of the studies show that technological interventions can enhance the recovery period of stroke survivors. The consultation session suggested that the technological interventions should facilitate the needs of the survivors, caregivers, and practitioners during the rehabilitation. Conclusions The integration of technology into conventional therapies has shown a positive outcome and show significant improvement during stroke recovery. Future studies are recommended to investigate the potential of home-based technological intervention and lower extremities.
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Affiliation(s)
- Siti Nur Suhaidah Selamat
- Department of Industrial Design, Faculty of Design and Architecture, Universiti Putra Malaysia, Seri Kembangan, Malaysia
| | - Rosalam Che Me
- Department of Industrial Design, Faculty of Design and Architecture, Universiti Putra Malaysia, Seri Kembangan, Malaysia
- Malaysian Research Institute on Ageing, Universiti Putra Malaysia, Seri Kembangan, Malaysia
- *Correspondence: Rosalam Che Me
| | - Husna Ahmad Ainuddin
- Department of Rehabilitation Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Seri Kembangan, Malaysia
- Centre of Occupational Therapy Studies, Faculty of Health Sciences, Universiti Teknologi MARA Selangor, Shah Alam, Malaysia
| | - Mazatulfazura S. F. Salim
- Malaysian Research Institute on Ageing, Universiti Putra Malaysia, Seri Kembangan, Malaysia
- Department of Rehabilitation Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Seri Kembangan, Malaysia
- Department of Rehabilitation Medicine, Hospital Pengajar, Universiti Putra Malaysia, Seri Kembangan, Malaysia
| | - Hafiz Rashidi Ramli
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Seri Kembangan, Malaysia
| | - Muhammad Hibatullah Romli
- Malaysian Research Institute on Ageing, Universiti Putra Malaysia, Seri Kembangan, Malaysia
- Department of Rehabilitation Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Seri Kembangan, Malaysia
- Department of Rehabilitation Medicine, Hospital Pengajar, Universiti Putra Malaysia, Seri Kembangan, Malaysia
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Motor Imagery-Based Brain-Computer Interface Combined with Multimodal Feedback to Promote Upper Limb Motor Function after Stroke: A Preliminary Study. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2021; 2021:1116126. [PMID: 34777531 PMCID: PMC8580676 DOI: 10.1155/2021/1116126] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 10/11/2021] [Indexed: 01/21/2023]
Abstract
Background Recently, the brain-computer interface (BCI) has seen rapid development, which may promote the recovery of motor function in chronic stroke patients. Methods Twelve stroke patients with severe upper limb and hand motor impairment were enrolled and randomly assigned into two groups: motor imagery (MI)-based BCI training with multimodal feedback (BCI group, n = 7) and classical motor imagery training (control group, n = 5). Motor function and electrophysiology were evaluated before and after the intervention. The Fugl-Meyer assessment-upper extremity (FMA-UE) is the primary outcome measure. Secondary outcome measures include an increase in wrist active extension or surface electromyography (the amplitude and cocontraction of extensor carpi radialis during movement), the action research arm test (ARAT), the motor status scale (MSS), and Barthel index (BI). Time-frequency analysis and power spectral analysis were used to reflect the electroencephalogram (EEG) change before and after the intervention. Results Compared with the baseline, the FMA-UE score increased significantly in the BCI group (p = 0.006). MSS scores improved significantly in both groups, while ARAT did not improve significantly. In addition, before the intervention, all patients could not actively extend their wrists or just had muscle contractions. After the intervention, four patients regained the ability to extend their paretic wrists (two in each group). The amplitude and area under the curve of extensor carpi radialis improved to some extent, but there was no statistical significance between the groups. Conclusion MI-based BCI combined with sensory and visual feedback might improve severe upper limb and hand impairment in chronic stroke patients, showing the potential for application in rehabilitation medicine.
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Kruse A, Suica Z, Taeymans J, Schuster-Amft C. Effect of brain-computer interface training based on non-invasive electroencephalography using motor imagery on functional recovery after stroke - a systematic review and meta-analysis. BMC Neurol 2020; 20:385. [PMID: 33092554 PMCID: PMC7584076 DOI: 10.1186/s12883-020-01960-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 10/14/2020] [Indexed: 01/25/2023] Open
Abstract
Background Training with brain-computer interface (BCI) technology in the rehabilitation of patients after a stroke is rapidly developing. Numerous RCT investigated the effects of BCI training (BCIT) on recovery of motor and brain function in patients after stroke. Methods A systematic literature search was performed in Medline, IEEE Xplore Digital Library, Cochrane library, and Embase in July 2018 and was repeated in March 2019. RCT or controlled clinical trials that included BCIT for improving motor and brain recovery in patients after a stroke were identified. Data were meta-analysed using the random-effects model. Standardized mean difference (SMD) with 95% confidence (95%CI) and 95% prediction interval (95%PI) were calculated. A meta-regression was performed to evaluate the effects of covariates on the pooled effect-size. Results In total, 14 studies, including 362 patients after ischemic and hemorrhagic stroke (cortical, subcortical, 121 females; mean age 53.0+/− 5.8; mean time since stroke onset 15.7+/− 18.2 months) were included. Main motor recovery outcome measure used was the Fugl-Meyer Assessment. Quantitative analysis showed that a BCI training compared to conventional therapy alone in patients after stroke was effective with an SMD of 0.39 (95%CI: 0.17 to 0.62; 95%PI of 0.13 to 0.66) for motor function recovery of the upper extremity. An SMD of 0.41 (95%CI: − 0.29 to 1.12) for motor function recovery of the lower extremity was found. BCI training enhanced brain function recovery with an SMD of 1.11 (95%CI: 0.64 to 1.59; 95%PI ranging from 0.33 to 1.89). Covariates such as training duration, impairment level of the upper extremity, and the combination of both did not show significant effects on the overall pooled estimate. Conclusion This meta-analysis showed evidence that BCI training added to conventional therapy may enhance motor functioning of the upper extremity and brain function recovery in patients after a stroke. We recommend a standardised evaluation of motor imagery ability of included patients and the assessment of brain function recovery should consider neuropsychological aspects (attention, concentration). Further influencing factors on motor recovery due to BCI technology might consider factors such as age, lesion type and location, quality of performance of motor imagery, or neuropsychological aspects. Trial Registration PROSPERO registration: CRD42018105832. Supplementary information Supplementary information accompanies this paper at 10.1186/s12883-020-01960-5.
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Affiliation(s)
- Antje Kruse
- Department of Health Professions, Bern University Applied Science, Schwarztorstrasse 48, 3007, Bern, Switzerland.,Private Practice, Baslerstrasse 60, 4102, Binningen, Switzerland
| | - Zorica Suica
- Research Department, Reha Rheinfelden, Salinenstrasse 98, 4310, Rheinfelden, Switzerland
| | - Jan Taeymans
- Department of Health Professions, Bern University Applied Science, Schwarztorstrasse 48, 3007, Bern, Switzerland.,Vrije Universiteit Brussel, Pleinlaan 2, 1050, Brussels, Belgium
| | - Corina Schuster-Amft
- Research Department, Reha Rheinfelden, Salinenstrasse 98, 4310, Rheinfelden, Switzerland. .,Department of Engineering and Information Technology, Pestalozzistrasse 20, 3401, Burgdorf, Switzerland. .,Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320 B, 4052, Basel, Switzerland.
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Chew E, Teo WP, Tang N, Ang KK, Ng YS, Zhou JH, Teh I, Phua KS, Zhao L, Guan C. Using Transcranial Direct Current Stimulation to Augment the Effect of Motor Imagery-Assisted Brain-Computer Interface Training in Chronic Stroke Patients-Cortical Reorganization Considerations. Front Neurol 2020; 11:948. [PMID: 32973672 PMCID: PMC7481473 DOI: 10.3389/fneur.2020.00948] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 07/22/2020] [Indexed: 12/29/2022] Open
Abstract
Introduction: Transcranial direct current stimulation (tDCS) has been shown to modulate cortical plasticity, enhance motor learning and post-stroke upper extremity motor recovery. It has also been demonstrated to facilitate activation of brain-computer interface (BCI) in stroke patients. We had previously demonstrated that BCI-assisted motor imagery (MI-BCI) can improve upper extremity impairment in chronic stroke participants. This study was carried out to investigate the effects of priming with tDCS prior to MI-BCI training in chronic stroke patients with moderate to severe upper extremity paresis and to investigate the cortical activity changes associated with training. Methods: This is a double-blinded randomized clinical trial. Participants were randomized to receive 10 sessions of 20-min 1 mA tDCS or sham-tDCS before MI-BCI, with the anode applied to the ipsilesional, and the cathode to the contralesional primary motor cortex (M1). Upper extremity sub-scale of the Fugl-Meyer Assessment (UE-FM) and corticospinal excitability measured by transcranial magnetic stimulation (TMS) were assessed before, after and 4 weeks after intervention. Results: Ten participants received real tDCS and nine received sham tDCS. UE-FM improved significantly in both groups after intervention. Of those with unrecordable motor evoked potential (MEP-) to the ipsilesional M1, significant improvement in UE-FM was found in the real-tDCS group, but not in the sham group. Resting motor threshold (RMT) of ipsilesional M1 decreased significantly after intervention in the real-tDCS group. Short intra-cortical inhibition (SICI) in the contralesional M1 was reduced significantly following intervention in the sham group. Correlation was found between baseline UE-FM score and changes in the contralesional SICI for all, as well as between changes in UE-FM and changes in contralesional RMT in the MEP- group. Conclusion: MI-BCI improved the motor function of the stroke-affected arm in chronic stroke patients with moderate to severe impairment. tDCS did not confer overall additional benefit although there was a trend toward greater benefit. Cortical activity changes in the contralesional M1 associated with functional improvement suggests a possible role for the contralesional M1 in stroke recovery in more severely affected patients. This has important implications in designing neuromodulatory interventions for future studies and tailoring treatment. Clinical Trial Registration: The study was registered at https://clinicaltrials.gov (NCT01897025).
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Affiliation(s)
- Effie Chew
- Division of Neurology, Department of Medicine, National University Hospital, Singapore, Singapore.,Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Wei-Peng Teo
- National Institute of Education, Nanyang Technological University, Singapore, Singapore.,School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition, Deakin University, Melbourne, VIC, Australia
| | - Ning Tang
- Division of Neurology, Department of Medicine, National University Hospital, Singapore, Singapore
| | - Kai Keng Ang
- Institute for Infocomm Research (I2R), ASTAR, Singapore, Singapore
| | - Yee Sien Ng
- Department of Rehabilitation Medicine, Singapore General Hospital, Singapore, Singapore
| | - Juan Helen Zhou
- Center for Sleep and Cognition, Center for Translational MR Research, Yong Loo Lin School of Medicine, Singapore, Singapore.,Neuroscience and Behavioral Disorders Program, Duke-NUS Medical School, Singapore, Singapore
| | - Irvin Teh
- School of Medicine, University of Leeds, Leeds, United Kingdom
| | - Kok Soon Phua
- Institute for Infocomm Research (I2R), ASTAR, Singapore, Singapore
| | - Ling Zhao
- Division of Neurology, Department of Medicine, National University Hospital, Singapore, Singapore
| | - Cuntai Guan
- School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
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Dai G, Zhou J, Huang J, Wang N. HS-CNN: a CNN with hybrid convolution scale for EEG motor imagery classification. J Neural Eng 2020; 17:016025. [PMID: 31476743 DOI: 10.1088/1741-2552/ab405f] [Citation(s) in RCA: 99] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
OBJECTIVE Electroencephalography (EEG) motor imagery classification has been widely used in healthcare applications such as mobile assistive robots and post-stroke rehabilitation. Recently, EEG motor imagery classification methods based on convolutional neural networks (CNNs) have been proposed and have achieved relatively high classification accuracy. However, these methods use single convolution scale in the CNN, while the best convolution scale differs from subject to subject. This limits the classification accuracy. Another issue is that the classification accuracy degrades when training data is limited. APPROACH To address these issues, we have proposed a hybrid-scale CNN architecture with a data augmentation method for EEG motor imagery classification. MAIN RESULTS Compared with several state-of-the-art methods, the proposed method achieves an average classification accuracy of 91.57% and 87.6% on two commonly used datasets, which outperforms several state-of-the-art EEG motor imagery classification methods. SIGNIFICANCE The proposed method effectively addresses the issues of existing CNN-based EEG motor imagery classification methods and improves the classification accuracy.
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Affiliation(s)
- Guanghai Dai
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China
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Guan S, Zhao K, Yang S. Motor Imagery EEG Classification Based on Decision Tree Framework and Riemannian Geometry. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2019; 2019:5627156. [PMID: 30804988 PMCID: PMC6360593 DOI: 10.1155/2019/5627156] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Revised: 12/20/2018] [Accepted: 01/03/2019] [Indexed: 11/30/2022]
Abstract
This paper proposes a novel classification framework and a novel data reduction method to distinguish multiclass motor imagery (MI) electroencephalography (EEG) for brain computer interface (BCI) based on the manifold of covariance matrices in a Riemannian perspective. For method 1, a subject-specific decision tree (SSDT) framework with filter geodesic minimum distance to Riemannian mean (FGMDRM) is designed to identify MI tasks and reduce the classification error in the nonseparable region of FGMDRM. Method 2 includes a feature extraction algorithm and a classification algorithm. The feature extraction algorithm combines semisupervised joint mutual information (semi-JMI) with general discriminate analysis (GDA), namely, SJGDA, to reduce the dimension of vectors in the Riemannian tangent plane. And the classification algorithm replaces the FGMDRM in method 1 with k-nearest neighbor (KNN), named SSDT-KNN. By applying method 2 on BCI competition IV dataset 2a, the kappa value has been improved from 0.57 to 0.607 compared to the winner of dataset 2a. And method 2 also obtains high recognition rate on the other two datasets.
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Affiliation(s)
- Shan Guan
- School of Mechanical Engineering, Northeast Electric Power University, 132012 Jilin, China
| | - Kai Zhao
- School of Mechanical Engineering, Northeast Electric Power University, 132012 Jilin, China
| | - Shuning Yang
- School of Mechanical Engineering, Northeast Electric Power University, 132012 Jilin, China
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Hu M, Ji F, Lu Z, Huang W, Khosrowabadi R, Zhao L, Ang KK, Phua KS, Nasrallah FA, Chuang KH, Stephenson MC, Totman J, Jiang X, Chew E, Guan C, Zhou J. Differential Amplitude of Low-Frequency Fluctuations in brain networks after BCI Training with and without tDCS in Stroke. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2018; 2018:1050-1053. [PMID: 30440571 DOI: 10.1109/embc.2018.8512395] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Mapping the brain alterations post stroke and post intervention is important for rehabilitation therapy development. Previous work has shown changes in functional connectivity based on resting-state fMRI, structural connectivity derived from diffusion MRI and perfusion as a result of brain-computer interface-assisted motor imagery (MI-BCI) and transcranial direct current stimulation (tDCS) in upper-limb stroke rehabilitation. Besides functional connectivity, regional amplitude of local low-frequency fluctuations (ALFF) may provide complementary information on the underlying neural mechanism in disease. Yet, findings on spontaneous brain activity during resting-state in stroke patients after intervention are limited and inconsistent. Here, we sought to investigate the different brain alteration patterns induced by tDCS compared to MI-BCI for upper-limb rehabilitation in chronic stroke patients using resting-state fMRI-based ALFF method. Our results suggested that stroke patients have lower ALFF in the ipsilesional somatomotor network compared to controls at baseline. Increased ALFF at contralesional somatomotor network and alterations in higher-level cognitive networks such as the default mode network (DMN) and salience networks accompany motor recovery after intervention; though the MI-BCI alone group and MI-BCI combined with tDCS group exhibit differential patterns.
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Elsner B, Kwakkel G, Kugler J, Mehrholz J. Transcranial direct current stimulation (tDCS) for improving capacity in activities and arm function after stroke: a network meta-analysis of randomised controlled trials. J Neuroeng Rehabil 2017; 14:95. [PMID: 28903772 PMCID: PMC5598049 DOI: 10.1186/s12984-017-0301-7] [Citation(s) in RCA: 101] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Accepted: 08/30/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Transcranial Direct Current Stimulation (tDCS) is an emerging approach for improving capacity in activities of daily living (ADL) and upper limb function after stroke. However, it remains unclear what type of tDCS stimulation is most effective. Our aim was to give an overview of the evidence network regarding the efficacy and safety of tDCS and to estimate the effectiveness of the different stimulation types. METHODS We performed a systematic review of randomised trials using network meta-analysis (NMA), searching the following databases until 5 July 2016: Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, CINAHL, AMED, Web of Science, and four other databases. We included studies with adult people with stroke. We compared any kind of active tDCS (anodal, cathodal, or dual, that is applying anodal and cathodal tDCS concurrently) regarding improvement of our primary outcome of ADL capacity, versus control, after stroke. PROSPERO ID CRD42016042055. RESULTS We included 26 studies with 754 participants. Our NMA showed evidence of an effect of cathodal tDCS in improving our primary outcome, that of ADL capacity (standardized mean difference, SMD = 0.42; 95% CI 0.14 to 0.70). tDCS did not improve our secondary outcome, that of arm function, measured by the Fugl-Meyer upper extremity assessment (FM-UE). There was no difference in safety between tDCS and its control interventions, measured by the number of dropouts and adverse events. CONCLUSION Comparing different forms of tDCS shows that cathodal tDCS is the most promising treatment option to improve ADL capacity in people with stroke.
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Affiliation(s)
- Bernhard Elsner
- Department of Public Health, Dresden Medical School, Technical University Dresden, Fetscherstr. 74, 01307, Dresden, Germany. .,Physiotherapy, SRH University of Applied Health Sciences Gera, Gera, Germany.
| | - Gert Kwakkel
- Department of Rehabilitation Medicine, VU University Medical Center, MOVE Research Institute Amsterdam, Amsterdam, The Netherlands.,Neurorehabilitation, Amsterdam Rehabilitation Research Center Reade, Amsterdam, The Netherlands.,Neuroscience Campus Amsterdam, VU University Amsterdam, Amsterdam, The Netherlands.,Department of Physical Therapy and Human Movement Sciences, Northwestern University, Evanston, IL, USA
| | - Joachim Kugler
- Department of Public Health, Dresden Medical School, Technical University Dresden, Fetscherstr. 74, 01307, Dresden, Germany
| | - Jan Mehrholz
- Department of Public Health, Dresden Medical School, Technical University Dresden, Fetscherstr. 74, 01307, Dresden, Germany.,Physiotherapy, SRH University of Applied Health Sciences Gera, Gera, Germany.,Wissenschaftliches Institut, Private Europäische Medizinische Akademie der Klinik Bavaria in Kreischa GmbH, Kreischa, Germany
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Antal A, Alekseichuk I, Bikson M, Brockmöller J, Brunoni AR, Chen R, Cohen LG, Dowthwaite G, Ellrich J, Flöel A, Fregni F, George MS, Hamilton R, Haueisen J, Herrmann CS, Hummel FC, Lefaucheur JP, Liebetanz D, Loo CK, McCaig CD, Miniussi C, Miranda PC, Moliadze V, Nitsche MA, Nowak R, Padberg F, Pascual-Leone A, Poppendieck W, Priori A, Rossi S, Rossini PM, Rothwell J, Rueger MA, Ruffini G, Schellhorn K, Siebner HR, Ugawa Y, Wexler A, Ziemann U, Hallett M, Paulus W. Low intensity transcranial electric stimulation: Safety, ethical, legal regulatory and application guidelines. Clin Neurophysiol 2017; 128:1774-1809. [PMID: 28709880 PMCID: PMC5985830 DOI: 10.1016/j.clinph.2017.06.001] [Citation(s) in RCA: 670] [Impact Index Per Article: 95.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2017] [Revised: 05/29/2017] [Accepted: 06/06/2017] [Indexed: 12/11/2022]
Abstract
Low intensity transcranial electrical stimulation (TES) in humans, encompassing transcranial direct current (tDCS), transcutaneous spinal Direct Current Stimulation (tsDCS), transcranial alternating current (tACS), and transcranial random noise (tRNS) stimulation or their combinations, appears to be safe. No serious adverse events (SAEs) have been reported so far in over 18,000 sessions administered to healthy subjects, neurological and psychiatric patients, as summarized here. Moderate adverse events (AEs), as defined by the necessity to intervene, are rare, and include skin burns with tDCS due to suboptimal electrode-skin contact. Very rarely mania or hypomania was induced in patients with depression (11 documented cases), yet a causal relationship is difficult to prove because of the low incidence rate and limited numbers of subjects in controlled trials. Mild AEs (MAEs) include headache and fatigue following stimulation as well as prickling and burning sensations occurring during tDCS at peak-to-baseline intensities of 1-2mA and during tACS at higher peak-to-peak intensities above 2mA. The prevalence of published AEs is different in studies specifically assessing AEs vs. those not assessing them, being higher in the former. AEs are frequently reported by individuals receiving placebo stimulation. The profile of AEs in terms of frequency, magnitude and type is comparable in healthy and clinical populations, and this is also the case for more vulnerable populations, such as children, elderly persons, or pregnant women. Combined interventions (e.g., co-application of drugs, electrophysiological measurements, neuroimaging) were not associated with further safety issues. Safety is established for low-intensity 'conventional' TES defined as <4mA, up to 60min duration per day. Animal studies and modeling evidence indicate that brain injury could occur at predicted current densities in the brain of 6.3-13A/m2 that are over an order of magnitude above those produced by tDCS in humans. Using AC stimulation fewer AEs were reported compared to DC. In specific paradigms with amplitudes of up to 10mA, frequencies in the kHz range appear to be safe. In this paper we provide structured interviews and recommend their use in future controlled studies, in particular when trying to extend the parameters applied. We also discuss recent regulatory issues, reporting practices and ethical issues. These recommendations achieved consensus in a meeting, which took place in Göttingen, Germany, on September 6-7, 2016 and were refined thereafter by email correspondence.
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Affiliation(s)
- A Antal
- Department of Clinical Neurophysiology, University Medical Center Göttingen, Georg August University, Göttingen, Germany.
| | - I Alekseichuk
- Department of Clinical Neurophysiology, University Medical Center Göttingen, Georg August University, Göttingen, Germany
| | - M Bikson
- Department of Biomedical Engineering, The City College of New York, New York, USA
| | - J Brockmöller
- Department of Clinical Pharmacology, University Medical Center Goettingen, Germany
| | - A R Brunoni
- Service of Interdisciplinary Neuromodulation, Department and Institute of Psychiatry, Laboratory of Neurosciences (LIM-27) and Interdisciplinary Center for Applied Neuromodulation University Hospital, University of São Paulo, São Paulo, Brazil
| | - R Chen
- Division of Neurology, Department of Medicine, University of Toronto and Krembil Research Institute, Toronto, Ontario, Canada
| | - L G Cohen
- Human Cortical Physiology and Neurorehabilitation Section, National Institute of Neurological Disorders and Stroke NIH, Bethesda, USA
| | | | - J Ellrich
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark; Institute of Physiology and Pathophysiology, University of Erlangen-Nürnberg, Erlangen, Germany; EBS Technologies GmbH, Europarc Dreilinden, Germany
| | - A Flöel
- Universitätsmedizin Greifswald, Klinik und Poliklinik für Neurologie, Greifswald, Germany
| | - F Fregni
- Spaulding Neuromodulation Center, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, USA
| | - M S George
- Brain Stimulation Division, Medical University of South Carolina, and Ralph H. Johnson Veterans Affairs Medical Center, Charleston, SC, USA
| | - R Hamilton
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - J Haueisen
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Germany
| | - C S Herrmann
- Experimental Psychology Lab, Department of Psychology, European Medical School, Carl von Ossietzky Universität, Oldenburg, Germany
| | - F C Hummel
- Defitech Chair of Clinical Neuroengineering, Centre of Neuroprosthetics (CNP) and Brain Mind Institute, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland; Defitech Chair of Clinical Neuroengineering, Clinique Romande de Réadaptation, Swiss Federal Institute of Technology (EPFL Valais), Sion, Switzerland
| | - J P Lefaucheur
- Department of Physiology, Henri Mondor Hospital, Assistance Publique - Hôpitaux de Paris, and EA 4391, Nerve Excitability and Therapeutic Team (ENT), Faculty of Medicine, Paris Est Créteil University, Créteil, France
| | - D Liebetanz
- Department of Clinical Neurophysiology, University Medical Center Göttingen, Georg August University, Göttingen, Germany
| | - C K Loo
- School of Psychiatry & Black Dog Institute, University of New South Wales, Sydney, Australia
| | - C D McCaig
- Institute of Medical Sciences, University of Aberdeen, Aberdeen, Scotland, UK
| | - C Miniussi
- Center for Mind/Brain Sciences CIMeC, University of Trento, Rovereto, Italy; Cognitive Neuroscience Section, IRCCS Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - P C Miranda
- Institute of Biophysics and Biomedical Engineering, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - V Moliadze
- Institute of Medical Psychology and Medical Sociology, University Hospital of Schleswig-Holstein (UKSH), Campus Kiel, Christian-Albrechts-University, Kiel, Germany
| | - M A Nitsche
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany; Department of Neurology, University Hospital Bergmannsheil, Bochum, Germany
| | - R Nowak
- Neuroelectrics, Barcelona, Spain
| | - F Padberg
- Department of Psychiatry and Psychotherapy, Munich Center for Brain Stimulation, Ludwig-Maximilian University Munich, Germany
| | - A Pascual-Leone
- Division of Cognitive Neurology, Harvard Medical Center and Berenson-Allen Center for Noninvasive Brain Stimulation at Beth Israel Deaconess Medical Center, Boston, USA
| | - W Poppendieck
- Department of Information Technology, Mannheim University of Applied Sciences, Mannheim, Germany
| | - A Priori
- Center for Neurotechnology and Experimental Brain Therapeutich, Department of Health Sciences, University of Milan Italy; Deparment of Clinical Neurology, University Hospital Asst Santi Paolo E Carlo, Milan, Italy
| | - S Rossi
- Department of Medicine, Surgery and Neuroscience, Human Physiology Section and Neurology and Clinical Neurophysiology Section, Brain Investigation & Neuromodulation Lab, University of Siena, Italy
| | - P M Rossini
- Area of Neuroscience, Institute of Neurology, University Clinic A. Gemelli, Catholic University, Rome, Italy
| | | | - M A Rueger
- Department of Neurology, University Hospital of Cologne, Germany
| | | | | | - H R Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Y Ugawa
- Department of Neurology, Fukushima Medical University, Fukushima, Japan; Fukushima Global Medical Science Center, Advanced Clinical Research Center, Fukushima Medical University, Japan
| | - A Wexler
- Department of Science, Technology & Society, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - U Ziemann
- Department of Neurology & Stroke, and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - M Hallett
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA
| | - W Paulus
- Department of Clinical Neurophysiology, University Medical Center Göttingen, Georg August University, Göttingen, Germany
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14
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Hong X, Lu ZK, Teh I, Nasrallah FA, Teo WP, Ang KK, Phua KS, Guan C, Chew E, Chuang KH. Brain plasticity following MI-BCI training combined with tDCS in a randomized trial in chronic subcortical stroke subjects: a preliminary study. Sci Rep 2017; 7:9222. [PMID: 28835651 PMCID: PMC5569072 DOI: 10.1038/s41598-017-08928-5] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2016] [Accepted: 05/24/2017] [Indexed: 12/17/2022] Open
Abstract
Brain-computer interface-assisted motor imagery (MI-BCI) or transcranial direct current stimulation (tDCS) has been used in stroke rehabilitation, though their combinatory effect is unknown. We investigated brain plasticity following a combined MI-BCI and tDCS intervention in chronic subcortical stroke patients with unilateral upper limb disability. Nineteen patients were randomized into tDCS and sham-tDCS groups. Diffusion and perfusion MRI, and transcranial magnetic stimulation were used to study structural connectivity, cerebral blood flow (CBF), and corticospinal excitability, respectively, before and 4 weeks after the 2-week intervention. After quality control, thirteen subjects were included in the CBF analysis. Eleven healthy controls underwent 2 sessions of MRI for reproducibility study. Whereas motor performance showed comparable improvement, long-lasting neuroplasticity can only be detected in the tDCS group, where white matter integrity in the ipsilesional corticospinal tract and bilateral corpus callosum was increased but sensorimotor CBF was decreased, particularly in the ipsilesional side. CBF change in the bilateral parietal cortices also correlated with motor function improvement, consistent with the increased white matter integrity in the corpus callosum connecting these regions, suggesting an involvement of interhemispheric interaction. The preliminary results indicate that tDCS may facilitate neuroplasticity and suggest the potential for refining rehabilitation strategies for stroke patients.
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Affiliation(s)
- Xin Hong
- Singapore Bioimaging Consortium, Agency for Science Technology and Research, 11 Biopolis Way, #02-02 Helios, Singapore, 138667, Singapore
| | - Zhong Kang Lu
- Institute for Infocomm Research, Agency for Science Technology and Research, 1 Fusionopolis Way, #21-01 Connexis (South Tower), Singapore, 138632, Singapore
| | - Irvin Teh
- Clinical Imaging Research Center, Agency for Science Technology and Research, Centre for Translational Medicine (MD6), 14 Medical Drive, #B1-01, Singapore, 117599, Singapore
- Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Fatima Ali Nasrallah
- Singapore Bioimaging Consortium, Agency for Science Technology and Research, 11 Biopolis Way, #02-02 Helios, Singapore, 138667, Singapore
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Wei Peng Teo
- Division of Neurology, National University Hospital System, 5 Lower Kent Ridge Road, Singapore, 119074, Singapore
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Highway, Burwood, VIC 3125, Australia
| | - Kai Keng Ang
- Institute for Infocomm Research, Agency for Science Technology and Research, 1 Fusionopolis Way, #21-01 Connexis (South Tower), Singapore, 138632, Singapore
| | - Kok Soon Phua
- Institute for Infocomm Research, Agency for Science Technology and Research, 1 Fusionopolis Way, #21-01 Connexis (South Tower), Singapore, 138632, Singapore
| | - Cuntai Guan
- Institute for Infocomm Research, Agency for Science Technology and Research, 1 Fusionopolis Way, #21-01 Connexis (South Tower), Singapore, 138632, Singapore
- School of Computer Science and Engineering, Nanynag Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Effie Chew
- Division of Neurology, National University Hospital System, 5 Lower Kent Ridge Road, Singapore, 119074, Singapore.
- Yong Loo Lin School of Medicine, National University of Singapore, NUHS Tower Block, Level 11, 1E Kent Ridge Road, Singapore, 119228, Singapore.
| | - Kai-Hsiang Chuang
- Singapore Bioimaging Consortium, Agency for Science Technology and Research, 11 Biopolis Way, #02-02 Helios, Singapore, 138667, Singapore.
- Clinical Imaging Research Center, Agency for Science Technology and Research, Centre for Translational Medicine (MD6), 14 Medical Drive, #B1-01, Singapore, 117599, Singapore.
- Queensland Brain Institute and Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, 4072, Australia.
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15
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Angulo-Sherman IN, Rodríguez-Ugarte M, Iáñez E, Azorín JM. Low Intensity Focused tDCS Over the Motor Cortex Shows Inefficacy to Improve Motor Imagery Performance. Front Neurosci 2017; 11:391. [PMID: 28729822 PMCID: PMC5498512 DOI: 10.3389/fnins.2017.00391] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Accepted: 06/22/2017] [Indexed: 11/30/2022] Open
Abstract
Transcranial direct current stimulation (tDCS) is a brain stimulation technique that can enhance motor activity by stimulating the motor path. Thus, tDCS has the potential of improving the performance of brain-computer interfaces during motor neurorehabilitation. tDCS effects depend on several aspects, including the current density, which usually varies between 0.02 and 0.08 mA/cm2, and the location of the stimulation electrodes. Hence, testing tDCS montages at several current levels would allow the selection of current parameters for improving stimulation outcomes and the comparison of montages. In a previous study, we found that cortico-cerebellar tDCS shows potential of enhancing right-hand motor imagery. In this paper, we aim to evaluate the effects of the focal stimulation of the motor cortex over motor imagery. In particular, the effect of supplying tDCS with a 4 × 1 ring montage, which consists in placing an anode on the motor cortex and four cathodes around it, over motor imagery was assessed with different current densities. Electroencephalographic (EEG) classification into rest or right-hand/feet motor imagery was evaluated on five healthy subjects for two stimulation schemes: applying tDCS for 10 min on the (1) right-hand or (2) feet motor cortex before EEG recording. Accuracy differences related to the tDCS intensity, as well as μ and β band power changes, were tested for each subject and tDCS modality. In addition, a simulation of the electric field induced by the montage was used to describe its effect on the brain. Results show no improvement trends on classification for the evaluated currents, which is in accordance with the observation of variable EEG band power results despite the focused stimulation. The lack of effects is probably related to the underestimation of the current intensity required to apply a particular current density for small electrodes and the relatively short inter-electrode distance. Hence, higher current intensities should be evaluated in the future for this montage.
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Affiliation(s)
- Irma N Angulo-Sherman
- Monterrey's Unit, Biomedical Signal Processing Laboratory, Center for Research and Advanced StudiesApodaca, Mexico
| | - Marisol Rodríguez-Ugarte
- Brain-Machine Interface Systems Lab, Systems Engineering and Automation Department, Universidad Miguel Hernández de ElcheElche, Spain
| | - Eduardo Iáñez
- Brain-Machine Interface Systems Lab, Systems Engineering and Automation Department, Universidad Miguel Hernández de ElcheElche, Spain
| | - Jose M Azorín
- Brain-Machine Interface Systems Lab, Systems Engineering and Automation Department, Universidad Miguel Hernández de ElcheElche, Spain
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16
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Simonetti D, Zollo L, Milighetti S, Miccinilli S, Bravi M, Ranieri F, Magrone G, Guglielmelli E, Di Lazzaro V, Sterzi S. Literature Review on the Effects of tDCS Coupled with Robotic Therapy in Post Stroke Upper Limb Rehabilitation. Front Hum Neurosci 2017; 11:268. [PMID: 28588467 PMCID: PMC5440520 DOI: 10.3389/fnhum.2017.00268] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2016] [Accepted: 05/05/2017] [Indexed: 11/17/2022] Open
Abstract
Today neurological diseases such as stroke represent one of the leading cause of long-term disability. Many research efforts have been focused on designing new and effective rehabilitation strategies. In particular, robotic treatment for upper limb stroke rehabilitation has received significant attention due to its ability to provide high-intensity and repetitive movement therapy with less effort than traditional methods. In addition, the development of non-invasive brain stimulation techniques such as transcranial Direct Current Stimulation (tDCS) has also demonstrated the capability of modulating brain excitability thus increasing motor performance. The combination of these two methods is expected to enhance functional and motor recovery after stroke; to this purpose, the current trends in this research field are presented and discussed through an in-depth analysis of the state-of-the-art. The heterogeneity and the restricted number of collected studies make difficult to perform a systematic review. However, the literature analysis of the published data seems to demonstrate that the association of tDCS with robotic training has the same clinical gain derived from robotic therapy alone. Future studies should investigate combined approach tailored to the individual patient's characteristics, critically evaluating the brain areas to be targeted and the induced functional changes.
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Affiliation(s)
- Davide Simonetti
- Research Unit of Biomedical Robotics and Biomicrosystems, Università Campus Bio-Medico di RomaRome, Italy
| | - Loredana Zollo
- Research Unit of Biomedical Robotics and Biomicrosystems, Università Campus Bio-Medico di RomaRome, Italy
| | - Stefano Milighetti
- Unit of Physical and Rehabilitation Medicine, Università Campus Bio-Medico di RomaRome, Italy
| | - Sandra Miccinilli
- Unit of Physical and Rehabilitation Medicine, Università Campus Bio-Medico di RomaRome, Italy
| | - Marco Bravi
- Unit of Physical and Rehabilitation Medicine, Università Campus Bio-Medico di RomaRome, Italy
| | - Federico Ranieri
- Unit of Neurology, Neurophysiology and Neurobiology, Università Campus Bio-Medico di RomaRome, Italy
| | - Giovanni Magrone
- Unit of Physical and Rehabilitation Medicine, Università Campus Bio-Medico di RomaRome, Italy
| | - Eugenio Guglielmelli
- Research Unit of Biomedical Robotics and Biomicrosystems, Università Campus Bio-Medico di RomaRome, Italy
| | - Vincenzo Di Lazzaro
- Unit of Neurology, Neurophysiology and Neurobiology, Università Campus Bio-Medico di RomaRome, Italy
| | - Silvia Sterzi
- Unit of Physical and Rehabilitation Medicine, Università Campus Bio-Medico di RomaRome, Italy
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17
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Mao X, Li M, Li W, Niu L, Xian B, Zeng M, Chen G. Progress in EEG-Based Brain Robot Interaction Systems. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2017; 2017:1742862. [PMID: 28484488 PMCID: PMC5397651 DOI: 10.1155/2017/1742862] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/28/2016] [Accepted: 03/21/2017] [Indexed: 11/17/2022]
Abstract
The most popular noninvasive Brain Robot Interaction (BRI) technology uses the electroencephalogram- (EEG-) based Brain Computer Interface (BCI), to serve as an additional communication channel, for robot control via brainwaves. This technology is promising for elderly or disabled patient assistance with daily life. The key issue of a BRI system is to identify human mental activities, by decoding brainwaves, acquired with an EEG device. Compared with other BCI applications, such as word speller, the development of these applications may be more challenging since control of robot systems via brainwaves must consider surrounding environment feedback in real-time, robot mechanical kinematics, and dynamics, as well as robot control architecture and behavior. This article reviews the major techniques needed for developing BRI systems. In this review article, we first briefly introduce the background and development of mind-controlled robot technologies. Second, we discuss the EEG-based brain signal models with respect to generating principles, evoking mechanisms, and experimental paradigms. Subsequently, we review in detail commonly used methods for decoding brain signals, namely, preprocessing, feature extraction, and feature classification, and summarize several typical application examples. Next, we describe a few BRI applications, including wheelchairs, manipulators, drones, and humanoid robots with respect to synchronous and asynchronous BCI-based techniques. Finally, we address some existing problems and challenges with future BRI techniques.
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Affiliation(s)
- Xiaoqian Mao
- School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China
| | - Mengfan Li
- School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China
| | - Wei Li
- School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China
- Department of Computer & Electrical Engineering and Computer Science, California State University, Bakersfield, CA 93311, USA
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Shenyang, Liaoning 110016, China
| | - Linwei Niu
- Department of Math and Computer Science, West Virginia State University, Institute, WV 25112, USA
| | - Bin Xian
- School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China
| | - Ming Zeng
- School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China
| | - Genshe Chen
- Intelligent Fusion Technology, Inc., Germantown, MD 20876, USA
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18
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Middleton A, Fritz SL, Liuzzo DM, Newman-Norlund R, Herter TM. Using clinical and robotic assessment tools to examine the feasibility of pairing tDCS with upper extremity physical therapy in patients with stroke and TBI: a consideration-of-concept pilot study. NeuroRehabilitation 2015; 35:741-54. [PMID: 25323084 DOI: 10.3233/nre-141178] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND Transcranial direct current stimulation (tDCS) may provide a safe, non-invasive technique for modulating neural excitability during neurorehabilitation. OBJECTIVE 1) Assess feasibility and potential effectiveness of tDCS as an adjunct to standard upper extremity (UE) physical therapy (PT) for motor impairments resulting from neurological insult. 2) Determine sustainability of improvements over a six month period. METHODS Five participants with chronic neurologic insult (stroke or traumatic brain injury > 6 months prior) completed 24 sessions (40 minutes, three times/week) of UE-PT combined with bihemispheric tDCS delivered at 1.5 mA over the motor cortex during the first 15 minutes of each PT session. Outcomes were assessed using clinical (UE Fugl-Meyer, Purdue Pegboard, Box and Block, Stroke Impact Scale) and robotic (unimanual and bimanual motor control) measures. Change in scores and associated effects sizes from Pre-test to Post-test and a six month Follow-up were calculated for each participant and group as a whole. RESULTS Scores on UE Fugl-Meyer, Box and Block, Purdue Pegboard, Stroke Impact Scale, and robotic measures improved from Pre- to Post-test. Improvements on UE Fugl-Meyer, Box and Block, and robotic measures were largely sustained at six months. CONCLUSIONS Combining bihemispheric tDCS with UE-PT in individuals with neurological insult warrants further investigation.
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Affiliation(s)
- Addie Middleton
- University of South Carolina, Department of Exercise Science, Division of Rehabilitation Sciences, Columbia, SC, USA
| | - Stacy L Fritz
- University of South Carolina, Department of Exercise Science, Division of Rehabilitation Sciences, Columbia, SC, USA
| | - Derek M Liuzzo
- University of South Carolina, Department of Exercise Science, Division of Rehabilitation Sciences, Columbia, SC, USA
| | - Roger Newman-Norlund
- University of South Carolina, Department of Exercise Science, Division of Rehabilitation Sciences, Columbia, SC, USA
| | - Troy M Herter
- University of South Carolina, Department of Exercise Science, Division of Rehabilitation Sciences, Columbia, SC, USA
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19
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Tung SW, Guan C, Ang KK, Phua KS, Wang C, Zhao L, Teo WP, Chew E. Motor imagery BCI for upper limb stroke rehabilitation: An evaluation of the EEG recordings using coherence analysis. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2015; 2013:261-4. [PMID: 24109674 DOI: 10.1109/embc.2013.6609487] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Brain-computer interface (BCI) technology has the potential as a post-stroke rehabilitation tool, and the efficacy of the technology is most often demonstrated through output peripherals such as robots, orthosis and computers. In this study, the EEG signals recorded during the course of upper limb stroke rehabilitaion using motor imagery BCI were analyzed to better understand the effect of BCI therapy for post-stroke rehabilitation. The stroke patients recruited underwent 10 sessions of 1-hour BCI with robotic feedback for 2 weeks, 5 times a week. The analysis was performed by computing the coherences of the EEG in the lesion and contralesion side of the hemisphere from each session, and the coherence index of the lesion hemisphere (0 ≤ CI ≤ 1) was computed. The coherence index represents the rate of activation of the lesion hemisphere, and the correlation with the Fugl-Meyer assessment (FMA) before and after the BCI therapy was investigated. Significant improvement in the FMA scores was reported for five of the six patients (p = 0.01). The analysis showed that the number of sessions with CI ≥ 0.5 correlated with the change in the FMA scores. This suggests that post-stroke motor recovery best results from the activation in the lesion hemisphere, which is in agreement with previous studies performed using multimodal imaging technologies.
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20
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Huggins JE, Guger C, Allison B, Anderson CW, Batista A, Brouwer AM(AM, Brunner C, Chavarriaga R, Fried-Oken M, Gunduz A, Gupta D, Kübler A, Leeb R, Lotte F, Miller LE, Müller-Putz G, Rutkowski T, Tangermann M, Thompson DE. Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future. BRAIN-COMPUTER INTERFACES 2014; 1:27-49. [PMID: 25485284 PMCID: PMC4255956 DOI: 10.1080/2326263x.2013.876724] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The Fifth International Brain-Computer Interface (BCI) Meeting met June 3-7th, 2013 at the Asilomar Conference Grounds, Pacific Grove, California. The conference included 19 workshops covering topics in brain-computer interface and brain-machine interface research. Topics included translation of BCIs into clinical use, standardization and certification, types of brain activity to use for BCI, recording methods, the effects of plasticity, special interest topics in BCIs applications, and future BCI directions. BCI research is well established and transitioning to practical use to benefit people with physical impairments. At the same time, new applications are being explored, both for people with physical impairments and beyond. Here we provide summaries of each workshop, illustrating the breadth and depth of BCI research and high-lighting important issues for future research and development.
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Affiliation(s)
- Jane E. Huggins
- Department of Physical Medicine and Rehabilitation, Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States, 325 East Eisenhower, Room 3017; Ann Arbor, Michigan 48108-5744, 734-936-7177
| | - Christoph Guger
- Christoph Guger, g.tec medical engineering GmbH/Guger Technologies OG, Austria, Sierningstrasse 14, 4521 Schiedlberg, Austria, +43725122240-0
| | - Brendan Allison
- University of California at San Diego, La Jolla, CA 91942 (415) 490 7551
| | - Charles W. Anderson
- Department of Computer Science, Colorado State University, Fort Collins, CO 80523; telephone: 970-491-7491
| | - Aaron Batista
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, 3501 5th Av, BST3 4074; Pittsburgh, PA 15261; (412) 383-5394
| | - Anne-Marie (A.-M.) Brouwer
- The Netherlands Organization for Applied Scientific Research; P.O. Box 23/Kampweg 5, 3769 ZG Soesterberg, the Netherlands, ++31 (0)888 665960
| | - Clemens Brunner
- Institute for Knowledge Discovery, Laboratory of Brain-Computer Interfaces, Graz University of Technology, Inffeldgasse 13/4, 8010; Graz, Austria
| | - Ricardo Chavarriaga
- Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne, Switzerland, EPFL-STI-CNBI, Station 11, 1005 Lausanne, Switzerland; Telephone: +41 21 693 6968
| | - Melanie Fried-Oken
- Oregon Health & Science University; Institute on Development & Disability; 707 SW Gaines Street; Portland, Oregon, United States; O: 503.494.7587, F: 503.494.6868
| | - Aysegul Gunduz
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA; Phone: +1 (352) 273 6877; Fax: +1 (352) 273 9221
| | - Disha Gupta
- Dept. of Neurology, Albany Medical College/Brain Computer Interfacing Lab, Wadsworth Center, NY State Dept. of Health, Albany, New York, USA
| | - Andrea Kübler
- Institute of Psychology, University of Würzburg; Marcusstr.9-11; 97070 Würzburg, Germany. Phone.: 0049 931 31 80179; Fax: 0049 931 31 82424
| | - Robert Leeb
- Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne, Switzerland
| | - Fabien Lotte
- Inria Bordeaux Sud-Ouest/LaBRI, 200 avenue de la vieille tour, 33405, Talence Cedex, France, Tel: +33 5 24 57 41 26
| | - Lee E. Miller
- Departments of Physiology, Physical Medicine and Rehab, and Biomedical Engineering; Feinberg School of Medicine; Northwestern University; Chicago, Illinois, United States; Ward 5-01; 303 East Chicago Avenue; Chicago, Illinois 60611; Phone: (312) 503 – 8677; Fax: (312) 503 – 5101
| | - Gernot Müller-Putz
- Institute for Knowledge Discovery, Laboratory of Brain-Computer Interfaces, Graz University of Technology, Inffeldgasse 13/4, 8010; Graz, Austria
| | - Tomasz Rutkowski
- Life Science Center of TARA, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8577 Japan; TEL: +81 (0)29-853-6261
| | - Michael Tangermann
- Excellence Cluster BrainLinks-BrainTools, Dept. Computer Science, University of Freiburg, Freiburg, Germany, Albertstr. 23; 79104 Freiburg; Germany; Phone: +49.(0)761.2038423, Fax : +49.(0)761.2038417
| | - David Edward Thompson
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States, 2800 Plymouth Road, Bdlg 26 Rm G06W-B; Ann Arbor, MI 48109; 734-763-7104
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Malouin F, Jackson PL, Richards CL. Towards the integration of mental practice in rehabilitation programs. A critical review. Front Hum Neurosci 2013; 7:576. [PMID: 24065903 PMCID: PMC3776942 DOI: 10.3389/fnhum.2013.00576] [Citation(s) in RCA: 104] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2013] [Accepted: 08/28/2013] [Indexed: 11/21/2022] Open
Abstract
Many clinical studies have investigated the use of mental practice (MP) through motor imagery (MI) to enhance functional recovery of patients with diverse physical disabilities. Although beneficial effects have been generally reported for training motor functions in persons with chronic stroke (e.g., reaching, writing, walking), attempts to integrate MP within rehabilitation programs have been met with mitigated results. These findings have stirred further questioning about the value of MP in neurological rehabilitation. In fact, despite abundant systematic reviews, which customarily focused on the methodological merits of selected studies, several questions about factors underlying observed effects remain to be addressed. This review discusses these issues in an attempt to identify factors likely to hamper the integration of MP within rehabilitation programs. First, the rationale underlying the use of MP for training motor function is briefly reviewed. Second, three modes of MI delivery are proposed based on the analysis of the research protocols from 27 studies in persons with stroke and Parkinson's disease. Third, for each mode of MI delivery, a general description of MI training is provided. Fourth, the review discusses factors influencing MI training outcomes such as: the adherence to MI training, the amount of training and the interaction between physical and mental rehearsal; the use of relaxation, the selection of reliable, valid and sensitive outcome measures, the heterogeneity of the patient groups, the selection of patients and the mental rehearsal procedures. To conclude, the review proposes a framework for integrating MP in rehabilitation programs and suggests research targets for steering the implementation of MP in the early stages of the rehabilitation process. The challenge has now shifted towards the demonstration that MI training can enhance the effects of regular therapy in persons with subacute stroke during the period of spontaneous recovery.
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Affiliation(s)
- Francine Malouin
- Département de Réadaptation, Faculté de Médecine, Université Laval Québec, QC, Canada ; Centre Interdisciplinaire de Recherche en Réadaptation et Intégration Sociale Québec, QC, Canada
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