Noninvasive brain-computer interface driven hand orthosis

King, Christine; Wang, Po T.; Mizuta, Masato; Reinkensmeyer, David J.; An, Hongyu; Moromugi, Shunji; Nenadic, Zoran

doi:10.1109/iembs.2011.6091432

Cited by 23 publications

(20 citation statements)

References 16 publications

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“…For patients who cannot recover previous levels of mobility or communication, BCI based prosthetic limbs, also called neuroprosthetic devices, can be used to regain normal functionality [46][47][48][49].…”

Section: Rehabilitation and Restorationmentioning

confidence: 99%

Brain computer interfacing: Applications and challenges

Abdulkader

Atia

Mostafa

2015

Egyptian Informatics Journal

427

247

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Brain computer interface technology represents a highly growing field of research with application systems. Its contributions in medical fields range from prevention to neuronal rehabilitation for serious injuries. Mind reading and remote communication have their unique fingerprint in numerous fields such as educational, self-regulation, production, marketing, security as well as games and entertainment. It creates a mutual understanding between users and the surrounding systems. This paper shows the application areas that could benefit from brain waves in facilitating or achieving their goals. We also discuss major usability and technical challenges that face brain signals utilization in various components of BCI system. Different solutions that aim to limit and decrease their effects have also been reviewed.Ó 2015 Production and hosting by Elsevier B.V. on behalf

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Section: Rehabilitation and Restorationmentioning

confidence: 99%

Brain computer interfacing: Applications and challenges

Abdulkader

Atia

Mostafa

2015

Egyptian Informatics Journal

427

247

View full text Add to dashboard Cite

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“…In order to facilitate hand MI and account for significant time-points in the EEG data, all the studies employed a cue-feedback strategy during their trials. 19 of the studies presented a form of visual cue while the rest, except for two unspecified [69,87], involved cues in auditory ("bleep") [76,[80][81][82][83], textual [78,79,89] or verbal [88] forms. As for the provision of a matching sensory feedback, 16 studies presented a combination of kinaesthetic and visual feedback with some also providing auditory feedback during successful movement attempts.…”

Section: Discussionmentioning

confidence: 99%

“…A final list with 30 studies was identified as eligible for qualitative review. Among the 30 studies, 11 [60][61][62][63][64][65][66][67][68][69][70] were involved in testing the BCI-hand robot system on chronic and subacute stroke patients ( [60,65] are RCTs) while the rest involved testing on healthy participants [71][72][73][74][75][76][77][78][79][80][81][82][83][84][85][86][87][88][89].…”

Section: Figure 1 Study Selection Flowchartmentioning

confidence: 99%

Brain-Computer Interface Robotics for Hand Rehabilitation After Stroke: A Systematic Review

Baniqued

Stanyer

Awais

et al. 2019

Preprint

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Electroencephalography-based brain-computer interfaces (BCI) that allow the control of robotic devices to support stroke patients during upper limb rehabilitation are increasingly popular. Hand rehabilitation is focused on improving dexterity and fine motor control and is a core approach for helping stroke survivors regain activities of daily living. This systematic review examines recent developments in BCI-robotic systems for hand rehabilitation and identifies evidence-based clinical studies on stroke patients. A search for January 2010-October 2019 articles using Ovid MEDLINE, Embase, PEDro, PsycINFO, IEEE Xplore and Cochrane Library databases was performed. The selection criteria included BCI-hand robotic systems for rehabilitation in various development stages involving tests on healthy human subjects or stroke survivors. Data fields include those related to study design, participant characteristics, technical specifications of the system, and clinical outcome measures. 30 studies were identified as eligible for qualitative review and among these, 11 studies involved testing a BCI-hand robot on chronic and subacute stroke patients. Statistically significant improvements in motor assessment scores relative to controls were observed for two BCI-hand robot interventions. The degree of robot control for the majority of studies was limited to triggering the device to perform grasping or pinching movements using motor imagery. Most employed a combination of kinaesthetic and visual response via the robotic device and display screen, respectively, to match feedback to motor imagery. Most studies on BCI-robotic systems for hand rehabilitation report systems at prototype or pre-clinical stages of development. Some studies report statistically significant improvements in functional recovery after stroke, but there is a need to develop a standard protocol for assessing technical and clinical outcomes so that the necessary evidence base on efficiency and efficacy can be developed.

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“…Similar to the authors’ prior work [ 2 - 4 , 10 , 12 , 13 ], the BCI-RoGO system is modeled as a binary state machine with “idling” and “walking” states. This step is necessary to reduce noise in the online BCI operation and minimize the mental workload of the subject.…”

Section: Methodsmentioning

confidence: 99%

Brain-computer interface controlled robotic gait orthosis

Wang

King

et al. 2013

Journal of NeuroEngineering and Rehabilitation

146

112

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BackgroundExcessive reliance on wheelchairs in individuals with tetraplegia or paraplegia due to spinal cord injury (SCI) leads to many medical co-morbidities, such as cardiovascular disease, metabolic derangements, osteoporosis, and pressure ulcers. Treatment of these conditions contributes to the majority of SCI health care costs. Restoring able-body-like ambulation in this patient population can potentially reduce the incidence of these medical co-morbidities, in addition to increasing independence and quality of life. However, no biomedical solution exists that can reverse this loss of neurological function, and hence novel methods are needed. Brain-computer interface (BCI) controlled lower extremity prostheses may constitute one such novel approach.MethodsOne able-bodied subject and one subject with paraplegia due to SCI underwent electroencephalogram (EEG) recordings while engaged in alternating epochs of idling and walking kinesthetic motor imagery (KMI). These data were analyzed to generate an EEG prediction model for online BCI operation. A commercial robotic gait orthosis (RoGO) system (suspended over a treadmill) was interfaced with the BCI computer to allow for computerized control. The subjects were then tasked to perform five, 5-min-long online sessions where they ambulated using the BCI-RoGO system as prompted by computerized cues. The performance of this system was assessed with cross-correlation analysis, and omission and false alarm rates.ResultsThe offline accuracy of the EEG prediction model averaged 86.30% across both subjects (chance: 50%). The cross-correlation between instructional cues and the BCI-RoGO walking epochs averaged across all subjects and all sessions was 0.812±0.048 (p-value <10−4). Also, there were on average 0.8 false alarms per session and no omissions.ConclusionThese results provide preliminary evidence that restoring brain-controlled ambulation after SCI is feasible. Future work will test the function of this system in a population of subjects with SCI. If successful, this may justify the future development of BCI-controlled lower extremity prostheses for free overground walking for those with complete motor SCI. Finally, this system can also be applied to incomplete motor SCI, where it could lead to improved neurological outcomes beyond those of standard physiotherapy.

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Noninvasive brain-computer interface driven hand orthosis

Cited by 23 publications

References 16 publications

Brain computer interfacing: Applications and challenges

Brain computer interfacing: Applications and challenges

Brain-Computer Interface Robotics for Hand Rehabilitation After Stroke: A Systematic Review

Brain-computer interface controlled robotic gait orthosis

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