Evidence map›Paper›PMID 27555805›Full record

ArticleFrontiers in neuroscience2016

Hybrid Neuroprosthesis for the Upper Limb: Combining Brain-Controlled Neuromuscular Stimulation with a Multi-Joint Arm Exoskeleton.

Florian Grimm, Armin Walter, Martin Spüler, Georgios Naros, Wolfgang Rosenstiel, Alireza Gharabaghi

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 4 pooled it
3.7field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 4 syntheses or guidelines pooled it, 67 citations in OpenAlex.

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  15. Brain-Machine Neurofeedback: Robotics or Electrical Stimulation?Frontiers in bioengineering and biotechnology · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Florian GrimmDivision of Functional and Restorative Neurosurgery, Centre for Integrative Neuroscience, Eberhard Karls University Tuebingen Tuebingen, Germany.
Armin WalterDepartment of Computer Engineering, Wilhelm Schickard Institute for Computer Science, Eberhard Karls University Tuebingen Tuebingen, Germany.
Martin SpülerDepartment of Computer Engineering, Wilhelm Schickard Institute for Computer Science, Eberhard Karls University Tuebingen Tuebingen, Germany.
Georgios NarosDivision of Functional and Restorative Neurosurgery, Centre for Integrative Neuroscience, Eberhard Karls University Tuebingen Tuebingen, Germany.
Wolfgang RosenstielDepartment of Computer Engineering, Wilhelm Schickard Institute for Computer Science, Eberhard Karls University Tuebingen Tuebingen, Germany.
Alireza GharabaghiDivision of Functional and Restorative Neurosurgery, Centre for Integrative Neuroscience, Eberhard Karls University Tuebingen Tuebingen, Germany.
University of Tübingen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain-machine interface-controlled (BMI) neurofeedback training aims to modulate cortical physiology and is applied during neurorehabilitation to increase the responsiveness of the brain to subsequent physiotherapy. In a parallel line of research, robotic exoskeletons are used in goal-oriented rehabilitation exercises for patients with severe motor impairment to extend their range of motion (ROM) and the intensity of training. Furthermore, neuromuscular electrical stimulation (NMES) is applied in neurologically impaired patients to restore muscle strength by closing the sensorimotor loop. In this proof-of-principle study, we explored an integrated approach for providing assistance as needed to amplify the task-related ROM and the movement-related brain modulation during rehabilitation exercises of severely impaired patients. For this purpose, we combined these three approaches (BMI, NMES, and exoskeleton) in an integrated neuroprosthesis and studied the feasibility of this device in seven severely affected chronic stroke patients who performed wrist flexion and extension exercises while receiving feedback via a virtual environment. They were assisted by a gravity-compensating, seven degree-of-freedom exoskeleton which was attached to the paretic arm. NMES was applied to the wrist extensor and flexor muscles during the exercises and was controlled by a hybrid BMI based on both sensorimotor cortical desynchronization (ERD) and electromyography (EMG) activity. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e., induced no overt support. The hybrid BMI controlled the stimulation significantly better than the offline analyzed ERD (p = 0.028) or EMG (p = 0.021) modality alone. Neuromuscular stimulation could be well integrated into the exoskeleton-based training and amplified both the task-related ROM (p = 0.009) and the movement-related brain modulation (p = 0.019). Combining a hybrid BMI with neuromuscular stimulation and antigravity assistance augments upper limb function and brain activity during rehabilitation exercises and may thus provide a novel restorative framework for severely affected stroke patients.

Indexed as

brain-computer interfacebrain-machine interfacebrain-robot interfacefunctional electrical stimulationfunctional restorationmotor recoveryrobot-assisted rehabilitationupper-limb assistance

Identifiers

PMID27555805
PMCPMC4977295
OpenAlexW2503897305

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.