scholarly journals A study on the effect of electrical stimulation as a user stimuli for motor imagery classification in Brain-Machine Interface

2016 ◽  
Vol 26 (2) ◽  
Author(s):  
Saugat Bhattacharyya ◽  
Maureen Clerc ◽  
Mitsuhiro Hayashibe
Keyword(s):  
Electrical Stimulation ◽  
Motor Imagery ◽  
Hand Movement ◽  
Movement Training ◽  
Peripheral Muscle ◽  
Motor Intention ◽  
Machine Interface ◽  
The Subject ◽  
Muscle Groups ◽  
Muscle Activations

Functional Electrical Stimulation (FES) provides a neuroprosthetic interface to non-recovered muscle groups by stimulating the affected region of the human body. FES in combination with Brain-machine interfacing (BMI) has a wide scope in rehabilitation because this system directly links the cerebral motor intention of the users with its corresponding peripheral muscle activations. In this paper, we examine the effect of FES on the electroencephalography (EEG) during motor imagery (left- and right-hand movement) training of the users. Results suggest a significant improvement in the classification accuracy when the subject was induced with FES stimuli as compared to the standard visual one.

scholarly journals Brain oscillatory signatures of motor tasks

2015 ◽  
Vol 113 (10) ◽  
pp. 3663-3682 ◽  
Author(s):  
Ander Ramos-Murguialday ◽  
Niels Birbaumer
Keyword(s):  
Motor Imagery ◽  
Brain Activity ◽  
Hand Movement ◽  
Active Movement ◽  
Motor Rehabilitation ◽  
Motor Tasks ◽  
Time Frequency ◽  
Motor Intention ◽  
Sensorimotor Rhythm ◽  
Specific Frequency

Noninvasive brain-computer-interfaces (BCI) coupled with prosthetic devices were recently introduced in the rehabilitation of chronic stroke and other disorders of the motor system. These BCI systems and motor rehabilitation in general involve several motor tasks for training. This study investigates the neurophysiological bases of an EEG-oscillation-driven BCI combined with a neuroprosthetic device to define the specific oscillatory signature of the BCI task. Controlling movements of a hand robotic orthosis with motor imagery of the same movement generates sensorimotor rhythm oscillation changes and involves three elements of tasks also used in stroke motor rehabilitation: passive and active movement, motor imagery, and motor intention. We recorded EEG while nine healthy participants performed five different motor tasks consisting of closing and opening of the hand as follows: 1) motor imagery without any external feedback and without overt hand movement, 2) motor imagery that moves the orthosis proportional to the produced brain oscillation change with online proprioceptive and visual feedback of the hand moving through a neuroprosthetic device (BCI condition), 3) passive and 4) active movement of the hand with feedback (seeing and feeling the hand moving), and 5) rest. During the BCI condition, participants received contingent online feedback of the decrease of power of the sensorimotor rhythm, which induced orthosis movement and therefore proprioceptive and visual information from the moving hand. We analyzed brain activity during the five conditions using time-frequency domain bootstrap-based statistical comparisons and Morlet transforms. Activity during rest was used as a reference. Significant contralateral and ipsilateral event-related desynchronization of sensorimotor rhythm was present during all motor tasks, largest in contralateral-postcentral, medio-central, and ipsilateral-precentral areas identifying the ipsilateral precentral cortex as an integral part of motor regulation. Changes in task-specific frequency power compared with rest were similar between motor tasks, and only significant differences in the time course and some narrow specific frequency bands were observed between motor tasks. We identified EEG features representing active and passive proprioception (with and without muscle contraction) and active intention and passive involvement (with and without voluntary effort) differentiating brain oscillations during motor tasks that could substantially support the design of novel motor BCI-based rehabilitation therapies. The BCI task induced significantly different brain activity compared with the other motor tasks, indicating neural processes unique to the use of body actuators control in a BCI context.

scholarly journals Dual Head and Dual Attention in Deep Learning for End-to-End EEG Motor Imagery Classification

2021 ◽  
Vol 11 (22) ◽  
pp. 10906
Author(s):  
Meiyan Xu ◽  
Junfeng Yao ◽  
Hualiang Ni
Keyword(s):  
Motor Imagery ◽  
Independent Set ◽  
Trained Subjects ◽  
Average Accuracy ◽  
Proposed Model ◽  
Machine Interface ◽  
The Subject ◽  
Temporal Dimensions ◽  
Electroencephalogram Eeg

Event-Related Desynchronization (ERD) or Electroencephalogram (EEG) wavelet is essential for motor imagery (MI) classification and BMI (Brain–Machine Interface) application. However, it is difficult to recognize multiple tasks for non-trained subjects that are indispensable for the complexities of the task or the uncertainties in the environment. The subject-independent scenario, where an inter-subject trained model can be directly applied to new users without precalibration, is particularly desired. Therefore, this paper focuses on an effective attention mechanism which can be applied to a subject-independent set to learn EEG motor imagery features. Firstly, a custom form of sequence inputs with spatial and temporal dimensions is adopted for dual headed attention via deep convolution net (DHDANet). Secondly, DHDANet simultaneously learns temporal and spacial features. The features of spacial attention on each input head are divided into two parts for spatial attentional learning subsequently. The proposed model is validated based on the EEG-MI signals collected from 54 subjects in two sessions with 200 trials in each sessions. The classification of left and right hand motor imagery in this paper achieves an average accuracy of 75.52%, a significant improvement compared to state-of-the-art methods. In addition, the visualization of the frequency analysis method demonstrates that the temporal-convolution and spectral-attention is capable of identifying the ERD for EEG-MI. The proposed machine learning structure enables cross-session and cross-subject classification and makes significant progress in the BMI transfer learning problem.

Simulation of sports movement training based on machine learning and brain-computer interface

2020 ◽  
pp. 1-12
Author(s):  
Linuo Wang
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Joint Learning ◽  
Scientific Methods ◽  
Learning Framework ◽  
Brain Functions ◽  
Movement Training ◽  
Practical Effect ◽  
Machine Interface ◽  
The Brain

Injuries and hidden dangers in training have a greater impact on athletes ’careers. In particular, the brain function that controls the motor function area has a greater impact on the athlete ’s competitive ability. Based on this, it is necessary to adopt scientific methods to recognize brain functions. In this paper, we study the structure of motor brain-computer and improve it based on traditional methods. Moreover, supported by machine learning and SVM technology, this study uses a DSP filter to convert the preprocessed EEG signal X into a time series, and adjusts the distance between the time series to classify the data. In order to solve the inconsistency of DSP algorithms, a multi-layer joint learning framework based on logistic regression model is proposed, and a brain-machine interface system of sports based on machine learning and SVM is constructed. In addition, this study designed a control experiment to improve the performance of the method proposed by this study. The research results show that the method in this paper has a certain practical effect and can be applied to sports.

scholarly journals Insights into the combination of neuromuscular electrical stimulation and motor imagery in a training-based approach

2021 ◽  
Author(s):  
Amandine Bouguetoch ◽  
Alain Martin ◽  
Sidney Grosprêtre
Keyword(s):  
Electrical Stimulation ◽  
Motor Imagery ◽  
Neural Plasticity ◽  
Neuromuscular Electrical Stimulation ◽  
Voluntary Contraction ◽  
Muscle Architecture ◽  
Fascicle Length ◽  
Before And After ◽  
V Wave ◽  
And Control

Abstract Introduction Training stimuli that partially activate the neuromuscular system, such as motor imagery (MI) or neuromuscular electrical stimulation (NMES), have been previously shown as efficient tools to induce strength gains. Here the efficacy of MI, NMES or NMES + MI trainings has been compared. Methods Thirty-seven participants were enrolled in a training program of ten sessions in 2 weeks targeting plantar flexor muscles, distributed in four groups: MI, NMES, NMES + MI and control. Each group underwent forty contractions in each session, NMES + MI group doing 20 contractions of each modality. Before and after, the neuromuscular function was tested through the recording of maximal voluntary contraction (MVC), but also electrophysiological and mechanical responses associated with electrical nerve stimulation. Muscle architecture was assessed by ultrasonography. Results MVC increased by 11.3 ± 3.5% in NMES group, by 13.8 ± 5.6% in MI, while unchanged for NMES + MI and control. During MVC, a significant increase in V-wave without associated changes in superimposed H-reflex has been observed for NMES and MI, suggesting that neural adaptations occurred at supraspinal level. Rest spinal excitability was increased in the MI group while decreased in the NMES group. No change in muscle architecture (pennation angle, fascicle length) has been found in any group but muscular peak twitch and soleus maximal M-wave increased in the NMES group only. Conclusion Finally, MI and NMES seem to be efficient stimuli to improve strength, although both exhibited different and specific neural plasticity. On its side, NMES + MI combination did not provide the expected gains, suggesting that their effects are not simply cumulative, or even are competitive.

scholarly journals Evaluation of Individualized Functional Electrical Stimulation-Induced Acute Changes during Walking: A Case Series in Children with Cerebral Palsy

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4452
Author(s):  
Nicole Zahradka ◽  
Ahad Behboodi ◽  
Ashwini Sansare ◽  
Samuel C. K. Lee
Keyword(s):  
Cerebral Palsy ◽  
Electrical Stimulation ◽  
Functional Electrical Stimulation ◽  
Physical Therapists ◽  
Physical Therapist ◽  
Case Series ◽  
Phase Detection ◽  
Lower Extremity Muscle ◽  
Children With Cerebral Palsy ◽  
Muscle Groups

Functional electrical stimulation (FES) walking interventions have demonstrated improvements to gait parameters; however, studies were often confined to stimulation of one or two muscle groups. Increased options such as number of muscle groups targeted, timing of stimulation delivery, and level of stimulation are needed to address subject-specific gait deviations. We aimed to demonstrate the feasibility of using a FES system with increased stimulation options during walking in children with cerebral palsy (CP). Three physical therapists designed individualized stimulation programs for six children with CP to target participant-specific gait deviations. Stimulation settings (pulse duration and current) were tuned to each participant. Participants donned our custom FES system that utilized gait phase detection to control stimulation to lower extremity muscle groups and walked on a treadmill at a self-selected speed. Motion capture data were collected during walking with and without the individualized stimulation program. Eight gait metrics and associated timing were compared between walking conditions. The prescribed participant-specific stimulation programs induced significant change towards typical gait in at least one metric for each participant with one iteration of FES-walking. FES systems with increased stimulation options have the potential to allow the physical therapist to better target the individual’s gait deviations than a one size fits all device.

scholarly journals The Benefits of Neuromuscular Electrical Stimulation in the Muscular and Functional Capacity of Patients With Liver Cirrhosis: Protocol for a Randomized Clinical Trial

2018 ◽  
Vol 11 ◽  
pp. 117955221881183
Author(s):  
Carolina Luana de Mello ◽  
Thaís Martins Albanaz da Conceição ◽  
Tarcila Dal Pont ◽  
Catherine Corrêa Peruzzolo ◽  
Mariana Nunes Lúcio ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Pulmonary Function ◽  
Functional Capacity ◽  
Neuromuscular Electrical Stimulation ◽  
Rectus Femoris ◽  
Training Group ◽  
Functional Independence ◽  
Peripheral Muscle ◽  
Ultrasound Evaluation ◽  
Daily Physical Activities

Cirrhosis causes systemic and metabolic changes that culminate in various complications, such as compromised pulmonary function, ascites, hepatic encephalopathy, weight loss, and muscle weakness with significant physical function limitations. Our aim is to evaluate the effects of training with neuromuscular electrical stimulation (NMES) on the muscular and functional capacity of patients with cirrhosis classified as Child-Pugh B and C. A total of 72 patients diagnosed with cirrhosis will be recruited and randomized to perform an NMES protocol for 50 minutes, 3 times a week, for 4 weeks. The evaluations will be performed at the beginning and after 12 sessions, and patients will be submitted to a pulmonary function test, an ultrasound evaluation of the rectus femoris, an evaluation of peripheral muscle strength, a submaximal exercise capacity test associated with an evaluation of peripheral tissue oxygenation, a quality of life evaluation, and orientation about monitoring daily physical activities. The evaluators and patients will be blinded to the allocation of the groups. Training Group will be treated with the following parameters: frequency of 50 Hz, pulse width of 400 μs, rise and fall times of 2 s, and on:off 1:1; Sham Group: 5 Hz, 100 μs, on:off 1:3. The data will be analyzed using the principles of the intention to treat. This study provides health professionals with information on the benefits of this intervention. In this way, we believe that the results of this study could stimulate the use of NMES as a way of rehabilitating patients with more severe cirrhosis, with the objective of improving these patients’ functional independence.

Effect of electrical stimulation on intracellular triacylglycerol in isolated skeletal muscle

1990 ◽  
Vol 68 (1) ◽  
pp. 348-354 ◽  
Author(s):  
J. F. Hopp ◽  
W. K. Palmer
Keyword(s):  
Skeletal Muscle ◽  
Electrical Stimulation ◽  
Glucose Control ◽  
Muscle Preparation ◽  
Bicarbonate Buffer ◽  
Intermittent Stimulation ◽  
Flexor Digitorum Brevis ◽  
Muscle Groups ◽  
Flexor Digitorum

The contribution of intracellular triacylglycerol (TG) as a substrate for skeletal muscle during electrical stimulation is equivocal. Therefore, the purpose of this study was to investigate the effect of electrical stimulation on the TG content in the isolated intact rat flexor digitorum brevis skeletal muscle preparation by use of two different stimulation protocols. Muscles were electrically stimulated for 1 h either continuously at 1 Hz or intermittently (30 s on, 60 s off) at 5 Hz while incubated in 21 degrees C Krebs bicarbonate buffer (pH 7.4) that contained 11 mM glucose. Control muscles were either frozen immediately after excision or incubated for 1 h. TG content was significantly decreased (P less than 0.05) compared with control concentrations in both stimulated muscle groups, with the greatest reduction (60%) occurring after 5-Hz intermittent stimulation. These data indicate that intramuscular TG is hydrolyzed in response to electrical stimulation in the isolated flexor digitorum brevis muscle preparation. In addition, the type of stimulation (higher frequency intermittent vs. lower frequency continuous) employed influences the amount of intracellular TG hydrolyzed.

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