scholarly journals Investigating the impact of feedback update interval on the efficacy of restorative brain–computer interfaces

2017 ◽  
Vol 4 (8) ◽  
pp. 170660 ◽  
Author(s):  
Sam Darvishi ◽  
Michael C. Ridding ◽  
Brenton Hordacre ◽  
Derek Abbott ◽  
Mathias Baumert
Keyword(s):  
Sensory Feedback ◽  
Motor Evoked Potentials ◽  
Single Case ◽  
Maximum Voluntary Contraction ◽  
Voluntary Contraction ◽  
Brain Computer Interfaces ◽  
Computer Interfaces ◽  
Timely Fashion ◽  
Clinically Significant ◽  
The Impact

Restorative brain–computer interfaces (BCIs) have been proposed to enhance stroke rehabilitation. Restorative BCIs are able to close the sensorimotor loop by rewarding motor imagery (MI) with sensory feedback. Despite the promising results from early studies, reaching clinically significant outcomes in a timely fashion is yet to be achieved. This lack of efficacy may be due to suboptimal feedback provision. To the best of our knowledge, the optimal feedback update interval (FUI) during MI remains unexplored. There is evidence that sensory feedback disinhibits the motor cortex. Thus, in this study, we explore how shorter than usual FUIs affect behavioural and neurophysiological measures following BCI training for stroke patients using a single-case proof-of-principle study design. The action research arm test was used as the primary behavioural measure and showed a clinically significant increase (36%) over the course of training. The neurophysiological measures including motor evoked potentials and maximum voluntary contraction showed distinctive changes in early and late phases of BCI training. Thus, this preliminary study may pave the way for running larger studies to further investigate the effect of FUI magnitude on the efficacy of restorative BCIs. It may also elucidate the role of early and late phases of motor learning along the course of BCI training.

The strength of the corticospinal coherence depends on the predictability of modulated isometric forces

2013 ◽  
Vol 109 (6) ◽  
pp. 1579-1588 ◽  
Author(s):  
Ignacio Mendez-Balbuena ◽  
Jose Raul Naranjo ◽  
Xi Wang ◽  
Agnieska Andrykiewicz ◽  
Frank Huethe ◽  
...  
Keyword(s):  
Sensory Feedback ◽  
Muscle Activation ◽  
Maximum Voluntary Contraction ◽  
Voluntary Contraction ◽  
Visuomotor Task ◽  
Gamma Range ◽  
Cortical Motor ◽  
Contralateral Hand ◽  
Hand Motor Area ◽  
Isometric Forces

Isometric compensation of predictably frequency-modulated low forces is associated with corticomuscular coherence (CMC) in beta and low gamma range. It remains unclear how the CMC is influenced by unpredictably modulated forces, which create a mismatch between expected and actual sensory feedback. We recorded electroencephalography from the contralateral hand motor area, electromyography (EMG), and the motor performance of 16 subjects during a visuomotor task in which they had to isometrically compensate target forces at 8% of the maximum voluntary contraction with their right index finger. The modulated forces were presented with predictable or unpredictable frequencies. We calculated the CMC, the cortical motor alpha-, beta-, and gamma-range spectral powers (SP), and the task-related desynchronization (TRD), as well as the EMG SP and the performance. We found that in the unpredictable condition the CMC was significantly lower and associated with lower cortical motor SP, stronger TRD, higher EMG SP, and worse performance. The findings suggest that due to the mismatch between predicted and actual sensory feedback leading to higher computational load and less stationary motor state, the unpredictable modulation of the force leads to a decrease in corticospinal synchrony, an increase in cortical and muscle activation, and a worse performance.

scholarly journals Crossfit Practice: An Electromyographic Analysis of Masticatory Muscles

2020 ◽  
Author(s):  
Nayara Soares da Silva ◽  
Marcelo Palinkas ◽  
Evandro Marianetti Fioco ◽  
Edson Donizetti Verri ◽  
Saulo César Vallin Fabrin ◽  
...  
Keyword(s):  
Maximum Voluntary Contraction ◽  
Masticatory Muscles ◽  
Voluntary Contraction ◽  
Control Group ◽  
Electromyographic Activity ◽  
Physical Conditioning ◽  
Striated Muscles ◽  
Functional Changes ◽  
Significant Difference ◽  
The Impact

Abstract Background: CrossFit is a regular high-intensity physical conditioning exercise for skeletal striated muscles, which promotes functional changes in the human body. The aim of this study was to investigate the impact of CrossFit exercise on the electromyographic activity of the masseter and temporalis muscles. Methods: Forty participants were divided into two groups: athletes who practiced CrossFit (n=20) and controls who did not practice sports (n=20). The electromyographic activities of the masseter and temporalis muscles were measured using mandibular tasks at rest, protrusion, right laterality, left laterality, and dental clenching in maximum voluntary contraction and habitual chewing of peanuts and raisins. Both the groups were matched for age, sex, and body mass index. The data were analyzed using the t-test with a 5% significance level. Results: Reduced electromyographic activities were found in all mandibular tasks in the CrossFit group than in the control group, with a significant difference for the right masseter (p=0.01), left masseter (p=0.001), and left temporal muscles (p=0.001) at mandibular rest; right (p=0.001) and left (p=0.001) masseter in chewing of peanuts. Conclusion: The results of this study suggest that CrossFit promotes positive changes in electromyographic activity of the masticatory muscles, especially in the mandibular rest and chewing of hard food. CrossFit exercise practiced within the appropriate technical protocols improves masticatory muscle function.

scholarly journals Noise-based cyberattacks generating fake P300 waves in brain–computer interfaces

2021 ◽  
Author(s):  
Enrique Tomás Martínez Beltrán ◽  
Mario Quiles Pérez ◽  
Sergio López Bernal ◽  
Alberto Huertas Celdrán ◽  
Gregorio Martínez Pérez
Keyword(s):  
At Risk ◽  
Acquisition Phase ◽  
Brain Computer Interfaces ◽  
Proper Functioning ◽  
Computer Interfaces ◽  
Electroencephalographic Signals ◽  
The Impact

AbstractMost of the current Brain–Computer Interfaces (BCIs) application scenarios use electroencephalographic signals (EEG) containing the subject’s information. It means that if EEG were maliciously manipulated, the proper functioning of BCI frameworks could be at risk. Unfortunately, it happens in frameworks sensitive to noise-based cyberattacks, and more efforts are needed to measure the impact of these attacks. This work presents and analyzes the impact of four noise-based cyberattacks attempting to generate fake P300 waves in two different phases of a BCI framework. A set of experiments show that the greater the attacker’s knowledge regarding the P300 waves, processes, and data of the BCI framework, the higher the attack impact. In this sense, the attacker with less knowledge impacts 1% in the acquisition phase and 4% in the processing phase, while the attacker with the most knowledge impacts 22% and 74%, respectively.

An Analysis of the Impact of Brain-Computer Interfaces on Autonomy

Neuroethics ◽  
2018 ◽  
Author(s):  
Orsolya Friedrich ◽  
Eric Racine ◽  
Steffen Steinert ◽  
Johannes Pömsl ◽  
Ralf J. Jox
Keyword(s):  
Brain Computer Interfaces ◽  
Computer Interfaces ◽  
The Impact

Brain-Computer Interfaces With Multi-Sensory Feedback for Stroke Rehabilitation: A Case Study

2017 ◽  
Vol 41 (11) ◽  
pp. E178-E184 ◽  
Author(s):  
Danut C. Irimia ◽  
Woosang Cho ◽  
Rupert Ortner ◽  
Brendan Z. Allison ◽  
Bogdan E. Ignat ◽  
...  
Keyword(s):  
Stroke Rehabilitation ◽  
Sensory Feedback ◽  
Brain Computer Interfaces ◽  
Computer Interfaces

scholarly journals Breaching Subjects’ Thoughts Privacy: A Study with Visual Stimuli and Brain-Computer Interfaces

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Mario Quiles Pérez ◽  
Enrique Tomás Martínez Beltrán ◽  
Sergio López Bernal ◽  
Alberto Huertas Celdrán ◽  
Gregorio Martínez Pérez
Keyword(s):  
Evoked Potentials ◽  
Visual Stimuli ◽  
System Response ◽  
Sensitive Information ◽  
Brain Computer Interfaces ◽  
Sensitive Data ◽  
Computer Interfaces ◽  
Clinical Scenarios ◽  
Important Challenge ◽  
The Impact

Brain-computer interfaces (BCIs) started being used in clinical scenarios, reaching nowadays new fields such as entertainment or learning. Using BCIs, neuronal activity can be monitored for various purposes, with the study of the central nervous system response to certain stimuli being one of them, being the case of evoked potentials. However, due to the sensitivity of these data, the transmissions must be protected, with blockchain being an interesting approach to ensure the integrity of the data. This work focuses on the visual sense, and its relationship with the P300 evoked potential, where several open challenges related to the privacy of subjects’ information and thoughts appear when using BCI. The first and most important challenge is whether it would be possible to extract sensitive information from evoked potentials. This aspect becomes even more challenging and dangerous if the stimuli are generated when the subject is not aware or conscious that they have occurred. There is an important gap in this regard in the literature, with only one work existing dealing with subliminal stimuli and BCI and having an unclear methodology and experiment setup. As a contribution of this paper, a series of experiments, five in total, have been created to study the impact of visual stimuli on the brain tangibly. These experiments have been applied to a heterogeneous group of ten subjects. The experiments show familiar visual stimuli and gradually reduce the sampling time of known images, from supraliminal to subliminal. The study showed that supraliminal visual stimuli produced P300 potentials about 50% of the time on average across all subjects. Reducing the sample time between images degraded the attack, while the impact of subliminal stimuli was not confirmed. Additionally, younger subjects generally presented a shorter response latency. This work corroborates that subjects’ sensitive data can be extracted using visual stimuli and P300.

Force Capacity of Back Extensor Muscles in Healthy Males: Effects of Age and Recovery Time

2014 ◽  
Vol 30 (6) ◽  
pp. 713-721 ◽  
Author(s):  
Eduard Kurz ◽  
Christoph Anders ◽  
Mario Walther ◽  
Philipp Schenk ◽  
Hans-Christoph Scholle
Keyword(s):  
Recovery Time ◽  
Maximum Voluntary Contraction ◽  
Age Groups ◽  
Voluntary Contraction ◽  
Upper Body ◽  
Normative Values ◽  
Mean Values ◽  
The Impact ◽  
Back Extensor ◽  
Healthy Males

To judge a person’s maximum trunk extension performance as either age-appropriate or deconditioned is challenging. The current study aimed at determining age and anthropometrically adjusted maximum voluntary contraction (MVC) of back extensors considering the number and recovery time between trials. Thirty-one younger (20–30 years) and 33 older (50–60 years) healthy males performed five repetitions of maximal isometric trunk extensions in an upright standing position with randomized recovery times ranging between one to five minutes at one minute intervals. Torque values were normalized according to the individual’s upper body mass resulting in upper body torque ratios (UBTR). To evaluate the impact of age, recovery time, and fatigue on UBTR we applied a linear mixed-effects model. Based on surface EMG data muscular fatigue could be excluded for both groups. For all MVC trials, UBTR levels differed significantly between age groups (range of mean values: younger: 2.26–2.28, older: 1.78–1.87, effect size: 1.00) but were independent from recovery time. However, the older males tended to exert higher UBTR values after shorter recovery periods. The study provides normative values of anthropometrically and age-group adjusted maximum back extensor forces. For the investigated groups, only two MVC trials with a recovery time of about one minute seem appropriate.

scholarly journals Recruitment Curves during Different Types of Muscle Activity in Non-dominant Hand: A Transcranial Magnetic Stimulation Study

2020 ◽  
Vol 24 (4) ◽  
pp. 393-402
Author(s):  
Kapka Mancheva ◽  
◽  
Teodora Vukova ◽  
Georgi Atanasov ◽  
Andon Kossev ◽  
...  
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Muscle Activity ◽  
Magnetic Stimulation ◽  
Motor Evoked Potentials ◽  
Maximum Voluntary Contraction ◽  
Voluntary Contraction ◽  
Dominant Hand ◽  
Antagonist Muscles ◽  
Co Activation ◽  
Different Types

Motor evoked potentials (MEPs) were recorded from first dorsal interosseous muscle of non-dominant hand in response to contralateral transcranial magnetic stimulation (TMS) in seven right-handed healthy volunteers during relaxed muscles (without electromyorgaphic activity and zero force production), isometric index finger abduction (20% of individual measured maximum voluntary contraction in direction of abduction) and co-activation of antagonist muscles (simultaneously activated antagonist muscles, matching level equal to 20% of individual measured maximum voluntary contraction in direction of abduction by increasing the angle stiffness without producing of external force). The excitability of motor cortex was assessed by the amplitudes of MEPs recorded in response to increasing stimulation intensity: 100%, 110%, 120%, 130%, 140% of individually measured motor threshold at relax. The aim of the present study was using the method of transcranial magnetic stimulation to investigate the effect of different types of muscle activity in non-dominant hand. The secondary purpose was to compare new collected data with our previous data about dominant hand. At non-dominant hand we found significant changes between relax condition and each of the two active motor tasks almost at all five investigated TMS intensities. Also, we found that MEP amplitudes during abduction were significantly bigger than MEP amplitudes during co-activation of antagonist muscles, both in non-dominant hand and in dominant hand. We observed changes between MEP amplitudes of non-dominant and dominant hand during the performance of the same motor task.

scholarly journals Vividness of Visual Imagery and Personality Impact Motor-Imagery Brain Computer Interfaces

2021 ◽  
Vol 15 ◽  
Author(s):  
Nikki Leeuwis ◽  
Alissa Paas ◽  
Maryam Alimardani
Keyword(s):  
Motor Imagery ◽  
Visual Imagery ◽  
Personality Factors ◽  
Classification Error ◽  
Imagery Task ◽  
Brain Computer Interfaces ◽  
Classification Error Rate ◽  
Psychological Measures ◽  
Computer Interfaces ◽  
The Impact

Brain-computer interfaces (BCIs) are communication bridges between a human brain and external world, enabling humans to interact with their environment without muscle intervention. Their functionality, therefore, depends on both the BCI system and the cognitive capacities of the user. Motor-imagery BCIs (MI-BCI) rely on the users’ mental imagination of body movements. However, not all users have the ability to sufficiently modulate their brain activity for control of a MI-BCI; a problem known as BCI illiteracy or inefficiency. The underlying mechanism of this phenomenon and the cause of such difference among users is yet not fully understood. In this study, we investigated the impact of several cognitive and psychological measures on MI-BCI performance. Fifty-five novice BCI-users participated in a left- versus right-hand motor imagery task. In addition to their BCI classification error rate and demographics, psychological measures including personality factors, affinity for technology, and motivation during the experiment, as well as cognitive measures including visuospatial memory and spatial ability and Vividness of Visual Imagery were collected. Factors that were found to have a significant impact on MI-BCI performance were Vividness of Visual Imagery, and the personality factors of orderliness and autonomy. These findings shed light on individual traits that lead to difficulty in BCI operation and hence can help with early prediction of inefficiency among users to optimize training for them.

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