EEG correlates of postural audio-biofeedback

Cortical activity in body balance tasks as a function of motor and cognitive demands: A systematic review

Technological tools, like electroencephalography and functional near-infrared spectroscopy, have deepened our understanding of cortical regions involved in balance control. In this systematic literature review, we aimed to identify the prevalent cortical areas activated during balance tasks with specific motor or cognitive demands. Our search strategy encompassed terms related to balance control and cortical activity, yielding 2250 results across five databases. After screening, 67 relevant articles were included in the review. Results indicated that manipulations of visual and/or somatosensory information led to prevalent activity in the parietal, frontal and temporal regions; manipulations of the support base led to prevalent activity of the parietal and frontal regions; both balance-cognitive dual-tasking and reactive responses to extrinsic perturbations led to prevalent activity in the frontal and central regions. These findings deepen our comprehension of the cortical regions activated to manage the complex demands of maintaining body balance in the performance of tasks posing specific requirements. By understanding these cortical activation patterns, researchers and clinicians can develop targeted interventions for balance-related disorders.

EEG Dynamics of Locomotion and Balancing: Solution to Neuro-Rehabilitation

The past decade has witnessed tremendous growth in analyzing the cortical representation of human locomotion and balance using Electroencephalography (EEG). With the advanced developments in miniaturized electronics, wireless brain recording systems have been developed for mobile recordings, such as in locomotion. In this review, the cortical dynamics during locomotion are presented with extensive focus on motor imagery, and employing the treadmill as a tool for performing different locomotion tasks. Further, the studies that examine the cortical dynamics during balancing, focusing on two types of balancing tasks, ie, static and dynamic, with the challenges in sensory inputs and cognition (dual-task), are presented. Moreover, the current literature demonstrates the advancements in signal processing methods to detect and remove the artifacts from EEG signals. Prior studies show the electrocortical sources in the anterior cingulate, posterior parietal, and sensorimotor cortex was found to be activated during locomotion. The event-related potential has been observed to increase in the fronto-central region for a wide range of balance tasks. The advanced knowledge of cortical dynamics during mobility can benefit various application areas such as neuroprosthetics and gait/balance rehabilitation. This review will be beneficial for the development of neuroprostheses, and rehabilitation devices for patients suffering from movement or neurological disorders.

Accelerometry applications and methods to assess standing balance in older adults and mobility-limited patient populations: a narrative review

Accelerometers provide an opportunity to expand standing balance assessments outside of the laboratory. The purpose of this narrative review is to show that accelerometers are accurate, objective, and accessible tools for balance assessment. Accelerometry has been validated against current gold standard technology, such as optical motion capture systems and force plates. Many studies have been conducted to show how accelerometers can be useful for clinical examinations. Recent studies have begun to apply classification algorithms to accelerometry balance measures to discriminate populations at risk for falls. In addition to healthy older adults, accelerometry can monitor balance in patient populations such as Parkinson's disease, multiple sclerosis, and traumatic brain injury. The lack of software packages or easy-to-use applications have hindered the shift into the clinical space. Lack of consensus on outcome metrics has also slowed the clinical adoption of accelerometer-based balance assessments. Future studies should focus on metrics that are most helpful to evaluate balance in specific populations and protocols that are clinically efficacious.

Objective Evaluation of Obstacle Perception Using Spontaneous Body Movements of Blind People Evoked by Movements of Acoustic Virtual Wall

Obstacle perception using sound is the ability to detect silent objects, such as walls and poles. It is very important for blind people to recognize their environment using acoustic information through their auditory sense when walking or conducting various daily activities. In this paper, to develop an objective method for evaluating the degree of obstacle perception acquisition in the education and rehabilitation of the blind, the authors measured the spontaneous body movements evoked by the approach of an acoustic virtual wall. Ten blind persons who have experienced obstacle perception in their daily life, and seven sighted persons with no such experience participated in the experiment. The reciprocal (approach and receding) movements of the virtual wall were presented using simulated reflected sound, and the spontaneous body movements of the subjects were measured. As the results indicate, eight of the ten blind participants showed large maximum values for the correlation function between the wall and their body movements, whereas six of the seven sighted participants showed small maximum values. These results indicate that body movements can be used for an objective evaluation of obstacle perception. In particular, it was determined that the maximum value of the correlation function is the most appropriate for such an evaluation, because it does not depend on the subject’s physique.

Differentiation in Theta and Beta Electrocortical Activity between Visual and Physical Perturbations to Walking and Standing Balance

Human balance is a complex process in healthy adults, requiring precisely timed coordination among sensory information, cognitive processing, and motor control. It has been difficult to quantify brain dynamics during human balance control due to limitations in brain-imaging modalities. The goal of this study was to determine whether by using high-density electroencephalography (EEG) and independent component analysis, we can identify common cortical responses to visual and physical balance perturbations during walking and standing. We studied the responses of 30 healthy young adults to sensorimotor perturbations that challenged their balance. Subjects performed four 10 min trials of beam walking and tandem stance while either being mediolaterally pulled at the waist or viewing brief 20° field-of-view rotations in virtual reality. We recorded high-density EEG, motion capture, lower leg electromyography (EMG), and neck EMG. We hypothesized that both physical pull and visual rotation perturbations would elicit time-frequency fluctuations in theta (4-8 Hz) and beta (13-30 Hz) bands, with increased occipito-parietal activity during visual rotations compared with pull perturbations. Our results confirmed this hypothesis. For both perturbations, we found early theta synchronization and late alpha-beta (8-30 Hz) desynchronization following perturbation onset. This pattern was strongest in occipito-parietal areas during visual perturbations and strongest in sensorimotor areas during pull perturbations. These results suggest a similar time-frequency electrocortical pattern when humans respond to sensorimotor conflict, but with substantive differences in the brain areas involved for visual versus physical perturbations. Our findings may have important implications for assessing and training balance in individuals with and without motor disabilities.

BIARAM: A process for analyzing correlated brain regions using association rule mining

BACKGROUND AND OBJECTIVE

Because examining correlated (vs. individual) brain activity is a superior method for locating neural correlates of a stimulus, using a network approach for analyzing brain activity is gaining interest. In this study, we propose and illustrate the use of association rule mining (ARM) to analyze brain regions that are activated simultaneously. ARM is commonly used in marketing and other disciplines to help determine items that might be purchased together. We apply this technique toward identifying correlated brain regions that may respond simultaneously to specific stimuli. Our objective is to introduce ARM, describe a process for converting neural images into viable datasets (for analyses), and suggest how to apply this process for generating insights about the brain's responses to specific stimuli (e.g. technology-associated interruptions).

METHODS

We analyze electroencephalogram (EEG) data collected from 46 participants; convert brain waves into images via a source localization algorithm known as sLORETA (i.e., standardized low-resolution brain electromagnetic tomography); reorganize these into a "transactional" dataset; and generate association rules through ARM.

RESULTS

We compare the results with more conventional methods for analyzing neuroimaging data. We show that there is a stronger correlation between frontal lobe and sublobar/insula regions after interruptions. This result would not be obvious from independent analysis of each region.

CONCLUSIONS

The main contribution of this paper is introducing ARM as a method for analyzing multiple images. We suggest that the biomedical community may apply this commonly available data mining technique to develop further insights about correlated regions affected by specific stimuli.

Neuroimaging of Human Balance Control: A Systematic Review

This review examined 83 articles using neuroimaging modalities to investigate the neural correlates underlying static and dynamic human balance control, with aims to support future mobile neuroimaging research in the balance control domain. Furthermore, this review analyzed the mobility of the neuroimaging hardware and research paradigms as well as the analytical methodology to identify and remove movement artifact in the acquired brain signal. We found that the majority of static balance control tasks utilized mechanical perturbations to invoke feet-in-place responses (27 out of 38 studies), while cognitive dual-task conditions were commonly used to challenge balance in dynamic balance control tasks (20 out of 32 studies). While frequency analysis and event related potential characteristics supported enhanced brain activation during static balance control, that in dynamic balance control studies was supported by spatial and frequency analysis. Twenty-three of the 50 studies utilizing EEG utilized independent component analysis to remove movement artifacts from the acquired brain signals. Lastly, only eight studies used truly mobile neuroimaging hardware systems. This review provides evidence to support an increase in brain activation in balance control tasks, regardless of mechanical, cognitive, or sensory challenges. Furthermore, the current body of literature demonstrates the use of advanced signal processing methodologies to analyze brain activity during movement. However, the static nature of neuroimaging hardware and conventional balance control paradigms prevent full mobility and limit our knowledge of neural mechanisms underlying balance control.

Effects of magnitude and magnitude predictability of postural perturbations on preparatory cortical activity in older adults with and without Parkinson's disease

The goal of this study was to identify whether impaired cortical preparation may relate to impaired scaling of postural responses of people with Parkinson's disease (PD). We hypothesized that impaired scaling of postural responses in participants with PD would be associated with impaired set-dependent cortical activity in preparation for perturbations of predictable magnitudes. Participants performed postural responses to backward surface translations. We examined the effects of perturbation magnitude (predictable small vs. predictable large) and predictability of magnitude (predictable vs. unpredictable-in-magnitude) on postural responses (center-of-pressure (CoP) displacements) and on preparatory electroencephalographic (EEG) measures of contingent negative variation (CNV) and alpha and beta event-related desynchronization (ERD). Our results showed that unpredictability of perturbation magnitude, but not the magnitude of the perturbation itself, was associated with increased CNV amplitude at the CZ electrode in both groups. While control participants scaled their postural responses to the predicted magnitude of the perturbation, their condition-related changes in CoP displacements were not correlated with condition-related changes in EEG preparatory activity (CNV or ERD). In contrast, participants with PD did not scale their postural responses to the predicted magnitude of the perturbation, but they did demonstrate greater beta ERD in the condition of predictably small-magnitude perturbations and greater beta ERD than the control participants at the CZ electrode. In addition, increased beta ERD in PD was associated with decreased adaptability of postural responses, suggesting that preparatory cortical activity may have a more direct influence on postural response scaling for people with PD than for control participants.

Wearable systems with minimal set-up for monitoring and training of balance and mobility

With the objective to release solutions which can be easily manageable by their final users, including older users, we worked to design methods and devices which rely on a minimal set-up for monitoring and rehabilitation of balance and mobility. A single inertial sensing unit, typically worn on the trunk, was hence engineered to accomplish for activity monitoring and event detection (including fall detection), tremor rejection, instrumented clinical tests (e.g. stabilometry, Timed-Up and Go), and sensory biofeedback (audio, visual or tactile). The sensing unit is wirelessly connected with a processing unit, which can in turn act as a gateway to remote applications or caregivers. Promising results were obtained, which may pave the way to novel intensive and pervasive neurorehabilitation strategies.