Effects of Computerized Biofeedback-based Balance Intervention on the Muscle Coactivation Patterns during Dynamic Postural Control in Traumatic Brain Injury.

Balance Dysfunction (BDF) is a severe conse-quence of Traumatic Brain Injury (TBI) that significantly increases the falls risk. However, the neuromuscular mecha-nisms of the BDF are not adequately researched. Therefore, in this study, our objective was to investigate the effects of a Computerized Biofeedback-based Balance Intervention (CBBI) on the muscle coactivation patterns in a group of TBI participants. This study presents the findings from 13 TBI individuals randomized into the Intervention group (TBI - INT, N=6) and Control group (TBI-CTL, N=7). Using a computerized posturography platform (Neurocom Balance Master) during baseline and follow-up assessment visits, the participant's pos-tural response to anterior-posterior balance perturbations were recorded in a multimodal setup including electroencephalogra-phy (EEG), electromyography (EMG), and the platform sway in terms of center of pressure (COP). The muscle responses were recorded from lower-limb muscles, including tibialis an-terior (TA) and gastrocnemius (GAST), whose coactivation was computed using a metric called Co-Contraction Index (CCI). Clinical outcome measures such as Berg Balance Scale (BBS), 10 Meter Walk Test (10MWT), and Timed Up-and-Go (TUG) tests were used to evaluate functional balance and mobility. The comparison of CCI values across time points (baseline and follow-up) revealed a significant decrease (p<0.01) in the TBI-INT group but not TBI-CTL. The intervention-related changes in CCI correlated with the changes in BBS score (from baseline to follow-up). These preliminary findings demonstrate that the CBBI training may help postural stability by facilitating the coactivation between muscles involved in postural control. Clinical relevance- The current knowledge of changes in the neuromuscular response to balance perturbation in TBI is limited. Our study opens the possibility of using the muscle CCI metric to evaluate the muscle response in individuals with impaired balance.

Enhancing sensory acuity and balance function using near-sensory biofeedback-based perturbation intervention for individuals with traumatic brain injury.

BACGROUND: Interventions addressing balance dysfunction after traumatic brain injury (TBI) only target compensatory aspects and do not investigate perceptual mechanisms such as sensory acuity. OBJECTIVE: To evaluate the efficacy of a novel intervention that integrates sensory acuity with a perturbation-based approach for improving the perception and functional balance after TBI. METHODS: A two-group design was implemented to evaluate the effect of a novel, perturbation-based balance intervention. The intervention group (n = 5) performed the intervention with the sinusoidal (0.33, 0.5, and 1 Hz) perturbations to the base of support with amplitudes derived using our novel outcome of sensory acuity - perturbation perception threshold (PPT). The efficacy is evaluated using changes in PPT and functional outcomes (Berg Balance Scale (BBS), Timed-up and Go (TUG), 5-meter walk test (5MWT), and 10-meter walk test (10MWT)). RESULTS: There was a significant post-intervention change in PPT for 0.33 Hz (p = 0.021). Additionally, clinically and statistically significant improvements in TUG (p = 0.03), 5MWT (p = 0.05), and 10MWT (p = 0.04) were observed. CONCLUSIONS: This study provides preliminary efficacy of a novel, near-sensory balance intervention for individuals with TBI. The use of PPT is suggested for a comprehensive understanding and treatment of balance dysfunction. The promising results support the investigation in a larger cohort.

Improving Perception of Perturbations and Balance Using a Novel Dynamic Computerized Biofeedback Based Intervention after Traumatic Brain Injury.

Traumatic Brain Injury (TBI) impairs the integration and organization of the visual, auditory, and somatosensory inputs that permit body position awareness in relation to self and environment resulting in balance dysfunction (BD). The sensitivity levels to which the environmental perturbations are perceived are also critical for attaining the position awareness and the equilibrium. Undetectable perturbations, however small they may be, can result in fatal falls, especially after TBI. In this investigation, we used a novel dynamic computerized biofeedback based (CBB) intervention aimed at improving the perception of external perturbations, and static and dynamic balance in individuals with TBI. The effect of the CBB intervention on balance was accessed using a clinical measure - Berg Balance Scale (BBS), a novel psychophysical measure - perception of perturbation threshold (PPT), and biomechanical measures derived from center of pressure (COP) data during controlled sinusoidal varied-amplitudes anterior-posterior perturbations of 0.33 Hz, 0.5 Hz, and 1 Hz to the base of support. At baseline, the TBI-Control (TBI-C) group (n=5) and the TBI-Intervention (TBI-I) group (n=2) showed impaired balance compared to the healthy control (HC) group (n=5). This was shown by lower BBS and elevated values of PPT and COP measures (RMS COP, COP velocity, Phase Plane Indices (PPI)). Post CBB intervention, TBI-I group showed increased BBS and reduction in PPTs, COP measures (velocity and PPI), suggesting improvements in postural stability and balance. This investigation explores a potential link between the perception of perturbations and balance and demonstrates the applicability of the CBB intervention for improving interpretation and organization of multisensory information in a task-specific environment to improve balance post-TBI.

Application of Empirical Mode Decomposition Combined With Notch Filtering for Interpretation of Surface Electromyograms During Functional Electrical Stimulation.

The goal of this paper is to demonstrate a novel approach that combines Empirical Mode Decomposition (EMD) with Notch filtering to remove the electrical stimulation (ES) artifact from surface electromyogram (EMG) data for interpretation of muscle responses during functional electrical stimulation (FES) experiments. FES was applied to the rectus femoris (RF) muscle unilaterally of six able bodied (AB) and one individual with spinal cord injury (SCI). Each trial consisted of three repetitions of ES. We hypothesized that the EMD algorithm provides a suitable platform for decomposing the EMG signal into physically meaningful intrinsic mode functions (IMFs) which can be further used to isolate electrical stimulation (ES) artifact. A basic EMD algorithm was used to decompose the EMG signals collected during FES into IMFs for each repetition separately. IMFs most contaminated by ES were identified based on the standard deviation (SD) of each IMF. Each artifact IMF was Notch filtered to filter ES harmonics and added to remaining IMFs containing pure EMG data to get a version of a filtered EMG signal. Of all such versions of filtered signals generated from each artifact IMF, the one with maximum signal to noise ratio (SNR) was chosen as the final output. The validity of the filtered signal was assessed by quantitative metrics, 1) root mean squared error (RMSE) and signal to noise (SNR) ratio values obtained by comparing a clean EMG and EMD-Notch filtered signal from the combination of simulated ES and clean EMG and, 2) using EMG-force correlation analysis on the data collected from AB individuals. Finally, the potential applicability of this algorithm on a neurologically impaired population was shown by applying the algorithm on EMG data collected from an individual with SCI. EMD combined with Notch filtering successfully extracted the EMG signal buried under ES artifact. Filtering performance was validated by smaller RMSE values and greater SNR post filtering. The amplitude values of the filtered EMG signal were seen to be consistent for three repetitions of ES and there was no significant difference among the repetition for all subjects. For the individual with a SCI the algorithm was shown to successfully isolate the underlying bursts of muscle activations during FES. The data driven nature of EMD algorithm and its ability to act as a filter bank at different bandwidths make this method extremely suitable for dissecting ES induced EMG into IMFs. Such IMFs clearly show the presence of ES artifact at different intensities as well as pure artifact free EMG. This allows the application of Notch filters to IMFs containing ES artifact to further isolate the EMG. As a result of such stepwise approach, the extraction of EMG is achieved with minimal data loss. This study provides a unique approach to dissect and interpret the EMG signal during FES applications.

Postural responses after utilization of a computerized biofeedback based intervention aimed at improving static and dynamic balance in traumatic brain injury: a case study.

Balance dysfunction is one of the most disabling aspects of Traumatic Brain Injury (TBI). Without rapid transmission and accurate perception of somatosensory inputs, the automatic postural responses required during standing may be delayed or absent after TBI which can lead to instability. Further, the sensitivity level to which environmental perturbations can be detected is also vital, as the central nervous system will only employ balance control strategies when it perceives a change in equilibrium. Such undetectable perturbations, however small they may be, can result in fatal falls, especially after TBI. In this investigation we used a novel computerized biofeedback based (CBB) intervention aimed at improving perception of external perturbations, and static and dynamic balance in a single male participant with severe TBI. We used an adaptive single interval adjustment matrix (SIAM) protocol to determine the perception of perturbation threshold (PPT) at baseline (1 day pre-intervention) and follow up (1 day post-intervention). External perturbations were provided through sinusoidal translations of 0.5 Hz to the base of support in anterior-posterior direction. Outcome measures included PPT, the Berg balance scale (BBS) and bilateral surface electromyography (EMG) of the lower limbs at baseline and follow up. PPT assessment post intervention showed a decrease in PPT, suggesting an improvement in the ability (gain of 0.42 mm) to detect (even smaller) perturbations which were not perceivable prior to the intervention. There was a significant increase in BBS (6 points) at follow up. The participant demonstrated increased muscle activation for the right gastrocnemius, left soleus, right bicep femoris and left vastus lateralis muscles at follow up. This investigation demonstrate the potential use of the CBB intervention for improving interpretation and organization of multisensory information in a task specific environment to improve balance dysfunction post TBI.

EMG of the tibialis anterior demonstrates a training effect after utilization of a foot drop stimulator.

BACKGROUND: Functional Electrical Stimulation (FES) applied through a foot drop stimulator (FDS) is a rehabilitation intervention that can stimulate the common peroneal nerve to provide dorsiflexion at the correct timing during gait. OBJECTIVE: To determine if FES applied to the peroneal nerve during walking through a FDS would effectively retrain the electromyographic temporal activation of the tibialis anterior in individuals with stroke. METHODS: Surface electromyography (EMG) were collected bilaterally from the tibialis anterior (TA) while participants (n = 4) walked with and without the FDS at baseline and 4 weeks. Comparisons were made between stimulation timing and EMG activation timing to produce a burst duration similarity index (BDSI). RESULTS: At baseline, participants displayed variable temporal activation of the TA. At 4 weeks, TA activation during walking without the FDS more closely resembled the pre-programmed FDS timing demonstrated by an increase in BDSI scores in all participants (P = 0.05). CONCLUSIONS: Continuous use of FDS during a task specific movement can re-train the neuromuscular system. After 4 weeks of utilization the FDS trained the TA to replicate the programmed temporal activation patterns. These findings begin to establish the FDS as a rehabilitation intervention that may facilitate recovery rather than just compensate for stroke related gait impairments due to foot drop.