Arvind Ramanujam

Evaluation of wheelchair tire rolling resistance using dynamometer- based coast-down tests

The objective of this study was to compare the rolling resistance of four common manual wheelchair tires (two pneumatic and two airless solid) and the solid tires used on a commercially available force- and moment-sensing wheel. Coast-down tests were performed with a wheelchair positioned on a two-drum dynamometer. Within each of three load conditions, tire type had a significant effect on rolling resistance (p < 0.001). The pneumatic tires had smaller rolling resistances and were less affected by load increases than the solid tires. Within the two tire types, higher air pressure or firmness and lower profile tread corresponded to less rolling resistance. Wheelchair users, clinicians, and researchers must consider the effect of tire type on wheelchair rolling resistance when selecting a manual wheelchair tire.

Neuromechanical adaptations during a robotic powered exoskeleton assisted walking session

Objective: To evaluate gait parameters and neuromuscular profiles of exoskeleton-assisted walking under Max Assist condition during a single-session for; (i) able bodied (AB) individuals walking assisted with (EXO) and without (non-EXO) a powered exoskeleton, (ii) non-ambulatory SCI individuals walking assisted with a powered exoskeleton. Design: Single-session. Setting: Motion analysis laboratory. Participants: Four AB individuals and four individuals with SCI. Interventions: Powered lower extremity exoskeleton. Outcome Measures: Temporal-spatial parameters, kinematics, walking velocity and electromyography data. Results: AB individuals in exoskeleton showed greater stance time and a significant reduction in walking velocity (P < 0.05) compared to non-EXO walking. Interestingly, when the AB individuals voluntarily assisted the exoskeleton movements, they walked with an increased velocity and lowered stance time to resemble that of slow walking. For SCI individuals, mean percent stance time was higher and walking velocity was lower compared to all AB walking conditions (P < 0.05). There was muscle activation in several lower limb muscles for SCI group. For AB individuals, there were similarities among EXO and non-EXO walking conditions however there were differences in several lower limb EMGs for phasing of muscle activation. Conclusion: The data suggests that our AB individuals experienced reduction in walking velocity and muscle activation amplitudes while walking in the exoskeleton and moreover with voluntary control there is a greater temporal-spatial response of the lower limbs. Also, there are neuromuscular phasic adaptions for both AB and SCI groups while walking in the exoskeleton that are inconsistent to non-EXO gait muscle activation.

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.

Validation of empirical mode decomposition combined with notch filtering to extract electrical stimulation artifact from surface electromyograms during functional electrical stimulation

This paper presents the validity of Empirical Mode Decomposition (EMD) combined 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. 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. The basic EMD algorithm was used to decompose the ES induced EMG signals into IMFs. IMFs most contaminated by ES were identified based on the standard deviation (SD) criterion. An IMF with the maximum signal to noise ratio (SNR) was Notch filtered and added to IMFs containing pure EMG data to get the filtered EMG signal. The method was tested on 5 able bodied (AB) and 2 spinal cord injured (SCI) participants. The validity of the filtered signal was assessed by normalized root mean squared error (NRMSE) and signal to noise (SNR) ratio values obtained by comparing a clean EMG collected during maximum volitional contraction (MVC) and EMD-Notch filtered signal from the combination of a clean EMG with i) simulated ES and, ii) real ES with no activation generated at different ES amplitudes. The results showed that the EMD-Notch filtering approach was successful, reliable and repeatable in extracting pure muscle responses during ES showing improved values for NRMSE and SNR in both AB and SCI individuals.

Training Response to Longitudinal Powered Exoskeleton Training for SCI

The goal of this research is to assess how powered exoskeleton-training for 5 h per week over 20 weeks can change gait parameters to increase walking speed for chronic SCI. Gait parameters include Center of Mass (CoM) excursions, walking velocity, initial double stance time (IDS), single stance time (SS), terminal double stance time (TDS), swing time (SW), and spatial parameters such as step length, step width and stride length. Exoskeleton training had a significant effect on walking velocity due to specific temporal spatial gait parameters (IDS, TDS, Step and Stride Length) and increased stability (CoM).

Alterations in Spectral Attributes of Surface Electromyograms after Utilization of a Foot Drop Stimulator during Post-Stroke Gait

Background A foot drop stimulator (FDS) is a rehabilitation intervention that stimulates the common peroneal nerve to facilitate ankle dorsiflexion at the appropriate time during post-stroke hemiplegic gait. Time–frequency analysis (TFA) of non-stationary surface electromyograms (EMG) and spectral variables such as instantaneous mean frequency (IMNF) can provide valuable information on the long-term effects of FDS intervention in terms of changes in the motor unit (MU) recruitment during gait, secondary to improved dorsiflexion. Objective The aim of this study was to apply a wavelet-based TFA approach to assess the changes in neuromuscular activation of the tibialis anterior (TA), soleus (SOL), and gastrocnemius (GA) muscles after utilization of an FDS during gait post-stroke. Methods Surface EMG were collected bilaterally from the TA, SOL, and GA muscles from six participants (142.9 ± 103.3 months post-stroke) while walking without the FDS at baseline and 6 months post-FDS utilization. Continuous wavelet transform was performed to get the averaged time–frequency distribution of band pass filtered (20–300 Hz) EMGs during multiple walking trials. IMNFs were computed during normalized gait and were averaged during the stance and swing phases. Percent changes in the energies associated with each frequency band of 25 Hz between 25 and 300 Hz were computed and compared between visits. Results Averaged time–frequency representations of the affected TA, SOL, and GA EMG show altered spectral attributes post-FDS utilization during normalized gait. The mean IMNF values for the affected TA were significantly lower than the unaffected TA at baseline (p = 0.026) and follow-up (p = 0.038) during normalized stance. The mean IMNF values significantly increased (p = 0.017) for the affected GA at follow-up during normalized swing. The frequency band of 250–275 Hz significantly increased in the energies post-FDS utilization for all muscles. Conclusion The application of wavelet-based TFA of EMG and outcome measures (IMNF, energy) extracted from the time–frequency distributions suggest alterations in MU recruitment strategies after the use of FDS in individuals with chronic stroke. This further establishes the efficacy of FDS as a rehabilitation intervention that may promote motor recovery in addition to treating the secondary complications of foot drop due to post-stroke hemiplegia.

Neuromotor response of the leg muscles following a supine, stand retraining with/without neuromuscular electrical stimulation training intervention for individuals with SCI: A case series

The goal of this paper is to study the effects of supine and stand retraining (SRT) interventions with and without multi muscle neuromuscular electrical stimulation (NMES) on the neuromuscular EMG responses of the leg muscles for individuals with motor complete SCI during walking on a body-weight support (BWS) treadmill. The main outcome variables were EMG amplitude, integrated EMG and co-contraction indices (co-excitation and co-activation) collected during a 10-minute walking treadmill trial. Data was analyzed for the first, fifth and tenth minute of walking. Results showed that both Supine+NMES and SRT+NMES interventions increased spatial-temporal aspects of muscle activity (mean EMG amplitude and integrated EMG) of lower limb muscles. SRT+NMES (loading) showed greater gains in the proximal anterior leg compartments. On the contrary, SRT without NMES (SRT only) exhibited deterioration of activity within the same muscle groups. Co-contraction indices increased for both post-NMES interventions suggesting that task-specificity of training is important to achieve the fundamental reciprocal firing known to able-bodied gait. These results show that combination of NMES+loading during passive rhythmic gait will induce neuroplasticity in the lower limbs that ultimately provides a potential effective means to recover gait in individuals with SCI.The goal of this paper is to study the effects of supine and stand retraining (SRT) interventions with and without multi muscle neuromuscular electrical stimulation (NMES) on the neuromuscular EMG responses of the leg muscles for individuals with motor complete SCI during walking on a body-weight support (BWS) treadmill. The main outcome variables were EMG amplitude, integrated EMG and co-contraction indices (co-excitation and co-activation) collected during a 10-minute walking treadmill trial. Data was analyzed for the first, fifth and tenth minute of walking. Results showed that both Supine+NMES and SRT+NMES interventions increased spatial-temporal aspects of muscle activity (mean EMG amplitude and integrated EMG) of lower limb muscles. SRT+NMES (loading) showed greater gains in the proximal anterior leg compartments. On the contrary, SRT without NMES (SRT only) exhibited deterioration of activity within the same muscle groups. Co-contraction indices increased for both post-NMES interventions suggesting that task-specificity of training is important to achieve the fundamental reciprocal firing known to able-bodied gait. These results show that combination of NMES+loading during passive rhythmic gait will induce neuroplasticity in the lower limbs that ultimately provides a potential effective means to recover gait in individuals with SCI.

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.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.

Multi-muscle electrical stimulation and stand training: Effects on standing

Objective: To examine the biomechanical and neuromuscular effects of a longitudinal multi-muscle electrical stimulation (submaximal intensities) training of the lower limbs combined with/without activity-based stand training, on the recovery of stability and function for one individual with spinal cord injury (SCI). Design: Single-subject, longitudinal study. Setting: Neuroplasticity laboratory. Participant: A 34-year-old male, with sensory- and motor-complete SCI (C5/C6). Interventions: Two consecutive interventions: 61 hours of supine, lower-limb ES (ES-alone) and 51 hours of ES combined with stand training using an overhead body-weight support system (ST + ES). Outcome Measures: Clinical measures, trunk stability, and muscle activity were assessed and compared across time points. Trunk Stability Limit (TSL) determined improvements in trunk independence. Results: Functional clinical values increased after both interventions, with further increases post ST + ES. Post ES-alone, trunk stability was maintained at 81% body-weight (BW) loading before failure; post ST + ES, BW loading increased to 95%. TSL values decreased post ST + ES (TSLA/P=54.0 kg.cm, TSLM/L=14.5 kg.cm), compared to ES-alone (TSLA/P=8.5 kg.cm, TSLM/L=3.9 kg.cm). Trunk muscle activity decreased post ST + ES training, compared to ES-alone. Conclusion: Neuromuscular and postural trunk control dramatically improved following the multi-muscle ES of the lower limbs with stand training. Multi-muscle ES training paradigm of the lower limb, using traditional parameters, may contribute to the functional recovery of the trunk.

Exoskeleton Controller and Design Considerations: Effect on Training Response for Persons with SCI

The objective of this research is to identify the demographic, physiological, kinematic and biomechanical determinants of exoskeleton assisted gait speed for individuals with a spinal cord injury (SCI). High number (300) of gait cycles across multiple time-points were analyzed to identify the parameter estimates from mixed model for dependent variable walk speed. Step length, step width, single stance time did not contribute to walk speed whereas trunk lean mass, stride length, step frequency were the most significant contributors. These variables were more significant than any of the spatial temporal parameters that are associated with human gait. Future research should determine the relative contributions of each independent variable to walk speed for different devices. Understanding the effects of exoskeleton/human interface for different devices is crucial for developing effective/efficient training protocols for community ambulation, rehabilitation and recovery post SCI.