Gail F. Forrest

Empirical mode decomposition as a tool to remove the function Electrical stimulation artifact from surface electromyograms: Preliminary investigation

Rectification of surface EMGs during electrical stimulations (ES) is still a problem to be solved. The broad band frequency components of ES artifact overlap with the EMG spectrum, make this task challenging. In this study, we investigate the potential use of empirical mode decomposition (EMD) method to remove the stimulus artifact from surface EMGs collected during such applications. We hypothesize that the EMD algorithm provides a suitable platform for decomposing the EMG signal into physically meaningful intrinsic modes which can be used to isolate ES artifact. Basic EMD is tested on two signals - ES induced EMG and EMG of voluntary contractions added with simulated ES signal. The algorithm isolates the EMG from ES artifact with considerable success. Further, the EMD method along with the energy operator -TKEO gives even better representation of the EMG signal. However, some high frequency data was lost during reconstruction process. Hence, there is further need to investigate the relationship between the EMD parameters and stimulus artifact properties so that the algorithm can be optimized to reconstruct pure artifact free EMG signal with minimum lost of data.

Longitudinal Recovery and Reduced Costs After 120 Sessions of Locomotor Training for Motor Incomplete Spinal Cord Injury

OBJECTIVE To determine the impact of long-term, body weight-supported locomotor training after chronic, incomplete spinal cord injury (SCI), and to estimate the health care costs related to lost recovery potential and preventable secondary complications that may have occurred because of visit limits imposed by insurers. DESIGN Prospective observational cohort with longitudinal follow-up. SETTING Eight outpatient rehabilitation centers that participate in the Christopher & Dana Reeve Foundation NeuroRecovery Network (NRN). PARTICIPANTS Individuals with motor incomplete chronic SCI (American Spinal Injury Association Impairment Scale C or D; N=69; 0.1-45y after SCI) who completed at least 120 NRN physical therapy sessions. INTERVENTIONS Manually assisted locomotor training (LT) in a body weight-supported treadmill environment, overground standing and stepping activities, and community integration tasks. MAIN OUTCOME MEASURES International Standards for Neurological Classification of Spinal Cord Injury motor and sensory scores, orthostatic hypotension, bowel/bladder/sexual function, Spinal Cord Injury Functional Ambulation Inventory (SCI-FAI), Berg Balance Scale, Modified Functional Reach, 10-m walk test, and 6-minute walk test. Longitudinal outcome measure collection occurred every 20 treatments and at 6- to 12-month follow-up after discharge from therapy. RESULTS Significant improvement occurred for upper and lower motor strength, functional activities, psychological arousal, sensation of bowel movement, and SCI-FAI community ambulation. Extended training enabled minimal detectable changes at 60, 80, 100, and 120 sessions. After detectable change occurred, it was sustained through 120 sessions and continued 6 to 12 months after treatment. CONCLUSIONS Delivering at least 120 sessions of LT improves recovery from incomplete chronic SCI. Because walking reduces rehospitalization, LT delivered beyond the average 20-session insurance limit can reduce rehospitalizations and long-term health costs.

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.

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).

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.

Development of an OpenSim Shoulder Model for Manual Wheelchair Users With Tetraplegia

Extended manual wheelchair use has been associated with repetitive strain injuries in the shoulder and has been identified as a contributing factor to upper limb pain experienced by manual wheelchair users with spinal cord injury (SCI) [1]. Due to the nature of their SCI, individuals with tetraplegia (formerly quadriplegia) may be at an even greater risk for developing shoulder injuries because they often have only partial innervation of their shoulder, scapular, and thoracohumeral muscles [2].Copyright

Submaximal marker for investigating peak muscle torque using NMES after paralysis

Spinal cord injury (SCI) results in deleterious skeletal muscle adaptations, such as relevant atrophy and loss of force. In particular, the relevant loss of lower-limb force-generating capacity may limit functional mobility even if neuronal control was sufficient. Currently, methods of assessing maximal force-generating capacity using neuromuscular electrical stimulation (NMES) are limited in individuals who cannot tolerate higher stimulation amplitudes, such as those with residual sensation and those at risk of fracture. In this study, we examined the relationship between NMES amplitude and muscle torque exerted (recruitment curve) in order to determine whether maximal torque output can be characterized by a submaximal marker. Recruitment curves for knee extensors, knee flexors, and ankle plantarflexors were recorded from 30 individuals with motor complete SCI. NMES was delivered starting with an amplitude of 5 mA, and increasing by 5 mA for every subsequent stimulation until either the participant requested to stop the stimulation or the maximum stimulation amplitude (140 mA) was reached. Significant correlations between peak slope of the recruitment curve and peak torque for all muscle groups were found (knee extensors, r = 0.75; p < 0.0001; knee flexors, r = 0.68; p < 0.0001; ankle plantarflexors, r = 0.91; p < 0.0001), indicating that muscles that show greater peak slope of the recruitment curve tend to generate a greater peak torque. This suggests that peak slope, which was achieved at an average stimulation intensity (55.0 mA) that was 43% smaller than that corresponding to peak torque (97.4 mA), may be used as a submaximal marker for characterizing maximal torque output in individuals with SCI.

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.

Center of Mass and Postural Adaptations During Robotic Exoskeleton-Assisted Walking for Individuals with Spinal Cord Injury

The goal of this study is to understand the postural adaptations characterized by the whole body center of mass (COM) for individuals with SCI while walking with powered robotic exoskeletons, EksoGTTM and ReWalkTM. COM excursions showed a greater medial-lateral weight shift approach while walking in the EksoGTTM compared to a more forward-lean approach in the ReWalk™, however, postural trunk lean was significantly (p < 0.05) higher in the ReWalkTM. Understanding the effects of exoskeleton designs on posture and sway is crucial towards developing effective and efficient training protocols for rehabilitation and recovery post SCI.

Effects of lower limb electrical stimulation on trunk stability in persons with SCI during walking: A case series

The purpose of the present case series was to investigate whether three lower limb rehabilitation training approaches have any effects on trunk stability of persons with motor complete SCI during a 10-minute assisted walk. These trainings included electrical stimulation (ES), standing retraining (SRT), and a novel multi-modality approach that combined ES with SRT. We observed that multi-muscle ES directed at the lower limbs had a prominent, indirect effect on the upper and lower muscles of the trunk. More specifically, trunk muscle activations of the ES+SRT subject increased after training for the more distal muscles of the trunk. This study provides preliminary evidence that combining lower limb ES with SRT may provide beneficial effects in improving trunk control and stability.The purpose of the present case series was to investigate whether three lower limb rehabilitation training approaches have any effects on trunk stability of persons with motor complete SCI during a 10-minute assisted walk. These trainings included electrical stimulation (ES), standing retraining (SRT), and a novel multi-modality approach that combined ES with SRT. We observed that multi-muscle ES directed at the lower limbs had a prominent, indirect effect on the upper and lower muscles of the trunk. More specifically, trunk muscle activations of the ES+SRT subject increased after training for the more distal muscles of the trunk. This study provides preliminary evidence that combining lower limb ES with SRT may provide beneficial effects in improving trunk control and stability.