Quantification of the dynamic properties of EMG patterns during gait

Prediction of Gait Kinematics and Kinetics: A Systematic Review of EMG and EEG Signal Use and Their Contribution to Prediction Accuracy

Human-machine interfaces hold promise in enhancing rehabilitation by predicting and responding to subjects' movement intent. In gait rehabilitation, neural network architectures utilize lower-limb muscle and brain activity to predict continuous kinematics and kinetics during stepping and walking. This systematic review, spanning five databases, assessed 16 papers meeting inclusion criteria. Studies predicted lower-limb kinematics and kinetics using electroencephalograms (EEGs), electromyograms (EMGs), or a combination with kinematic data and anthropological parameters. Long short-term memory (LSTM) and convolutional neural network (CNN) tools demonstrated highest accuracies. EEG focused on joint angles, while EMG predicted moments and torque joints. Useful EEG electrode locations included C3, C4, Cz, P3, F4, and F8. Vastus Lateralis, Rectus Femoris, and Gastrocnemius were the most commonly accessed muscles for kinematic and kinetic prediction using EMGs. No studies combining EEGs and EMGs to predict lower-limb kinematics and kinetics during stepping or walking were found, suggesting a potential avenue for future development in this technology.

Characterizing Pelvic Floor Muscle Activity During Walking and Jogging in Continent Adults: A Cross-Sectional Study

Introduction

The pelvic floor muscles (PFM) are active during motor tasks that increase intra-abdominal pressure, but little is known about how the PFM respond to dynamic activities, such as gait. The purpose of this study was to characterize and compare PFM activity during walking and jogging in continent adults across the entire gait cycle.

Methods

17 able-bodied individuals (8 females) with no history of incontinence participated in this study. We recorded electromyography (EMG) from the abdominal muscles, gluteus maximus (GM), and PFM while participants performed attempted maximum voluntary contractions (aMVC) of all muscles and completed 60–70 strides in four gait conditions: slow walk (1 km/h); regular walk (self-selected comfortable pace); transition walk (self-selected fastest walking pace); jog (same speed as transition walking). We quantified activity throughout the whole gait cycle (%aMVCGC) and during periods of bursting (%aMVCBR) for each participant, and analyzed the timing of PFM bursting periods to explore when the PFM were most active in the gait cycle. We also conducted a phase metric analysis on the PFM and GM burst timings. We performed a Spearman's rank-order correlation to examine the effect of speed on %aMVCGC, %aMVCBR, and phase metric score, and used the Wilcoxon Signed-Rank test to evaluate the effect of gait modality, matched for speed (walking vs. jogging), on these variables.

Results

The PFM were active throughout the gait cycle, with bursts typically occurring during single-leg support. The PFM and GM were in phase for 44–69% of the gait cycle, depending on condition. There was a positive correlation between gait speed and both %aMVCGC and %aMVCBR (p < 0.001). Phase metric scores were significantly higher during jogging than transition walking (p = 0.005), but there was no difference between gait modality on %aMVCGC or %aMVCBR (p = 0.059). Where possible we disaggregated data by sex, although were unable to make statistical comparisons due to low sample sizes.

Conclusion

The PFM are active during walking and jogging, with greater activity at faster speeds and with bursts in activity around single-leg support. The PFM and GM co-activate during gait, but are not completely in phase with each other.

Development and Electromyographic Validation of a Compliant Human-Robot Interaction Controller for Cooperative and Personalized Neurorehabilitation

BACKGROUND

Appropriate training modalities for post-stroke upper-limb rehabilitation are key features for effective recovery after the acute event. This study presents a cooperative control framework that promotes compliant motion and implements a variety of high-level rehabilitation modalities with a unified low-level explicit impedance control law. The core idea is that we can change the haptic behavior perceived by a human when interacting with the rehabilitation robot by tuning three impedance control parameters.

METHODS

The presented control law is based on an impedance controller with direct torque measurement, provided with positive-feedback compensation terms for disturbances rejection and gravity compensation. We developed an elbow flexion-extension experimental setup as a platform to validate the performance of the proposed controller to promote the desired high-level behavior. The controller was first characterized through experimental trials regarding joint transparency, torque, and impedance tracking accuracy. Then, to validate if the controller could effectively render different physical human-robot interaction according to the selected rehabilitation modalities, we conducted tests on 14 healthy volunteers and measured their muscular voluntary effort through surface electromyography (sEMG). The experiments consisted of one degree-of-freedom elbow flexion/extension movements, executed under six high-level modalities, characterized by different levels of (i) corrective assistance, (ii) weight counterbalance assistance, and (iii) resistance.

RESULTS

The unified controller demonstrated suitability to promote good transparency and render both compliant and stiff behavior at the joint. We demonstrated through electromyographic monitoring that a proper combination of stiffness, damping, and weight assistance could induce different user participation levels, render different physical human-robot interaction, and potentially promote different rehabilitation training modalities.

CONCLUSION

We proved that the proposed control framework could render a wide variety of physical human-robot interaction, helping the user to accomplish the task while exploiting physiological muscular activation patterns. The reported results confirmed that the control scheme could induce different levels of the subject's participation, potentially applicable to the clinical practice to adapt the rehabilitation treatment to the subject's progress. Further investigation is needed to validate the presented approach to neurological patients.

Robotic Exoskeleton Gait Training in Stroke: An Electromyography-Based Evaluation

The recovery of symmetric and efficient walking is one of the key goals of a rehabilitation program in patients with stroke. The use of overground exoskeletons alongside conventional gait training might help foster rhythmic muscle activation in the gait cycle toward a more efficient gait. About twenty-nine patients with subacute stroke have been recruited and underwent either conventional gait training or experimental training, including overground gait training using a wearable powered exoskeleton alongside conventional therapy. Before and after the rehabilitation treatment, we assessed: (i) gait functionality by means of clinical scales combined to obtain a Capacity Score, and (ii) gait neuromuscular lower limbs pattern using superficial EMG signals. Both groups improved their ability to walk in terms of functional gait, as detected by the Capacity Score. However, only the group treated with the robotic exoskeleton regained a controlled rhythmic neuromuscular pattern in the proximal lower limb muscles, as observed by the muscular activation analysis. Coherence analysis suggested that the control group (CG) improvement was mediated mainly by spinal cord control, while experimental group improvements were mediated by cortical-driven control. In subacute stroke patients, we hypothesize that exoskeleton multijoint powered fine control overground gait training, alongside conventional care, may lead to a more fine-tuned and efficient gait pattern.

Sock-Type Wearable Sensor for Estimating Lower Leg Muscle Activity Using Distal EMG Signals

Lower leg muscle activity contributes to body control; thus, monitoring lower leg muscle activity is beneficial to understand the body condition and prevent accidents such as falls. Amplitude features such as the mean absolute values of electromyography (EMG) are used widely for monitoring muscle activity. Garment-type EMG measurement systems use electrodes and they enable us to monitor muscle activity in daily life without any specific knowledge and the installation for electrode placement. However, garment-type measurement systems require a high compression area around the electrodes to prevent electrode displacement. This makes it difficult for users to wear such measurement systems. A less restraining wearable system, wherein the electrodes are placed around the ankle, is realized for target muscles widely distributed around the shank. The signals obtained from around the ankle are propagated biosignals from several muscles, and are referred to as distal EMG signals. Our objective is to develop a sock-type wearable sensor for estimating lower leg muscle activity using distal EMG signals. We propose a signal processing method based on multiple bandpass filters from the perspectives of noise separation and feature augmentation. We conducted an experiment for designing the hardware configuration, and three other experiments for evaluating the estimation accuracy and dependability of muscle activity analysis. Compared to the baseline based on a 20-500 Hz bandpass filter, the results indicated that the proposed system estimates muscle activity with higher accuracy. Experimental results suggest that lower leg muscle activity can be estimated using distal EMG signals.

Altered muscle activation patterns (AMAP): an analytical tool to compare muscle activity patterns of hemiparetic gait with a normative profile

Background

Stroke survivors often have lower extremity sensorimotor impairments, resulting in an inability to sufficiently recruit muscle activity at appropriate times in a gait cycle. Currently there is a lack of a standardized method that allows comparison of muscle activation in hemiparetic gait post-stroke to a normative profile.

Methods

We developed a new tool to quantify altered muscle activation patterns (AMAP). AMAP accounts for spatiotemporal asymmetries in stroke gait by evaluating the deviations of muscle activation specific to each gait sub-phase. It also recognizes the characteristic variability within the healthy population. The inter-individual variability of normal electromyography (EMG) patterns within some sub-phases of the gait cycle is larger compared to others, therefore AMAP penalizes more for deviations in a gait sub-phase with a constant profile (absolute active or inactive) vs variable profile. EMG data were collected during treadmill walking, from eight leg muscles of 34 stroke survivors at self-selected speeds and 20 healthy controls at four different speeds. Stroke survivors’ AMAP scores, for timing and amplitude variations, were computed in comparison to healthy controls walking at speeds matched to the stroke survivors’ self-selected speeds.

Results

Altered EMG patterns in the stroke population quantified using AMAP agree with the previously reported EMG alterations in stroke gait that were identified using qualitative methods. We defined scores ranging between ±2.57 as “normal”. Only 9% of healthy controls were outside “normal” window for timing and amplitude. Percentages of stroke subjects outside the “normal” window for each muscle were, Soleus = 79%; 73%, Medial Gastrocnemius = 62%; 79%, Tibialis Anterior = 62%; 59%, and Gluteus Medius = 48%; 51% for amplitude and timing component respectively, alterations were relatively smaller for the other four muscles. Paretic-propulsion was negatively correlated to AMAP scores for the timing component of Soleus. Stroke survivors’ self-selected walking speed was negatively correlated with AMAP scores for amplitude and timing of Soleus but only amplitude of Medial gastrocnemius (p < 0.05).

Conclusions

Our results validate the ability of AMAP to identify alterations in the EMG patterns within the stroke population and its potential to be used to identify the gait phases that may require more attention when developing an optimal gait training paradigm.

Trial registration

ClinicalTrials.govNCT00712179, Registered July 3rd 2008

Electronic supplementary material

The online version of this article (10.1186/s12984-019-0487-y) contains supplementary material, which is available to authorized users.

Automatic Setting Procedure for Exoskeleton-Assisted Overground Gait: Proof of Concept on Stroke Population

Stroke-related locomotor impairments are often associated with abnormal timing and intensity of recruitment of the affected and non-affected lower limb muscles. Restoring the proper lower limbs muscles activation is a key factor to facilitate recovery of gait capacity and performance, and to reduce maladaptive plasticity. Ekso is a wearable powered exoskeleton robot able to support over-ground gait training. The user controls the exoskeleton by triggering each single step during the gait cycle. The fine-tuning of the exoskeleton control system is crucial-it is set according to the residual functional abilities of the patient, and it needs to ensure lower limbs powered gait to be the most physiological as possible. This work focuses on the definition of an automatic calibration procedure able to detect the best Ekso setting for each patient. EMG activity has been recorded from Tibialis Anterior, Soleus, Rectus Femoris, and Semitendinosus muscles in a group of 7 healthy controls and 13 neurological patients. EMG signals have been processed so to obtain muscles activation patterns. The mean muscular activation pattern derived from the controls cohort has been set as reference. The developed automatic calibration procedure requires the patient to perform overground walking trials supported by the exoskeleton while changing parameters setting. The Gait Metric index is calculated for each trial, where the closer the performance is to the normative muscular activation pattern, in terms of both relative amplitude and timing, the higher the Gait Metric index is. The trial with the best Gait Metric index corresponds to the best parameters set. It has to be noted that the automatic computational calibration procedure is based on the same number of overground walking trials, and the same experimental set-up as in the current manual calibration procedure. The proposed approach allows supporting the rehabilitation team in the setting procedure. It has been demonstrated to be robust, and to be in agreement with the current gold standard (i.e., manual calibration performed by an expert engineer). The use of a graphical user interface is a promising tool for the effective use of an automatic procedure in a clinical context.

The effect of prolonged level and uphill walking on the postural control of older adults

Prolonged walking could alter postural control leading to an increased risk of falls in older adults. The aim of this study was to determine the effect of level and uphill prolonged walking on the postural control of older adults. Sixteen participants (64 ± 5 years) attended 3 visits. Postural control was assessed during quiet standing and the limits of stability immediately pre, post and post 15 min rest a period of 30 min walking on level and uphill (5.25%) gradients on separate visits. Each 30 min walk was divided into 3 10 min blocks, the limits of stability were measured between each block. Postural sway elliptical area (PRE: 1.38 ± 0.22 cm², POST: 2.35 ± 0.50 cm², p = .01), medio-lateral (PRE: 1.33 ± 0.03, POST: 1.40 ± 0.03, p = .01) and anterio-posterior detrended fluctuation analysis alpha exponent (PRE: 1.43 ± 0.02, POST: 1.46 ± 0.02, p = .04) increased following walking. Medio-lateral alpha exponent decreased between post and post 15 min' rest (POST: 1.40 ± 0.03, POST15: 1.36 ± 0.03, p = .03). Forward limits of stability decreased between the second walking interval and post 15 min' rest (Interval 2: 28.1 ± 1.6%, POST15: 25.6 ± 1.6%, p = .01) and left limits of stability increased from pre-post 15 min' rest (PRE: 27.7 ± 1.2%, POST15: 29.4 ± 1.1%, p = .01). The neuromuscular alterations caused by prolonged walking decreased the anti-persistence of postural sway and altered the limits of stability in older adults. However, 15 min' rest was insufficient to return postural control to pre-exercise levels.

Non-gait-specific intervention for the rehabilitation of walking after SCI: role of the arms

Arm movements modulate leg activity and improve gait efficiency; however, current rehabilitation interventions focus on improving walking through gait-specific training and do not actively involve the arms. The goal of this project was to assess the effect of a rehabilitation strategy involving simultaneous arm and leg cycling on improving walking after incomplete spinal cord injury (iSCI). We investigated the effect of 1) non-gait-specific training and 2) active arm involvement during training on changes in over ground walking capacity. Participants with iSCI were assigned to simultaneous arm-leg cycling (A&L) or legs only cycling (Leg) training paradigms, and cycling movements were assisted with electrical stimulation. Overground walking speed significantly increased by 0.092 ± 0.022 m/s in the Leg group and 0.27 ± 0.072m/s in the A&L group after training. Whereas the increases in the Leg group were similar to those seen after current locomotor training strategies, increases in the A&L group were significantly larger than those in the Leg group. Walking distance also significantly increased by 32.12 ± 8.74 m in the Leg and 91.58 ± 36.24 m in the A&L group. Muscle strength, sensation, and balance improved in both groups; however, the A&L group had significant improvements in most gait measures and had more regulated joint kinematics and muscle activity after training compared with the Leg group. We conclude that electrical stimulation-assisted cycling training can produce significant improvements in walking after SCI. Furthermore, active arm involvement during training can produce greater improvements in walking performance. This strategy may also be effective in people with other neural disorders or diseases. NEW & NOTEWORTHY This work challenges concepts of task-specific training for the rehabilitation of walking and encourages coordinated training of the arms and legs after spinal cord injury. Cycling of the legs produced significant improvements in walking that were similar in magnitude to those reported with gait-specific training. Moreover, active engagement of the arms simultaneously with the legs generated nearly double the improvements obtained by leg training only. The cervico-lumbar networks are critical for the improvement of walking.

Electromyography Exposes Heterogeneity in Muscle Co-Contraction following Stroke

Walking after stroke is often described as requiring excessive muscle co-contraction, yet, evidence that co-contraction is a ubiquitous motor control strategy for this population remains inconclusive. Co-contraction, the simultaneous activation of agonist and antagonist muscles, can be assessed with electromyography (EMG) but is often described qualitatively. Here, our goal is to determine if co-contraction is associated with gait impairments following stroke. Fifteen individuals with chronic stroke and nine healthy controls walked on an instrumented treadmill at self-selected speed. Surface EMGs were collected from the medial gastrocnemius (MG), soleus (SOL), and tibialis anterior (TA) of each leg. EMG envelope amplitudes were assessed in three ways: (1) no normalization, (2) normalization to the maximum value across the gait cycle, or (3) normalization to maximal M-wave. Three co-contraction indices were calculated across each agonist/antagonist muscle pair (MG/TA and SOL/TA) to assess the effect of using various metrics to quantify co-contraction. Two factor ANOVAs were used to compare effects of group and normalization for each metric. Co-contraction during the terminal stance (TSt) phase of gait is not different between healthy controls and the paretic leg of individuals post-stroke, regardless of the metric used to quantify co-contraction. Interestingly, co-contraction was similar between M-max and non-normalized EMG; however, normalization does not impact the ability to resolve group differences. While a modest correlation is revealed between the amount of TSt co-contraction and walking speed, the relationship is not sufficiently strong to motivate further exploration of a causal link between co-contraction and walking function after stroke. Co-contraction does not appear to be a common strategy employed by individuals after stroke. We recommend exploration of alternative EMG analysis approaches in an effort to learn more about the causal mechanisms of gait impairment following stroke.

ESTIMATING MUSCLE FORCES AND KNEE JOINT TORQUE USING SURFACE ELECTROMYOGRAPHY: A MUSCULOSKELETAL BIOMECHANICAL MODEL

Surface electromyography (sEMG) is a useful tool for revealing the underlying musculoskeletal dynamic properties in the human body movement. In this paper, a musculoskeletal biomechanical model which relates the sEMG and knee joint torque is proposed. First, the dynamic model relating sEMG to skeletal muscle activation considering frequency and amplitude is built. Second, a muscle contraction model based on sliding-filament theory is developed to reflect the physiological structure and micro mechanical properties of the muscle. The muscle force and displacement vectors are determined and the transformation from muscle force to knee joint moment is realized, and finally a genetic algorithm-based calibration method for the Newton–Euler dynamics and overall musculoskeletal biomechanical model is put forward. Following the model calibration, the flexion/extension (FE) knee joint torque of eight subjects under different walking speeds was predicted. Results show that the forward biomechanical model can capture the general shape and timing of the joint torque, with normalized mean residual error (NMRE) of [Formula: see text]10.01%, normalized root mean square error (NRMSE) of [Formula: see text]12.39% and cross-correlation coefficient of [Formula: see text]0.926. The musculoskeletal biomechanical model proposed and validated in this work could facilitate the study of neural control and how muscle forces generate and contribute to the knee joint torque during human movement.

Shared muscle synergies in human walking and cycling

The motor system may rely on a modular organization (muscle synergies activated in time) to execute different tasks. We investigated the common control features of walking and cycling in healthy humans from the perspective of muscle synergies. Three hypotheses were tested: 1) muscle synergies extracted from walking trials are similar to those extracted during cycling; 2) muscle synergies extracted from one of these motor tasks can be used to mathematically reconstruct the electromyographic (EMG) patterns of the other task; 3) muscle synergies of cycling can result from merging synergies of walking. A secondary objective was to identify the speed (and cadence) at which higher similarities emerged. EMG activity from eight muscles of the dominant leg was recorded in eight healthy subjects during walking and cycling at four matched cadences. A factorization technique [nonnegative matrix factorization (NNMF)] was applied to extract individual muscle synergy vectors and the respective activation coefficients behind the global muscular activity of each condition. Results corroborated hypotheses 2 and 3, showing that 1) four synergies from walking and cycling can successfully explain most of the EMG variability of cycling and walking, respectively, and 2) two of four synergies from walking appear to merge together to reconstruct one individual synergy of cycling, with best reconstruction values found for higher speeds. Direct comparison of the muscle synergy vectors of walking and the muscle synergy vectors of cycling (hypothesis 1) produced moderated values of similarity. This study provides supporting evidence for the hypothesis that cycling and walking share common neuromuscular mechanisms.

Control strategies to re-establish glenohumeral stability after shoulder injury

BACKGROUND

Muscles are important "sensors of the joint instability". The aim of this study was to identify the neuro-motor control strategies adopted by patients with anterior shoulder instability during overhead shoulder elevation in two planes.

METHODS

The onset, time of peak activation, and peak magnitude of seven shoulder muscles (posterior deltoid, bilateral upper trapezius, biceps brachii, infraspinatus, supraspinatus and teres major) were identified using electromyography as 19 pre-operative patients with anterior shoulder instability (mean 27.95 years, SD = 7.796) and 25 age-matched asymptomatic control subjects (mean 23.07 years, SD = 2.952) elevated their arm above 90 degrees in the sagittal and coronal planes.

RESULTS

Temporal characteristics of time of muscle onsets were significantly different between groups expect for teres major in the coronal plane (t = 1.1220, p = 0.2646) Patients recruited the rotator cuff muscles earlier and delayed the onset of ipsilateral upper trapezius compared with subjects (p<0.001) that control subjects. Furthermore, significant alliances existed between the onsets of infraspinatus and supraspinatus (sagittal: r = 0.720; coronal: r = 0.756 at p<0.001) and ipsilateral upper trapezius and infraspinatus (sagittal: r = -0.760, coronal: r = -0.818 at p<0.001). The peak activation of all seven muscles occurred in the mid-range of elevation among patients with anterior shoulder instability whereas subjects spread peak activation of all 7 muscles throughout range. Peak magnitude of patients' infraspinatus muscle was six times higher (sagittal: t = -8.6428, coronal: t = -54.1578 at p<0.001) but magnitude of their supraspinatus was lower (sagittal: t = 36.2507, coronal: t = 35.9350 at p<0.001) that subjects.

CONCLUSIONS

Patients with anterior shoulder instability adopted a "stability before mobility" neuro-motor control strategy to initiate elevation and a "stability at all cost" strategy to ensure concavity compression in the mid-to-150 degrees of elevation in both sagittal and coronal planes.

KeR-EGI, a new index of gait quantification based on electromyography

PURPOSE

To define a new index of gait pathology in adults based on electromyographic data: the Ker-EGI for Kerpape-Rennes EMG-based Gait Index. The principle is similar to the one of Gait Deviation Index but using EMG profiles instead of joint angles. It first needs to build a database of healthy subjects gait to be able then to quantify the deviation of one peculiar patient's gait from this typical behavior.

METHODS

Ninety adults (59 healthy and 31 pathological) participated to this study. All pathological subjects had a diagnosis of central nervous system disorder. On each subject we collected the joint angles and the activation profile of seven muscles of each lower limb. Moreover, we recorded two videos (face and profile) of each patient to compute his/her Edinburgh Visual Gait Score (EVGS). Then for each patient, we computed the GGI (Gillette Gait Index), the GDI (Gait Deviation Index) and the Ker-EGI.

RESULTS

Correlation Ker-EGI and each of the three kinematical indices (GGI, GDI, EVGS) is fair to good (respectively R(2)=0.62, 0.42, and 0.69).

CONCLUSION

KeR-EGI is a valid index to evaluate gait and is complementary to one of these three kinematical indices providing synthetic vision on patients' motor control abilities.

Feasibility and effects of patient-cooperative robot-aided gait training applied in a 4-week pilot trial

BACKGROUND

Functional training is becoming the state-of-the-art therapy approach for rehabilitation of individuals after stroke and spinal cord injury. Robot-aided treadmill training reduces personnel effort, especially when treating severely affected patients. Improving rehabilitation robots towards more patient-cooperative behavior may further increase the effects of robot-aided training. This pilot study aims at investigating the feasibility of applying patient-cooperative robot-aided gait rehabilitation to stroke and incomplete spinal cord injury during a therapy period of four weeks. Short-term effects within one training session as well as the effects of the training on walking function are evaluated.

METHODS

Two individuals with chronic incomplete spinal cord injury and two with chronic stroke trained with the Lokomat gait rehabilitation robot which was operated in a new, patient-cooperative mode for a period of four weeks with four training sessions of 45 min per week. At baseline, after two and after four weeks, walking function was assessed with the ten meter walking test. Additionally, muscle activity of the major leg muscles, heart rate and the Borg scale were measured under different walking conditions including a non-cooperative position control mode to investigate the short-term effects of patient-cooperative versus non-cooperative robot-aided gait training.

RESULTS

Patient-cooperative robot-aided gait training was tolerated well by all subjects and performed without difficulties. The subjects trained more actively and with more physiological muscle activity than in a non-cooperative position-control mode. One subject showed a significant and relevant increase of gait speed after the therapy, the three remaining subjects did not show significant changes.

CONCLUSIONS

Patient-cooperative robot-aided gait training is feasible in clinical practice and overcomes the main points of criticism against robot-aided gait training: It enables patients to train in an active, variable and more natural way. The limited number of subjects in this pilot trial does not permit valid conclusions on the effect of patient-cooperative robot-aided gait training on walking function. A large, possibly multi-center randomized controlled clinical trial is required to shed more light on this question.

Gait analysis using wearable sensors

Gait analysis using wearable sensors is an inexpensive, convenient, and efficient manner of providing useful information for multiple health-related applications. As a clinical tool applied in the rehabilitation and diagnosis of medical conditions and sport activities, gait analysis using wearable sensors shows great prospects. The current paper reviews available wearable sensors and ambulatory gait analysis methods based on the various wearable sensors. After an introduction of the gait phases, the principles and features of wearable sensors used in gait analysis are provided. The gait analysis methods based on wearable sensors is divided into gait kinematics, gait kinetics, and electromyography. Studies on the current methods are reviewed, and applications in sports, rehabilitation, and clinical diagnosis are summarized separately. With the development of sensor technology and the analysis method, gait analysis using wearable sensors is expected to play an increasingly important role in clinical applications.

Effect of functional electrical stimulation (FES) combined with robotically assisted treadmill training on the EMG profile

Functional electrical stimulation (FES) is used to assist spinal cord injury patients during walking. However, FES has yet to be shown to have lasting effects on the underlying neurophysiology which lead to long-term rehabilitation. A new approach to FES has been developed by which stimulation is timed to robotically controlled movements in an attempt to promote long-term rehabilitation of walking. This approach was tested in a rodent model of spinal cord injury. Rats who received this FES therapy during a 2-week training period exhibited peak EMG activity during the appropriate phase of the gait cycle; whereas, rats who received stimulation which was randomly timed with respect to their motor activity exhibited no clear pattern in their EMG profile. These results from our newly developed FES system serve as a launching point for many future studies to test and understand the long-term effect of FES on spinal cord rehabilitation.

Segmental Muscle Vibration Improves Walking in Chronic Stroke Patients With Foot Drop: A Randomized Controlled Trial

Background. Studies have described the effects of segmental muscle vibration (SMV) on brain plasticity and corticomotor excitability. Information on the treatment-induced effects of SMV in stroke patients is, however, still limited. Objectives. To assess whether the application of SMV to ankle dorsiflexor muscles of chronic stroke patients can improve walking. Methods. Forty-four patients were randomly assigned to either an experimental group (EG) or a control group (CG) and underwent 12 sessions over 4 weeks of general physical therapy. Patients in the EG also received SMV at 120 Hz over the peroneus longus and tibialis anterior for 30 minutes at the end of each session. All the participants underwent pretreatment and posttreatment gait analysis assessments. Time—distance, kinematic, and surface electromyography (EMG) data were used as outcome measures. Results. A moderate improvement in mean gait speed, normal-side swing velocity, bilateral stride length, and normal-side toe-off percentage was observed only in the EG. A significant increase in bilateral ankle dorsiflexion angle at heel contact was associated with increased maximum ankle dorsiflexion and plantarflexion degrees during the swing phase on the paretic side after treatment in EG. Surface EMG during the swing phase revealed a significant increase in the activation of the tibialis anterior muscle on the paretic side in the posttreatment assessment in the EG. Conclusions. SMV added to general physical therapy may improve gait performance in patients with foot drop secondary to chronic stroke. The authors hypothesize that this may be due to the mechanical vibration stimulation, probably as a consequence of effective brain reorganization.

A time-frequency based electromyographic analysis technique for use in cerebral palsy

Surface electromyography (sEMG) is part of an instrumented gait assessment, however, the interpretation of the data in a clinically meaningful manner is often limited to the extraction of individual sEMG characteristics. The purpose of this study was to develop an assessment methodology using sEMG time and frequency characteristics extracted using wavelet analyses to provide clinically relevant information in children with cerebral palsy (CP). A retrospective study was conducted with 37 children (16 children with typical development (TD) and 21 children with spastic CP). sEMG signals were examined from selected musculature of the lower extremities during level ground walking. Wavelet analysis techniques, along with functional principal component analyses, were employed to calculate a sEMG index. The data indicated a grouping in the EMG index based on the level of motor impairment and the clinical diagnosis of spastic hemiplegia or diplegia. Further analyses of the index exhibited moderate to high (r=-0.43 to -0.74 and r=0.62-0.65) correlations with the existing gait kinetics, kinematics, and clinical measures of motor impairment, and was sensitive to walking ability according to the Gross Motor Functional Classification Scale (GMFCS). Overall, this methodology may have the potential to provide additional insight into the outcome of a clinical intervention that was not available previously, and may find use as a predictive tool that can be utilized for clinical decision making.

The reaction strategy of lower extremity muscles when slips occur to individuals with trans-femoral amputation

The aim of this study is to investigate the surface electromyography (sEMG) responses of lower extremity muscles for both healthy people and individuals with trans-femoral amputation (TFA), when slip events occur during level walking. Six male individuals with unilateral TFA and five healthy subjects participated in this study. Each subject was required to walk at a self-selected comfortable pace along a 5m plastic walkway, and to perform walking trials on dry and oily conditions respectively. The sEMG signals of muscles on legs and around waist were recorded in each trial and the normalized instantaneous muscle power (IMP) values were employed to quantify the response intensity. The IMP profiles of each muscle in oily-surface walking trials were compared quantitatively with that in dry-surface trials. There are three main findings in this study. (1) Different muscle reaction strategies are employed in slip events by the healthy persons and the individuals with TFA, respectively. Moreover, when the slip event occurs on the prosthetic leg and the intact leg of the individuals with TFA respectively, the muscle reaction strategies are also different. (2) The individuals with TFA face higher risks of fall than the healthy persons no mater slips occur on the prosthetic side or the intact side. (3) The hip muscles, especially the gluteus maximus (GMA) muscles, always enormously contribute to posture adjustment and balance recovery in slip events.

Physiological evaluation of gait disturbances post stroke

A large proportion of stroke survivors have to deal with problems in mobility. Proper evaluations must be undertaken to understand the sensorimotor impairments underlying locomotor disorders post stroke, so that evidence-based interventions can be developed. The current electrophysiological, biomechanical, and imagery evaluations that provide insight into locomotor dysfunction post stroke, as well as their advantages and limitations, are reviewed in this paper. In particular, electrophysiological evaluations focus on the contrast of electromyographic patterns and integrity of spinal reflex pathways during perturbed and unperturbed locomotion between persons with stroke and healthy individuals. At a behavioral level, biomechanical evaluations that include temporal distance factors, kinematic and kinetic analyses, as well as the mechanical energy and metabolic cost, are useful when combined with electrophysiological measures for the interpretation of gait disturbances that are related to the control of the central nervous system or secondary to biomechanical constraints. Finally, current methods in imaging and transcranial magnetic stimulation can provide further insight into cortical control of locomotion and the integrity of the corticospinal pathways.

Activity-based therapies

Therapeutic activity is a mainstay of clinical neurorehabilitation, but is typically unstructured and directed at compensation rather than restoration of central nervous system function. Newer activity-based therapies (ABTs) are in early stages of development and testing. The ABTs attempt to restore function via standardized therapeutic activity based on principles of experimental psychology, exercise physiology, and neuroscience. Three of the best developed ABTs are constraint-induced therapy, robotic therapy directed at the hemiplegic arm, and treadmill training techniques aimed at improving gait in persons with stroke and spinal cord injury. These treatments appear effective in improving arm function and gait, but they have not yet been clearly demonstrated to be more effective than equal amounts of traditional techniques. Resistance training is clearly demonstrated to improve strength in persons with stroke and brain injury, and most studies show that it does not increase hypertonia. Clinical trials of ABTs face several methodological challenges. These challenges include defining dosage, standardizing treatment parameters across subjects and within treatment sessions, and determining what constitutes clinically significant treatment effects. The long-term goal is to develop prescriptive ABT, where specific activities are proven to treat specific motor system disorders. Activity-based therapies are not a cure, but are likely to play an important role in future treatment cocktails for stroke and spinal cord injury.