Hip circumduction is not a compensation for reduced knee flexion angle during gait

Myoelectric interface for neurorehabilitation conditioning to reduce abnormal leg co-activation after stroke: a pilot study

BACKGROUND

The ability to walk is an important factor in quality of life after stroke. Co-activation of hip adductors and knee extensors has been shown to correlate with gait impairment. We have shown previously that training with a myoelectric interface for neurorehabilitation (MINT) can reduce abnormal muscle co-activation in the arms of stroke survivors.

METHODS

Here, we extend MINT conditioning to stroke survivors with leg impairment. The aim of this pilot study was to assess the safety and feasibility of using MINT to reduce abnormal co-activation between hip adductors and knee extensors and assess any effects on gait. Nine stroke survivors with moderate to severe gait impairment received 6 h of MINT conditioning over six sessions, either in the laboratory or at home.

RESULTS

MINT participants completed a mean of 159 repetitions per session without any adverse events. Further, participants learned to isolate their muscles effectively, resulting in a mean reduction of co-activation of 70% compared to baseline. Moreover, gait speed increased by a mean of 0.15 m/s, more than the minimum clinically important difference. Knee flexion angle increased substantially, and hip circumduction decreased.

CONCLUSION

MINT conditioning is safe, feasible at home, and enables reduction of co-activation in the leg. Further investigation of MINT's potential to improve leg movement and function after stroke is warranted. Abnormal co-activation of hip adductors and knee extensors may contribute to impaired gait after stroke. Trial registration This study was registered at ClinicalTrials.gov (NCT03401762, Registered 15 January 2018, https://clinicaltrials.gov/study/NCT03401762?tab=history&a=4 ).

A comparative study on the overlapping effects of clinically applicable therapeutic interventions in patients with central nervous system damage

This study was conducted to investigate the effects of anti-gravity treadmill (AGT) training, which provides visual feedback and Biorescue training on proprioception, muscle strength, balance, and gait, in stroke patients. A total of 45 people diagnosed with post-stroke were included as study subjects; they were randomized to an AGT training group provided with visual feedback (Group A), a Biorescue training group provided with visual feedback (Group B), and an AGT/Biorescue group that subsequently received AGT training and Biorescue training (Group C). A muscle strength-measuring device was used to evaluate muscle strength. Timed Up and Go and Bug Balance Scale assessment sheets were used to evaluate balance ability. Dartfish software was used to evaluate gait ability. The results of the study showed that Groups A and C had a significant increase in muscle strength compared with Group B; in terms of balance and gait abilities, Group C showed a significant increase in balance ability and gait speed and a significant change in knee joint angle compared with Groups A and B. In conclusion, this study suggests that including a method that applies multiple therapeutic interventions is desirable in the rehabilitation of stroke patients to improve their independence.

Myoelectric interface for neurorehabilitation conditioning to reduce abnormal leg co-activation after stroke: a pilot study

Background

The ability to walk is an important factor in quality of life after stroke. Co-activation of hip adductors and knee extensors has been shown to correlate with gait impairment. We have shown previously that training with a myoelectric interface for neurorehabilitation (MINT) can reduce abnormal muscle co-activation in the arms of stroke survivors.

Methods

Here, we extend MINT conditioning to stroke survivors with leg impairment. The aim of this pilot study was to assess the safety and feasibility of using MINT to reduce abnormal co-activation between hip adductors and knee extensors and assess any effects on gait. Nine stroke survivors with moderate to severe gait impairment received six hours of MINT conditioning over six sessions, either in the laboratory or at home.

Results

MINT participants completed a mean of 159 repetitions per session without any adverse events. Further, participants learned to isolate their muscles effectively, resulting in a mean reduction of co-activation of 70% compared to baseline. Moreover, gait speed increased by a mean of 0.15 m/s, more than the minimum clinically important difference. Knee flexion angle increased substantially, and hip circumduction decreased.

Conclusion

MINT conditioning is safe, feasible at home, and enables reduction of co-activation in the leg. Further investigation of MINT's potential to improve leg movement and function after stroke is warranted. Abnormal co-activation of hip adductors and knee extensors may contribute to impaired gait after stroke.

Trial registration

This study was registered at ClinicalTrials.gov (NCT03401762, Registered 15 January 2018, https://clinicaltrials.gov/study/NCT03401762?tab=history&a=4).

Adapted Assistance and Resistance Training With a Knee Exoskeleton After Stroke

Studies on robotic interventions for gait rehabilitation after stroke require: (i) rigorous performance evidence; (ii) systematic procedures to tune the control parameters; and (iii) combination of control modes. In this study, we investigated how stroke individuals responded to training for two weeks with a knee exoskeleton (ABLE-KS) using both Assistance and Resistance training modes together with auditory feedback to train peak knee flexion angle. During the training, the torque provided by the ABLE-KS and the biofeedback were systematically adapted based on the subject's performance and perceived exertion level. We carried out a comprehensive experimental analysis that evaluated a wide range of biomechanical metrics, together with usability and users' perception metrics. We found significant improvements in peak knee flexion ( p = 0.0016 ), minimum knee angle during stance ( p = 0.0053 ), paretic single support time ( p = 0.0087 ) and gait endurance ( p = 0.022 ) when walking without the exoskeleton after the two weeks of training. Participants significantly ( ) improved the knee angle during the stance and swing phases when walking with the exoskeleton powered in the high Assistance mode in comparison to the No Exo and the Unpowered conditions. No clinically relevant differences were found between Assistance and Resistance training sessions. Participants improved their performance with the exoskeleton (24-55 %) for the peak knee flexion angle throughout the training sessions. Moreover, participants showed a high level of acceptability of the ABLE-KS (QUEST 2.0 score: 4.5 ± 0.3 out of 5). Our preliminary findings suggest that the proposed training approach can produce similar or larger improvements in post-stroke individuals than other studies with knee exoskeletons that used higher training intensities.

Speed-dependent biomechanical changes vary across individual gait metrics post-stroke relative to neurotypical adults

BACKGROUND

Gait training at fast speeds is recommended to reduce walking activity limitations post-stroke. Fast walking may also reduce gait kinematic impairments post-stroke. However, it is unknown if differences in gait kinematics between people post-stroke and neurotypical adults decrease when walking at faster speeds.

OBJECTIVE

To determine the effect of faster walking speeds on gait kinematics post-stroke relative to neurotypical adults walking at similar speeds.

METHODS

We performed a secondary analysis with data from 28 people post-stroke and 50 neurotypical adults treadmill walking at multiple speeds. We evaluated the effects of speed and group on individual spatiotemporal and kinematic metrics and performed k-means clustering with all metrics at self-selected and fast speeds.

RESULTS

People post-stroke decreased step length asymmetry and trailing limb angle impairment, reducing between-group differences at fast speeds. Speed-dependent changes in peak swing knee flexion, hip hiking, and temporal asymmetries exaggerated between-group differences. Our clustering analyses revealed two clusters. One represented neurotypical gait behavior, composed of neurotypical and post-stroke participants. The other characterized stroke gait behavior-comprised entirely of participants post-stroke with smaller lower extremity Fugl-Meyer scores than the post-stroke participants in the neurotypical gait behavior cluster. Cluster composition was largely consistent at both speeds, and the distance between clusters increased at fast speeds.

CONCLUSIONS

The biomechanical effect of fast walking post-stroke varied across individual gait metrics. For participants within the stroke gait behavior cluster, walking faster led to an overall gait pattern more different than neurotypical adults compared to the self-selected speed. This suggests that to potentiate the biomechanical benefits of walking at faster speeds and improve the overall gait pattern post-stroke, gait metrics with smaller speed-dependent changes may need to be specifically targeted within the context of fast walking.

Computer Vision and Machine Learning-Based Gait Pattern Recognition for Flat Fall Prediction

BACKGROUND

Gait recognition has been applied in the prediction of the probability of elderly flat ground fall, functional evaluation during rehabilitation, and the training of patients with lower extremity motor dysfunction. Gait distinguishing between seemingly similar kinematic patterns associated with different pathological entities is a challenge for the clinician. How to realize automatic identification and judgment of abnormal gait is a significant challenge in clinical practice. The long-term goal of our study is to develop a gait recognition computer vision system using artificial intelligence (AI) and machine learning (ML) computing. This study aims to find an optimal ML algorithm using computer vision techniques and measure variables from lower limbs to classify gait patterns in healthy people. The purpose of this study is to determine the feasibility of computer vision and machine learning (ML) computing in discriminating different gait patterns associated with flat-ground falls.

METHODS

We used the Kinect^® Motion system to capture the spatiotemporal gait data from seven healthy subjects in three walking trials, including normal gait, pelvic-obliquity-gait, and knee-hyperextension-gait walking. Four different classification methods including convolutional neural network (CNN), support vector machine (SVM), K-nearest neighbors (KNN), and long short-term memory (LSTM) neural networks were used to automatically classify three gait patterns. Overall, 750 sets of data were collected, and the dataset was divided into 80% for algorithm training and 20% for evaluation.

RESULTS

The SVM and KNN had a higher accuracy than CNN and LSTM. The SVM (94.9 ± 3.36%) had the highest accuracy in the classification of gait patterns, followed by KNN (94.0 ± 4.22%). The accuracy of CNN was 87.6 ± 7.50% and that of LSTM 83.6 ± 5.35%.

CONCLUSIONS

This study revealed that the proposed AI machine learning (ML) techniques can be used to design gait biometric systems and machine vision for gait pattern recognition. Potentially, this method can be used to remotely evaluate elderly patients and help clinicians make decisions regarding disposition, follow-up, and treatment.

The effect of asymmetrical gait induced by unilateral knee brace on the knee flexor and extensor muscles

Asymmetrical stiff knee gait is a mechanical pathology that can disrupt lower extremity muscle coordination. A better understanding of this condition can help identify potential complications. This study proposes the use of dynamic musculoskeletal modelling simulation to investigate the effect of induced mechanical perturbation on the kneeand to examine the muscle behaviour without invasive technique. Thirty-eight healthy participants were recruited. Asymmetrical gait was simulated using knee brace. Knee joint angle, joint moment and knee flexor and extensor muscle forces were computed using OpenSim. Differences inmuscle force between normal and abnormal conditions were investigated using ANOVA and Tukey-Kramer multiple comparison test.The results revealed that braced knee experienced limited range of motion with smaller flexion moment occuring at late swing phase. Significant differences were found in all flexormuscle forces and in several extensor muscle forces (p<0.05). Normal knee produced larger flexor muscle force than braced knee. Braced knee generated the largest extensor muscle force at early swing phase. In summary, musculoskeletal modelling simulation can be a computational tool to map and detect the differences between normal and asymmetrical gaits.

Isolating the energetic and mechanical consequences of imposed reductions in ankle and knee flexion during gait

BACKGROUND

Weakness of ankle and knee musculature following injury or disorder results in reduced joint motion associated with metabolically expensive gait compensations to enable limb support and advancement. However, neuromechanical coupling between the ankle and knee make it difficult to discern independent roles of these restrictions in joint motion on compensatory mechanics and metabolic penalties.

METHODS

We sought to determine relative impacts of ankle and knee impairment on compensatory gait strategies and energetic outcomes using an unimpaired cohort (N = 15) with imposed unilateral joint range of motion restrictions as a surrogate for reduced motion resulting from gait pathology. Participants walked on a dual-belt instrumented treadmill at 0.8 m s^-1 using a 3D printed ankle stay and a knee brace to systematically limit ankle motion (restricted-ank), knee motion (restricted-knee), and ankle and knee motion (restricted-a + k) simultaneously. In addition, participants walked without any ankle or knee bracing (control) and with knee bracing worn but unrestricted (braced).

RESULTS

When ankle motion was restricted (restricted-ank, restricted-a + k) we observed decreased peak propulsion relative to the braced condition on the restricted limb. Reduced knee motion (restricted-knee, restricted-a + k) increased restricted limb circumduction relative to the restricted-ank condition through ipsilateral hip hiking. Interestingly, restricted limb average positive hip power increased in the restricted-ank condition but decreased in the restricted-a + k and restricted-knee conditions, suggesting that locking the knee impeded hip compensation. As expected, reduced ankle motion, either without (restricted-ank) or in addition to knee restriction (restricted-a + k) yielded significant increase in net metabolic rate when compared with the braced condition. Furthermore, the relative increase in metabolic cost was significantly larger with restricted-a + k when compared to restricted-knee condition.

CONCLUSIONS

Our methods allowed for the reproduction of asymmetric gait characteristics including reduced propulsive symmetry and increased circumduction. The metabolic consequences bolster the potential energetic benefit of targeting ankle function during rehabilitation.

TRIAL REGISTRATION

N/A.

Effects of selectively assisting impaired subtasks of walking in chronic stroke survivors

BACKGROUND

Recently developed controllers for robot-assisted gait training allow for the adjustment of assistance for specific subtasks (i.e. specific joints and intervals of the gait cycle that are related to common impairments after stroke). However, not much is known about possible interactions between subtasks and a better understanding of this can help to optimize (manual or automatic) assistance tuning in the future. In this study, we assessed the effect of separately assisting three commonly impaired subtasks after stroke: foot clearance (FC, knee flexion/extension during swing), stability during stance (SS, knee flexion/extension during stance) and weight shift (WS, lateral pelvis movement). For each of the assisted subtasks, we determined the influence on the performance of the respective subtask, and possible effects on other subtasks of walking and spatiotemporal gait parameters.

METHODS

The robotic assistance for the FC, SS and WS subtasks was assessed in nine mildly impaired chronic stroke survivors while walking in the LOPES II gait trainer. Seven trials were performed for each participant in a randomized order: six trials in which either 20% or 80% of assistance was provided for each of the selected subtasks, and one baseline trial where the participant did not receive subtask-specific assistance. The influence of the assistance on performances (errors compared to reference trajectories) for the assisted subtasks and other subtasks of walking as well as spatiotemporal parameters (step length, width and height, swing and stance time) was analyzed.

RESULTS

Performances for the impaired subtasks (FC, SS and WS) improved significantly when assistance was applied for the respective subtask. Although WS performance improved when assisting this subtask, participants were not shifting their weight well towards the paretic leg. On a group level, not many effects on other subtasks and spatiotemporal parameters were found. Still, performance for the leading limb angle subtask improved significantly resulting in a larger step length when applying FC assistance.

CONCLUSION

FC and SS assistance leads to clear improvements in performance for the respective subtask, while our WS assistance needs further improvement. As effects of the assistance were mainly confined to the assisted subtasks, tuning of FC, SS and WS can be done simultaneously. Our findings suggest that there may be no need for specific, time-intensive tuning protocols (e.g. tuning subtasks after each other) in mildly impaired stroke survivors.

Pelvic obliquity as a compensatory mechanism leading to lower energy recovery: Characterization among the types of prostheses in subjects with transfemoral amputation

BACKGROUND

Subjects with transfemoral amputation (TFA) show an asymmetric gait pattern associated with a decreased ability to recover mechanical energy and an increased metabolic cost of walking.

RESEARCH QUESTION

This study aimed to identify the spatio-temporal and kinematic gait variables correlated with mechanical energy values in subjects with TFA and to observe the ability of the identified parameters to discriminate between TFA and controls according to the type of prosthesis.

METHODS

The gait of 40 subjects with TFA was evaluated with a motion 3-D optoelectronic system. Nine subjects wore a mechanical prosthesis (TFAm), seventeen a C-Leg prosthesis (TFAc), and fourteen a Genium prosthesis (TFAg). Spatio-temporal and pelvic kinematic parameters were measured. Energy recovery was measured relative to the whole-body center of mass (CoM) kinematics as the fraction of mechanical energy recovered during each walking step (R-step). Correlation tests and multiple linear regression analyses were used to evaluate the correlation and association between kinematic and energy variables, respectively. Receiver operating characteristics curves were plotted to assess the ability of the correlated parameter to distinguish subjects with TFA from controls, and optimal cutoff point values were calculated according to the type of prosthesis.

RESULTS

Among the spatio-temporal and kinematic parameters correlated to R-step, only pelvic obliquity of the prosthetic side was significantly associated with R-step. It showed an excellent ability to discriminate between TFA and controls. Furthermore, pelvic obliquity showed an excellent discriminative ability in identifying TFAm and TFAc and a good discriminative ability in identifying TFAg from controls.

SIGNIFICANCE

Pelvic obliquity plays an important role in energy recovery during gait for subjects using prosthetics. This information might be exploited to monitor the adaptation of subjects with TFA to prosthetic devices, to lower the energetic cost of walking potentially, and to reduce the long-term risks of secondary physical complications in prosthetic users.

Neuromusculoskeletal Simulation Reveals Abnormal Rectus Femoris-Gluteus Medius Coupling in Post-stroke Gait

Post-stroke gait is often accompanied by muscle impairments that result in adaptations such as hip circumduction to compensate for lack of knee flexion. Our previous work robotically enhanced knee flexion in individuals post-stroke with Stiff-Knee Gait (SKG), however, this resulted in greater circumduction, suggesting the existence of abnormal coordination in SKG. The purpose of this work is to investigate two possible mechanisms of the abnormal coordination: (1) a reflex coupling between stretched quadriceps and abductors, and (2) a coupling between volitionally activated knee flexors and abductors. We used previously collected kinematic, kinetic and EMG measures from nine participants with chronic stroke and five healthy controls during walking with and without the applied knee flexion torque perturbations in the pre-swing phase of gait in the neuromusculoskeletal simulation. The measured muscle activity was supplemented by simulated muscle activations to estimate the muscle states of the quadriceps, hamstrings and hip abductors. We used linear mixed models to investigate two hypotheses: (H1) association between quadriceps and abductor activation during an involuntary period (reflex latency) following the perturbation and (H2) association between hamstrings and abductor activation after the perturbation was removed. We observed significantly higher rectus femoris (RF) activation in stroke participants compared to healthy controls within the involuntary response period following the perturbation based on both measured (H1, p < 0.001) and simulated (H1, p = 0.022) activity. Simulated RF and gluteus medius (GMed) activations were correlated only in those with SKG, which was significantly higher compared to healthy controls (H1, p = 0.030). There was no evidence of synergistic coupling between any combination of hamstrings and hip abductors (H2, p > 0.05) when the perturbation was removed. The RF-GMed coupling suggests an underlying abnormal coordination pattern in post-stroke SKG, likely reflexive in origin. These results challenge earlier assumptions that hip circumduction in stroke is simply a kinematic adaptation due to reduced toe clearance. Instead, abnormal coordination may underlie circumduction, illustrating the deleterious role of abnormal coordination in post-stroke gait.