Treatment of knee hyperextension in post-stroke gait. A systematic review

Categorizing knee hyperextension patterns in hemiparetic gait and examining associated impairments in patients with chronic stroke

BACKGROUND

Post-stroke hemiparetic gait exhibits considerable variations in motion patterns and abnormal muscle activities, notably knee hyperextension during the stance phase. Existing studies have primarily concentrated on its joint angle or moment. However, the underlying causes remain unclear. Thus, the causes of knee hyperextension were explored from a new perspective based on temporal-durational factors.

RESEARCH QUESTION

Does the temporal-durational difference of knee hyperextension presence result from specific decreased motor functions?

METHODS

Barefoot gait at a comfortable speed was captured using a three-dimensional camera system. Scores of knee hyperextension used a metric with the temporal-durational factor of knee hyperextension presence in each of four stance phases (1st double support, DS1; early single-leg stance, ESS; late single-leg stance, LSS; 2nd double support, DS2). These scores were used in cluster analysis. The classification and regression tree analysis characterizing each knee hyperextension cluster used the clinical measures of the lower limb and trunk motor function, muscle strength, and spasticity as explanatory variables.

RESULTS

Thirty patients with hemiparetic chronic stroke who exhibited knee hyperextension during gait were included. Four knee hyperextension clusters were shown: Momentary (almost no hyperextension), Continuous (DS1-DS2), ESS-LSS, and ESS-DS2. Knee flexor strength was lower in the groups with long hyperextension durations (Continuous and ESS-DS2) compared with short durations (ESS-LSS and Momentary). ESS-DS2 exhibited higher trunk motor function than Continuous, whereas more severe spasticity was observed in ESS-LSS than in Momentary.

SIGNIFICANCE

This study successfully classified four hemiparetic gait patterns with knee hyperextension based on the temporal-durational factor, providing valuable perspectives for understanding and addressing specific functional physical impairments. These findings offer guidance for focusing on related physical functions when striving for gait improvement with knee hyperextension and are expected to serve as a reference for treatment decision-making.

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.

Combined Ankle Robot Training and Robot-assisted Gait Training Improved the Gait Pattern of a Patient with Chronic Traumatic Brain Injury

Background

: Walking disability caused by central nervous system injury often lingers. In the chronic phase, there is great need to improve walking speed and gait, even for patients who walk independently. Robot-assisted gait training (RAGT) has been widely used, but few studies have focused on improving gait patterns, and its effectiveness for motor function has been limited. This report describes the combination of "RAGT to learn the gait pattern" and "ankle robot training to improve motor function" in a patient with chronic stage brain injury.

Case

: A 34-year-old woman suffered a traumatic brain injury 5 years ago. She had residual right hemiplegia [Fugl-Meyer Assessment-Lower Extremity (FMA-LE): 18 points] and mild sensory impairment, but she walked independently with a short leg brace and a cane. Her comfortable gait speed was 0.57 m/s without an orthosis, and her 6-m walk test distance was 240 m. The Gait Assessment and Intervention Tool (G.A.I.T.) score was 35 points. After hospitalization, ankle robot training was performed daily, with RAGT performed 10 times in total. Post-intervention evaluation performed on Day 28 showed: FMA-LE, 23 points; comfortable walking speed, 0.69 m/s; G.A.I.T., 27 points; and three-dimensional motion analysis showed ankle dorsiflexion improved from 3.22° to 12.59° and knee flexion improved from 1.75° to 16.54° in the swing phase.

Discussion

: This is one of few studies to have examined the combination of two robots. Combining the features of each robot improved the gait pattern and motor function, even in the chronic phase.

The Effects of Shock Wave Therapy on Spasticity and Walking Ability in People with Stroke: A Comparative Study of Different Application Sites

BACKGROUND

This study was conducted to investigate the effects of extracorporeal shock wave therapy on the improvement of walking ability through a reduction in spasticity in stroke patients.

METHODS

Thirty-three patients diagnosed with ischemic stroke by a rehabilitation medicine specialist were randomly assigned to three groups. The patients were divided into experimental group 1 in which shock waves were applied to the muscle-tendon junction, experimental group 2 in which shock waves were applied to the middle of the muscle, and experimental group 3 in which shock waves were applied to both the muscle-tendon junction and the middle of the muscle. The MAS was used to evaluate spasticity in the subjects, and the Dartfish software was used to measure knee and ankle angles during heel-off when walking.

RESULTS

Based on the results of the study, a significant decrease in spasticity and increased joint angles were found in experimental groups 1 and 3 compared to experimental group 2, and the change in joint angle was significantly greater in experimental group 3 than in experimental groups 1 and 2.

CONCLUSIONS

These results indicate that treatment effect may vary depending on the application site of the shock wave, and to obtain the best treatment effect, the shock wave should be applied to both the muscle-tendon junction and the middle part of the muscle.

Designing Ecological Auditory Feedback on Lower Limb Kinematics for Hemiparetic Gait Training

Auditory feedback has earlier been explored as a tool to enhance patient awareness of gait kinematics during rehabilitation. In this study, we devised and tested a novel set of concurrent feedback paradigms on swing phase kinematics in hemiparetic gait training. We adopted a user-centered design approach, where kinematic data recorded from 15 hemiparetic patients was used to design three feedback algorithms (wading sounds, abstract, musical) based on filtered gyroscopic data from four inexpensive wireless inertial units. The algorithms were tested (hands-on) by a focus group of five physiotherapists. They recommended that the abstract and musical algorithms be discarded due to sound quality and informational ambiguity. After modifying the wading algorithm (as per their feedback), we conducted a feasibility test involving nine hemiparetic patients and seven physiotherapists, where variants of the algorithm were applied to a conventional overground training session. Most patients found the feedback meaningful, enjoyable to use, natural-sounding, and tolerable for the typical training duration. Three patients exhibited immediate improvements in gait quality when the feedback was applied. However, minor gait asymmetries were found to be difficult to perceive in the feedback, and there was variability in receptiveness and motor change among the patients. We believe that our findings can advance current research in inertial sensor-based auditory feedback for motor learning enhancement during neurorehabilitation.

Walking on inclines alters the gait characteristics in patients with acute stroke

BACKGROUND

Stroke leads to severe difficulties in daily activities, even when performing a simple task, such as walking from one point to another. The first apparent compensatory strategy in stroke survivors during walking is to slow down the walking speed. Slowing down the walking speed directly reduces the step length and cadence and further increases the stance phase, double, and support time. These alterations are to develop a compensatory strategy; however, this strategy generally leads to joint injuries and increases the potential risks of falls.

RESEARCH QUESTION

A review strongly suggests that walking on the inclines may enhance this compensatory strategy. Therefore, this study attempted to extend the current knowledge to understand the fundamental gait control in patients with acute stroke during walking on inclines.

RESULTS

These results showed that (1) compared to healthy control, patients with acute stroke demonstrated different gait controls during walking on inclines, (2) the gait performance was enhanced when stroke patients were instructed on different inclines, and (3) the asymmetric gait pattern was reduced by walking on inclines.

SIGNIFICANCE

This study concluded that walking on inclines enhances gait performance (greater spatial but smaller temporal gait characteristics) and reduces spatial gait asymmetry.

Does higher knee hyperextension in patients with hemiplegia affect lateral and medial meniscus volume in the paretic leg? A cross-sectional study

BACKGROUND

After stroke, an abnormal gait pattern gradually leads to knee pain and joint lesions, resulting the gait instability. However, the correlation between the knee hyperextension and gait pattern, the meniscus volume, and the water content of meniscus in paretic and non-paretic legs has not been fully investigated. Moreover, most of physicians tend to ignore this knee hyperextension. This study attempted to emphasize the importance of knee hyperextension using gait analysis and Magnetic resonance imaging (Trial registration number ChiCTR2000039641, date of registration 04/11/2020).

METHODS

Eight patients with chronic hemiplegic (6 male, 2 female) volunteered to participate in this study. Participants was recruited if they had a hemiplegia following a stroke occurring more than 6 months, had an ability to walk 10 m without aids, had a Function Ambulation Category level at least 3 and above, and had a hemiplegic lower extremity identified as Brunnstrom state III or above identification. The spatial-temporal gait parameters and kinematic parameters in the paretic and the non-paretic legs and the percentage of free water content in deep and shallow layers.

RESULTS

Longer time since hemiplegia led to larger angles of knee hyperextension (R = 0.56, p = 0.016), larger angles of knee hyperextension led to more tears in meniscus (R =  - 0.53, - 0,57 and - 0.70), and larger angles of knee hyperextension decreased water content of the lateral meniscus in the non-paretic leg (R =  - 0.91) but increased water content of the medial meniscus (R = 0.53 and 0.63).

CONCLUSIONS

The knee hyperextension could not be ignored by physicians and needed to be diagnosed and treated as early as possible, the time since hemiplegia could be an indicator of sign of knee hyperextension.

An impairment-specific hip exoskeleton assistance for gait training in subjects with acquired brain injury: a feasibility study

This study was designed to investigate the feasibility and the potential effects on walking performance of a short gait training with a novel impairment-specific hip assistance (iHA) through a bilateral active pelvis orthosis (APO) in patients with acquired brain injury (ABI). Fourteen subjects capable of independent gait and exhibiting mild-to-moderate gait deficits, due to an ABI, were enrolled. Subjects presenting deficit in hip flexion and/or extension were included and divided into two groups based on the presence (group A, n = 6) or absence (group B, n = 8) of knee hyperextension during stance phase of walking. Two iHA-based profiles were developed for the groups. The protocol included two overground gait training sessions using APO, and two evaluation sessions, pre and post training. Primary outcomes were pre vs. post-training walking distance and steady-state speed in the 6-min walking test. Secondary outcomes were self-selected speed, joint kinematics and kinetics, gait symmetry and forward propulsion, assessed through 3D gait analysis. Following the training, study participants significantly increased the walked distance and average steady-state speed in the 6-min walking tests, both when walking with and without the APO. The increased walked distance surpassed the minimal clinically important difference for groups A and B, (respectively, 42 and 57 m > 34 m). In group A, five out of six subjects had decreased knee hyperextension at the post-training session (on average the peak of the knee extension angle was reduced by 36%). Knee flexion during swing phase increased, by 16% and 31%, for A and B groups respectively. Two-day gait training with APO providing iHA was effective and safe in improving walking performance and knee kinematics in ABI survivors. These preliminary findings suggest that this strategy may be viable for subject-specific post-ABI gait rehabilitation.

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 Inclines on Joint Angles in Stroke Survivors During Treadmill Walking

Stroke severely affects the quality of life, specifically in walking independently. Thus, it is crucial to understand the impaired gait pattern. This gait pattern has been widely investigated when walking on a level treadmill. However, knowledge about the gait pattern when walking on inclines is scarce. Therefore, this study attempted to fulfill this knowledge gap. In this study, 15 stroke survivors and 15 age/height/weight healthy controls were recruited. The participants were instructed to walk on three different inclines: 0°, 3°, and 6°. The participants were required to walk on each incline for 2 min and needed to complete each incline two times. The dependent variables were the peak values for ankle/knee/hip joint angles and the respective variability of these peak values. The results showed that an increment of the incline significantly increased the peak of the hip flexion and the peak of the knee flexion but did not affect the peak values of the ankle joints in the paretic leg in these stroke survivors. In comparison with the healthy controls, lower hip extension, lower hip flexion, lower knee flexion, and lower ankle plantar flexion were observed in stroke survivors. A clinical application of this work might assist the physical therapists in building an effective treadmill training protocol.

Analysis of Gait Characteristics Using Hip-Knee Cyclograms in Patients with Hemiplegic Stroke

Gait disturbance is a common sequela of stroke. Conventional gait analysis has limitations in simultaneously assessing multiple joints. Therefore, we investigated the gait characteristics in stroke patients using hip-knee cyclograms, which have the advantage of simultaneously visualizing the gait kinematics of multiple joints. Stroke patients (n = 47) were categorized into two groups according to stroke severity, and healthy controls (n = 32) were recruited. An inertial measurement unit sensor-based gait analysis system, which requires placing seven sensors on the dorsum of both feet, the shafts of both tibias, the middle of both femurs, and the lower abdomen, was used for the gait analysis. Then, the hip-knee cyclogram parameters (range of motion, perimeter, and area) were obtained from the collected data. The coefficient of variance of the cyclogram parameters was obtained to evaluate gait variability. The cyclogram parameters differed between the stroke patients and healthy controls, and differences according to stroke severity were also observed. The gait variability parameters mainly differed in patients with more severe stroke, and specific visualized gait patterns of stroke patients were obtained through cyclograms. In conclusion, the hip-knee cyclograms, which show inter-joint coordination and visualized gait cycle in stroke patients, are clinically significant.