Skin marker-based versus bone morphology-based coordinate systems of the hindfoot and forefoot.

Segment coordinate systems (CSs) of marker-based multi-segment foot models are used to measure foot kinematics, however their relationship to the underlying bony anatomy is barely studied. The aim of this study was to compare marker-based CSs (MCSs) with bone morphology-based CSs (BCSs) for the hindfoot and forefoot. Markers were placed on the right foot of fifteen healthy adults according to the Oxford, Rizzoli and Amsterdam Foot Model (OFM, RFM and AFM, respectively). A CT scan was made while the foot was loaded in a simulated weight-bearing device. BCSs were based on axes of inertia. The orientation difference between BCSs and MCSs was quantified in helical and 3D Euler angles. To determine whether the marker models were able to capture inter-subject variability in bone poses, linear regressions were performed. Compared to the hindfoot BCS, all MCSs were more toward plantar flexion and internal rotation, and RFM was also oriented toward more inversion. Compared to the forefoot BCS, OFM and RFM were oriented more toward dorsal and plantar flexion, respectively, and internal rotation, while AFM was not statistically different in the sagittal and transverse plane. In the frontal plane, OFM was more toward eversion and RFM and AFM more toward inversion compared to BCS. Inter-subject bone pose variability was captured with RFM and AFM in most planes of the hindfoot and forefoot, while this variability was not captured by OFM. When interpreting multi-segment foot model data it is important to realize that MCSs and BCSs do not always align.

The efficacy of different torque profiles for weight compensation of the hand.

Orthotic wrist supports will be beneficial for people with muscular weakness to keep their hand in a neutral rest position and prevent potential wrist contractures. Compensating the weight of the hands is complex since the level of support depends on both wrist and forearm orientations. To explore simplified approaches, two different weight compensation strategies (constant and linear) were compared to the theoretical ideal sinusoidal profile and no compensation in eight healthy subjects using a mechanical wrist support system. All three compensation strategies showed a significant reduction of 47-53% surface electromyography activity in the anti-gravity m. extensor carpi radialis. However, for the higher palmar flexion region, a significant increase of 44-61% in the m. flexor carpi radialis was found for all compensation strategies. No significant differences were observed between the various compensation strategies. Two conclusions can be drawn: (1) a simplified torque profile (e.g., constant or linear) for weight compensation can be considered as equally effective as the theoretically ideal sinusoidal profile and (2) even the theoretically ideal profile provides no perfect support as other factors than weight, such as passive joint impedance, most likely influence the required compensation torque for the wrist joint.

Design requirements of upper extremity supports for daily use in Duchenne muscular dystrophy with severe muscle weakness.

Background: People with Duchenne muscular dystrophy (DMD) cope with progressive muscular weakness and consequential upper extremity function loss. They benefit from arm supports, or arm exoskeletons, to assist arm function. Especially for severe muscle weakness (DMD ≥ Brooke Scale 4), the design of such arm support is challenging. This study aims to structurally develop functional and technical design requirements of arm supports for people with DMD Brooke Scale 4. Methods: An overview of clinical characteristics and a classification of clinically meaningful activities were derived from data from the Dutch Dystrophinopathy Database and available literature. Based on these, functional and technical design requirements of arm supports were developed and matched to the achievable needs of the user. Results: First, the clinical characteristics of the target population, such as strength, range of motion, and functional ability, are given. Next, clinically relevant activities of daily living are translated to functional requirements categorised in a 'must,' 'should,' and 'could' category. Last, the technical requirements to realise these functional goals are presented. Conclusions: The recommendations following from the functional user needs, technical requirements, and safety considerations can be used to make the development of assistive arm supports for people with DMD Brooke Scale 4 more user-centred.

Predictive simulations identify potential neuromuscular contributors to idiopathic toe walking.

BACKGROUND: Most cases of toe walking in children are idiopathic. We used pathology-specific neuromusculoskeletal predictive simulations to identify potential underlying neural and muscular mechanisms contributing to idiopathic toe walking. METHODS: A musculotendon contracture was added to the ankle plantarflexors of a generic musculoskeletal model to represent a pathology-specific contracture model, matching the reduced ankle dorsiflexion range-of-motion in a cohort of children with idiopathic toe walking. This model was employed in a forward dynamic simulation controlled by reflexes and supraspinal drive, governed by a multi-objective cost function to predict gait patterns with the contracture model. We validated the predicted gait using experimental gait data from children with idiopathic toe walking with ankle contracture, by calculating the root mean square errors averaged over all biomechanical variables. FINDINGS: A predictive simulation with the pathology-specific model with contracture approached experimental ITW data (root mean square error = 1.37SD). Gastrocnemius activation was doubled from typical gait simulations, but lacked a peak in early stance as present in electromyography. This synthesised idiopathic toe walking was more costly for all cost function criteria than typical gait simulation. Also, it employed a different neural control strategy, with increased length- and velocity-based reflex gains to the plantarflexors in early stance and swing than typical gait simulations. INTERPRETATION: The simulations provide insights into how a musculotendon contracture combined with altered neural control could contribute to idiopathic toe walking. Insights into these neuromuscular mechanisms could guide future computational and experimental studies to gain improved insight into the cause of idiopathic toe walking.

Comparison of Lower Arm Weight and Passive Elbow Joint Impedance Compensation Strategies in Non-Disabled Participants.

People with severe muscle weakness in the upper extremity are in need of an arm support to enhance arm function and improve their quality of life. In addition to weight support, compensation of passive joint impedance (pJimp) seems necessary. Existing devices do not compensate for pJimp yet, and the best way to compensate for it is still unknown. The aim of this study is to 1) identify pJimp of the elbow, and 2) compare four different compensation strategies of weight and combined weight and pJimp in an active elbow support system. The passive elbow joint moments, including gravitational and pJimp contributions, were measured in 12 non-disabled participants. The four compensation strategies (scaled-model, measured, hybrid, and fitted-model) were compared using a position-tracking task in the near vertical plane. All four strategies showed a significant reduction (20-47%) in the anti-gravity elbow flexor activity measured by surface electromyography. The pJimp turned out to contribute to a large extent to the passive elbow joint moments (range took up 60%) in non-disabled participants. This underlines the relevance of compensating for pJimp in arm support systems. The parameters of the scaled-model and hybrid strategy seem to overestimate the gravitational component. Therefore, the measured and fitted-model strategies are expected to be most promising to test in people with severe muscle weakness combined with elevated pJimp.

Predicting Gait Patterns of Children With Spasticity by Simulating Hyperreflexia.

Spasticity is a common impairment within pediatric neuromusculoskeletal disorders. How spasticity contributes to gait deviations is important for treatment selection. Our aim was to evaluate the pathophysiological mechanisms underlying gait deviations seen in children with spasticity, using predictive simulations. A cluster analysis was performed to extract distinct gait patterns from experimental gait data of 17 children with spasticity to be used as comparative validation data. A forward dynamic simulation framework was employed to predict gait with either velocity- or force-based hyperreflexia. This framework entailed a generic musculoskeletal model controlled by reflexes and supraspinal drive, governed by a multiobjective cost function. Hyperreflexia values were optimized to enable the simulated gait to best match experimental gait patterns. Three experimental gait patterns were extracted: (1) increased knee flexion, (2) increased ankle plantar flexion, and (3) increased knee flexion and ankle plantar flexion when compared with typical gait. Overall, velocity-based hyperreflexia outperformed force-based hyperreflexia. The first gait pattern could mostly be explained by rectus femoris and hamstrings velocity-based hyperreflexia, the second by gastrocnemius velocity-based hyperreflexia, and the third by gastrocnemius, soleus, and hamstrings velocity-based hyperreflexia. This study shows how velocity-based hyperreflexia from specific muscles contributes to different spastic gait patterns, which may help in providing targeted treatment.

Electromyographic biofeedback-driven gaming to alter calf muscle activation during gait in children with spastic cerebral palsy.

BACKGROUND: Children with cerebral palsy often show deviating calf muscle activation patterns during gait, with excess activation during early stance and insufficient activation during push-off. RESEARCH QUESTION: Can children with cerebral palsy improve their calf muscle activation patterns during gait using one session of biofeedback-driven gaming? METHODS: Eighteen children (6-17 y) with spastic cerebral palsy received implicit game-based biofeedback on electromyographic activity of the calf muscle (soleus or gastrocnemius medialis) while walking on a treadmill during one session. Biofeedback alternately aimed to reduce early stance activity, increase push-off activity, and both combined. Early stance and push-off activity and the double-bump-index (early stance divided by push-off activity) were determined during baseline and walking with feedback. Changes were assessed at group level using repeated measures ANOVA with simple contrast or Friedman test with post-hoc Wilcoxon signed rank test, as well as individually using independent t-tests or Wilcoxon rank sum tests. Perceived competence and interest-enjoyment were assessed through a questionnaire. RESULTS: Children successfully decreased their electromyographic activity during early stance feedback trials (relative decrease of 6.8 ± 12.2 %, P = 0.025), with a trend during the combined feedback trials (6.5 ± 13.9 %, P = 0.055), and increased their electromyographic activity during push-off feedback trials (8.1 ± 15.8 %, P = 0.038). Individual improvements were seen in twelve of eighteen participants. All children experienced high levels of interest-enjoyment (8.4/10) and perceived competence (8.1/10). SIGNIFICANCE: This exploratory study suggests that children with cerebral palsy can achieve small within-session improvements of their calf muscle activation pattern when provided with implicit biofeedback-driven gaming in an enjoyable manner. Follow-up gait training studies can incorporate this method to assess retention and long-term functional benefits of electromyographic biofeedback-driven gaming.

Towards automated video-based assessment of dystonia in dyskinetic cerebral palsy: A novel approach using markerless motion tracking and machine learning.

Introduction: Video-based clinical rating plays an important role in assessing dystonia and monitoring the effect of treatment in dyskinetic cerebral palsy (CP). However, evaluation by clinicians is time-consuming, and the quality of rating is dependent on experience. The aim of the current study is to provide a proof-of-concept for a machine learning approach to automatically assess scoring of dystonia using 2D stick figures extracted from videos. Model performance was compared to human performance. Methods: A total of 187 video sequences of 34 individuals with dyskinetic CP (8-23 years, all non-ambulatory) were filmed at rest during lying and supported sitting. Videos were scored by three raters according to the Dyskinesia Impairment Scale (DIS) for arm and leg dystonia (normalized scores ranging from 0-1). Coordinates in pixels of the left and right wrist, elbow, shoulder, hip, knee and ankle were extracted using DeepLabCut, an open source toolbox that builds on a pose estimation algorithm. Within a subset, tracking accuracy was assessed for a pretrained human model and for models trained with an increasing number of manually labeled frames. The mean absolute error (MAE) between DeepLabCut's prediction of the position of body points and manual labels was calculated. Subsequently, movement and position features were calculated from extracted body point coordinates. These features were fed into a Random Forest Regressor to train a model to predict the clinical scores. The model performance trained with data from one rater evaluated by MAEs (model-rater) was compared to inter-rater accuracy. Results: A tracking accuracy of 4.5 pixels (approximately 1.5 cm) could be achieved by adding 15-20 manually labeled frames per video. The MAEs for the trained models ranged from 0.21 ± 0.15 for arm dystonia to 0.14 ± 0.10 for leg dystonia (normalized DIS scores). The inter-rater MAEs were 0.21 ± 0.22 and 0.16 ± 0.20, respectively. Conclusion: This proof-of-concept study shows the potential of using stick figures extracted from common videos in a machine learning approach to automatically assess dystonia. Sufficient tracking accuracy can be reached by manually adding labels within 15-20 frames per video. With a relatively small data set, it is possible to train a model that can automatically assess dystonia with a performance comparable to human scoring.

Reaction moments matter when designing lower-extremity robots for tripping recovery.

Balance recovery after tripping often requires an active adaptation of foot placement. Thus far, few attempts have been made to actively assist forward foot placement for balance recovery employing wearable devices. This study aims to explore the possibilities of active forward foot placement through two paradigms of actuation: assistive moments exerted with the reaction moments either internal or external to the human body, namely 'joint' moments and 'free' moments, respectively. Both paradigms can be applied to manipulate the motion of segments of the body (e.g., the shank or thigh), but joint actuators also exert opposing reaction moments on neighbouring body segments, altering posture and potentially inhibiting tripping recovery. We therefore hypothesised that a free moment paradigm is more effective in assisting balance recovery following tripping. The simulation software SCONE was used to simulate gait and tripping over various ground-fixed obstacles during the early swing phase. To aid forward foot placement, joint moments and free moments were applied either on the thigh to augment hip flexion or on the shank to augment knee extension. Two realizations of joint moments on the hip were simulated, with the reaction moment applied to either the pelvis or the contralateral thigh. The simulation results show that assisting hip flexion with either actuation paradigm on the thigh can result in full recovery of gait with a margin of stability and leg kinematics closely matching the unperturbed case. However, when assisting knee extension with moments on the shank, free moment effectively assist balance but joint moments with the reaction moment on the thigh do not. For joint moments assisting hip flexion, placement of the reaction moment on the contralateral thigh was more effective in achieving the desired limb dynamics than placing the reaction on the pelvis. Poor choice of placement of reaction moments may therefore have detrimental consequences for balance recovery, and removing them entirely (i.e., free moment) could be a more effective and reliable alternative. These results challenge conventional assumptions and may inform the design and development of a new generation of minimalistic wearable devices to promote balance during gait.

Personalisation of Plantarflexor Musculotendon Model Parameters in Children with Cerebral Palsy.

Neuromusculoskeletal models can be used to evaluate aberrant muscle function in cerebral palsy (CP), for example by estimating muscle and joint contact forces during gait. However, to be accurate, models should include representative musculotendon parameters. We aimed to estimate personalised parameters that capture the mechanical behaviour of the plantarflexors in children with CP and typically developing (TD) children. Ankle angle (using motion capture), torque (using a load-cell), and medial gastrocnemius fascicle lengths (using ultrasound) were measured during slow passive ankle dorsiflexion rotation for thirteen children with spastic CP and thirteen TD children. Per subject, the measured rotation was input to a scaled OpenSim model to simulate the torque and fascicle length output. Musculotendon model parameters were personalised by the best match between simulated and experimental torque-angle and fascicle length-angle curves according to a least-squares fit. Personalised tendon slack lengths were significantly longer and optimal fibre lengths significantly shorter in CP than model defaults and than in TD. Personalised tendon compliance was substantially higher in both groups compared to the model default. The presented method to personalise musculotendon parameters will likely yield more accurate simulations of subject-specific muscle mechanics, to help us understand the effects of altered musculotendon properties in CP.

The associations of knee extensor muscle steadiness with maximal voluntary torque and physical function in patients with knee osteoarthritis.

BACKGROUND: Muscle weakness is characteristic of knee osteoarthritis. Muscle steadiness may be an important adjunct to knee muscle strength in improving physical function in knee osteoarthritis. However, the role of muscle steadiness is uncertain. AIMS: To determine the associations of knee extensor muscle steadiness with maximal voluntary torque and physical function in patients with knee osteoarthritis. METHODS: Baseline data from 177 patients in a randomized clinical trial were used. Isokinetic knee extension torque was processed into maximal voluntary torque [Nm]. Muscle steadiness was expressed as the coefficient of variance [%] and as peak power frequency [Hz]. Physical function was assessed using the Western Ontario and McMaster Universities Osteoarthritis Index, the Get-Up-and-Go and Stair-climb tests. Associations were determined using regression analyses and adjusted for confounders. FINDINGS: Lower muscle steadiness (i.e., higher coefficient of variance and peak power frequency) was associated with lower maximal voluntary torque (B = - 7.38, [-10.8, -3.95], R2 = 0.10 and B = -14.71, [-28.29, -1.13], R2 = 0.03, respectively). Higher coefficient of variance was associated with lower self-reported physical function (B = 1.14, [0.11,2.17], R2 = 0.03) and remained significant after adjusting for potential confounders. Peak power frequency was not associated with physical function. INTERPRETATION: Low muscle steadiness was weakly associated with low muscle strength and poorer self-reported physical function. Muscle steadiness and muscle strength seem to be different attributes of muscle function. There is no convincing evidence that muscle steadiness is an important adjunct in studying physical function in patients with knee osteoarthritis.

Home-Based Measurements of Dystonia in Cerebral Palsy Using Smartphone-Coupled Inertial Sensor Technology and Machine Learning: A Proof-of-Concept Study.

Accurate and reliable measurement of the severity of dystonia is essential for the indication, evaluation, monitoring and fine-tuning of treatments. Assessment of dystonia in children and adolescents with dyskinetic cerebral palsy (CP) is now commonly performed by visual evaluation either directly in the doctor's office or from video recordings using standardized scales. Both methods lack objectivity and require much time and effort of clinical experts. Only a snapshot of the severity of dyskinetic movements (i.e., choreoathetosis and dystonia) is captured, and they are known to fluctuate over time and can increase with fatigue, pain, stress or emotions, which likely happens in a clinical environment. The goal of this study was to investigate whether it is feasible to use home-based measurements to assess and evaluate the severity of dystonia using smartphone-coupled inertial sensors and machine learning. Video and sensor data during both active and rest situations from 12 patients were collected outside a clinical setting. Three clinicians analyzed the videos and clinically scored the dystonia of the extremities on a 0-4 scale, following the definition of amplitude of the Dyskinesia Impairment Scale. The clinical scores and the sensor data were coupled to train different machine learning models using cross-validation. The average F1 scores (0.67 ± 0.19 for lower extremities and 0.68 ± 0.14 for upper extremities) in independent test datasets indicate that it is possible to detected dystonia automatically using individually trained models. The predictions could complement standard dyskinetic CP measures by providing frequent, objective, real-world assessments that could enhance clinical care. A generalized model, trained with data from other subjects, shows lower F1 scores (0.45 for lower extremities and 0.34 for upper extremities), likely due to a lack of training data and dissimilarities between subjects. However, the generalized model is reasonably able to distinguish between high and lower scores. Future research should focus on gathering more high-quality data and study how the models perform over the whole day.

The Amsterdam Foot Model: a clinically informed multi-segment foot model developed to minimize measurement errors in foot kinematics.

BACKGROUND: Foot and ankle joint kinematics are measured during clinical gait analyses with marker-based multi-segment foot models. To improve on existing models, measurement errors due to soft tissue artifacts (STAs) and marker misplacements should be reduced. Therefore, the aim of this study is to define a clinically informed, universally applicable multi-segment foot model, which is developed to minimize these measurement errors. METHODS: The Amsterdam foot model (AFM) is a follow-up of existing multi-segment foot models. It was developed by consulting a clinical expert panel and optimizing marker locations and segment definitions to minimize measurement errors. Evaluation of the model was performed in three steps. First, kinematic errors due to STAs were evaluated and compared to two frequently used foot models, i.e. the Oxford and Rizzoli foot models (OFM, RFM). Previously collected computed tomography data was used of 15 asymptomatic feet with markers attached, to determine the joint angles with and without STAs taken into account. Second, the sensitivity to marker misplacements was determined for AFM and compared to OFM and RFM using static standing trials of 19 asymptomatic subjects in which each marker was virtually replaced in multiple directions. Third, a preliminary inter- and intra-tester repeatability analysis was performed by acquiring 3D gait analysis data of 15 healthy subjects, who were equipped by two testers for two sessions. Repeatability of all kinematic parameters was assessed through analysis of the standard deviation (σ) and standard error of measurement (SEM). RESULTS: The AFM was defined and all calculation methods were provided. Errors in joint angles due to STAs were in general similar or smaller in AFM (≤2.9°) compared to OFM (≤4.0°) and RFM (≤6.7°). AFM was also more robust to marker misplacement than OFM and RFM, as a large sensitivity of kinematic parameters to marker misplacement (i.e. > 1.0°/mm) was found only two times for AFM as opposed to six times for OFM and five times for RFM. The average intra-tester repeatability of AFM angles was σ:2.2[0.9°], SEM:3.3 ± 0.9° and the inter-tester repeatability was σ:3.1[2.1°], SEM:5.2 ± 2.3°. CONCLUSIONS: Measurement errors of AFM are smaller compared to two widely-used multi-segment foot models. This qualifies AFM as a follow-up to existing foot models, which should be evaluated further in a range of clinical application areas.

Responsiveness of the Foot Profile Score in children with hemiplegia.

BACKGROUND: The Foot Profile Score (FPS) is a single score that summarises foot posture and dynamic foot motion during the gait cycle based on the kinematic data of the Oxford Foot Model. The FPS enables clinicians and researchers to quantify foot abnormalities during gait, to monitor change in foot/ankle motion over time, and to measure the outcome of intervention. With the creation of a new outcome measure, it is important to test its responsiveness in a clinical population for whom it may be sensitive to change. AIM: To evaluate the responsiveness of the FPS in a clinical population following isolated foot and ankle surgery. METHODS: Using previous work completed to validate the FPS, we defined the minimal clinically important difference (MCID) for the FPS. Using this MCID, we applied it to a clinical population of 37 children with cerebral palsy, spastic hemiplegia, comparing their FPS before and after foot and ankle surgery. A regression analysis looked at potential relationships between the change in FPS and their pre-operative FPS, age at surgery, and time since surgery. RESULTS: An MCID of 2.4 degrees was calculated through regression analysis. The mean change from the pre-operative FPS to the post-operative FPS was 4.6 (SD 3.7 with a range from -0.1 to 13.4). Twenty-eight children (76%) had a change in their FPS greater than the MCID. A regression analyses only showed a clear regression between pre-operative FPS and change in FPS (R2 = 0.58 p < 0.01).

Exergaming improves balance in children with spastic cerebral palsy with low balance performance: results from a multicenter controlled trial.

PURPOSE: Previous studies investigating the effectiveness of exergame balance-training (using video-games) in children with cerebral palsy (CP) yielded inconsistent results that could be related to underpowered studies. Therefore, in this multicenter intervention study, we investigated whether exergaming improves balance clinically in spastic CP. MATERIALS AND METHODS: In total, 35 children with unilateral or bilateral spastic CP (GMFCS-level I-II) were included (age-range: 7-16 years); 16 at VUMC (trial: NTR6034), 19 at UHG (trial: NCT03219112). All participants received care as usual. The intervention group (n = 24) additionally performed exergame-training; 6-8 weeks home-based X-box One Kinect training focused on balance. Balance performance was assessed with the pediatric balance scale (PBS) and two subscales of the Bruininks-Oseretsky Test of Motor Proficiency-2nd edition ("balance" [BOTbal] and "running speed and agility" [BOTrsa]). Mixed model ANOVAs with between and within factors were used to test differences between and within groups. RESULTS: On group level, no post-intervention differences were found between the intervention and control group (PBS: p = 0.248, ηp2 = 0.040; BOTbal: p = 0.374, ηp2 = 0.024; BOTrsa: p = 0.841, ηp2 = 0.001). Distribution of CP-symptoms (unilateral versus bilateral) did not affect training (PBS: p = 0.373, ηp2 = 0.036; BOTbal: p = 0.127, ηp2 = 0.103; BOTrsa: p = 0.474, ηp2 = 0.024). Children with low baseline balance performance (based on PBS) in the intervention group showed improvements in balance performance after training (PBS: p = 0.003, ηp2 = 0.304; BOTbal: p = 0.008, ηp2 = 0.258), whereas children with high baseline balance performance did not. CONCLUSIONS: This exergame-training resulted in balance improvements for the current population of CP that had a low baseline function.IMPLICATIONS FOR REHABILITATIONExergame-training (training using video-games) shows mixed results in children with cerebral palsy (CP).Children with spastic CP (GMFCS level I-II) with a high baseline balance-level did not show functional balance improvements after this home-based exergame-training, suggesting that these children should not be enrolled in this type of exergame-training protocol.Children with spastic CP (GMFCS level I-II) with a low baseline balance-level showed clinically relevant functional balance improvements after this home-based exergame-training, suggesting that these children can benefit from enrolment in this type of exergame-training protocol to improve their balance.The distribution of CP-symptoms did not affect the effectiveness of this balance exergame-training in children with spastic CP with GMFCS-level I and II.

The Stumblemeter: Design and Validation of a System That Detects and Classifies Stumbles during Gait.

Stumbling during gait is commonly encountered in patients who suffer from mild to serious walking problems, e.g., after stroke, in osteoarthritis, or amputees using a lower leg prosthesis. Instead of self-reporting, an objective assessment of the number of stumbles in daily life would inform clinicians more accurately and enable the evaluation of treatments that aim to achieve a safer walking pattern. An easy-to-use wearable might fulfill this need. The goal of the present study was to investigate whether a single inertial measurement unit (IMU) placed at the shank and machine learning algorithms could be used to detect and classify stumbling events in a dataset comprising of a wide variety of daily movements. Ten healthy test subjects were deliberately tripped by an unexpected and unseen obstacle while walking on a treadmill. The subjects stumbled a total of 276 times, both using an elevating recovery strategy and a lowering recovery strategy. Subjects also performed multiple Activities of Daily Living. During data processing, an event-defined window segmentation technique was used to trace high peaks in acceleration that could potentially be stumbles. In the reduced dataset, time windows were labelled with the aid of video annotation. Subsequently, discriminative features were extracted and fed to train seven different types of machine learning algorithms. Trained machine learning algorithms were validated using leave-one-subject-out cross-validation. Support Vector Machine (SVM) algorithms were most successful, and could detect and classify stumbles with 100% sensitivity, 100% specificity, and 96.7% accuracy in the independent testing dataset. The SVM algorithms were implemented in a user-friendly, freely available, stumble detection app named Stumblemeter. This work shows that stumble detection and classification based on SVM is accurate and ready to apply in clinical practice.

Functional assessment of stretch hyperreflexia in children with cerebral palsy using treadmill perturbations.

BACKGROUND: As hyperactive muscle stretch reflexes hinder movement in patients with central nervous system disorders, they are a common target of treatment. To improve treatment evaluation, hyperactive reflexes should be assessed during activities as walking rather than passively. This study systematically explores the feasibility, reliability and validity of sudden treadmill perturbations to evoke and quantify calf muscle stretch reflexes during walking in children with neurological disorders. METHODS: We performed an observational cross-sectional study including 24 children with cerebral palsy (CP; 6-16 years) and 14 typically developing children (TD; 6-15 years). Short belt accelerations were applied at three different intensities while children walked at comfortable speed. Lower leg kinematics, musculo-tendon lengthening and velocity, muscle activity and spatiotemporal parameters were measured to analyze perturbation responses. RESULTS: We first demonstrated protocol feasibility: the protocol was completed by all but three children who ceased participation due to fatigue. All remaining children were able to maintain their gait pattern during perturbation trials without anticipatory adaptations in ankle kinematics, spatiotemporal parameters and muscle activity. Second, we showed the protocol's reliability: there was no systematic change in muscle response over time (P = 0.21-0.54) and a bootstrapping procedure indicated sufficient number of perturbations, as the last perturbation repetition only reduced variability by ~ 2%. Third, we evaluated construct validity by showing that responses comply with neurophysiological criteria for stretch reflexes: perturbations superimposed calf muscle lengthening (P < 0.001 for both CP and TD) in all but one participant. This elicited increased calf muscle activity (359 ± 190% for CP and 231 ± 68% for TD, both P < 0.001) in the gastrocnemius medialis muscle, which increased with perturbation intensity (P < 0.001), according to the velocity-dependent nature of stretch reflexes. Finally, construct validity was shown from a clinical perspective: stretch reflexes were 1.7 times higher for CP than TD for the gastrocnemius medialis muscle (P = 0.017). CONCLUSIONS: The feasibility and reliability of the protocol, as well as the construct validity-shown by the exaggerated velocity-dependent nature of the measured responses-strongly support the use of treadmill perturbations to quantify stretch hyperreflexia during gait. We therefore provided a framework which can be used to inform clinical decision making and treatment evaluation.

A most painful knee does not induce interlimb differences in knee and hip moments during gait in patients with knee osteoarthritis.

BACKGROUND: Patients with knee osteoarthritis can adapt their gait to unload the most painful knee joint in order to try to reduce pain and improve physical function. However, these gait adaptations can cause higher loads on the contralateral joints. The aim of the study was to investigate the interlimb differences in knee and hip frontal plane moments during gait in patients with knee osteoarthritis and in healthy controls. METHODS: Forty patients with knee osteoarthritis and 19 healthy matched controls were measured during comfortable treadmill walking. Frontal plane joint moments were obtained of both hip and knee joints. Differences in interlimb moments within each group were assessed using statistical parametric mapping and discrete gait parameters. FINDINGS: No interlimb differences were observed in patients with knee osteoarthritis and control subjects at group level. Furthermore, the patients presented similar interlimb variability as the controls. In a small subgroup (n = 12) of patients, the moments in the most painful knee were lower than in the contralateral knee, while the other patients (n = 28) showed higher moments in the most painful knee compared to the contralateral knee. However, no interlimb differences in the hip moments were observed within the subgroups. INTERPRETATION: Patients with knee osteoarthritis do not have interlimb differences in knee and hip joint moments. Patients and healthy subjects demonstrate a similar interlimb variability in the moments of the lower extremities. In this context, differences in knee pain in patients with knee osteoarthritis did not induce any interlimb differences in the frontal plane knee and hip moments.

Responses in knee joint muscle activation patterns to different perturbations during gait in healthy subjects.

PURPOSE: To compare the responses in knee joint muscle activation patterns to different perturbations during gait in healthy subjects. SCOPE: Nine healthy participants were subjected to perturbed walking on a split-belt treadmill. Four perturbation types were applied, each at five intensities. The activations of seven muscles surrounding the knee were measured using surface EMG. The responses in muscle activation were expressed by calculating mean, peak, co-contraction (CCI) and perturbation responses (PR) values. PR captures the responses relative to unperturbed gait. Statistical parametric mapping analysis was used to compare the muscle activation patterns between conditions. RESULTS: Perturbations evoked only small responses in muscle activation, though higher perturbation intensities yielded a higher mean activation in five muscles, as well as higher PR. Different types of perturbation led to different responses in the rectus femoris, medial gastrocnemius and lateral gastrocnemius. The participants had lower CCI just before perturbation compared to the same phase of unperturbed gait. CONCLUSIONS: Healthy participants respond to different perturbations during gait with small adaptations in their knee joint muscle activation patterns. This study provides insights in how the muscles are activated to stabilize the knee when challenged. Furthermore it could guide future studies in determining aberrant muscle activation in patients with knee disorders.