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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.

Duchenne Muscular Dystrophy (DMD) progressively leads to loss of limb function due to muscle weakness. The incurable nature of the disease shifts the focus to improving quality of life, including assistive supports to improve arm function. Over time, the passive joint impedance (Jimp) of people with DMD increases. Force-based controlled motorised arm supports require a clear distinction between the user’s movement intention and passive forces, such as passive Jimp. Therefore, Jimp identification is essential. This review aims to define Jimp, identify factors influencing it, and outline experimental methods used for quantification, with a focus on the upper extremities in DMD. A literature review was performed in May 2021 and updated in March 2024 using SCOPUS, PubMed, IEEEXplore, and WebOfScience. The results reveal confusion in definitions and show various Jimp measuring practices for both DMD and individuals without muscle weakness. This study presents an overview and lists important parameters affecting passive Jimp, such as the joint’s position, velocity and the multi-articular nature of the upper arm muscles. For personalised passive Jimp compensation in arm supports, ramp-type perturbations with constant velocity across the full joint range appear most optimal for identifying the elevated and non-linear nature of the passive Jimp in DMD.

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.

Background In people with calf muscle weakness, the stiffness of dorsal leaf spring ankle–foot orthoses (DLS-AFO) needs to be individualized to maximize its effect on walking. Orthotic suppliers may recommend a certain stiffness based on body weight and activity level. However, it is unknown whether these recommendations are sufficient to yield the optimal stiffness for the individual. Therefore, we assessed whether the stiffness following the supplier’s recommendation of the Carbon Ankle7 (CA7) dorsal leaf matched the experimentally optimized AFO stiffness. Methods Thirty-four persons with calf muscle weakness were included and provided a new DLS-AFO of which the stiffness could be varied by changing the CA7® (Ottobock, Duderstadt, Germany) dorsal leaf. For five different stiffness levels, including the supplier recommended stiffness, gait biomechanics, walking energy cost and speed were assessed. Based on these measures, the individual experimentally optimal AFO stiffness was selected. Results In only 8 of 34 (23%) participants, the supplier recommended stiffness matched the experimentally optimized AFO stiffness, the latter being on average 1.2 ± 1.3 Nm/degree more flexible. The DLS-AFO with an experimentally optimized stiffness resulted in a significantly lower walking energy cost (− 0.21 ± 0.26 J/kg/m, p  < 0.001) and a higher speed (+ 0.02 m/s, p  = 0.003). Additionally, a larger ankle range of motion (+ 1.3 ± 0.3 degrees, p  < 0.001) and higher ankle power (+ 0.16 ± 0.04 W/kg, p  < 0.001) were found with the experimentally optimized stiffness compared to the supplier recommended stiffness. Conclusions In people with calf muscle weakness, current supplier’s recommendations for the CA7 stiffness level result in the provision of DLS-AFOs that are too stiff and only achieve 80% of the reduction in energy cost achieved with an individual optimized stiffness. It is recommended to experimentally optimize the CA7 stiffness in people with calf muscle weakness in order to maximize treatment outcomes. Trial registration Nederlands Trial Register 5170. Registration date: May 7th 2015. http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5170 .

Rigid Ankle-Foot Orthoses (AFOs) are commonly prescribed to counteract excessive knee flexion during the stance phase of gait in children with cerebral palsy (CP). While rigid AFOs may normalize knee kinematics and kinetics effectively, it has the disadvantage of impeding push-off power. A spring-like AFO may enhance push-off power, which may come at the cost of reducing the knee flexion less effectively. Optimizing this trade-off between enhancing push-off power and normalizing knee flexion in stance is expected to maximize gait efficiency. This study investigated the effects of varying AFO stiffness on gait biomechanics and efficiency in children with CP who walk with excessive knee flexion in stance. Fifteen children with spastic CP (11 boys, 10±2 years) were prescribed with a ventral shell spring-hinged AFO (vAFO). The hinge was set into a rigid, or spring-like setting, using both a stiff and flexible performance. At baseline (i.e. shoes-only) and for each vAFO, a 3D-gait analysis and 6-minute walk test with breath-gas analysis were performed at comfortable speed. Lower limb joint kinematics and kinetics were calculated. From the 6-minute walk test, walking speed and the net energy cost were determined. A generalized estimation equation (p<0.05) was used to analyze the effects of different conditions. Compared to shoes-only, all vAFOs improved the knee angle and net moment similarly. Ankle power generation and work were preserved only by the spring-like vAFOs. All vAFOs decreased the net energy cost compared to shoes-only, but no differences were found between vAFOs, showing that the effects of spring-like vAFOs to promote push-off power did not lead to greater reductions in walking energy cost. These findings suggest that, in this specific group of children with spastic CP, the vAFO stiffness that maximizes gait efficiency is primarily determined by its effect on knee kinematics and kinetics rather than by its effect on push-off power. Dutch Trial Register NTR3418.

Background To improve gait, persons with calf muscle weakness can be provided with a dorsal leaf spring ankle foot orthosis (DLS-AFO). These AFOs can store energy during stance and return this energy during push-off, which, in turn, reduces walking energy cost. Simulations indicate that the effect of the DLS-AFO on walking energy cost and gait biomechanics depends on its stiffness and on patient characteristics. We therefore studied the effect of varying DLS-AFO stiffness on reducing walking energy cost, and improving gait biomechanics and AFO generated power in persons with non-spastic calf muscle weakness, and whether the optimal AFO stiffness for maximally reducing walking energy cost varies between persons. Methods Thirty-seven individuals with neuromuscular disorders and non-spastic calf muscle weakness were included. Participants were provided with a DLS-AFO of which the stiffness could be varied. For 5 stiffness configurations (ranging from 2.8 to 6.6 Nm/degree), walking energy cost (J/kg/m) was assessed using a 6-min comfortable walk test. Selected gait parameters, e.g. maximal dorsiflexion angle, ankle power, knee angle, knee moment and AFO generated power, were derived from 3D gait analysis. Results On group level, no significant effect of DLS-AFO stiffness on reducing walking energy cost was found ( p  = 0.059, largest difference: 0.14 J/kg/m). The AFO stiffness that reduced energy cost the most varied between persons. The difference in energy cost between the least and most efficient AFO stiffness was on average 10.7%. Regarding gait biomechanics, increasing AFO stiffness significantly decreased maximal ankle dorsiflexion angle (− 1.1 ± 0.1 degrees per 1 Nm/degree, p  < 0.001) and peak ankle power (− 0.09 ± 0.01 W/kg, p  < 0.001). The reduction in minimal knee angle (− 0.3 ± 0.1 degrees, p  = 0.034), and increment in external knee extension moment in stance (− 0.01 ± 0.01 Nm/kg, p  = 0.016) were small, although all stiffness’ substantially affected knee angle and knee moment compared to shoes only. No effect of stiffness on AFO generated power was found ( p  = 0.900). Conclusions The optimal efficient DLS-AFO stiffness varied largely between persons with non-spastic calf muscle weakness. Results indicate this is caused by an individual trade-off between ankle angle and ankle power affected differently by AFO stiffness. We therefore recommend that the AFO stiffness should be individually optimized to best improve gait. Trial registration number Nederlands Trial Register 5170. Registration date: May 7th 2015. http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5170

Movement of skin markers with respect to their underlying bone (i.e. soft tissue artifacts (STAs)) might corrupt the accuracy of marker-based movement analyses. This study aims to quantify STAs in 3D for foot markers and their effect on multi-segment foot kinematics as calculated by the Oxford and Rizzoli Foot Models (OFM, RFM). Fifteen subjects with asymptomatic feet were seated on a custom-made loading device on a computed tomography (CT) table, with a combined OFM and RFM marker set on their right foot. One unloaded reference CT-scan with neutral foot position was performed, followed by 9 loaded CT-scans at different foot positions. The 3D-displacement (i.e. STA) of each marker in the underlying bone coordinate system between the reference scan and other scans was calculated. Subsequently, segment orientations and joint angles were calculated from the marker positions according to OFM and RFM definitions with and without STAs. The differences in degrees were defined as the errors caused by the marker displacements. Markers on the lateral malleolus and proximally on the posterior aspect of the calcaneus showed the largest STAs. The hindfoot-shank joint angle was most affected by STAs in the most extreme foot position (40° plantar flexion) in the sagittal plane for RFM (mean: 6.7°, max: 11.8°) and the transverse plane for OFM (mean: 3.9°, max: 6.8°). This study showed that STAs introduce clinically relevant errors in multi-segment foot kinematics. Moreover, it identified marker locations that are most affected by STAs, suggesting that their use within multi-segment foot models should be reconsidered.

Background Gait retraining interventions using real-time biofeedback have been proposed to alter the loading across the knee joint in patients with knee osteoarthritis. Despite the demonstrated benefits of these conservative treatments, their clinical adoption is currently obstructed by the high complexity, spatial demands, and cost of optical motion capture systems. In this study we propose and evaluate a wearable visual feedback system for gait retraining of the foot progression angle (FPA). Methods The primary components of the system are inertial measurement units, which track the human movement without spatial limitations, and an augmented reality headset used to project the visual feedback in the visual field. The adapted gait protocol contained five different target angles ranging from 15 degrees toe-out to 5 degrees toe-in. Eleven healthy participants walked on an instrumented treadmill, and the protocol was performed using both an established laboratory visual feedback driven by optical motion capture, and the proposed wearable system. Results and conclusions The wearable system tracked FPA with an accuracy of 2.4 degrees RMS and ICC=0.94 across all target angles and subjects, when compared to an optical motion capture reference. In addition, the effectiveness of the biofeedback, reflected by the number of steps with FPA value ±2 degrees from the target, was found to be around 50% in both wearable and laboratory approaches. These findings demonstrate that retraining of the FPA using wearable inertial sensing and visual feedback is feasible with effectiveness matching closely an established laboratory method. The proposed wearable setup may reduce the complexity of gait retraining applications and facilitate their transfer to routine clinical practice.

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.

Background In this systematic review we investigate which instrumented measurements are available to assess motor impairments, related activity limitations and participation restrictions in children and young adults with dyskinetic cerebral palsy. We aim to classify these instrumented measurements using the categories of the international classification of functioning, disability and health for children and youth (ICF-CY) and provide an overview of the outcome parameters. Methods A systematic literature search was performed in November 2019. We electronically searched Pubmed, Embase and Scopus databases. Search blocks included (a) cerebral palsy, (b) athetosis, dystonia and/or dyskinesia, (c) age 2–24 years and (d) instrumented measurements (using keywords such as biomechanics, sensors, smartphone, and robot). Results Our search yielded 4537 articles. After inspection of titles and abstracts, a full text of 245 of those articles were included and assessed for further eligibility. A total of 49 articles met our inclusion criteria. A broad spectrum of instruments and technologies are used to assess motor function in dyskinetic cerebral palsy, with the majority using 3D motion capture and surface electromyography. Only for a small number of instruments methodological quality was assessed, with only one study showing an adequate assessment of test-retest reliability. The majority of studies was at ICF-CY function and structure level and assessed control of voluntary movement (29 of 49) mainly in the upper extremity, followed by assessment of involuntary movements (15 of 49), muscle tone/motor reflex (6 of 49), gait pattern (5 of 49) and muscle power (2 of 49). At ICF-CY level of activities and participation hand and arm use (9 of 49), fine hand use (5 of 49), lifting and carrying objects (3 of 49), maintaining a body position (2 of 49), walking (1 of 49) and moving around using equipment (1 of 49) was assessed. Only a few methods are potentially suitable outside the clinical environment (e.g. inertial sensors, accelerometers). Conclusion Although the current review shows the potential of several instrumented methods to be used as objective outcome measures in dyskinetic cerebral palsy, their methodological quality is still unknown. Future development should focus on evaluating clinimetrics, including validating against clinical meaningfulness. New technological developments should aim for measurements that can be applied outside the laboratory.