Upper Extremity Muscle Activation Pattern Prediction Through Synergy Extrapolation and Electromyography-Driven Modeling.

Patients with neuromuscular disease fail to produce necessary muscle force and have trouble maintaining joint moment required to perform activities of daily living. Measuring muscle force values in patients with neuromuscular disease is important but challenging. Electromyography (EMG) can be used to obtain muscle activation values, which can be converted to muscle forces and joint torques. Surface electrodes can measure activations of superficial muscles, but fine-wire electrodes are needed for deep muscles, although it is invasive and require skilled personnel and preparation time. EMG-driven modeling with surface electrodes alone could underestimate the net torque. In this research, authors propose a methodology to predict muscle activations from deeper muscles of the upper extremity. This method finds missing muscle activation one at a time by combining an EMG-driven musculoskeletal model and muscle synergies. This method tracks inverse dynamics joint moments to determine synergy vector weights and predict muscle activation of selected shoulder and elbow muscles of a healthy subject. In addition, muscle-tendon parameter values (optimal fiber length, tendon slack length, and maximum isometric force) have been personalized to the experimental subject. The methodology is tested for a wide range of rehabilitation tasks of the upper extremity across multiple healthy subjects. Results show this methodology can determine single unmeasured muscle activation up to Pearson's correlation coefficient (R) of 0.99 (root mean squared error, RMSE = 0.001) and 0.92 (RMSE = 0.13) for the elbow and shoulder muscles, respectively, for one degree-of-freedom (DoF) tasks. For more complicated five DoF tasks, activation prediction accuracy can reach up to R = 0.71 (RMSE = 0.29).

Systematic Evaluation of a Knee Exoskeleton Misalignment Compensation Mechanism Using a Robotic Dummy Leg.

The objective and quantitative assessment of physical human-exoskeletons interaction (pHEI) represents a pressing necessity in the wearable robots field. This process remains of difficult execution, especially for early stage devices, in which the inclusion of human testing could pose ethical and safety concerns. This manuscript proposes a methodology for pHEI assessment based on an active dummy leg named Leg Replica, which is able to sense interaction forces while wearing an exoskeleton. We tested this methodology on a wearable active knee exoskeleton prototype, with the goal to evaluate the effects of a misalignment compensation mechanism. Through this methodology, it was possible to show how the misalignment compensation mechanism was able to reduce the interaction forces during passive exoskeleton motion. Such reduction was less evident when the exoskeleton was active. The tests allowed to identify specific points of improvements for the exoskeleton, enabling a more specific upgrade of the device based on these experimental results. This study demonstrates the ability of the proposed methodology to objectively benchmark different aspects of pHEI, and to accelerate the iterative development of new devices prior to human testing.

Inertial sensors for gait monitoring and design of adaptive controllers for exoskeletons after stroke: a feasibility study.

Introduction: Tuning the control parameters is one of the main challenges in robotic gait therapy. Control strategies that vary the control parameters based on the user's performance are still scarce and do not exploit the potential of using spatiotemporal metrics. The goal of this study was to validate the feasibility of using shank-worn Inertial Measurement Units (IMUs) for clinical gait analysis after stroke and evaluate their preliminary applicability in designing an automatic and adaptive controller for a knee exoskeleton (ABLE-KS). Methods: First, we estimated the temporal (i.e., stride time, stance, and swing duration) and spatial (i.e., stride length, maximum vertical displacement, foot clearance, and circumduction) metrics in six post-stroke participants while walking on a treadmill and overground and compared these estimates with data from an optical motion tracking system. Next, we analyzed the relationships between the IMU-estimated metrics and an exoskeleton control parameter related to the peak knee flexion torque. Finally, we trained two machine learning algorithms, i.e., linear regression and neural network, to model the relationship between the exoskeleton torque and maximum vertical displacement, which was the metric that showed the strongest correlations with the data from the optical system [r = 0.84; ICC(A,1) = 0.73; ICC(C,1) = 0.81] and peak knee flexion torque (r = 0.957). Results: Offline validation of both neural network and linear regression models showed good predictions (R2 = 0.70-0.80; MAE = 0.48-0.58 Nm) of the peak torque based on the maximum vertical displacement metric for the participants with better gait function, i.e., gait speed > 0.7 m/s. For the participants with worse gait function, both models failed to provide good predictions (R2 = 0.00-0.19; MAE = 1.15-1.29 Nm) of the peak torque despite having a moderate-to-strong correlation between the spatiotemporal metric and control parameter. Discussion: Our preliminary results indicate that the stride-by-stride estimations of shank-worn IMUs show potential to design automatic and adaptive exoskeleton control strategies for people with moderate impairments in gait function due to stroke.

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.

Novel computational protocol to support transfemoral prosthetic alignment procedure using machine learning techniques.

BACKGROUND: The prosthetic alignment procedure considers biomechanical, anatomical and comfort characteristics of the amputee to achieve an acceptable gait. Prosthetic malalignment induces long-term disease. The assessment of alignment is highly variable and subjective to the experience of the prosthetist, so the use of machine learning could assist the prosthetist during the judgment of optimal alignment. RESEARCH OBJECTIVE: To assist the prosthetist during the assessment of prosthetic alignment using a new computational protocol based on machine learning. METHODS: Sixteen transfemoral amputees were recruited for training and validation of the alignment protocol. Four misalignments and one nominal alignment were performed. Eleven prosthetic limb ground reaction force parameters were recorded. A support vector machine with a Gaussian kernel radial basis function and a Bayesian regularization neural network were trained to predict the alignment condition, as well as the magnitude and angle of required to align the prosthesis correctly. The alignment protocol was validated by one junior and one senior prosthetist during the prosthetic alignment of two transfemoral amputees. RESULTS: The support vector machine-based model detected the nominal alignment 92.6 % of the time. The neural network recovered 94.11 % of the angles needed to correct the prosthetic misalignment with a fitting error of 0.51°. During the validation of the alignment protocol, the computational models and the prosthetists agreed on the alignment assessment. The gait quality evaluated by the prosthetists reached a satisfaction level of 8/10 for the first amputee and 9.6/10 for the second amputee. IMPORTANCE: The new computational prosthetic alignment protocol is a tool that helps the prosthetist during the prosthetic alignment procedure thereby decreasing the likelihood of gait deviations and musculoskeletal diseases associated with misalignments and consequently improving the amputees-prosthesis adherence.

Control strategies used in lower limb exoskeletons for gait rehabilitation after brain injury: a systematic review and analysis of clinical effectiveness.

BACKGROUND: In the past decade, there has been substantial progress in the development of robotic controllers that specify how lower-limb exoskeletons should interact with brain-injured patients. However, it is still an open question which exoskeleton control strategies can more effectively stimulate motor function recovery. In this review, we aim to complement previous literature surveys on the topic of exoskeleton control for gait rehabilitation by: (1) providing an updated structured framework of current control strategies, (2) analyzing the methodology of clinical validations used in the robotic interventions, and (3) reporting the potential relation between control strategies and clinical outcomes. METHODS: Four databases were searched using database-specific search terms from January 2000 to September 2020. We identified 1648 articles, of which 159 were included and evaluated in full-text. We included studies that clinically evaluated the effectiveness of the exoskeleton on impaired participants, and which clearly explained or referenced the implemented control strategy. RESULTS: (1) We found that assistive control (100% of exoskeletons) that followed rule-based algorithms (72%) based on ground reaction force thresholds (63%) in conjunction with trajectory-tracking control (97%) were the most implemented control strategies. Only 14% of the exoskeletons implemented adaptive control strategies. (2) Regarding the clinical validations used in the robotic interventions, we found high variability on the experimental protocols and outcome metrics selected. (3) With high grade of evidence and a moderate number of participants (N = 19), assistive control strategies that implemented a combination of trajectory-tracking and compliant control showed the highest clinical effectiveness for acute stroke. However, they also required the longest training time. With high grade of evidence and low number of participants (N = 8), assistive control strategies that followed a threshold-based algorithm with EMG as gait detection metric and control signal provided the highest improvements with the lowest training intensities for subacute stroke. Finally, with high grade of evidence and a moderate number of participants (N = 19), assistive control strategies that implemented adaptive oscillator algorithms together with trajectory-tracking control resulted in the highest improvements with reduced training intensities for individuals with chronic stroke. CONCLUSIONS: Despite the efforts to develop novel and more effective controllers for exoskeleton-based gait neurorehabilitation, the current level of evidence on the effectiveness of the different control strategies on clinical outcomes is still low. There is a clear lack of standardization in the experimental protocols leading to high levels of heterogeneity. Standardized comparisons among control strategies analyzing the relation between control parameters and biomechanical metrics will fill this gap to better guide future technical developments. It is still an open question whether controllers that provide an on-line adaptation of the control parameters based on key biomechanical descriptors associated to the patients' specific pathology outperform current control strategies.

Relationship between spatiotemporal parameters and clinical outcomes in children with bilateral spastic cerebral palsy: Clinical interpretation proposal.

BACKGROUND: Understanding the links between gait disorders, impairments, and activity limitations is essential for correctly interpreting the instrumented gait analysis. We aimed to evaluate the relationships between spatiotemporal parameters and clinical outcomes in children with bilateral spastic cerebral palsy, and find out whether spatiotemporal parameters provide clinical information regarding gait pattern and walking. METHODS: Data from 19 children with bilateral spastic cerebral palsy (nine males, ten females, 9.6 ± 2.8 years old) were collected retrospectively. All children underwent an instrumented gait analysis and a standardized clinical assessment. Seven spatiotemporal parameters were calculated: non-dimensional cadence, stride length, step width, gait speed, first double support, single support, and time of toe off. Clinical outcomes included measures of two different components of the International Classification of Functioning, Disability and Health - Children and Youth version: body functions and structures (spasticity, contractures and range of motion, and deformities), and activities and participation (gross motor function, and walking capacity). Pearson correlation, ANOVA, Student's t, Mann-Whitney U, and Kruskal-Wallis tests were used to analyze relationships. Spatiotemporal parameters related to clinical outcomes of body functions and structures were interpreted as outcome measures of gait pattern, while those related to clinical outcomes of activities and participation were interpreted as outcome measures of walking. RESULTS: Non-dimensional cadence, stride length, and gait speed showed relationships (p < 0.05) with hip flexors spasticity and hindfoot deformity, ankle plantar flexors spasticity, and hindfoot deformity, respectively. All spatiotemporal parameters except non-dimensional cadence showed correlation (p < 0.05) with gross motor function and walking capacity. CONCLUSIONS: Spatiotemporal parameters provide clinical information regarding both gait pattern and walking.

Comparing walking with knee-ankle-foot orthoses and a knee-powered exoskeleton after spinal cord injury: a randomized, crossover clinical trial.

Recovering the ability to stand and walk independently can have numerous health benefits for people with spinal cord injury (SCI). Wearable exoskeletons are being considered as a promising alternative to conventional knee-ankle-foot orthoses (KAFOs) for gait training and assisting functional mobility. However, comparisons between these two types of devices in terms of gait biomechanics and energetics have been limited. Through a randomized, crossover clinical trial, this study compared the use of a knee-powered lower limb exoskeleton (the ABLE Exoskeleton) against passive orthoses, which are the current standard of care for verticalization and gait ambulation outside the clinical setting in people with SCI. Ten patients with SCI completed a 10-session gait training program with each device followed by user satisfaction questionnaires. Walking with the ABLE Exoskeleton improved gait kinematics compared to the KAFOs, providing a more physiological gait pattern with less compensatory movements (38% reduction of circumduction, 25% increase of step length, 29% improvement in weight shifting). However, participants did not exhibit significantly better results in walking performance for the standard clinical tests (Timed Up and Go, 10-m Walk Test, and 6-min Walk Test), nor significant reductions in energy consumption. These results suggest that providing powered assistance only on the knee joints is not enough to significantly reduce the energy consumption required by people with SCI to walk compared to passive orthoses. Active assistance on the hip or ankle joints seems necessary to achieve this outcome.

Computational evaluation of psoas muscle influence on walking function following internal hemipelvectomy with reconstruction.

An emerging option for internal hemipelvectomy surgery is custom prosthesis reconstruction. This option typically recapitulates the resected pelvic bony anatomy with the goal of maximizing post-surgery walking function while minimizing recovery time. However, the current custom prosthesis design process does not account for the patient's post-surgery prosthesis and bone loading patterns, nor can it predict how different surgical or rehabilitation decisions (e.g., retention or removal of the psoas muscle, strengthening the psoas) will affect prosthesis durability and post-surgery walking function. These factors may contribute to the high observed failure rate for custom pelvic prostheses, discouraging orthopedic oncologists from pursuing this valuable treatment option. One possibility for addressing this problem is to simulate the complex interaction between surgical and rehabilitation decisions, post-surgery walking function, and custom pelvic prosthesis design using patient-specific neuromusculoskeletal models. As a first step toward developing this capability, this study used a personalized neuromusculoskeletal model and direct collocation optimal control to predict the impact of ipsilateral psoas muscle strength on walking function following internal hemipelvectomy with custom prosthesis reconstruction. The influence of the psoas muscle was targeted since retention of this important muscle can be surgically demanding for certain tumors, requiring additional time in the operating room. The post-surgery walking predictions emulated the most common surgical scenario encountered at MD Anderson Cancer Center in Houston. Simulated post-surgery psoas strengths included 0% (removed), 50% (weakened), 100% (maintained), and 150% (strengthened) of the pre-surgery value. However, only the 100% and 150% cases successfully converged to a complete gait cycle. When post-surgery psoas strength was maintained, clinical gait features were predicted, including increased stance width, decreased stride length, and increased lumbar bending towards the operated side. Furthermore, when post-surgery psoas strength was increased, stance width and stride length returned to pre-surgery values. These results suggest that retention and strengthening of the psoas muscle on the operated side may be important for maximizing post-surgery walking function. If future studies can validate this computational approach using post-surgery experimental walking data, the approach may eventually influence surgical, rehabilitation, and custom prosthesis design decisions to meet the unique clinical needs of pelvic sarcoma patients.

The effect of prosthetic alignment on the stump temperature and ground reaction forces during gait in transfemoral amputees.

BACKGROUND: Lower limb prosthetic alignment is a procedure mostly subjective. A prosthetic misaligned induces gait deviations and long-term joint diseases. The alignment effects for each lower limb and the stump stays uncertain. RESEARCH OBJECTIVE: To identify the effect of the transfemoral alignment prosthesis on ground reaction forces and thermal images of the residual limb. METHODS: The effect of misalignment and nominal alignment was evaluated in sixteen transfemoral amputees. The nominal alignment was considered as the optimal alignment for each subject. Misalignment included random variations in the anterior-posterior and medial-lateral translation of the prosthetic foot and the angle of flexion-extension, abduction-adduction, and internal-external rotation of the socket and prosthetic foot. The control group consisted of fifteen non-amputee individuals. The ground reaction force parameters and stump temperature were analyzed for each alignment condition. The statistical analysis included the one-way ANOVA, Kruskal-Wallis, and multiple comparison tests. RESULTS: The prosthesis did not produce statistically significant changes in the average temperature of residual limbs. However, the temperature distribution on the stump skin was different (P < 0.05). The transfemoral prosthesis misalignment produced an irregular heat diffusion on the anterior, posterior, and lateral sides of the stump contour compared to the nominal alignment (P < 0.05). The sound limb did not show differences between nominal alignments and misalignments for most ground reaction force parameters. For almost all GRF parameters, significant differences were observed for the prosthetic limb between misalignment and nominal alignment (P < 0.001). The symmetry indices of ground reaction force parameters of transfemoral amputees did not show any kind of significant improvements after aligning the prosthesis nominally. SIGNIFICANCE: The stump's temperature distribution and the ground reaction force findings for the prosthetic limb provide a better understanding of the alignment procedure of the transfemoral prosthesis and improve the amputees' compliance to the prosthesis.

Gait event detection using kinematic data in children with bilateral spastic cerebral palsy.

BACKGROUND: Ground reaction forces are the gold standard for detecting gait events, but they are not always applicable in cerebral palsy. Ghoussayni's algorithm is an event detection method based on the sagittal plane velocity of heel and toe markers. We aimed to evaluate whether Ghoussayni's algorithm, using two different thresholds, was a valid event detection method in children with bilateral spastic cerebral palsy. We also aimed to define a new adaptation of Ghoussayni's algorithm for detecting foot strike in cerebral palsy, and study the effect of event detection methods on spatiotemporal parameters. METHODS: Synchronized kinematic and kinetic data were collected retrospectively from 16 children with bilateral spastic cerebral palsy (7 males and 9 females; age 8.9 ± 2.7 years) walking barefoot at self-selected speed. Gait events were detected using methods: 1) ground reaction forces, 2) Ghoussayni's algorithm with a threshold of 0.5 m/s, and 3) Ghoussayni's algorithm with a walking speed dependent threshold. The new adaptation distinguished how foot strikes were performed (heel and/or toe) comparing the timing when the foot markers velocities fell below the threshold. Differences between the three methods, and between spatiotemporal parameters calculated from the two Ghoussayni's thresholds were analyzed. FINDINGS: There were statistically significant (P < 0.05) differences between methods 1 and 3, and between some spatiotemporal parameters calculated from methods 2 and 3. Ghoussayni's algorithm showed better performance for foot strike than for toe off. INTERPRETATION: Ghoussayni's algorithm using 0.5 m/s is valid in children with bilateral spastic cerebral palsy. Event detection methods affect spatiotemporal parameters.

Systematic review on wearable lower-limb exoskeletons for gait training in neuromuscular impairments.

Gait disorders can reduce the quality of life for people with neuromuscular impairments. Therefore, walking recovery is one of the main priorities for counteracting sedentary lifestyle, reducing secondary health conditions and restoring legged mobility. At present, wearable powered lower-limb exoskeletons are emerging as a revolutionary technology for robotic gait rehabilitation. This systematic review provides a comprehensive overview on wearable lower-limb exoskeletons for people with neuromuscular impairments, addressing the following three questions: (1) what is the current technological status of wearable lower-limb exoskeletons for gait rehabilitation?, (2) what is the methodology used in the clinical validations of wearable lower-limb exoskeletons?, and (3) what are the benefits and current evidence on clinical efficacy of wearable lower-limb exoskeletons? We analyzed 87 clinical studies focusing on both device technology (e.g., actuators, sensors, structure) and clinical aspects (e.g., training protocol, outcome measures, patient impairments), and make available the database with all the compiled information. The results of the literature survey reveal that wearable exoskeletons have potential for a number of applications including early rehabilitation, promoting physical exercise, and carrying out daily living activities both at home and the community. Likewise, wearable exoskeletons may improve mobility and independence in non-ambulatory people, and may reduce secondary health conditions related to sedentariness, with all the advantages that this entails. However, the use of this technology is still limited by heavy and bulky devices, which require supervision and the use of walking aids. In addition, evidence supporting their benefits is still limited to short-intervention trials with few participants and diversity among their clinical protocols. Wearable lower-limb exoskeletons for gait rehabilitation are still in their early stages of development and randomized control trials are needed to demonstrate their clinical efficacy.

Evaluation of Optimal Control Approaches for Predicting Active Knee-Ankle-Foot-Orthosis Motion for Individuals With Spinal Cord Injury.

Gait restoration of individuals with spinal cord injury can be partially achieved using active orthoses or exoskeletons. To improve the walking ability of each patient as much as possible, it is important to personalize the parameters that define the device actuation. This study investigates whether using an optimal control-based predictive simulation approach to personalize pre-defined knee trajectory parameters for an active knee-ankle-foot orthosis (KAFO) used by spinal cord injured (SCI) subjects could potentially be an alternative to the current trial-and-error approach. We aimed to find the knee angle trajectory that produced an improved orthosis-assisted gait pattern compared to the one with passive support (locked knee). We collected experimental data from a healthy subject assisted by crutches and KAFOs (with locked knee and with knee flexion assistance) and from an SCI subject assisted by crutches and KAFOs (with locked knee). First, we compared different cost functions and chose the one that produced results closest to experimental locked knee walking for the healthy subject (angular coordinates mean RMSE was 5.74°). For this subject, we predicted crutch-orthosis-assisted walking imposing a pre-defined knee angle trajectory for different maximum knee flexion parameter values, and results were evaluated against experimental data using that same pre-defined knee flexion trajectories in the real device. Finally, using the selected cost function, gait cycles for different knee flexion assistance were predicted for an SCI subject. We evaluated changes in four clinically relevant parameters: foot clearance, stride length, cadence, and hip flexion ROM. Simulations for different values of maximum knee flexion showed variations of these parameters that were consistent with experimental data for the healthy subject (e.g., foot clearance increased/decreased similarly in experimental and predicted motions) and were reasonable for the SCI subject (e.g., maximum parameter values were found for moderate knee flexion). Although more research is needed before this method can be applied to choose optimal active orthosis controller parameters for specific subjects, these findings suggest that optimal control prediction of crutch-orthosis-assisted walking using biomechanical models might be used in place of the trial-and-error method to select the best maximum knee flexion angle during gait for a specific SCI subject.

Adaptation Strategies for Personalized Gait Neuroprosthetics.

Personalization of gait neuroprosthetics is paramount to ensure their efficacy for users, who experience severe limitations in mobility without an assistive device. Our goal is to develop assistive devices that collaborate with and are tailored to their users, while allowing them to use as much of their existing capabilities as possible. Currently, personalization of devices is challenging, and technological advances are required to achieve this goal. Therefore, this paper presents an overview of challenges and research directions regarding an interface with the peripheral nervous system, an interface with the central nervous system, and the requirements of interface computing architectures. The interface should be modular and adaptable, such that it can provide assistance where it is needed. Novel data processing technology should be developed to allow for real-time processing while accounting for signal variations in the human. Personalized biomechanical models and simulation techniques should be developed to predict assisted walking motions and interactions between the user and the device. Furthermore, the advantages of interfacing with both the brain and the spinal cord or the periphery should be further explored. Technological advances of interface computing architecture should focus on learning on the chip to achieve further personalization. Furthermore, energy consumption should be low to allow for longer use of the neuroprosthesis. In-memory processing combined with resistive random access memory is a promising technology for both. This paper discusses the aforementioned aspects to highlight new directions for future research in gait neuroprosthetics.

Evaluation of an exercise-enabling control interface for powered wheelchair users: a feasibility study with Duchenne muscular dystrophy.

BACKGROUND: Powered wheelchairs are an essential technology to support mobility, yet their use is associated with a high level of sedentarism that can have negative health effects for their users. People with Duchenne muscular dystrophy (DMD) start using a powered wheelchair in their early teens due to the loss of strength in their legs and arms. There is evidence that low-intensity exercise can help preserve the functional abilities of people with DMD, but options for exercise when sitting in a powered wheelchair are limited. METHODS: In this paper, we present the design and the feasibility study of a new version of the MOVit device that allows powered-wheelchair users to exercise while driving the chair. Instead of using a joystick to drive the wheelchair, users move their arms through a cyclical motion using two powered, mobile arm supports that provide controller inputs to the chair. The feasibility study was carried out with a group of five individuals with DMD and five unimpaired individuals. Participants performed a series of driving tasks in a wheelchair simulator and on a real driving course with a standard joystick and with the MOVit 2.0 device. RESULTS: We found that driving speed and accuracy were significantly lowered for both groups when driving with MOVit compared to the joystick, but the decreases were small (speed was 0.26 m/s less and maximum path error was 0.1 m greater). Driving with MOVit produced a significant increase in heart rate (7.5 bpm) compared to the joystick condition. Individuals with DMD reported a high level of satisfaction with their performance and comfort in using MOVit. CONCLUSIONS: These results show for the first time that individuals with DMD can easily transition to driving a powered wheelchair using cyclical arm motions, achieving a reasonable driving performance with a short period of training. Driving in this way elicits cardiopulmonary exercise at an intensity found previously to produce health-related benefits in DMD.

Assessment of residual reduction procedures for high-speed tasks.

BACKGROUND: Experimental and modeling errors can lead to dynamically inconsistent results when performing inverse dynamic analyses of human movement. Adding low-value residual pelvis actuators could deal with such a problem. However, in certain tasks, these residuals may remain quite large, and strategies based on motion or force variation must be applied. RESEARCH QUESTION: Can the dynamic inconsistency be handled by an optimal control algorithm that changes the measured kinematics in the preparatory phase of the single leg triple hop test, a relatively high-speed and torque-demanding task, so that residuals are kept within a low range? METHODS: The proposed optimal control algorithm was developed as a tracking problem, in which the implicit form of dynamics was used. Equations of motion were introduced as path constraints, as well as residual forces and moments acting on the pelvis. To do so, GPOPS-II and IPOPT were employed to solve the optimization problem. Furthermore, OpenSim API was called at each iteration to solve the equations of motion through an inverse dynamic analysis. RESULTS: Results presented a high reduction in all six components of residual actuators during the entire task. Moreover, resulting motion after the optimization showed a very similar evolution than the reference motion before the ascending phase of the task. Once the ascending phase started, some coordinates presented a more significant discrepancy compared to the reference, such as the pelvis tilt and lumbar extension. SIGNIFICANCE: The findings suggest that the proposed algorithm can deal with dynamic inconsistency in high-speed tasks, obtaining low residual forces and moments while keeping similar kinematics. Hence, it could complement other optimal control algorithms that simulate new motions, relying on dynamically consistent data.

Muscular tension significantly affects stability in standing posture.

BACKGROUND: Muscular co-contraction is a strategy commonly used by elders with the aim to increase stability. However, co-contraction leads to stiffness which in turns reduces stability. Some literature seems to suggest an opposite approach and to point out relaxation as a way to improve stability. Teaching relaxation is therefore becoming the aim of many studies letting unclear whether tension or relaxation are the most effective muscular strategy to improve stability. Relaxation is a misleading concept in our society. It is often confused with rest, while it should be addressed during stressing tasks, where it should aim to reduce energetic costs and increase stability. The inability to relax can be related to sub-optimal neuro-motor control, which can lead to increased stresses. RESEARCH QUESTION: The objective of the study is to investigate the effect of voluntary muscle contraction and relaxation over the stability of human standing posture, answering two specific research questions: (1) Does the muscular tension have an impact on stability of standing posture? (2) Could this impact be estimated by using a minimally invasive procedure? METHODS: By using a force plate, we analysed the displacement of the center of pressure of 30 volunteers during state of tension and relaxation in comparison with a control state, and with open and closed eyes. RESULTS: We found that tension significantly reduced the stability of subjects (15 out of 16 parameters, p < 0.003). SIGNIFICANCE: Our results show that daily situations of stress can lead to decreased stability. Such a loss might actually increase the risk of chronic joint overload or fall. Finally, breathing has direct effect over the management of pain and stress, and the results reported here point out the need to explicitly explore the troubling fact that a large portion of population might not be able to properly breath.

Gait parameters in children with bilateral spastic cerebral palsy: a systematic review of randomized controlled trials.

AIM: To identify the gait parameters used to assess gait disorders in children with bilateral spastic cerebral palsy (CP) and evaluate their responsiveness to treatments. METHOD: A systematic search within PubMed, Web of Science, and Scopus (in English, 2000-2016) for randomized controlled trials of children with bilateral spastic CP who were assessed by instrumented gait analysis (IGA) was performed. Data related to participants and study characteristics, risk of bias, and outcome measures were collected. A list of gait parameters responsive to clinical interventions was obtained. RESULTS: Twenty-one articles met the inclusion criteria. Eighty-nine gait parameters were identified, 56 of which showed responsiveness to treatments. Spatiotemporal and kinematic parameters were widely used compared to kinetic and surface electromyography data. The majority of responsive gait parameters were joint angles at the sagittal plane (flexion-extension). INTERPRETATION: The IGA yields responsive outcome measures for the gait assessment of children with bilateral spastic CP. Spatiotemporal and kinematic (at sagittal plane) parameters are the gait parameters used most frequently. Further research is needed to establish the relevant gait parameters for each clinical problem. WHAT THIS PAPER ADDS: Fifty-six responsive gait parameters for children with bilateral spastic cerebral palsy were identified. Most responsive gait parameters belong to joint angles time-series at sagittal plane. Spatiotemporal and kinematic parameters are widely used compared to kinetic and surface electromyography parameters.

PARÁMETROS DE LA MARCHA EN NIÑOS CON PARÁLISIS CEREBRAL ESPÁSTICA BILATERAL: UNA REVISIÓN SISTEMÁTICA DE ENSAYOS CONTROLADOS ALEATORIOS: OBJETIVO: Identificar los parámetros de la marcha utilizados para evaluar los trastornos de la marcha en niños con parálisis cerebral espástica (PC) bilateral y evaluar su capacidad de respuesta a los tratamientos. MÉTODO: Se realizó una búsqueda sistemática en PubMed, Web of Science y Scopus (en inglés, 2000-2016) de ensayos controlados aleatorios de niños con PC espástica bilateral que fueron evaluados mediante análisis de marcha instrumentado (AMI). Se recopilaron datos relacionados con los participantes y las características del estudio, el riesgo de sesgo y las medidas de resultado. Se obtuvo una lista de parámetros de marcha que respondieron a las intervenciones clínicas. RESULTADOS: Veintiún artículos cumplieron con los criterios de inclusión. Se identificaron 89 parámetros de la marcha, 56 de los cuales mostraron capacidad de respuesta a los tratamientos. Los parámetros espaciotemporales y cinemáticos fueron utilizados ampliamente en comparación con los datos de electromiografía de superficie y cinética. La mayoría de los parámetros de marcha que respondieron fueron ángulos articulares en el plano sagital (flexión-extensión). INTERPRETACIÓN: El AMI produce medidas de resultados que responden a la evaluación de la marcha de los niños con PC espástica bilateral. Los parámetros espaciotemporales y cinemáticos son los parámetros de la marcha utilizados con más frecuencia. Se necesita más investigación para establecer los parámetros de marcha relevantes para cada problema clínico.

PARÂMETROS DE MARCHA EM CRIANÇAS COM PARALISIA CEREBRAL BILATERAL ESPÁSTIA: UMA REVISÃO SISTEMÁTICA DE ESTUDOS RANDOMIZADOS CONTROLADOS: OBJETIVO: Identificar os parâmetros de marcha usados para avaliar desordens da marcha em crianças com paralisia cerebral espástica (PC) e avaliar sua responsividade a tratamentos. MÉTODO: Uma busca sistemática na PubMed, Web of Science, e Scopus (Inglês, 2000-2016) por estudos randomizados controlados de crianças com PC bilateral que foram avaliadas com análise de marcha instrumental (AMI) foi realizada. Os dados relacionados a participantes e características dos estudos, risco de vies, e medidas de resultado foram coletadas. Uma lista de parâmetros responsivos a intervenções clínicas foi obtida. RESULTADOS: Vinte e um artigos atenderam aos critérios de inclusão. Oitenta e nove parâmetros de marcha foram identificados, 56 dos quais mostraram responsividade a tratamentos. Parâmetros espaço-temporais e cinemáticos foram amplamente usados em comparação com dados cinéticos e de eletromiografia de superfície. A maioria dos parâmetros responsivos foram ângulos articulares no plano sagittal (flexo-extensão). INTERPRETAÇÃO: A AMI fornece medidas de resultados responsivas para avaliação da marcha em crianças com PC bilateral espástica. Parâmetros espaço-temporais e cinemáticos são os mais frequentemente usados. Mais pesquisas são necessárias para estabelecer os parâmetros relevantes para cada problema clínico.

Neuromusculoskeletal Model Calibration Significantly Affects Predicted Knee Contact Forces for Walking.

Though walking impairments are prevalent in society, clinical treatments are often ineffective at restoring lost function. For this reason, researchers have begun to explore the use of patient-specific computational walking models to develop more effective treatments. However, the accuracy with which models can predict internal body forces in muscles and across joints depends on how well relevant model parameter values can be calibrated for the patient. This study investigated how knowledge of internal knee contact forces affects calibration of neuromusculoskeletal model parameter values and subsequent prediction of internal knee contact and leg muscle forces during walking. Model calibration was performed using a novel two-level optimization procedure applied to six normal walking trials from the Fourth Grand Challenge Competition to Predict In Vivo Knee Loads. The outer-level optimization adjusted time-invariant model parameter values to minimize passive muscle forces, reserve actuator moments, and model parameter value changes with (Approach A) and without (Approach B) tracking of experimental knee contact forces. Using the current guess for model parameter values but no knee contact force information, the inner-level optimization predicted time-varying muscle activations that were close to experimental muscle synergy patterns and consistent with the experimental inverse dynamic loads (both approaches). For all the six gait trials, Approach A predicted knee contact forces with high accuracy for both compartments (average correlation coefficient r = 0.99 and root mean square error (RMSE) = 52.6 N medial; average r = 0.95 and RMSE = 56.6 N lateral). In contrast, Approach B overpredicted contact force magnitude for both compartments (average RMSE = 323 N medial and 348 N lateral) and poorly matched contact force shape for the lateral compartment (average r = 0.90 medial and -0.10 lateral). Approach B had statistically higher lateral muscle forces and lateral optimal muscle fiber lengths but lower medial, central, and lateral normalized muscle fiber lengths compared to Approach A. These findings suggest that poorly calibrated model parameter values may be a major factor limiting the ability of neuromusculoskeletal models to predict knee contact and leg muscle forces accurately for walking.