12,502 research outputs found
Muscle Synergies Facilitate Computational Prediction of Subject-Specific Walking Motions.
Researchers have explored a variety of neurorehabilitation approaches to restore normal walking function following a stroke. However, there is currently no objective means for prescribing and implementing treatments that are likely to maximize recovery of walking function for any particular patient. As a first step toward optimizing neurorehabilitation effectiveness, this study develops and evaluates a patient-specific synergy-controlled neuromusculoskeletal simulation framework that can predict walking motions for an individual post-stroke. The main question we addressed was whether driving a subject-specific neuromusculoskeletal model with muscle synergy controls (5 per leg) facilitates generation of accurate walking predictions compared to a model driven by muscle activation controls (35 per leg) or joint torque controls (5 per leg). To explore this question, we developed a subject-specific neuromusculoskeletal model of a single high-functioning hemiparetic subject using instrumented treadmill walking data collected at the subject's self-selected speed of 0.5 m/s. The model included subject-specific representations of lower-body kinematic structure, foot-ground contact behavior, electromyography-driven muscle force generation, and neural control limitations and remaining capabilities. Using direct collocation optimal control and the subject-specific model, we evaluated the ability of the three control approaches to predict the subject's walking kinematics and kinetics at two speeds (0.5 and 0.8 m/s) for which experimental data were available from the subject. We also evaluated whether synergy controls could predict a physically realistic gait period at one speed (1.1 m/s) for which no experimental data were available. All three control approaches predicted the subject's walking kinematics and kinetics (including ground reaction forces) well for the model calibration speed of 0.5 m/s. However, only activation and synergy controls could predict the subject's walking kinematics and kinetics well for the faster non-calibration speed of 0.8 m/s, with synergy controls predicting the new gait period the most accurately. When used to predict how the subject would walk at 1.1 m/s, synergy controls predicted a gait period close to that estimated from the linear relationship between gait speed and stride length. These findings suggest that our neuromusculoskeletal simulation framework may be able to bridge the gap between patient-specific muscle synergy information and resulting functional capabilities and limitations
Simulation and design of an active orthosis for an incomplete spinal cord injured subject
The dynamic simulation of incomplete spinal cord injured individuals equipped with active orthoses is a challenging problem due to the redundancy of the simultaneous human-orthosis actuation. The objective of this work is two-fold. Firstly, a physiological static optimization approach to solve the muscle-orthosis actuation sharing problem is presented. For this purpose, a biomechanical model based on multibody dynamics techniques is used. The muscles are modeled as Hill-type actuators and the atrophy of denervated muscles is considered by adding stiff and dissipative elements. Secondly, the mechanical design of a new active stance-control knee-ankle-foot orthosis (A-SCKAFO) is addressed. The proposed device consists of a passive joint that constrains ankle plantar flexion, along with a powered knee unit that prevents flexion during stance and controls flexion-extension during swing. The knee actuation is selected based on the results obtained through the optimization approach.Peer ReviewedPostprint (published version
User-centered design of a dynamic-autonomy remote interaction concept for manipulation-capable robots to assist elderly people in the home
In this article, we describe the development of a human-robot interaction concept for service robots to assist elderly people in the home with physical tasks. Our approach is based on the insight that robots are not yet able to handle all tasks autonomously with sufficient reliability in the complex and heterogeneous environments of private homes. We therefore employ remote human operators to assist on tasks a robot cannot handle completely autonomously. Our development methodology was user-centric and iterative, with six user studies carried out at various stages involving a total of 241 participants. The concept is under implementation on the Care-O-bot 3 robotic platform. The main contributions of this article are (1) the results of a survey in form of a ranking of the demands of elderly people and informal caregivers for a range of 25 robot services, (2) the results of an ethnography investigating the suitability of emergency teleassistance and telemedical centers for incorporating robotic teleassistance, and (3) a user-validated human-robot interaction concept with three user roles and corresponding three user interfaces designed as a solution to the problem of engineering reliable service robots for home environments
Multi-level personalization of neuromusculoskeletal models to estimate physiologically plausible knee joint contact forces in children
Neuromusculoskeletal models are a powerful tool to investigate the internal biomechanics of an individual. However, commonly used neuromusculoskeletal models are generated via linear scaling of generic templates derived from elderly adult anatomies and poorly represent a child, let alone children with a neuromuscular disorder whose musculoskeletal structures and muscle activation patterns are profoundly altered. Model personalization can capture abnormalities and appropriately describe the underlying (altered) biomechanics of an individual. In this work, we explored the effect of six different levels of neuromusculoskeletal model personalization on estimates of muscle forces and knee joint contact forces to tease out the importance of model personalization for normal and abnormal musculoskeletal structures and muscle activation patterns. For six children, with and without cerebral palsy, generic scaled models were developed and progressively personalized by (1) tuning and calibrating musculotendon units' parameters, (2) implementing an electromyogram-assisted approach to synthesize muscle activations, and (3) replacing generic anatomies with image-based bony geometries, and physiologically and physically plausible muscle kinematics. Biomechanical simulations of gait were performed in the OpenSim and CEINMS software on ten overground walking trials per participant. A mixed-ANOVA test, with Bonferroni corrections, was conducted to compare all models' estimates. The model with the highest level of personalization produced the most physiologically plausible estimates. Model personalization is crucial to produce physiologically plausible estimates of internal biomechanical quantities. In particular, personalization of musculoskeletal anatomy and muscle activation patterns had the largest effect overall. Increased research efforts are needed to ease the creation of personalized neuromusculoskeletal models
Advances in Human-Robot Interaction
Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers
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AN EMG OPTIMIZATION MODEL OF THE KINETIC DEMANDS ON THE LOWER BACK DURING ASYMMETRICAL GAIT AND LOAD CARRIAGE
Gait asymmetries are associated with a high incidence of lower back pain (LBP). Although there are several causes of gait asymmetry (i.e. amputation, injury, or deformities), lower back kinetic demands have not been quantified and suitably compared due to experimental limitations in these clinical populations. Further, the impact of gait asymmetry on lower back demands during carrying tasks has not been established. This dissertation addressed these issues by artificially and safely inducing gait asymmetry in healthy able-bodied participants during walking and carrying tasks. LBP risk was assessed by L5/S1 vertebral joint force levels estimated with an OpenSim musculoskeletal model of the lower back adapted to incorporate participant-specific responses using an EMG optimization approach. The model was evaluated systematically for force estimate efficacy and sensitivity to input parameters prior to gait asymmetry assessments.
Twelve participants performed walking and carrying tasks on a treadmill at individually scaled speeds while kinematics, external kinetics, and muscle activities (EMG) were recorded. Walking conditions consisted of unperturbed symmetrical gait, and asymmetrical gait induced by perturbing the right leg with a 2.54 cm shoe leveler, ~1 kg ankle weight, combined weight and shoe leveler, or a clinical walking boot that restricted ankle joint motion and added mass. Load carrying was performed while holding 7.5% and 15% bodyweight dumbbells in one or two hands during symmetric gait and asymmetric gait induced by the walking boot.
The perturbations were successful in producing different degrees of gait asymmetry. However, L5/S1 joint forces were not significantly different between conditions despite unique spatiotemporal asymmetries. This indicates that LBP in those with gait asymmetry may not be due solely to level planar walking. During carrying tasks, gait asymmetry induced by the walking boot increased some metrics of lower back loading. Further, carrying a load in the hand contralateral to the walking boot produced larger forces than when carried on the same side. These results emphasize the importance of evaluating specific sources of gait asymmetry during daily activities other than walking when assessing LBP risk and would encourage more inclusive ergonomic carrying guidelines
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