Stretch hyperreflexia in children with cerebral palsy:Assessment - Contextualization - Modulation

Cerebral palsy (CP) is a neurological disorder and the most frequent cause of motor impairment in children in Europe. Around 85% of children with CP experience stretch hyperreflexia, also known as “spasticity”. Stretch hyperreflexia is an excessive response to muscle stretch, leading to increased joint resistance. The joint hyper-resistance causes limitations in activities such as walking. Multiple methods have been developed to measure stretch hyperreflexia, but evidence supporting the use of these methods for diagnostics and treatment evaluation in children with CP is insufficient. Furthermore, most methods are designed to assess stretch reflexes in passive conditions, which might not translate to the limitations encountered due to stretch reflexes during activities. Furthermore, while a broad range of stretch hyperreflexia treatments is available, many are invasive, non-specific, or temporary and might have adverse side effects. Training methods to reduce stretch reflexes using biofeedback are promising non-invasive methods with potential long-term sustained effects. Still, clinical feasibility needs to be improved before implementation in clinical rehabilitation of children with CP. This thesis aimed to develop methods to assess stretch hyperreflexia of the calf muscles during passive conditions, as well as in the context of walking. Additionally, this thesis aimed to develop clinically feasible methods to modulate stretch hyperreflexia in the calf muscle of children with CP. The outcomes are described in eight different studies presented in this thesis. All in all, the work presented in this thesis shows that sagittal plane clinical gait analysis can be performed using the human body model and can be complemented with ultrasound imaging of the calf muscle. Motorized methods to assess stretch hyperreflexia in passive conditions might be useful for evaluation in adults after SCI/Stroke. Still, limitations regarding feasibility and validity limit clinical application for children with CP. Furthermore, this thesis provides additional evidence that the deviating muscle activation patterns during walking, particularly the increased activation around initial contact, are caused by stretch hyper-reflexes in children with CP. The deviating muscle activation patterns, with increased activation during early stance and reduced activation around push-off, can be modulated within one session by several children with CP. Therefore, the next step is to develop a training program to modulate the activation pattern and potentially decrease stretch hyper-reflexes in children with CP to improve the gait patter

ESTIMATION OF MULTI-DIRECTIONAL ANKLE IMPEDANCE AS A FUNCTION OF LOWER EXTREMITY MUSCLE ACTIVATION

The purpose of this research is to investigate the relationship between the mechanical impedance of the human ankle and the corresponding lower extremity muscle activity. Three experimental studies were performed to measure the ankle impedance about multiple degrees of freedom (DOF), while the ankle was subjected to different loading conditions and different levels of muscle activity. The first study determined the non-loaded ankle impedance in the sagittal, frontal, and transverse anatomical planes while the ankle was suspended above the ground. The subjects actively co-contracted their agonist and antagonistic muscles to various levels, measured using electromyography (EMG). An Artificial Neural Network (ANN) was implemented to characterize the relationship between the EMG and non-loaded ankle impedance in 3-DOF. The next two studies determined the ankle impedance and muscle activity during standing, while the foot and ankle were subjected to ground perturbations in the sagittal and frontal planes. These studies investigate the performance of subject-dependent models, aggregated models, and the feasibility of a generic, subject-independent model to predict ankle impedance based on the muscle activity of any person. Several regression models, including Least Square, Support Vector Machine, Gaussian Process Regression, and ANN, and EMG feature extraction techniques were explored. The resulting subject-dependent and aggregated models were able to predict ankle impedance with reasonable accuracy. Furthermore, preliminary efforts toward a subject-independent model showed promising results for the design of an EMG-impedance model that can predict ankle impedance using new subjects. This work contributes to understanding the relationship between the lower extremity muscles and the mechanical impedance of the ankle in multiple DOF. Applications of this work could be used to improve user intent recognition for the control of active ankle-foot prostheses

Down-Conditioning of Soleus Reflex Activity using Mechanical Stimuli and EMG Biofeedback

Spasticity is a common syndrome caused by various brain and neural injuries, which can severely impair walking ability and functional independence. To improve functional independence, conditioning protocols are available aimed at reducing spasticity by facilitating spinal neuroplasticity. This down-conditioning can be performed using different types of stimuli, electrical or mechanical, and reflex activity measures, EMG or impedance, used as biofeedback variable. Still, current results on effectiveness of these conditioning protocols are incomplete, making comparisons difficult. We aimed to show the within-session task- dependent and across-session long-term adaptation of a conditioning protocol based on mechanical stimuli and EMG biofeedback. However, in contrast to literature, preliminary results show that subjects were unable to successfully obtain task-dependent modulation of their soleus short-latency stretch reflex magnitude

Strategies for control of neuroprostheses through Brain-Machine Interfaces

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005.Includes bibliographical references (p. 145-153).The concept of brain controlled machines sparks our imagination with many exciting possibilities. One potential application is in neuroprostheses for paralyzed patients or amputees. The quality of life of those who have extremely limited motor abilities can potentially be improved if we have a means of inferring their motor intent from neural signals and commanding a robotic device that can be controlled to perform as a smart prosthesis. In our recent demonstration of such Brain Machine Interfaces (BMIs) monkeys were able to control a robot arm in 3-D motion directly, due to advances in accessing, recording, and decoding electrical activity of populations of single neurons in the brain, together with algorithms for driving robotic devices with the decoded neural signals in real time. However, such demonstrations of BMI thus far have been limited to simple position control of graphical cursors or robots in free space with non-human primates. There still remain many challenges in reducing this technology to practice in a neuroprosthesis for humans. The research in this thesis introduces strategies for optimizing the information extracted from the recorded neural signals, so that a practically viable and ultimately useful neuroprosthesis can be achieved. A framework for incorporating robot sensors and reflex like behavior has been introduced in the form of Continuous Shared Control. The strategy provides means for more steady and natural movement by compensating for the natural reflexes that are absent in direct brain control. The Muscle Activation Method, an alternative decoding algorithm for extracting motor parameters from the neural activity, has been presented.(cont.) The method allows the prosthesis to be controlled under impedance control, which is similar to how our natural limbs are controlled. Using this method, the prosthesis can perform a much wider range in of tasks in partially known and unknown environments. Finally preparations have been made for clinical trials with humans, which would signify a major step in reaching the ultimate goal of human brain operated machines.by Hyun K. Kim.Ph.D

Towards the development of a dynamic device for the evaluation of hypertonia of the upper extremity

Includes bibliographical references.Traditional evaluation techniques for spastic hypertonia, such as the Modified Ashworth Scale (MAS), are prone to subjectivity and have been shown to have poor inter- and intra-rater reliability. Automated objective electromechanical devices for upper-limb evaluation do exist, such as the commercially available NeuroFlexor device. These assess combined wrist and finger flexor tone by monitoring wrist joint torque during passive wrist extension. Wrist flexor tone evaluations made by manipulation of the wrist joint alone, however, could be affected by possible hypertonia of the finger flexors due to the moment arm that these muscles‟ tendons have at the wrist joint. As such, robotic wrist flexor evaluation devices that measure only the wrist joint torque cannot distinguish between wrist and finger flexor hypertonia. A robotic device measuring involuntary resistance at the wrist and finger joints separately during wrist manipulation can be used to provide wrist flexor tone assessments that compensate for the influence of hypertonia of the finger flexor muscles, and therefore provide more accurate tone assessments of the wrist flexor muscles. To design, construct and evaluate a patient-safe device for the independent measurement of wrist and finger joint torque during wrist extension, and to use the device to accurately evaluate wrist flexor tone, in isolation from possible effects of finger flexor tone. Evaluations were made using the device in a clinical setting with volunteers (n=6) with varying levels of hypertonia in the hands and wrists. Volunteers’ wrist flexor tone was also assessed by three clinicians using the MAS score

Biomechatronics: Harmonizing Mechatronic Systems with Human Beings

This eBook provides a comprehensive treatise on modern biomechatronic systems centred around human applications. A particular emphasis is given to exoskeleton designs for assistance and training with advanced interfaces in human-machine interaction. Some of these designs are validated with experimental results which the reader will find very informative as building-blocks for designing such systems. This eBook will be ideally suited to those researching in biomechatronic area with bio-feedback applications or those who are involved in high-end research on manmachine interfaces. This may also serve as a textbook for biomechatronic design at post-graduate level

Distance-based analysis of dynamical systems and time series by optimal transport

The concept of distance is a fundamental notion that forms a basis for the orientation in space. It is related to the scientific measurement process: quantitative measurements result in numerical values, and these can be immediately translated into distances. Vice versa, a set of mutual distances defines an abstract Euclidean space. Each system is thereby represented as a point, whose Euclidean distances approximate the original distances as close as possible. If the original distance measures interesting properties, these can be found back as interesting patterns in this space. This idea is applied to complex systems: The act of breathing, the structure and activity of the brain, and dynamical systems and time series in general. In all these situations, optimal transportation distances are used; these measure how much work is needed to transform one probability distribution into another. The reconstructed Euclidean space then permits to apply multivariate statistical methods. In particular, canonical discriminant analysis makes it possible to distinguish between distinct classes of systems, e.g., between healthy and diseased lungs. This offers new diagnostic perspectives in the assessment of lung and brain diseases, and also offers a new approach to numerical bifurcation analysis and to quantify synchronization in dynamical systems.LEI Universiteit LeidenNWO Computational Life Sciences, grant no. 635.100.006Analyse en stochastie

Neuromuscular Reflex Control for Prostheses and Exoskeletons

Recent powered lower-limb prosthetic and orthotic (P/O) devices aim to restore legged mobility for persons with an amputation or spinal cord injury. Though various control strategies have been proposed for these devices, specifically finite-state impedance controllers, natural gait mechanics are not usually achieved. The goal of this project was to invent a biologically-inspired controller for powered P/O devices. We hypothesize that a more muscle-like actuation system, including spinal reflexes and vestibular feedback, can achieve able-bodied walking and also respond to outside perturbations. The outputs of the Virtual Muscle Reflex (VMR) controller are joint torque commands, sent to the electric motors of a P/O device. We identified the controller parameters through optimizations using human experimental data of perturbed walking, in which we minimized the error between the torque produced by our controller and the standard torque trajectories observed in the able-bodied experiments. In simulations, we then compare the VMR controller to a four-phase impedance controller. For both controllers the coefficient of determination R^2 and root-mean-square (RMS) error were calculated as a function of the gait cycle. When simulating the hip, knee, and ankle joints, the RMS error and R^2 across all joints and all trials is 15.65 Nm and 0.28 for the impedance controller, respectively, and for the VMR controller, these values are 15.15 Nm and 0.29, respectively. With similar performance, it was concluded that the VMR controller can reproduce characteristics of human walking in response to perturbations as effectively as an impedance controller. We then implemented the VMR controller on the Parker Hannifin powered exoskeleton and performed standard isokinetic and isometric knee rehabilitation exercises to observe the behavior of the virtual muscle model. In the isometric results, RMS error between the measured and commanded extension and flexion torques are 3.28 Nm and 1.25 Nm, respectively. In the isokinetic trials, we receive RMS error between the measured and commanded extension and flexion torques of 0.73 Nm and 0.24 Nm. Since the onboard virtual muscles demonstrate similar muscle force-length and force-velocity relationships observed in humans, we conclude the model is capable of the same stabilizing capabilities as observed in an impedance controller