A High-Level Control Algorithm Based on sEMG Signalling for an Elbow Joint SMA Exoskeleton

A high-level control algorithm capable of generating position and torque references from surface electromyography signals (sEMG) was designed. It was applied to a shape memory alloy (SMA)-actuated exoskeleton used in active rehabilitation therapies for elbow joints. The sEMG signals are filtered and normalized according to data collected online during the first seconds of a therapy session. The control algorithm uses the sEMG signals to promote active participation of patients during the therapy session. In order to generate the reference position pattern with good precision, the sEMG normalized signal is compared with a pressure sensor signal to detect the intention of each movement. The algorithm was tested in simulations and with healthy people for control of an elbow exoskeleton in flexion&-extension movements. The results indicate that sEMG signals from elbow muscles, in combination with pressure sensors that measure arm&-exoskeleton interaction, can be used as inputs for the control algorithm, which adapts the reference for exoskeleton movements according to a patient's intention.The research was funded by RoboHealth (DPI2013-47944-C4-3-R) and the EDAM (DPI2016-75346-R) Spanish research projects

Modelling and EMG based Control of Upper Limb Exoskeletons for Hand Impairments

Functional losses associated with hand impairments have led to the growing development of hand exoskeletons. The main challenges are to develop the exoskeletons that work according to the user’s motion intention, which can be done by utilizing the electromyogram signals generated by forearm muscles contributed from the movement and/or grasping abilities of the hand. In this research, modelling and EMG based control of hand exoskeletons with the aim to assist stroke survivors in regaining their hand strength and functionality, and improve their quality of life is presented

Sensor-Based Adaptive Control and Optimization of Lower-Limb Prosthesis.

Recent developments in prosthetics have enabled the development of powered prosthetic ankles (PPA). The advent of such technologies drastically improved impaired gait by increasing balance and reducing metabolic energy consumption by providing net positive power. However, control challenges limit performance and feasibility of today’s devices. With addition of sensors and motors, PPA systems should continuously make control decisions and adapt the system by manipulating control parameters of the prostheses. There are multiple challenges in optimization and control of PPAs. A prominent challenge is the objective setup of the system and calibration parameters to fit each subject. Another is whether it is possible to detect changes in intention and terrain before prosthetic use and how the system should react and adapt to it. In the first part of this study, a model for energy expenditure was proposed using electromyogram (EMG) signals from the residual lower-limbs PPA users. The proposed model was optimized to minimize energy expenditure. Optimization was performed using a modified Nelder-Mead approach with a Latin Hypercube sampling. Results of the proposed method were compared to expert values and it was shown to be a feasible alternative for tuning in a shorter time. In the second part of the study, the control challenges regarding lack of adaptivity for PPAs was investigated. The current PPA system used is enhanced with impedance-controlled parameters that allow the system to provide different assistance. However, current systems are set to a fixed value and fail to acknowledge various terrain and intentions throughout the day. In this study, a pseudo-real-time adaptive control system was proposed to predict the changes in the gait and provide a smoother gait. The proposed control system used physiological, kinetic, and kinematic data and fused them to predict the change. The prediction was done using machine learning-based methods. Results of the study showed an accuracy of up to 89.7 percent for prediction of change for four different cases

A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue

Muscle fatigue is an established area of research and various types of muscle fatigue have been investigated in order to fully understand the condition. This paper gives an overview of the various non-invasive techniques available for use in automated fatigue detection, such as mechanomyography, electromyography, near-infrared spectroscopy and ultrasound for both isometric and non-isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who wish to select the most appropriate methodology for research on muscle fatigue detection or prediction, or for the development of devices that can be used in, e.g., sports scenarios to improve performance or prevent injury. To date, research on localised muscle fatigue focuses mainly on the clinical side. There is very little research carried out on the implementation of detecting/predicting fatigue using an autonomous system, although recent research on automating the process of localised muscle fatigue detection/prediction shows promising results

Mechanical factors affecting the estimation of tibialis anterior force using an EMG-driven modelling approach

The tibialis anterior (TA) muscle plays a vital role in human movement such as walking and running. Overuse of TA during these movements leads to an increased susceptibility of injuries e.g. chronic exertional compartment syndrome. TA activation has been shown to be affected by increases in exercise, age, and the external environment (i.e. incline and footwear). Because activation parameters of TA change with condition, it leads to the interpretation that force changes occur too. However,activation is only an approximate indicator of force output of a muscle. Therefore, the overall aim of this thesis was to investigate the parameters affecting accurate measure of TA force, leading to development of a subject-specific EMG-driven model, which takes into consideration specific methodological issues. The first study investigated the reasons why the tendon excursion and geometric method differ so vastly in terms of estimation of TA moment arm. Tendon length changes during the tendon excursion method, and location of the TA line of action and irregularities between talus and foot rotations during the geometric method, were found to affect the accuracy of TA moment arm measurement. A novel, more valid, method was proposed. The second study investigated the errors associated with methods used to account for plantar flexor antagonist co-contraction. A new approach was presented and shown to be, at worse, equivalent to current methods, but allows for accounting throughout the complete range of motion. The final study utilised the outputs from studies one and two to directly measure TA force in vivo. This was used to develop, and validate, an EMG-driven TA force model. Less error was found in the accuracy of estimating TA force when the contractile component length changes were modelled using the ankle, as opposed to the muscle. Overall, these findings increase our understanding of not only the mechanics associated with TA and the ankle, but also improves our ability to accurately monitor these

Mechanical factors affecting the estimation of tibialis anterior force using an EMG-driven modelling approach

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe tibialis anterior (TA) muscle plays a vital role in human movement such as walking and running. Overuse of TA during these movements leads to an increased susceptibility of injuries e.g. chronic exertional compartment syndrome. TA activation has been shown to be affected by increases in exercise, age, and the external environment (i.e. incline and footwear). Because activation parameters of TA change with condition, it leads to the interpretation that force changes occur too. However,activation is only an approximate indicator of force output of a muscle. Therefore, the overall aim of this thesis was to investigate the parameters affecting accurate measure of TA force, leading to development of a subject-specific EMG-driven model, which takes into consideration specific methodological issues. The first study investigated the reasons why the tendon excursion and geometric method differ so vastly in terms of estimation of TA moment arm. Tendon length changes during the tendon excursion method, and location of the TA line of action and irregularities between talus and foot rotations during the geometric method, were found to affect the accuracy of TA moment arm measurement. A novel, more valid, method was proposed. The second study investigated the errors associated with methods used to account for plantar flexor antagonist co-contraction. A new approach was presented and shown to be, at worse, equivalent to current methods, but allows for accounting throughout the complete range of motion. The final study utilised the outputs from studies one and two to directly measure TA force in vivo. This was used to develop, and validate, an EMG-driven TA force model. Less error was found in the accuracy of estimating TA force when the contractile component length changes were modelled using the ankle, as opposed to the muscle. Overall, these findings increase our understanding of not only the mechanics associated with TA and the ankle, but also improves our ability to accurately monitor these.Headley Court Trust and the Defence Medical Rehabilitation Centre

Differential activation of lumbar and sacral motor pools during walking at different speeds and slopes

Organization of spinal motor output has become of interest for investigating differential activation of lumbar and sacral motor pools during locomotor tasks. Motor pools are associated with functional grouping of motoneurons of the lower limb muscles. Here we examined how the spatiotemporal organization of lumbar and sacral motor pool activity during walking is orchestrated with slope of terrain and speed of progression. Ten subjects walked on an instrumented treadmill at different slopes and imposed speeds. Kinetics, kinematics, and electromyography of 16 lower limb muscles were recorded. The spinal locomotor output was assessed by decomposing the coordinated muscle activation profiles into a small set of common factors and by mapping them onto the rostrocaudal location of the motoneuron pools. Our results show that lumbar and sacral motor pool activity depend on slope and speed. Compared with level walking, sacral motor pools decrease their activity at negative slopes and increase at positive slopes, whereas lumbar motor pools increase their engagement when both positive and negative slope increase. These findings are consistent with a differential involvement of the lumbar and the sacral motor pools in relation to changes in positive and negative center of body mass mechanical power production due to slope and speed.NEW & NOTEWORTHY In this study, the spatiotemporal maps of motoneuron activity in the spinal cord were assessed during walking at different slopes and speeds. We found differential involvement of lumbar and sacral motor pools in relation to changes in positive and negative center of body mass power production due to slope and speed. The results are consistent with recent findings about the specialization of neuronal networks located at different segments of the spinal cord for performing specific locomotor tasks

Application of surface EMG in diabetic disease

Summary: English The World Health Organization warns that, in 2000, as many as 33 million Europeans suffered from diabetes, approximately 15% will likely develop foot ulcers, and approximately 15% to 20% of these patients will face lower-extremity amputation. In 2004, an estimated 3.4 million people died from consequences of high blood sugar. Diabetic neuropathy is the most common chronic complication associated with diabetes mellitus, affecting 20–50% of diabetic patients 10 years after their diagnosis. Peripheral neuropathy and peripheral arterial disease are the most common and invalidating diabetes’s complications, involved in the pathogenesis of diabetic foot. They account for the leading cause of non-traumatic lower limb amputations. It results from two factors. The first one is a reduced blow of blood in the inferior limbs, caused from the presence of obliterating peripheral arteriopathy disease. The second is the progressive laceration of nervous fibers (neuropathy) that cause a reduction of the sensitivity (also to the pain) and of the ability of movement, and that helps the appearance of lesions. Together with diabetes falls in older adults are a big public health concern and have provided much of the motivation for research into age-related changes in human gait. Tripping during walking is the predominant cause of falls not only in the elderly but also in the neuropathic subjects. Trips can occur during walking on a level ground, but also during crossing visible obstacle, stair ascending and descending. The social and economic weight of the diabetic foot and the tragic consequences that brings with it can be reduced through a prompt diagnosis and treatment from the very beginning. The aim of this thesis, was to evaluate differences in gait parameters, in performing stair ascending and descending task and evaluation of muscle fatigue during treadmill protocol in diabetes subjects with and without complications, in order to provide a further tool for early diagnosis which allows clinicians to change, if is necessary, or only to control, as soon as possible, the follow-up of patients according to their specific characteristics