Hybrid Neuroprosthesis for Lower Limbs

Assistive technologies have been proposed for the locomotion of people with spinal cord injury (SCI). One of them is the neuroprosthesis that arouses the interest of developers and health professionals bearing in mind the beneficial effects promoted in people with SCI. Thus, the first session of this chapter presents the principles of human motility and the impact that spinal cord injury causes on a person’s mobility. The second session presents functional electrical stimulation as a solution for the immobility of paralyzed muscles. It explains the working principles of constituent modules and main stimulatory parameters. The third session introduces the concepts and characteristics of neural prosthesis hybridization. The last two sessions present and discuss examples of hybrid neuroprostheses. Such systems employ hybrid assistive lower limb strategies to evoke functional movements in people with SCI, associating the motor effects of active and/or passive orthoses to a functional electrical stimulation (FES) system. Examples of typical applications of FES in rehabilitation are discussed

Development of a hybrid assist-as-need hand exoskeleton for stroke rehabilitation.

Stroke is one of the leading causes of disability globally and can significantly impair a patient’s ability to function on a daily basis. Through physical rehabilitative measures a patient may regain a level of functional independence. However, required therapy dosages are often not met. Rehabilitation is typically implemented through manual one-to-one assistance with a physiotherapist, which quickly becomes labour intensive and costly. Hybrid application of functional electrical stimulation (FES) and robotic support can access the physiological benefits of direct muscle activation while providing controlled and repeatable motion assistance. Furthermore, patient engagement can be heightened through the integration of a volitional intent measure, such as electromyography (EMG). Current hybrid hand-exoskeletons have demonstrated that a balanced hybrid support profile can alleviate FES intensity and motor torque requirements, whilst improving reference tracking errors. However, these support profiles remain fixed and patient fatigue is not addressed. The aim of this thesis was to develop a proof-of-concept assist-as-need hybrid exoskeleton for post-stroke hand rehabilitation, with fatigue monitoring to guide the balance of support modalities. The device required the development and integration of a constant current (CC) stimulator, stimulus-resistant EMG device, and hand-exoskeleton. The hand exoskeleton in this work was formed from a parametric Watt I linkage model that adapts to different finger sizes. Each linkage was optimised with respect to angular precision and compactness using Differential Evolution (DE). The exoskeleton’s output trajectory was shown to be sensitive to parameter variation, potentially caused by finger measurement error and shifts in coupler placement. However, in a set of cylindrical grasping trials it was observed that a range of movement strategies could be employed towards a successful grasp. As there are many possible trajectories that result in a successful grasp, it was deduced that the exoskeleton can still provide functional assistance despite its sensitivity to parameter variation. The CC stimulator developed in this work has a part cost of USD $145 and allows flexible adjustment of waveform parameters through an on-board micro-controller. The device is designed to output current up to ±30mA given a voltage compliance of ±50V. When applied across a 2kΩ load, the device exhibited a linear output transfer function, with a maximum ramp tracking error of 5 The stimulus-resistant EMG device builds on current designs by using a novel Schmitt trigger based artefact detection channel to adaptively blank stimulation artefacts without stimulator synchronisation. The design has a part cost of USD$150 and has been made open-source. The device demonstrated its ability to record EMG over its predominant energy spectrum during stimulation, through the stimulation electrodes or through separate electrodes. Pearson’s correlation coefficients greater than 0.84 were identified be- tween the normalised spectra of volitional EMG (vEMG) estimates during stimulation and of stimulation-free EMG recordings. This spectral similarity permits future research into applications such as spectral-based monitoring of fatigue and muscle coherence, posing an advantage over current same-electrode stimulation and recording systems, which can- not sample the lower end of the EMG spectrum due to elevated high-pass filter cut-off frequencies. The stimulus-resistant EMG device was used to investigate elicited EMG (eEMG)-based fatigue metrics during vEMG-controlled stimulation and hybrid support profiles. During intermittent vEMG-controlled stimulation, the eEMG peak-to-peak amplitude (PTP) index was the median frequency (MDF) had a negative correlation for all subjects with R > 0:62 during stimulation-induced wrist flexion and R > 0:55 during stimulation-induced finger flexion. During hybrid FES-robotic support trials, a 40% reduction in stimulus intensity resulted in an average 21% reduction in MDF gradient magnitudes. This reflects lower levels of fatigue during the hybrid support profile and indicates that the MDF gradient can provide useful information on the progression of muscle fatigue. A hybrid exoskeleton system was formed through the integration of the CC stimulator, stimulus-resistant EMG device, and the hand exoskeleton developed in this work. The system provided assist-as-need functional grasp assistance through stimulation and robotic components, governed by the user’s vEMG. The hybrid support profile demonstrated consistent motion assistance with lowered stimulation intensities, which in-turn lowered the subjects’ perceived levels of fatigue

Investigation and Quantification of FES Exercise – Isometric Electromechanics and Perceptions of Its Usage as an Exercise Modality for Various Populations

Functional Electrical Stimulation (FES) is the triggering of muscle contraction by use of an electrical current. It can be used to give paralyzed individuals several health benefits, through allowing artificial movement and exercise. Although many FES devices exist, many aspects require innovation to increase usability and home translation. In addition, the effect of changing electrical parameters on limb biomechanics is not entirely understood; in particular with regards to stimulation duty cycle. This thesis has two distinct components. In the first (public health component), interview studies were conducted to understand several issues related to FES technology enhancement, implementation and home translation. In the second (computational biomechanics component), novel signal processing algorithms were designed that can be used to measure mechanical responses of muscles subjected to electrical stimulation. These experiments were performed by changing duty cycle and measuring its effect on quadriceps-generated knee torque. The studies of this thesis have presented several ideas, toolkits and results which have the potential to guide future FES biomechanics studies and the translatability of systems into regular usage for patients. The public health studies have provided conceptual frameworks upon which FES may be used in the home by patients. In addition, they have elucidated a range of issues that need to be addressed should FES technology reach its true potential as a therapy. The computational biomechanics studies have put forward novel data analysis techniques which may be used for understanding how muscle responds to electrical stimulation, as measured via torque. Furthermore, the effect of changing the electrical stimulation duty cycle on torque was successfully described, adding to an understanding of how electrical stimulation parameter modulation can influence joint biomechanics