Design and control of a single-leg exoskeleton with gravity compensation for children with unilateral cerebral palsy

Children with cerebral palsy (CP) experience reduced quality of life due to limited mobility and independence. Recent studies have shown that lower-limb exoskeletons (LLEs) have significant potential to improve the walking ability of children with CP. However, the number of prototyped LLEs for children with CP is very limited, while no single-leg exoskeleton (SLE) has been developed specifically for children with CP. This study aims to fill this gap by designing the first size-adjustable SLE for children with CP aged 8 to 12, covering Gross Motor Function Classification System (GMFCS) levels I to IV. The exoskeleton incorporates three active joints at the hip, knee, and ankle, actuated by brushless DC motors and harmonic drive gears. Individuals with CP have higher metabolic consumption than their typically developed (TD) peers, with gravity being a significant contributing factor. To address this, the study designed a model-based gravity-compensator impedance controller for the SLE. A dynamic model of user and exoskeleton interaction based on the Euler–Lagrange formulation and following Denavit–Hartenberg rules was derived and validated in Simscape™ and Simulink® with remarkable precision. Additionally, a novel systematic simplification method was developed to facilitate dynamic modelling. The simulation results demonstrate that the controlled SLE can improve the walking functionality of children with CP, enabling them to follow predefined target trajectories with high accuracy

System Identification of Bipedal Locomotion in Robots and Humans

The ability to perform a healthy walking gait can be altered in numerous cases due to gait disorder related pathologies. The latter could lead to partial or complete mobility loss, which affects the patients’ quality of life. Wearable exoskeletons and active prosthetics have been considered as a key component to remedy this mobility loss. The control of such devices knows numerous challenges that are yet to be addressed. As opposed to fixed trajectories control, real-time adaptive reference generation control is likely to provide the wearer with more intent control over the powered device. We propose a novel gait pattern generator for the control of such devices, taking advantage of the inter-joint coordination in the human gait. Our proposed method puts the user in the control loop as it maps the motion of healthy limbs to that of the affected one. To design such control strategy, it is critical to understand the dynamics behind bipedal walking. We begin by studying the simple compass gait walker. We examine the well-known Virtual Constraints method of controlling bipedal robots in the image of the compass gait. In addition, we provide both the mechanical and control design of an affordable research platform for bipedal dynamic walking. We then extend the concept of virtual constraints to human locomotion, where we investigate the accuracy of predicting lower limb joints angular position and velocity from the motion of the other limbs. Data from nine healthy subjects performing specific locomotion tasks were collected and are made available online. A successful prediction of the hip, knee, and ankle joints was achieved in different scenarios. It was also found that the motion of the cane alone has sufficient information to help predict good trajectories for the lower limb in stairs ascent. Better estimates were obtained using additional information from arm joints. We also explored the prediction of knee and ankle trajectories from the motion of the hip joints

Physical Diagnosis and Rehabilitation Technologies

The book focuses on the diagnosis, evaluation, and assistance of gait disorders; all the papers have been contributed by research groups related to assistive robotics, instrumentations, and augmentative devices

Controller design of a robotic orthosis using sinusoidal-input describing function model

Stroke is one of top leading causes of death in the world and it happens to more than 15 million people yearly. According to the National Stroke Association of Malaysia (NASAM), stroke is the third leading cause of death in Malaysia with around 40,000 cases reported annually. Forty percent of stroke survivors suffer from movement impairments after stroke. My grandfather was one of the victims and he was unable to attend any rehabilitation sessions due to several reasons. Hence, he lost the golden time to regain his movement and freedom. There are a lot of similar cases that happen daily in Malaysia. Besides, as the number of stroke patients increases yearly, the need for physiotherapists or rehabilitation machines equally increases. Hence, a low-cost clinical rehabilitation device is essential to provide assistance for an effective rehabilitation program and substitute the conventional method, as well as to reduce the burden of physiotherapists. In future, the proposed rehabilitation device would benefit not only stroke patients, but any patients who lost their normal walking ability including post-accident patients or those who suffer from spinal cord injury. The rehabilitation device aims to provide training assistance to patients not only in rehabilitation centres but also at home for daily training. The robotic orthosis is planned to be configured based on moving joint angles of human lower extremities. In the first stage of this research, angle-time characteristics for knee and hip swinging motion are utilised as a sagittal motion reference for the rehabilitation devices. The aim of following a proper gait cycle during rehabilitation training is to train patients to perform standing and swinging phases at proper timing and simultaneously provide the correct position reference to the patient during rehabilitation training. This can prevent patients from walking abnormally with an asymmetric gait cycle along or after the rehabilitation program. Besides, various limitations and the bulky structure of other rehabilitation devices lead to the design of the two-link lower limb rehabilitation device. This project aims to develop an assistive robotic rehabilitation device that generates a human gait trajectory for hemiplegic stroke patient gait rehabilitation in future. The shortcomings of other control applications due to environmental conditions and disturbances lead to the implementation of the describing function approach in the development of the devices. A sinusoidal-input describing function (SIDF) approach was implemented to linearize the nonlinear robotic orthosis with linear transfer function. The reason for utilising the SIDF approach is due to the nonlinear actual plant model with the present of load torque disturbances, discontinuous nonlinearities such as saturation and backlash, and also multivariable in the system. The nonlinear properties of the plant were proven in the preliminary stage of the research. A conventional controller, PID control combined with position and trajectory inputs were also applied to the system in the early stage of research. However, the experimental results were not satisfying. Finally, the SIDF approach was chosen to linearize the nonlinear system. Hence, generating a controller is much easier with a linear model of the nonlinear system. A SIDF approach was implemented to generate a controller for the multivariable, nonlinear closed loop system. Firstly, the SIDF approach enables the determination of the linear function of the nonlinear model known as the SIDF model. By utilising the linear model to mimic the behaviour of the nonlinear rehabilitation system, the controller for the nonlinear plant was able to be generated. In this research a controller based on linear control theory technique was used. The MATLAB library was used to design the lead-lag controller for the rehabilitation device. Various simulations such as step responses, tracking and decoupling of both links were performed on the generated controller with the nonlinear model to study the capability of the controller. Besides that, real life experiment testing was carried out to validate the feasibility of the controller designed via the SIDF approach. Simulation and experimental results were obtained, compared, and discussed. The highly accurate responses gained from experimental setup showed the robustness of the controller generated via SIDF approach. The implementation of the SIDF approach in a rehabilitation device (vertical two-link manipulator) is a first and hence, fulfils a novelty requirement for this research

Design and Control of a Single-Leg Exoskeleton with Gravity Compensation for Children with Unilateral Cerebral Palsy

Children with cerebral palsy (CP) experience reduced quality of life due to limited mobility and independence. Recent studies have shown that lower-limb exoskeletons (LLEs) have significant potential to improve the walking ability of children with CP. However, the number of prototyped LLEs for children with CP is very limited, while no single-leg exoskeleton (SLE) has been developed specifically for children with CP. This study aims to fill this gap by designing the first size-adjustable SLE for children with CP aged 8 to 12, covering Gross Motor Function Classification System (GMFCS) levels I to IV. The exoskeleton incorporates three active joints at the hip, knee, and ankle, actuated by brushless DC motors and harmonic drive gears. Individuals with CP have higher metabolic consumption than their typically developed (TD) peers, with gravity being a significant contributing factor. To address this, the study designed a model-based gravity-compensator impedance controller for the SLE. A dynamic model of user and exoskeleton interaction based on the Euler–Lagrange formulation and following Denavit–Hartenberg rules was derived and validated in Simscape™ and Simulink® with remarkable precision. Additionally, a novel systematic simplification method was developed to facilitate dynamic modelling. The simulation results demonstrate that the controlled SLE can improve the walking functionality of children with CP, enabling them to follow predefined target trajectories with high accuracy