Rehabilitation Engineering

Population ageing has major consequences and implications in all areas of our daily life as well as other important aspects, such as economic growth, savings, investment and consumption, labour markets, pensions, property and care from one generation to another. Additionally, health and related care, family composition and life-style, housing and migration are also affected. Given the rapid increase in the aging of the population and the further increase that is expected in the coming years, an important problem that has to be faced is the corresponding increase in chronic illness, disabilities, and loss of functional independence endemic to the elderly (WHO 2008). For this reason, novel methods of rehabilitation and care management are urgently needed. This book covers many rehabilitation support systems and robots developed for upper limbs, lower limbs as well as visually impaired condition. Other than upper limbs, the lower limb research works are also discussed like motorized foot rest for electric powered wheelchair and standing assistance device

Intuitive Human-Machine Interfaces for Non-Anthropomorphic Robotic Hands

As robots become more prevalent in our everyday lives, both in our workplaces and in our homes, it becomes increasingly likely that people who are not experts in robotics will be asked to interface with robotic devices. It is therefore important to develop robotic controls that are intuitive and easy for novices to use. Robotic hands, in particular, are very useful, but their high dimensionality makes creating intuitive human-machine interfaces for them complex. In this dissertation, we study the control of non-anthropomorphic robotic hands by non-roboticists in two contexts: collaborative manipulation and assistive robotics. In the field of collaborative manipulation, the human and the robot work side by side as independent agents. Teleoperation allows the human to assist the robot when autonomous grasping is not able to deal sufficiently well with corner cases or cannot operate fast enough. Using the teleoperator’s hand as an input device can provide an intuitive control method, but finding a mapping between a human hand and a non-anthropomorphic robot hand can be difficult, due to the hands’ dissimilar kinematics. In this dissertation, we seek to create a mapping between the human hand and a fully actuated, non-anthropomorphic robot hand that is intuitive enough to enable effective real-time teleoperation, even for novice users. We propose a low-dimensional and continuous teleoperation subspace which can be used as an intermediary for mapping between different hand pose spaces. We first propose the general concept of the subspace, its properties and the variables needed to map from the human hand to a robot hand. We then propose three ways to populate the teleoperation subspace mapping. Two of our mappings use a dataglove to harvest information about the user's hand. We define the mapping between joint space and teleoperation subspace with an empirical definition, which requires a person to define hand motions in an intuitive, hand-specific way, and with an algorithmic definition, which is kinematically independent, and uses objects to define the subspace. Our third mapping for the teleoperation subspace uses forearm electromyography (EMG) as a control input. Assistive orthotics is another area of robotics where human-machine interfaces are critical, since, in this field, the robot is attached to the hand of the human user. In this case, the goal is for the robot to assist the human with movements they would not otherwise be able to achieve. Orthotics can improve the quality of life of people who do not have full use of their hands. Human-machine interfaces for assistive hand orthotics that use EMG signals from the affected forearm as input are intuitive and repeated use can strengthen the muscles of the user's affected arm. In this dissertation, we seek to create an EMG based control for an orthotic device used by people who have had a stroke. We would like our control to enable functional motions when used in conjunction with a orthosis and to be robust to changes in the input signal. We propose a control for a wearable hand orthosis which uses an easy to don, commodity forearm EMG band. We develop an supervised algorithm to detect a user’s intent to open and close their hand, and pair this algorithm with a training protocol which makes our intent detection robust to changes in the input signal. We show that this algorithm, when used in conjunction with an orthosis over several weeks, can improve distal function in users. Additionally, we propose two semi-supervised intent detection algorithms designed to keep our control robust to changes in the input data while reducing the length and frequency of our training protocol

Cortical beta oscillations are associated with motor performance following visuomotor learning

© 2019 The Authors People vary in their capacity to learn and retain new motor skills. Although the relationship between neuronal oscillations in the beta frequency range (15–30 Hz) and motor behaviour is well established, the electrophysiological mechanisms underlying individual differences in motor learning are incompletely understood. Here, we investigated the degree to which measures of resting and movement-related beta power from sensorimotor cortex account for inter-individual differences in motor learning behaviour in the young and elderly. Twenty young (18–30 years) and twenty elderly (62–77 years) healthy adults were trained on a novel wrist flexion/extension tracking task and subsequently retested at two different time points (45–60 min and 24 h after initial training). Scalp EEG was recorded during a separate simple motor task before each training and retest session. Although short-term motor learning was comparable between young and elderly individuals, there was considerable variability within groups with subsequent analysis aiming to find the predictors of this variability. As expected, performance during the training phase was the best predictor of performance at later time points. However, regression analysis revealed that movement-related beta activity significantly explained additional variance in individual performance levels 45–60 min, but not 24 h after initial training. In the context of disease, these findings suggest that measurements of beta-band activity may offer novel targets for therapeutic interventions designed to promote rehabilitative outcomes

A Survey of Applications and Human Motion Recognition with Microsoft Kinect

Microsoft Kinect, a low-cost motion sensing device, enables users to interact with computers or game consoles naturally through gestures and spoken commands without any other peripheral equipment. As such, it has commanded intense interests in research and development on the Kinect technology. In this paper, we present, a comprehensive survey on Kinect applications, and the latest research and development on motion recognition using data captured by the Kinect sensor. On the applications front, we review the applications of the Kinect technology in a variety of areas, including healthcare, education and performing arts, robotics, sign language recognition, retail services, workplace safety training, as well as 3D reconstructions. On the technology front, we provide an overview of the main features of both versions of the Kinect sensor together with the depth sensing technologies used, and review literatures on human motion recognition techniques used in Kinect applications. We provide a classification of motion recognition techniques to highlight the different approaches used in human motion recognition. Furthermore, we compile a list of publicly available Kinect datasets. These datasets are valuable resources for researchers to investigate better methods for human motion recognition and lower-level computer vision tasks such as segmentation, object detection and human pose estimation

The relationship between cortical beta oscillations and motor learning

The ability to learn and retain new motor skills is pivotal for everyday life activities and motor rehabilitation after stroke. However, people show considerable individual differences in motor learning. Understanding the neurophysiological processes underlying these individual differences is of significant scientific and clinical importance. At a mechanistic level, oscillations in the beta frequency range (15–30 Hz), fundamental for motor control, reflect underlying cortical inhibitory and excitatory mechanisms. As such, they may provide appropriate biomarkers with which to bridge the gap between cellular and behavioural accounts of cortical plasticity in both healthy and diseased states. This thesis explores the interplay between cortical beta oscillations and individual differences in short-term motor learning within the context of healthy ageing and after stroke. First, I assess the test-retest reliability of resting and movement-related beta estimates in a group of healthy subjects across several weeks. By demonstrating that EEG-derived power measures of beta activity are highly reliable, I validate the notion that these measures reflect meaningful individual differences that can be utilized in basic research and in the clinic. Second, I probe the neurophysiological mechanisms underlying natural inter-individual differences in short-term motor learning. I demonstrate comparable motor learning ability between young and elderly individuals, despite age-related alterations in beta activity. Implementing a multivariate approach, I show that beta dynamics explain some of the individual differences in post-training tracking performance. Third, I extend this line of research by focusing on stroke-related inter-individual variations in motor learning. Employing the same tasks and analyses, I demonstrate preserved, albeit reduced motor learning ability and no aberrant beta activity after stroke. Beta dynamics explained some of the individual differences in stroke patients’ performance 24 hours after training, and may thus offer novel targets for therapeutic interventions

Multimodality with Eye tracking and Haptics: A New Horizon for Serious Games?

The goal of this review is to illustrate the emerging use of multimodal virtual reality that can benefit learning-based games. The review begins with an introduction to multimodal virtual reality in serious games and we provide a brief discussion of why cognitive processes involved in learning and training are enhanced under immersive virtual environments. We initially outline studies that have used eye tracking and haptic feedback independently in serious games, and then review some innovative applications that have already combined eye tracking and haptic devices in order to provide applicable multimodal frameworks for learning-based games. Finally, some general conclusions are identified and clarified in order to advance current understanding in multimodal serious game production as well as exploring possible areas for new applications

Dispositivo de realidade virtual para melhoria da marcha em pacientes com a doença de Parkinson

Dissertação de mestrado em Computer ScienceIn recent years there have been many improvements to medical procedures, involving the use of augmented reality technology to provide new innovative approaches to difficult tasks that are often required of the patients, requiring less physical exertion from the to achieve the same results or simply looking at the problem in a new perspective. Virtual reality technology has the capability of creating an interactive, motivating environment in which practice intensity and feedback can be manipulated to create individualised treatments to retrain movement. Currently there is a very large amount of people suffering from minor to severe functional limitations, impairments such as loss of range of motion, decreased reacting times, disordered movement organisation, and impaired force generation create deficits in motor control that effect the personss capacity for independent living and economic self-sufficiency. The use of augmented reality is starting to be used in more medical scenario’s and in the treatment of many diseases generally co-related with motor difficulties or recovery treatments. One of the diseases that has been looked more prominently for augmented reality development is the Parkinson’s disease which causes its patients to suffer severe gait constriction and whose generalised gait treatments didn’t produce a significant improvement in the patients gait without the use of heavy medication. One other important detail to take notice is that the Parkinsons disease causes the patient to abruptly enter a freezing state without any kind of warning which can lead the patient to fall and severally harm itself depending on the situation at hand. The objective of this thesis is to explore the possibilities of the use of augmented reality in an attempt to improve gait in patients suffering from Parkinson’s disease. For this purpose many augmented reality glasses were analysed selecting the best one in terms of affordability, comfort and utility. The application developed has the objective of improving the patients gait by displaying an augmented reality supper- imposed path for the patient to follow matching auditory cues with each of the patients steps and also helping the patient of he suddenly finds himself affected by a ”freezing” episode.Recentemente tem sido feitos vários melhoramentos nos procedimentos médicos, recorrendo ao uso de tecnologias como realidade aumentada para fornecer uma nova abordagem a tarefas complicadas que são frequentemente requeridas aos pacientes, requerendo um menor esforço físico e feedback imediato ou simplesmente para obter uma nova perspetiva sobre o problema em questão. O uso de realidade aumentada tem vindo a ser cada vez maior, sendo usado em cada vez mais procedimentos e para tratamento de variadas condições principalmente focadas em dificuldades motoras e fisioterapia. Uma das doenças que despertou maior interesse no uso de realidade aumentada no seu tratamento é a doença de Parkinson, conhecida por causa deterioramento nas capacidades motoras dos afetados causando problemas na marcha da pessoa que, afetam varias tarefas do seu dia a dia. Outro detalhe importante da doença de Parkinson é que os afetados também tem o que são chamados de episódios de ”congelamento” que acontecem quando o paciente de repente e sem nenhum aviso previ-o fica paralisado durante uns instantes, o que pode provocar a queda da pessoa. Estes episódios não são constantes podendo variar bastante na ocorrência e na intensidade de pessoa a pessoa. O objetivo desta dissertação é a exploração das possibilidades do uso de realidade aumentada numa tentativa de melhorar a marcha das pessoas afetadas com a doença de Parkinson. Para este propósito muitas ferramentas de realidade virtual foram examinadas escolhendo uma que seja o menos intrusiva possível para facilitar o uso pelo paciente e que tenha as especificações necessárias para o bem funcionar da aplicação. A aplicação de realidade virtual terá então o objetivo de melhorar a marcha do paciente através do seu uso mostrando ”pégadas” que irão servir para o paciente se orientar e ajudar o paciente quando ele estiver sobre o efeito de congelamento para evitar que cause danos graves a si próprio caso ocorra numa situação complicada