168 research outputs found

    Virtual Stiffness: A Novel Biomechanical Approach to Estimate Limb Stiffness of a Multi-Muscle and Multi-Joint System

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    In recent years, different groups have developed algorithms to control the stiffness of a robotic device through the electromyographic activity collected from a human operator. However, the approaches proposed so far require an initial calibration, have a complex subject-specific muscle model, or consider the activity of only a few pairs of antagonist muscles. This study described and tested an approach based on a biomechanical model to estimate the limb stiffness of a multi-joint, multi-muscle system from muscle activations. The “virtual stiffness” method approximates the generated stiffness as the stiffness due to the component of the muscle-activation vector that does not generate any endpoint force. Such a component is calculated by projecting the vector of muscle activations, estimated from the electromyographic signals, onto the null space of the linear mapping of muscle activations onto the endpoint force. The proposed method was tested by using an upper-limb model made of two joints and six Hill-type muscles and data collected during an isometric force-generation task performed with the upper limb. The null-space projection of the muscle-activation vector approximated the major axis of the stiffness ellipse or ellipsoid. The model provides a good approximation of the voluntary stiffening performed by participants that could be directly implemented in wearable myoelectric controlled devices that estimate, in real-time, the endpoint forces, or endpoint movement, from the mapping between muscle activation and force, without any additional calibrations

    Design and Development of Biofeedback Stick Technology (BfT) to Improve the Quality of Life of Walking Stick Users

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    Biomedical engineering has seen a rapid growth in recent times, where the aim to facilitate and equip humans with the latest technology has become widespread globally. From high-tech equipment ranging from CT scanners, MRI equipment, and laser treatments, to the design, creation, and implementation of artificial body parts, the field of biomedical engineering has significantly contributed to mankind. Biomedical engineering has facilitated many of the latest developments surrounding human mobility, with advancement in mobility aids improving human movement for people with compromised mobility either caused by an injury or health condition. A review of the literature indicated that mobility aids, especially walking sticks, and appropriate training for their use, are generally prescribed by allied health professionals (AHP) to walking stick users for rehabilitation and activities of daily living (ADL). However, feedback from AHP is limited to the clinical environment, leaving walking stick users vulnerable to falls and injuries due to incorrect usage. Hence, to mitigate the risk of falls and injuries, and to facilitate a routine appraisal of individual patient’s usage, a simple, portable, robust, and reliable tool was developed which provides the walking stick users with real-time feedback upon incorrect usage during their activities of daily living (ADL). This thesis aimed to design and develop a smart walking stick technology: Biofeedback stick technology (BfT). The design incorporates the approach of patient and public involvement (PPI) in the development of BfT to ensure that BfT was developed as per the requirements of walking stick users and AHP recommendations. The newly developed system was tested quantitatively for; validity, reliability, and reproducibility against gold standard equipment such as the 3D motion capture system, force plates, optical measurement system for orientation, weight bearing, and step count. The system was also tested qualitatively for its usability by conducting semi-informal interviews with AHPs and walking stick users. The results of these studies showed that the newly developed system has good accuracy, reported above 95% with a maximum inaccuracy of 1°. The data reported indicates good reproducibility. The angles, weight, and steps recorded by the system during experiments are within the values published in the literature. From these studies, it was concluded that, BfT has the potential to improve the lives of walking stick users and that, with few additional improvements, appropriate approval from relevant regulatory bodies, and robust clinical testing, the technology has a huge potential to carve its way to a commercial market

    User-Centered Modelling and Design of Assistive Exoskeletons

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    Learning to Assist Different Wearers in Multitasks: Efficient and Individualized Human-In-the-Loop Adaption Framework for Exoskeleton Robots

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    One of the typical purposes of using lower-limb exoskeleton robots is to provide assistance to the wearer by supporting their weight and augmenting their physical capabilities according to a given task and human motion intentions. The generalizability of robots across different wearers in multiple tasks is important to ensure that the robot can provide correct and effective assistance in actual implementation. However, most lower-limb exoskeleton robots exhibit only limited generalizability. Therefore, this paper proposes a human-in-the-loop learning and adaptation framework for exoskeleton robots to improve their performance in various tasks and for different wearers. To suit different wearers, an individualized walking trajectory is generated online using dynamic movement primitives and Bayes optimization. To accommodate various tasks, a task translator is constructed using a neural network to generalize a trajectory to more complex scenarios. These generalization techniques are integrated into a unified variable impedance model, which regulates the exoskeleton to provide assistance while ensuring safety. In addition, an anomaly detection network is developed to quantitatively evaluate the wearer's comfort, which is considered in the trajectory learning procedure and contributes to the relaxation of conflicts in impedance control. The proposed framework is easy to implement, because it requires proprioceptive sensors only to perform and deploy data-efficient learning schemes. This makes the exoskeleton practical for deployment in complex scenarios, accommodating different walking patterns, habits, tasks, and conflicts. Experiments and comparative studies on a lower-limb exoskeleton robot are performed to demonstrate the effectiveness of the proposed framework.Comment: 16 pages journal articl

    ATHENA Research Book, Volume 2

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    ATHENA European University is an association of nine higher education institutions with the mission of promoting excellence in research and innovation by enabling international cooperation. The acronym ATHENA stands for Association of Advanced Technologies in Higher Education. Partner institutions are from France, Germany, Greece, Italy, Lithuania, Portugal and Slovenia: University of Orléans, University of Siegen, Hellenic Mediterranean University, Niccolò Cusano University, Vilnius Gediminas Technical University, Polytechnic Institute of Porto and University of Maribor. In 2022, two institutions joined the alliance: the Maria Curie-Skłodowska University from Poland and the University of Vigo from Spain. Also in 2022, an institution from Austria joined the alliance as an associate member: Carinthia University of Applied Sciences. This research book presents a selection of the research activities of ATHENA University's partners. It contains an overview of the research activities of individual members, a selection of the most important bibliographic works of members, peer-reviewed student theses, a descriptive list of ATHENA lectures and reports from individual working sections of the ATHENA project. The ATHENA Research Book provides a platform that encourages collaborative and interdisciplinary research projects by advanced and early career researchers

    Brain activity on encoding different textures EEG signal acquisition with ExoAtlet®

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    Powered exoskeletons play a crucial role in the rehabilitation field improving the quality of life for those who need them. Thus, being a major contribution for patients integration into society, providing them with more autonomy and freedom. In spite of these positive outcomes, a thorough description of the brain correlates connected to exoskeleton control is still needed. For instance, the perception of different pavement textures when wearing an exoskeleton is probably going to cause changes in cerebral activity, which could impact both sensory encoding and Brain-Computer Interface (BCI) control. Therefore, the main goal of this work is to describe the brain activity response to different textured pavements using ExoAtlet ® powered exoskeleton. In order to measure, process, analyze and classify the impact of different textures on neurophysiological rhythms, 4-minute signals were recorded by Electroencephalogram (EEG) with a 16-channel cap (actiCAP by Brain Products). Each of the three experimental subjects was instructed to walk in place on four different types of pavement (flat, carpet, foam, and rubber circles) with and without the exoskeleton, for a total of eight different experimental conditions. A counterbalanced design was applied, and informed consent was obtained from participants (Committee for Health Sciences of the Universidade Católica Portuguesa - 99/2022). Additionally, four machine learning methods, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), and Artificial Neural Network (ANN), were selected in order to analyze three distinct classification problems. This study found that there were changes associated with the delta frequency band for electrodes C3 and C4, and when comparing the classifiers performance, LDA presented the best accuracy across the three classification problems involving all subjects. Thereby, this work concludes that the results are consistent with the hypothesis that sensory processing of pavement textures during exoskeleton control induces neural changes and delta variations of the C3 and C4 electrodes. Additionally, LDA demonstrated the best performance across the three classifications of subject-independent problems.Os exoesqueletos motorizados desempenham um papel crucial no campo da reabilitação, melhorando a qualidade de vida das pessoas que deles necessitam. Deste modo, são um contributo importante para que os pacientes com condições físicas limitadas sejam mais facilmente integrados na sociedade, proporcionando-lhes mais autonomia e liberdade. Embora esta tecnologia tenha os seus aspetos positivos, ainda existe a necessidade de descrever os correlatos cerebrais direcionados para o controlo do exoesqueleto. Por exemplo, a percepção de diferentes pavimentos quando se usa um exoesqueleto vai provavelmente causar alterações na actividade cerebral, o que pode ter impacto tanto na codificação sensorial como no controlo da interface cérebro-máquina (BCI). Deste modo, o principal objetivo deste trabalho é descrever a atividade cerebral às diferentes texturas dos pavimentos, utilizando o exoesqueleto ExoAtlet ®. A fim de medir, processar, analisar e classificar o impacto de diferentes texturas em ritmos neurofisiológicos, foram registados sinais de 4 minutos atravês the Eletroencefalograma (EEG) com uma touca de 16 canais (actiCAP by Brain Products). Cada um dos três voluntários foi instruído a dar passos no lugar em quatro tipos diferentes de pavimento (plano, alcatifa, espuma, e círculos de borracha) com e sem o exosqueleto, num total de oito condições experimentais diferentes. Foi aplicado um desenho contrabalançado e foi obtido o consentimento informado dos participantes (Comissão para as Ciências da Saúde da Universidade Católica Portuguesa - 99/2022). Adicionalmente, foram selecionados quatro classificadores: máquinas de vetores de suporte (SVM), k-vizinhos mais próximos (KNN), análise discriminante linear (LDA) e redes neuronais artificiais (ANN) para analisar três problemas de classificação distintos. Os resultados obtidos por este estudo demonstraram que existiam alterações associadas à banda de frequência delta para os eléctrodos C3 e C4 e, ao comparar o desempenho dos classificadores, o LDA apresentou a melhor exatidão nos três problemas de classificação envolvendo todos os sujeitos. Assim, estes resultados são consistentes com a hipótese de que o processamento sensorial dos pavimentos durante o controlo do exoesqueleto induz alterações neuronais

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

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    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

    Proceedings of the 12th International Conference on Kinanthropology

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    Proceedings of the 12th Conference of Sport and Quality of Life 2019 gatheres submissions of participants of the conference. Every submission is the result of positive evaluation by reviewers from the corresponding field. Conference is divided into sections – Analysis of human movement; Sport training, nutrition and regeneration; Sport and social sciences; Active ageing and sarcopenia; Strength and conditioning training; section for PhD students
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