Towards a human-in-the-loop control for a smart orthotic system

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)Stroke is the main cause of paralysis. This pathology has provoked a considerable increase of persons with motor impairments. With a therapy focused on each clinical case, the total or partial recovery can be achieved. Powered orthoses have been developed to promote an effective recover, based on repetitive gait training and user’s active participation. Many control approaches have been developed to control these devices, but none of them promotes an user-oriented strategy focused to the user’s needs. In an attempt of solving this issue, a new approach named Human-in-the-loop is emerging. This strategy allows the adaptation of some assistive parameters based on the user’s energetic cost, promoting a therapy tailored to each end-user needs. However, to estimate the energy expenditure, the use of non-ergonomic sensors, not suitable for clinical context, is required. Thus, it is necessary to find new ways of estimating energy expenditure using wearable and comfortable sensors. In this dissertation, the first steps to introduce the Human-in-the-loop strategy into a powered orthosis are presented. For this purpose, two strategies were developed: a strategy that allows the angular trajectory adaptation in real-time and other that promotes a stiffness adaptation all over the gait cycle. Both strategies were validated with healthy subjects. In the first strategy, the orthosis was able to modify its assistance in a fraction of microseconds, and the end-users were able to follow her with a median error below 10%. Regarding the second strategy, the results show that the orthosis allowed an effective change in the systems’ interaction stiffness, promoting an active participation of each user during its assistance. The energetic impact of using the robotic assistive device is also presented. As it promotes an energy expenditure augmentation in more than 30% in comparison to walk without the device, the necessity of implementing the Human-in-the-loop strategy was highlighted. In an attempt of finding an ergonomic technique to estimate the energetic cost, the use of machine learning algorithms was tested. The results, obtained with a MLP and a LSTM, prove that it is possible to estimate the energy expenditure with a mean error close to 11%. Future work consists in the implementation of the model in real-time and the collection of more data with the aforementioned control approaches, in a way of constructing a more robust model.O AVC é uma das maiores causas de paralisia. Esta patologia, cada vez mais com maior incidência nos jovens, tem provocado um aumento considerável de pessoas com problemas de mobilidade. Com uma terapia focada a cada caso clínico, a recuperação total ou parcial pode ser conseguida. As ortóteses ativas têm vindo a ser desenvolvidas com o propósito de promover uma recuperação eficaz, baseada em treinos repetitivos e numa participação ativa dos utilizadores. Várias abordagens de controlo têm vindo a ser desenvolvidas para controlar estes dispositivos, mas nenhuma delas promove uma estratégia orientada às necessidades do utilizador. Na tentativa de solucionar este problema, uma nova abordagem, designada por Human-in-the-loop está a emergir. Baseada no custo energético, esta estratégia permite adaptar parâmetros da assistência, promovendo uma terapia focada e direcionada a cada utilizador. No entanto, para estimar o custo energético, recorre-se ao uso de sensores que não são adequados para contexto clínico. Assim, torna-se necessário estudar novas formas de estimar o custo energético. Nesta dissertação são apresentados os primeiros passos para introduzir o controlo Human-in-the-loop numa ortótese ativa. Para isso, duas estratégias foram apresentadas: uma estratégia que permite adaptar a trajetória angular da ortótese, em tempo real, e outra que promove a adaptação da complacência do sistema ao longo do ciclo da marcha. Ambas foram validadas com sujeitos saudáveis. Relativamente à primeira abordagem, a ortótese foi capaz de modificar a sua assistência em microssegundos, e os utilizadores foram capazes de a seguir com um erro mediano inferior a 10%. No que diz respeito à segunda abordagem, os resultados mostram que a ortótese promoveu uma alteração eficaz da complacência de interação, promovendo uma participação ativa do utilizador durante a sua assistência. O impacto energético do uso do sistema robótico é, também, apresentado. Promovendo um aumento do custo energético em mais de 30%, a necessidade da estratégia Human-in-the-loop foi realçada. Na tentativa de encontrar uma técnica para estimar o custo energético, recorreu-se ao uso de machine learning. Os resultados, obtidos com uma MLP e uma LSTM, provam que é possível estimar o custo energético com um erro médio próximo dos 11%. Trabalho futuro passa pela implementação do modelo em tempo real e a recolha de mais dados com as abordagens de controlo apresentadas, de forma a construir um modelo mais robusto

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

Machine Learning in Robot Assisted Upper Limb Rehabilitation: A Focused Review

Robot-assisted rehabilitation, which can provide repetitive, intensive and high-precision physics training, has a positive influence on motor function recovery of stroke patients. Current robots need to be more intelligent and more reliable in clinical practice. Machine learning algorithms (MLAs) are able to learn from data and predict future unknown conditions, which is of benefit to improve the effectiveness of robot-assisted rehabilitation. In this paper, we conduct a focused review on machine learning-based methods for robot-assisted upper limb rehabilitation. Firstly, the current status of upper rehabilitation robots is presented. Then, we outline and analyze the designs and applications of MLAs for upper limb movement intention recognition, human-robot interaction control and quantitative assessment of motor function. Meanwhile, we discuss the future directions of MLAs-based robotic rehabilitation. This review article provides a summary of MLAs for robotic upper limb rehabilitation and contributes to the design and development of future advanced intelligent medical devices

Haptic Transparency and Interaction Force Control for a Lower-Limb Exoskeleton

Controlling the interaction forces between a human and an exoskeleton is crucial for providing transparency or adjusting assistance or resistance levels. However, it is an open problem to control the interaction forces of lower-limb exoskeletons designed for unrestricted overground walking. For these types of exoskeletons, it is challenging to implement force/torque sensors at every contact between the user and the exoskeleton for direct force measurement. Moreover, it is important to compensate for the exoskeleton's whole-body gravitational and dynamical forces, especially for heavy lower-limb exoskeletons. Previous works either simplified the dynamic model by treating the legs as independent double pendulums, or they did not close the loop with interaction force feedback. The proposed whole-exoskeleton closed-loop compensation (WECC) method calculates the interaction torques during the complete gait cycle by using whole-body dynamics and joint torque measurements on a hip-knee exoskeleton. Furthermore, it uses a constrained optimization scheme to track desired interaction torques in a closed loop while considering physical and safety constraints. We evaluated the haptic transparency and dynamic interaction torque tracking of WECC control on three subjects. We also compared the performance of WECC with a controller based on a simplified dynamic model and a passive version of the exoskeleton. The WECC controller results in a consistently low absolute interaction torque error during the whole gait cycle for both zero and nonzero desired interaction torques. In contrast, the simplified controller yields poor performance in tracking desired interaction torques during the stance phase.Comment: 17 pages, 12 figure

Design and Development of a Lightweight Ankle Exoskeleton for Human Walking Augmentation

RESUMÉ La plupart des exosquelettes motorisés de la cheville ont une masse distale considérable, ce qui limite leur capacité à réduire l’énergie dépensée par l’utilisateur durant la marche. L’objectif de notre travail est de développer un exosquelette de chevilles avec le minimum de masse distale ajoutée comparé aux exosquelettes motorisés de chevilles existants. Aussi, l’exosquelette doit fournir au moins 50 Nm de support au couple de flexion plantaire. L’exosquelette développé dans le cadre de ce mémoire utilise deux câbles Bowden pour transmettre la force mécanique de l’unité d’actionnement attachée à la taille aux deux tiges en fibre de Carbonne attachées à la botte de l’utilisateur. Quand les deux tiges sont tirées, ils génèrent un couple qui supporte le mouvement de flexion plantaire à la fin de la phase d’appui du cycle de marche. Une pièce conçue sur mesure et imprimé en plastique par prototypage rapide a été attachée au tibia pour ajuster la direction des câbles. Une étude d’optimisation a été effectuée pour minimiser la masse des tiges limitant ainsi la masse distale de l’exosquelette (attaché au tibia et pied) à seulement 348 g. Le résultat principal obtenu à partir des tests de marche est la réduction de l’activité des muscles soléaire et gastrocnémien du sujet par une moyenne de 37% et 44% respectivement lors de la marche avec l’exosquelette comparée à la marche normale. Cette réduction s’est produite quand l’exosquelette a fourni une puissance mécanique de 19 ± 2 W avec un actionnement qui a commencé à 38% du cycle de marche. Ce résultat démontre le potentiel de notre exosquelette à réduire le cout métabolique de marche et souligne l’importance de réduire la masse distale d’un exosquelette de marche.----------ABSTRACT Most of powered ankle exoskeletons add considerable distal mass to the user which limits their capacity to reduce the metabolic energy of walking. The objective of the work presented in this master thesis is to develop an ankle exoskeleton with a minimum added distal mass compared to existing autonomous powered ankle exoskeletons, while providing at least 50 Nm of assistive plantar flexion torque. The exoskeleton developed in this master thesis uses Bowden cables to transmit the mechanical force from the actuation unit attached to the waist to the carbon fiber struts fixed on the boot. As the struts are pulled, they create an assistive ankle plantar flexion torque. A 3D-printed brace was attached to the shin to adjust the direction of the cables. A design optimization study was performed to minimize the mass of the struts, thereby limiting the total added distal mass, attached to the shin and foot, to only 348 g. The main result obtained from walking tests was the reduction of the soleus and gastrocnemius muscles activity by an average of 37% and 44% respectively when walking with the exoskeleton compared to normal walking. This reduction occurred when the exoskeleton delivered a mechanical power of 19 ± 2 W with an actuation onset fixed at 38% of the gait cycle. This result shows the potential of the proposed exoskeleton to reduce the metabolic cost of walking and emphasizes the importance of minimizing the distal mass of ankle exoskeletons