Design of a Simple and Modular 2-DOF Ankle Physiotherapy Device Relying on a Hybrid Serial-Parallel Robotic Architecture

The aim of this work is to propose a new 2-DOF robotic platform with hybrid parallel-serial structure and to undertake its parametric design so that it can follow the whole range of ankle related foot movements. This robot can serve as a human ankle rehabilitation device. The existing ankle rehabilitation devices present typically one or more of the following shortcomings: redundancy, large size, or high cost, hence the need for a device that could offer simplicity, modularity, and low cost of construction and maintenance. In addition, our targeted device must be safe during operation, disallow undesirable movements of the foot, while adaptable to any human foot. Our detailed study of foot kinematics has led us to a new hybrid architecture, which strikes a balance among all aforementioned goals. It consists of a passive serial kinematics chain with two adjustable screws so that the axes of the chain match the two main ankle-axes of typical feet. An active parallel chain, which consists of two prismatic actuators, provides the movement of the platform. Thus, the platform can follow the foot movements, thanks to the passive chain, and also possesses the advantages of parallel robots, including rigidity, high stiffness and force capabilities. The lack of redundancy yields a simpler device with lower size and cost. The paper describes the kinematics modelling of the platform and analyses the force and velocity transmission. The parametric design of the platform is carried out; our simulations confirm the platform's suitability for ankle rehabilitation

Development of lower-limb rehabilitation exercises using 3-PRS Parallel Robot and Dynamic Movement Primitives

[EN] The design of rehabilitation exercises applied to sprained ankles requires extreme caution, regarding the trajectories and the speed of the movements that will affect the patient. This paper presents a technique that allows a 3-PRS parallel robot to control such exercises, consisting of dorsi/plantar flexion and inversion/eversion ankle movements. The work includes a position control scheme for the parallel robot in order to follow a reference trajectory for each limb with the possibility of stopping the exercise in mid-execution without control loss. This stop may be motivated by the forces that the robot applies to the patient, acting like an alarm mechanism. The procedure introduced here is based on Dynamic Movement Primitives (DMPs).This work has been partially funded by FEDER-CICYT project with reference DPI2017-84201-R financed by Ministerio de Economía, Industria e Innovación (Spain).Escarabajal Sánchez, RJ.; Abu Dakka, FJM.; Pulloquinga Zapata, J.; Mata Amela, V.; Vallés Miquel, M.; Valera Fernández, Á. (2020). Development of lower-limb rehabilitation exercises using 3-PRS Parallel Robot and Dynamic Movement Primitives. Multidisciplinary Journal for Education, Social and Technological Sciences. 7(2):30-44. https://doi.org/10.4995/muse.2020.13907OJS304472Abu-Dakka, F. J., Valera, A., Escalera, J. A., Vallés, M., Mata, V., & Abderrahim, M. (2015). Trajectory adaptation and learning for ankle rehabilitation using a 3-PRS parallel robot. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9245, 483-494. https://doi.org/10.1007/978-3-319-22876-1_41Atkeson, C. G., Moore, A. W., & Schaal, S. (1997). Locally Weighted Learning. Artificial Intelligence Review, 11(1-5), 11-73. https://doi.org/10.1007/978-94-017-2053-3_2Brockett, C. L., & Chapman, G. J. (2016). Biomechanics of the ankle. Orthopaedics and Trauma, 30(3), 232-238. https://doi.org/10.1016/j.mporth.2016.04.015Dai, J. S., Zhao, T., & Nester, C. (2004). Sprained Ankle Physiotherapy Based Mechanism Synthesis and Stiffness Analysis of a Robotic Rehabilitation Device. Autonomous Robots, 16(2), 207-218. https://doi.org/10.1023/B:AURO.0000016866.80026.d7Díaz-Rodríguez, M., Mata, V., Valera, Á., & Page, Á. (2010). A methodology for dynamic parameters identification of 3-DOF parallel robots in terms of relevant parameters. Mechanism and Machine Theory, 45(9), 1337-1356. https://doi.org/10.1016/j.mechmachtheory.2010.04.007Díaz, I., Gil, J. J., & Sánchez, E. (2011). Lower-Limb Robotic Rehabilitation: Literature Review and Challenges. Journal of Robotics, 2011(i), 1-11. https://doi.org/10.1155/2011/759764Fanger, Y., Umlauft, J., & Hirche, S. (2016). Gaussian Processes for Dynamic Movement Primitives with application in knowledge-based cooperation. IEEE International Conference on Intelligent Robots and Systems, 2016-Novem, 3913-3919. https://doi.org/10.1109/IROS.2016.7759576Gosselin, C., & Angeles, J. (1990). Singularity Analysis of Closed-Loop Kinematic Chains. IEEE Transactions on Robotics and Automation, 6(3), 281-290. https://doi.org/10.1109/70.56660Hesse, S., & Uhlenbrock, D. (2000). A mechanized gait trainer for restoration of gait. Journal of Rehabilitation Research and Development, 37(6), 701-708.Ijspeert, A. J., Nakanishi, J., Hoffmann, H., Pastor, P., & Schaal, S. (2013). Dynamical movement primitives: Learning attractor models formotor behaviors. Neural Computation, 25(2), 328-373. https://doi.org/10.1162/NECO_a_00393Ijspeert, A. J., Nakanishi, J., & Schaal, S. (2002). Movement imitation with nonlinear dynamical systems in humanoid robots. Proceedings - IEEE International Conference on Robotics and Automation, 2, 1398-1403. https://doi.org/10.1109/ROBOT.2002.1014739Liu, G., Gao, J., Yue, H., Zhang, X., & Lu, G. (2006). Design and kinematics simulation of parallel robots for ankle rehabilitation. 2006 IEEE International Conference on Mechatronics and Automation, ICMA 2006, 2006, 1109-1113. https://doi.org/10.1109/ICMA.2006.257780Nakanishi, J., Morimoto, J., Endo, G., Cheng, G., Schaal, S., & Kawato, M. (2004). Learning from demonstration and adaptation of biped locomotion. Robotics and Autonomous Systems, 47(2-3), 79-91. https://doi.org/10.1016/j.robot.2004.03.003Nemec, B., & Ude, A. (2012). Action sequencing using dynamic movement primitives. Robotica, 30(5), 837-846. https://doi.org/10.1017/S0263574711001056Patel, Y. D., & George, P. M. (2012). Parallel Manipulators Applications-A Survey. Modern Mechanical Engineering, 02(03), 57-64. https://doi.org/10.4236/mme.2012.23008Paul, R. P. (1981). Robot Manipulators: Mathematics, Programming, and Control : the Computer Control of Robot Manipulators (p. 279).Reinkensmeyer, D. J., Aoyagi, D., Emken, J. L., Galvez, J. A., Ichinose, W., Kerdanyan, G., Maneekobkunwong, S., Minakata, K., Nessler, J. A., Weber, R., Roy, R. R., De Leon, R., Bobrow, J. E., Harkema, S. J., & Reggie Edgerton, V. (2006). Tools for understanding and optimizing robotic gait training. Journal of Rehabilitation Research and Development, 43(5), 657-670. https://doi.org/10.1682/JRRD.2005.04.0073Safran, M. R., Benedetti, R. S., Bartolozzi, A. R., & Mandelbaum, B. R. (1999). Lateral ankle sprains: A comprehensive review part 1: Etiology, pathoanatomy, histopathogenesis, and diagnosis. In Medicine and Science in Sports and Exercise (Vol. 31, Issue 7 SUPPL., pp. S429-S437).https://doi.org/10.1097/00005768-199907001-00004Saglia, J. A., Tsagarakis, N. G., Dai, J. S., & Caldwell, D. G. (2013). Control strategies for patient-assisted training using the ankle rehabilitation robot (ARBOT). IEEE/ASME Transactions on Mechatronics, 18(6), 1799-1808. https://doi.org/10.1109/TMECH.2012.2214228Schaal, S. (2006). Dynamic Movement Primitives -A Framework for Motor Control in Humans and Humanoid Robotics. In Adaptive Motion of Animals and Machines (pp. 261-280). https://doi.org/10.1007/4-431-31381-8_23Sui, P., Yao, L., Lin, Z., Yan, H., & Dai, J. S. (2009). Analysis and synthesis of ankle motion and rehabilitation robots. 2009 IEEE International Conference on Robotics and Biomimetics, ROBIO 2009, 3, 2533-2538. https://doi.org/10.1109/ROBIO.2009.5420487Tsoi, Y. H., Xie, S. Q., & Graham, A. E. (2009). Design, modeling and control of an ankle rehabilitation robot. Studies in Computational Intelligence, 177, 377-399. https://doi.org/10.1007/978-3-540-89933-4_18Vallés, M., Díaz-Rodrguez, M., Valera, Á., Mata, V., & Page, Á. (2012). Mechatronic development and dynamic control of a 3-dof parallel manipulator. Mechanics Based Design of Structures and Machines, 40(4), 434-452. https://doi.org/10.1080/15397734.2012.687292Xie, S. (2016). Advanced robotics for medical rehabilitation: current state of the art and recent advances. In Springer tracts in advanced robotics (Issue 108). https://doi.org/10.1007/978-3-319-19896-5Yoon, J., Ryu, J., & Lim, K. B. (2006). Reconfigurable ankle rehabilitation robot for various exercises. Journal of Robotic Systems, 22(SUPPL.), 15-33. https://doi.org/10.1002/rob.2015

Design and Development of Ankle-Foot Rehabilitation Exerciser (AFRE) System Using Pneumatic Actuator

This research presents the design and development of a novel strategy for an Ankle-Foot Rehabilitation Exerciser (AFRE) system. AFRE system can be used Continuous Passive Motion (CPM) device and strength endurance training device for early stage functional rehabilitation. The designed mechanism can allow desired maximum and minimum Range of Motion (ROM) for dorsiflexion and plantar flexion (upwards and downwards stretching). This device consists of a new moveable mechanism design prototype using a new double acting Intelligent Pneumatic Actuator (IPA), embedded controller and communication protocol. The drive system consists of a nonlinear moving pneumatic actuator that controls the angle position, force and compliance for stiffness characteristic of the ankle-foot orthosis platform. In addition, the device can be configured through MATLAB via personal computer where the user can adjust the required ROM and resistance for the user in real-time. Analysis carried out during the system validation and testing through selected subjects are presented and discussed. This AFRE system is expected to substitute the traditional therapy and motorized rehabilitation device to increase the healing time of the patient specifically

Passive exercise adaptation for ankle rehabilitation based on learning control framework

This article belongs to the Special Issue Human-Robot Interaction.Ankle injuries are among the most common injuries in sport and daily life. However, for their recovery, it is important for patients to perform rehabilitation exercises. These exercises are usually done with a therapist's guidance to help strengthen the patient's ankle joint and restore its range of motion. However, in order to share the load with therapists so that they can offer assistance to more patients, and to provide an efficient and safe way for patients to perform ankle rehabilitation exercises, we propose a framework that integrates learning techniques with a 3-PRS parallel robot, acting together as an ankle rehabilitation device. In this paper, we propose to use passive rehabilitation exercises for dorsiflexion/plantar flexion and inversion/eversion ankle movements. The therapist is needed in the first stage to design the exercise with the patient by teaching the robot intuitively through learning from demonstration. We then propose a learning control scheme based on dynamic movement primitives and iterative learning control, which takes the designed exercise trajectory as a demonstration (an input) together with the recorded forces in order to reproduce the exercise with the patient for a number of repetitions defined by the therapist. During the execution, our approach monitors the sensed forces and adapts the trajectory by adding the necessary offsets to the original trajectory to reduce its range without modifying the original trajectory and subsequently reducing the measured forces. After a predefined number of repetitions, the algorithm restores the range gradually, until the patient is able to perform the originally designed exercise. We validate the proposed framework with both real experiments and simulation using a Simulink model of the rehabilitation parallel robot that has been developed in our lab

Passive Exercise Adaptation for Ankle Rehabilitation Based on Learning Control Framework

[EN] Ankle injuries are among the most common injuries in sport and daily life. However, for their recovery, it is important for patients to perform rehabilitation exercises. These exercises are usually done with a therapist's guidance to help strengthen the patient's ankle joint and restore its range of motion. However, in order to share the load with therapists so that they can offer assistance to more patients, and to provide an efficient and safe way for patients to perform ankle rehabilitation exercises, we propose a framework that integrates learning techniques with a 3-PRS parallel robot, acting together as an ankle rehabilitation device. In this paper, we propose to use passive rehabilitation exercises for dorsiflexion/plantar flexion and inversion/eversion ankle movements. The therapist is needed in the first stage to design the exercise with the patient by teaching the robot intuitively through learning from demonstration. We then propose a learning control scheme based on dynamic movement primitives and iterative learning control, which takes the designed exercise trajectory as a demonstration (an input) together with the recorded forces in order to reproduce the exercise with the patient for a number of repetitions defined by the therapist. During the execution, our approach monitors the sensed forces and adapts the trajectory by adding the necessary offsets to the original trajectory to reduce its range without modifying the original trajectory and subsequently reducing the measured forces. After a predefined number of repetitions, the algorithm restores the range gradually, until the patient is able to perform the originally designed exercise. We validate the proposed framework with both real experiments and simulation using a Simulink model of the rehabilitation parallel robot that has been developed in our lab.This work has been partially funded by the FEDER-CICYT project with reference DPI2017-84201-R (Integracion de modelos biomecanicos en el desarrollo y operacion de robots rehabilitadores reconfigurables) financed by Ministerio de Economia, Industria e Innovacion (Spain).Abu-Dakka, FJ.; Valera Fernández, Á.; Escalera, JA.; Abderrahim, M.; Page Del Pozo, AF.; Mata Amela, V. (2020). Passive Exercise Adaptation for Ankle Rehabilitation Based on Learning Control Framework. Sensors. 20(21):1-23. https://doi.org/10.3390/s20216215S123202

serial and parallel robotics: energy saving systems and rehabilitation devices

This thesis focuses on the design and discussion of robotic devices and their applications. Robotics is the branch of technology that deals with the design, construction, operation, and application of robots as well as computer systems for their control, sensory feedback, and information processing [1]. Nowadays, robotics has been an unprecedented increase in applications of industry, military, health, domestic service, exploration, commerce, etc. Different applications require robots with different structures and different functions. Robotics normally includes serial and parallel structures. To have contribution to two kinds of structures, this thesis consisting of two sections is devoted to the design and development of serial and parallel robotic structures, focused on applications in the two different fields: industry and health

Effectiveness of robot-assisted therapy on ankle rehabilitation – a systematic review

Objective The aim of this study was to provide a systematic review of studies that investigated the effectiveness of robot-assisted therapy on ankle motor and function recovery from musculoskeletal or neurologic ankle injuries. Methods Thirteen electronic databases of articles published from January, 1980 to June, 2012 were searched using keywords ‘ankle*’, ‘robot*’, ‘rehabilitat*’ or ‘treat*’ and a free search in Google Scholar based on effects of ankle rehabilitation robots was also conducted. References listed in relevant publications were further screened. Eventually, twenty-nine articles were selected for review and they focused on effects of robot-assisted ankle rehabilitation. Results Twenty-nine studies met the inclusion criteria and a total of 164 patients and 24 healthy subjects participated in these trials. Ankle performance and gait function were the main outcome measures used to assess the therapeutic effects of robot-assisted ankle rehabilitation. The protocols and therapy treatments were varied, which made comparison among different studies difficult or impossible. Few comparative trials were conducted among different devices or control strategies. Moreover, the majority of study designs met levels of evidence that were no higher than American Academy for Cerebral Palsy (CP) and Developmental Medicine (AACPDM) level IV. Only one study used a Randomized Control Trial (RCT) approach with the evidence level being II. Conclusion All the selected studies showed improvements in terms of ankle performance or gait function after a period of robot-assisted ankle rehabilitation training. The most effective robot-assisted intervention cannot be determined due to the lack of universal evaluation criteria for various devices and control strategies. Future research into the effects of robot-assisted ankle rehabilitation should be carried out based on universal evaluation criteria, which could determine the most effective method of intervention. It is also essential to conduct trials to analyse the differences among different devices or control strategies

Design and modelling of a compliant ankle rehabilitation robot redundantly driven by pneumatic muscles

Ankle sprains are the most common type of ankle injuries for the general public. Due to the lack of human manual therapy resources, it is highly demanding for robot-assisted rehabilitation training. However, most of the current robotic ankle rehab devices are driven by rigid actuators and have problems such as limited degrees of freedom, lack of safety and compliance and poor flexibility. This paper will design a new version of compliant ankle rehabilitation robot redundantly driven by pneumatic muscles (PMs) to provide full range of motion and torque ability for human ankle with enhanced safety and adaptability, attributing to the PM's high power/mass ratio, good flexibility and light weight advantages. In this paper, the driving characteristics of the PM actuators, as well as the kinematics and rehabilitation requirements of the ankle joint are analyzed. A new type of ankle rehabilitation robot that is redundantly driven by five PMs is designed and modeled. The ankle joint can be compliantly driven by the robot with full three degrees of freedom to perform dorsiflexion/plantarflexion, inversion/ eversion and adduction/abduction training. Then the kinematics and dynamics model of the rehabilitation robot is established to validate and verify the design and the models

Three-Stage Design Analysis and Multicriteria Optimization of a Parallel Ankle Rehabilitation Robot Using Genetic Algorithm

This paper describes the design analysis and optimization of a novel 3-degrees of freedom (DOF) wearable parallel robot developed for ankle rehabilitation treatments. To address the challenges arising from the use of a parallel mechanism, flexible actuators, and the constraints imposed by the ankle rehabilitation treatment, a complete robot design analysis is performed. Three design stages of the robot, namely, kinematic design, actuation design, and structural design are identified and investigated, and, in the process, six important performance objectives are identified which are vital to achieve design goals. Initially, the optimization is performed by considering only a single objective. Further analysis revealed that some of these objectives are conflicting, and hence these are required to be simultaneously optimized. To investigate a further improvement in the optimal values of design objectives, a preference-based approach and evolutionary-algorithm-based nondominated sorting algorithm (NSGA II) are adapted to the present design optimization problem. Results from NSGA II are compared with the results obtained from the single objective optimization and preference-based optimization approaches. It is found that NSGA II is able to provide better design solutions and is adequate to optimize all of the objective functions concurrently. Finally, a fuzzy-based ranking method has been devised and implemented in order to select the final design solution from the set of nondominated solutions obtained through NSGA II. The proposed design analysis of parallel robots together with the multiobjective optimization and subsequent fuzzy-based ranking can be generalized with modest efforts for the development of all of the classes of parallel robots