Active exoskeleton control systems: State of the art

To get a compliant active exoskeleton controller, the force interaction controllers are mostly used in form of either the impedance or admittance controllers. The impedance or admittance controllers can only work if they are followed by either the force or the position controller respectively. These combinations place the impedance or admittance controller as high-level controller while the force or position controller as low-level controller. From the application point of view, the exoskeleton controllers are equipped by task controllers that can be formed in several ways depend on the aims. This paper presents the review of the control systems in the existing active exoskeleton in the last decade. The exoskeleton control system can be categorized according to the model system, the physical parameters, the hierarchy and the usage. These considerations give different control schemes. The main consideration of exoskeleton control design is how to achieve the best control performances. However, stability and safety are other important issues that have to be considered. © 2012 The Authors

Study on control of a robotic orthosis actuated by pneumatic artificial muscle for gait rehabilitation

芝浦工業大学2019年

Human Activity Recognition and Control of Wearable Robots

abstract: Wearable robotics has gained huge popularity in recent years due to its wide applications in rehabilitation, military, and industrial fields. The weakness of the skeletal muscles in the aging population and neurological injuries such as stroke and spinal cord injuries seriously limit the abilities of these individuals to perform daily activities. Therefore, there is an increasing attention in the development of wearable robots to assist the elderly and patients with disabilities for motion assistance and rehabilitation. In military and industrial sectors, wearable robots can increase the productivity of workers and soldiers. It is important for the wearable robots to maintain smooth interaction with the user while evolving in complex environments with minimum effort from the user. Therefore, the recognition of the user's activities such as walking or jogging in real time becomes essential to provide appropriate assistance based on the activity. This dissertation proposes two real-time human activity recognition algorithms intelligent fuzzy inference (IFI) algorithm and Amplitude omega ($A \omega$) algorithm to identify the human activities, i.e., stationary and locomotion activities. The IFI algorithm uses knee angle and ground contact forces (GCFs) measurements from four inertial measurement units (IMUs) and a pair of smart shoes. Whereas, the $A \omega$ algorithm is based on thigh angle measurements from a single IMU. This dissertation also attempts to address the problem of online tuning of virtual impedance for an assistive robot based on real-time gait and activity measurement data to personalize the assistance for different users. An automatic impedance tuning (AIT) approach is presented for a knee assistive device (KAD) in which the IFI algorithm is used for real-time activity measurements. This dissertation also proposes an adaptive oscillator method known as amplitude omega adaptive oscillator ($A\omega AO$) method for HeSA (hip exoskeleton for superior augmentation) to provide bilateral hip assistance during human locomotion activities. The $A \omega$ algorithm is integrated into the adaptive oscillator method to make the approach robust for different locomotion activities. Experiments are performed on healthy subjects to validate the efficacy of the human activities recognition algorithms and control strategies proposed in this dissertation. Both the activity recognition algorithms exhibited higher classification accuracy with less update time. The results of AIT demonstrated that the KAD assistive torque was smoother and EMG signal of Vastus Medialis is reduced, compared to constant impedance and finite state machine approaches. The $A\omega AO$ method showed real-time learning of the locomotion activities signals for three healthy subjects while wearing HeSA. To understand the influence of the assistive devices on the inherent dynamic gait stability of the human, stability analysis is performed. For this, the stability metrics derived from dynamical systems theory are used to evaluate unilateral knee assistance applied to the healthy participants.Dissertation/ThesisDoctoral Dissertation Aerospace Engineering 201

State of the Art Lower Limb Robotic Exoskeletons for Elderly Assistance

https://ieeexplore.ieee.org/document/8759880/keywords#keywordsThe number of elderly populations is rapidly increasing. Majority of elderly people face difficulties while walking because the muscular activity or other gait-related parameters start to deteriorate with aging. Therefore, the quality of life among them can be suffered. To make their life more comfortable, service providing robotic solutions in terms of wearable powered exoskeletons should be realized. Assistive powered exoskeletons are capable of providing additional torque to support various activities, such as walking, sit to stand, and stand to sit motions to subjects with mobility impairments. Specifically, the powered exoskeletons try to maintain and keep subjects' limbs on the specified motion trajectory. The state of the art of currently available lower limb assistive exoskeletons for weak and elderly people is presented in this paper. The technology employed in the assistive devices, such as actuation and power supply types, control strategies, their functional abilities, and the mechanism design, is thoroughly described. The outcome of studied literature reveals that there is still much work to be done in the improvement of assistive exoskeletons in terms of their technological aspects, such as choosing proper and effective control methods, developing user friendly interfaces, and decreasing the costs of device to make it more affordable, meanwhile ensuring safe interaction for the end-users

Active interaction control applied to a lower limb rehabilitation robot by using EMG recognition and impedance model

Purpose – The purpose of this paper is to propose a seamless active interaction control method integrating electromyography (EMG)-triggered assistance and the adaptive impedance control scheme for parallel robot-assisted lower limb rehabilitation and training. Design/methodology/approach – An active interaction control strategy based on EMG motion recognition and adaptive impedance model is implemented on a six-degrees of freedom parallel robot for lower limb rehabilitation. The autoregressive coefficients of EMG signals integrating with a support vector machine classifier are utilized to predict the movement intention and trigger the robot assistance. An adaptive impedance controller is adopted to influence the robot velocity during the exercise, and in the meantime, the user’s muscle activity level is evaluated online and the robot impedance is adapted in accordance with the recovery conditions. Findings – Experiments on healthy subjects demonstrated that the proposed method was able to drive the robot according to the user’s intention, and the robot impedance can be updated with the muscle conditions. Within the movement sessions, there was a distinct increase in the muscle activity levels for all subjects with the active mode in comparison to the EMG-triggered mode. Originality/value – Both users’ movement intention and voluntary participation are considered, not only triggering the robot when people attempt to move but also changing the robot movement in accordance with user’s efforts. The impedance model here responds directly to velocity changes, and thus allows the exercise along a physiological trajectory. Moreover, the muscle activity level depends on both the normalized EMG signals and the weight coefficients of involved muscles

Powered knee orthosis for human gait rehabilitation: first advances

This paper presents a new system for a powered knee orthosis, that was designed to assist and improve the gait function of patients with gait pathologies. The system contains the orthotic device (embedded with sensors for angle and user-orthosis interaction torque measurements, and an electric actuator) and wearable sensors (inertial measurement unit, force sensitive resistors, and electromyography sensors), which allows the generation of smart rehabilitation tools and several motion assistive techniques. The main goal is to present a conceptual overview and functional description of the system and use scenarios of each component. The attachment mechanism of the orthosis to the limb is also highlighted, being composed of a straps system fixed in the mechanical links of the joint. It was noticed that users with distinct lower-limb morphologies can presents difficulties wearing the orthosis, since the device needs constant adjust to align the mechanical and human joints. The system was validated in ground-level walking on healthy subjects, with emphasis on the impact of the device in the user. The subjects reported that the orthosis is comfortable to use, easy to wear, and no issues were raised regarding the aesthetics of the device. Only the weight was assimilated as a possible hindrance (compensated in the future). Future challenges involve the inclusion of an ankle joint in the system and the use of the proposed tool in rehabilitation.This work is supported by the FCT - Fundacao para a Ciencia e Tecnologia - with the reference scholarship SFRH/BD/108309/2015, with the reference project UID/EEA/04436/2013, and by FEDER funds through the COMPETE 2020 - Programa Operacional Competitividade e Internacionalizacao (POCI) - with the reference project POCI-01-0145-FEDER-006941, and partially supported with grant RYC-2014-16613 by Spanish Ministry of Economy and Competitiveness

An EMG-based force prediction and control approach for robot-assisted lower limb rehabilitation

This paper proposes an electromyography (EMG)-based method for online force prediction and control of a lower limb rehabilitation robot. Root mean square (RMS) features of EMG signals from four muscles of the lower limb are used as the inputs to a support vector regression (SVR) model to estimate the human-robot interaction force. The autoregressive algorithm is utilized to construct the relationship between EMG signals and the impact force. Combining the force prediction model with the position-based impedance controller, the robot can be controlled to track the desired force of the lower limb, and so as to achieve an adaptive and active rehabilitation mode, which is adaptable to the individual muscle strength and movement ability. Finally, the method was validated through experiments on a healthy subject. The results show that the EMG-based SVR model can predict the lower limb force accurately and the robot can be controlled to track the estimated force by using simplified impedance model

An EMG-based force prediction and control approach for robot-assisted lower limb rehabilitation

This paper proposes an electromyography (EMG)-based method for online force prediction and control of a lower limb rehabilitation robot. Root mean square (RMS) features of EMG signals from four muscles of the lower limb are used as the inputs to a support vector regression (SVR) model to estimate the human-robot interaction force. The autoregressive algorithm is utilized to construct the relationship between EMG signals and the impact force. Combining the force prediction model with the position-based impedance controller, the robot can be controlled to track the desired force of the lower limb, and so as to achieve an adaptive and active rehabilitation mode, which is adaptable to the individual muscle strength and movement ability. Finally, the method was validated through experiments on a healthy subject. The results show that the EMG-based SVR model can predict the lower limb force accurately and the robot can be controlled to track the estimated force by using simplified impedance model

Gait Training using Pneumatically Actuated Robot System

Powered exoskeleton device for gait rehabilitation has been designed and realized, together with proper control architecture. Its DOFs allow free leg motion, while the patient walks on a treadmill with its weight, completely or partially supported by the suspension system. The use of pneumatic actuators for actuation of this rehabilitation system is reasonable, because they offer high force output, good backdrivability, and good position and force control, at a relatively low cost. The effectiveness of the developed rehabilitation system and proposed control architecture was experimentally tested. During the experiments, the movement was natural and smooth while the limb moves along the target trajectory