Development of an exoskeleton robot for upper-limb rehabilitation

To assist or rehabilitate individuals with impaired upper-limb function, we have developed an upper-limb exoskeleton robot, the ETS-MARSE (motion assistive robotic-exoskeleton for superior extremity). The MARSE is comprised of a shoulder motion support part, an elbow and forearm motion support part, and a wrist motion support part. It is designed to be worn on the lateral side of the upper limb in order to provide naturalistic movements of the shoulder (i.e., vertical and horizontal flexion/extension, and internal/external rotation), elbow (i.e., flexion/extension), forearm (i.e., pronation/supination), and wrist joint (i.e., radial/ulnar deviation, and flexion/extension). This thesis focuses on the modeling, design (mechanical and electrical components), development, and control of the developed MARSE. The proposed MARSE was modeled based on the upper-limb biomechanics; it has a relatively low weight, an excellent power/weight ratio, can be easily fitted or removed, and is able to effectively compensate for gravity. Moreover, to avoid complex cable routing that could be found in many exoskeleton systems, a novel power transmission mechanism was introduced for assisting shoulder joint internal/external rotation and for forearm pronation/supination. The exoskeleton was designed for use by typical adults. However, provisions are included for link length adjustments to accommodate a wide range of users. The entire exoskeleton arm was fabricated primarily in aluminum except the high stress joint sections which were fabricated in mild steel to give the exoskeleton structure a relatively light weight. Brushless DC motors (incorporated with Harmonic Drives) were used to actuate the developed MARSE. The kinematic model of the MARSE was developed based on modified Denavit-Hartenberg notations. In dynamic modeling and control, robot parameters such as robot arm link lengths, upper-limb masses, and inertia, are estimated according to the upper limb properties of a typical adult. Though the exoskeleton was developed with the goal of providing different forms of rehab therapy (namely passive arm movements, active-assisted therapy, and resistive therapy), this research concentrated only on passive form of rehabilitation. Passive arm movements and exercises are usually performed slowly compared to the natural speed of arm movement. Therefore, to control the developed MARSE, a computationally inexpensive a PID controller and a PID-based compliance controller were primarily employed. Further, realizing the dynamic modeling of human arm movement which is nonlinear in nature, a nonlinear computed torque control (CTC) and a modified sliding mode exponential reaching law (mSMERL) techniques were employed to control the MARSE. Note that to improve transient tracking performance and to reduce chattering, this thesis proposed the mSMERL, a novel nonlinear control strategy that combined the concept of boundary layer technique and the exponential reaching law. The control architecture was implemented on a field-programmable gate array (FPGA) in conjunction with a RT-PC. In experiments, typical rehabilitation exercises for single and multi joint movements (e.g., reaching) were performed. Experiments were carried out with healthy human subjects where trajectories (i.e., pre-programmed trajectories recommended by therapist/clinician) tracking the form of passive rehabilitation exercises were carried out. This thesis also focused on the development of a 7DoFs upper-limb prototype (lower scaled) ‘master exoskeleton arm’ (mExoArm). Furthermore, experiments were carried out with the mExoArm where subjects (robot users) operate the mExoArm (like a joystick) to maneuver the MARSE to provide passive rehabilitation. Experimental results show that the developed MARSE can effectively perform passive rehabilitation exercises for shoulder, elbow and wrist joint movements. Using mExoArm offers users some flexibility over pre-programmed trajectories selection approach, especially in choosing range of movement and speed of motion. Moreover, the mExoArm could potentially be used to tele-operate the MARSE in providing rehabilitation exercises

New developments in prosthetic arm systems

Absence of an upper limb leads to severe impairments in everyday life, which can further influence the social and mental state. For these reasons, early developments in cosmetic and body-driven prostheses date some centuries ago, and they have been evolving ever since. Following the end of the Second World War, rapid developments in technology resulted in powered myoelectric hand prosthetics. In the years to come, these devices were common on the market, though they still suffered high user abandonment rates. The reasons for rejection were trifold - insufficient functionality of the hardware, fragile design, and cumbersome control. In the last decade, both academia and industry have reached major improvements concerning technical features of upper limb prosthetics and methods for their interfacing and control. Advanced robotic hands are offered by several vendors and research groups, with a variety of active and passive wrist options that can be articulated across several degrees of freedom. Nowadays, elbow joint designs include active solutions with different weight and power options. Control features are getting progressively more sophisticated, offering options for multiple sensor integration and multi-joint articulation. Latest developments in socket designs are capable of facilitating implantable and multiple surface electromyography sensors in both traditional and osseointegration-based systems. Novel surgical techniques in combination with modern, sophisticated hardware are enabling restoration of dexterous upper limb functionality. This article is aimed at reviewing the latest state of the upper limb prosthetic market, offering insights on the accompanying technologies and techniques. We also examine the capabilities and features of some of academia’s flagship solutions and methods

A Passivity-based Nonlinear Admittance Control with Application to Powered Upper-limb Control under Unknown Environmental Interactions

This paper presents an admittance controller based on the passivity theory for a powered upper-limb exoskeleton robot which is governed by the nonlinear equation of motion. Passivity allows us to include a human operator and environmental interaction in the control loop. The robot interacts with the human operator via F/T sensor and interacts with the environment mainly via end-effectors. Although the environmental interaction cannot be detected by any sensors (hence unknown), passivity allows us to have natural interaction. An analysis shows that the behavior of the actual system mimics that of a nominal model as the control gain goes to infinity, which implies that the proposed approach is an admittance controller. However, because the control gain cannot grow infinitely in practice, the performance limitation according to the achievable control gain is also analyzed. The result of this analysis indicates that the performance in the sense of infinite norm increases linearly with the control gain. In the experiments, the proposed properties were verified using 1 degree-of-freedom testbench, and an actual powered upper-limb exoskeleton was used to lift and maneuver the unknown payload.Comment: Accepted in IEEE/ASME Transactions on Mechatronics (T-MECH

Visual, Motor and Attentional Influences on Proprioceptive Contributions to Perception of Hand Path Rectilinearity during Reaching

We examined how proprioceptive contributions to perception of hand path straightness are influenced by visual, motor and attentional sources of performance variability during horizontal planar reaching. Subjects held the handle of a robot that constrained goal-directed movements of the hand to the paths of controlled curvature. Subjects attempted to detect the presence of hand path curvature during both active (subject driven) and passive (robot driven) movements that either required active muscle force production or not. Subjects were less able to discriminate curved from straight paths when actively reaching for a target versus when the robot moved their hand through the same curved paths. This effect was especially evident during robot-driven movements requiring concurrent activation of lengthening but not shortening muscles. Subjects were less likely to report curvature and were more variable in reporting when movements appeared straight in a novel “visual channel” condition previously shown to block adaptive updating of motor commands in response to deviations from a straight-line hand path. Similarly, compromised performance was obtained when subjects simultaneously performed a distracting secondary task (key pressing with the contralateral hand). The effects compounded when these last two treatments were combined. It is concluded that environmental, intrinsic and attentional factors all impact the ability to detect deviations from a rectilinear hand path during goal-directed movement by decreasing proprioceptive contributions to limb state estimation. In contrast, response variability increased only in experimental conditions thought to impose additional attentional demands on the observer. Implications of these results for perception and other sensorimotor behaviors are discussed

Brain computer interface based robotic rehabilitation with online modification of task speed

We present a systematic approach that enables online modification/adaptation of robot assisted rehabilitation exercises by continuously monitoring intention levels of patients utilizing an electroencephalogram (EEG) based Brain-Computer Interface (BCI). In particular, we use Linear Discriminant Analysis (LDA) to classify event-related synchronization (ERS) and desynchronization (ERD) patterns associated with motor imagery; however, instead of providing a binary classification output, we utilize posterior probabilities extracted from LDA classifier as the continuous-valued outputs to control a rehabilitation robot. Passive velocity field control (PVFC) is used as the underlying robot controller to map instantaneous levels of motor imagery during the movement to the speed of contour following tasks. In other words, PVFC changes the speed of contour following tasks with respect to intention levels of motor imagery. PVFC also allows decoupling of the task and the speed of the task from each other, and ensures coupled stability of the overall robot patient system. The proposed framework is implemented on AssistOn-Mobile - a series elastic actuator based on a holonomic mobile platform, and feasibility studies with healthy volunteers have been conducted test effectiveness of the proposed approach. Giving patients online control over the speed of the task, the proposed approach ensures active involvement of patients throughout exercise routines and has the potential to increase the efficacy of robot assisted therapies

Design and Development of an Affordable Haptic Robot with Force-Feedback and Compliant Actuation to Improve Therapy for Patients with Severe Hemiparesis

The study describes the design and development of a single degree-of-freedom haptic robot, Haptic Theradrive, for post-stroke arm rehabilitation for in-home and clinical use. The robot overcomes many of the weaknesses of its predecessor, the TheraDrive system, that used a Logitech steering wheel as the haptic interface for rehabilitation. Although the original TheraDrive system showed success in a pilot study, its wheel was not able to withstand the rigors of use. A new haptic robot was developed that functions as a drop-in replacement for the Logitech wheel. The new robot can apply larger forces in interacting with the patient, thereby extending the functionality of the system to accommodate low-functioning patients. A new software suite offers appreciably more options for tailored and tuned rehabilitation therapies. In addition to describing the design of the hardware and software, the paper presents the results of simulation and experimental case studies examining the system\u27s performance and usability