Olivier Lambercy

Control strategies for active lower extremity prosthetics and orthotics: a review

Technological advancements have led to the development of numerous wearable robotic devices for the physical assistance and restoration of human locomotion. While many challenges remain with respect to the mechanical design of such devices, it is at least equally challenging and important to develop strategies to control them in concert with the intentions of the user.This work reviews the state-of-the-art techniques for controlling portable active lower limb prosthetic and orthotic (P/O) devices in the context of locomotive activities of daily living (ADL), and considers how these can be interfaced with the user’s sensory-motor control system. This review underscores the practical challenges and opportunities associated with P/O control, which can be used to accelerate future developments in this field. Furthermore, this work provides a classification scheme for the comparison of the various control strategies.As a novel contribution, a general framework for the control of portable gait-assistance devices is proposed. This framework accounts for the physical and informatic interactions between the controller, the user, the environment, and the mechanical device itself. Such a treatment of P/Os – not as independent devices, but as actors within an ecosystem – is suggested to be necessary to structure the next generation of intelligent and multifunctional controllers.Each element of the proposed framework is discussed with respect to the role that it plays in the assistance of locomotion, along with how its states can be sensed as inputs to the controller. The reviewed controllers are shown to fit within different levels of a hierarchical scheme, which loosely resembles the structure and functionality of the nominal human central nervous system (CNS). Active and passive safety mechanisms are considered to be central aspects underlying all of P/O design and control, and are shown to be critical for regulatory approval of such devices for real-world use.The works discussed herein provide evidence that, while we are getting ever closer, significant challenges still exist for the development of controllers for portable powered P/O devices that can seamlessly integrate with the user’s neuromusculoskeletal system and are practical for use in locomotive ADL.

HandCARE : A Cable-Actuated Rehabilitation System to Train Hand Function After Stroke

We have developed a robotic interface to train hand and finger function. HandCARE is a Cable-actuated rehabilitation system, in which each finger is attached to an instrumented cable loop allowing force control and a predominantly linear displacement. The device, whose designed is based on biomechanical measurements, can assist the subject in opening and closing movements and can be adapted to accommodate various hand shapes and finger sizes. Main features of the interface include a differential sensing system, and a clutch system which allows independent movement of the five fingers with only one actuator. The device is safe, easily transportable, and offers multiple training possibilities. This paper presents the biomechanical measurements carried out to determine the requirements for a finger rehabilitation device, and the design and characterization of the complete system.

A Haptic Knob for Rehabilitation of Hand Function

This paper describes a novel two-degree-of-freedom robotic interface to train opening/closing of the hand and knob manipulation. The mechanical design, based on two parallelogram structures holding an exchangeable button, offers the possibility to adapt the interface to various hand sizes and finger orientations, as well as to right-handed or left-handed subjects. The interaction with the subject is measured by means of position encoders and four force sensors located close to the output measuring grasping and insertion forces. Various knobs can be mounted on the interface, including a cone mechanism to train a complete opening movement from a strongly contracted and closed hand to a large opened position. We describe the design based on measured biomechanics, the redundant safety mechanisms as well as the actuation and control architecture. Preliminary experiments show the performance of this interface and some of the possibilities it offers for the rehabilitation of hand function.

Effects of a robot-assisted training of grasp and pronation/supination in chronic stroke: a pilot study

BackgroundRehabilitation of hand function is challenging, and only few studies have investigated robot-assisted rehabilitation focusing on distal joints of the upper limb. This paper investigates the feasibility of using the HapticKnob, a table-top end-effector device, for robot-assisted rehabilitation of grasping and forearm pronation/supination, two important functions for activities of daily living involving the hand, and which are often impaired in chronic stroke patients. It evaluates the effectiveness of this device for improving hand function and the transfer of improvement to arm function.MethodsA single group of fifteen chronic stroke patients with impaired arm and hand functions (Fugl-Meyer motor assessment scale (FM) 10-45/66) participated in a 6-week 3-hours/week rehabilitation program with the HapticKnob. Outcome measures consisted primarily of the FM and Motricity Index (MI) and their respective subsections related to distal and proximal arm function, and were assessed at the beginning, end of treatment and in a 6-weeks follow-up.ResultsThirteen subjects successfully completed robot-assisted therapy, with significantly improved hand and arm motor functions, demonstrated by an average 3.00 points increase on the FM and 4.55 on the MI at the completion of the therapy (4.85 FM and 6.84 MI six weeks post-therapy). Improvements were observed both in distal and proximal components of the clinical scales at the completion of the study (2.00 FM wrist/hand, 2.55 FM shoulder/elbow, 2.23 MI hand and 4.23 MI shoulder/elbow). In addition, improvements in hand function were observed, as measured by the Motor Assessment Scale, grip force, and a decrease in arm muscle spasticity. These results were confirmed by motion data collected by the robot.ConclusionsThe results of this study show the feasibility of this robot-assisted therapy with patients presenting a large range of impairment levels. A significant homogeneous improvement in both hand and arm function was observed, which was maintained 6 weeks after end of the therapy.

Detection of motor execution using a hybrid fNIRS-biosignal BCI: a feasibility study.

BackgroundBrain-computer interfaces (BCIs) were recently recognized as a method to promote neuroplastic effects in motor rehabilitation. The core of a BCI is a decoding stage by which signals from the brain are classified into different brain-states. The goal of this paper was to test the feasibility of a single trial classifier to detect motor execution based on signals from cortical motor regions, measured by functional near-infrared spectroscopy (fNIRS), and the response of the autonomic nervous system. An approach that allowed for individually tuned classifier topologies was opted for. This promises to be a first step towards a novel form of active movement therapy that could be operated and controlled by paretic patients.MethodsSeven healthy subjects performed repetitions of an isometric finger pinching task, while changes in oxy- and deoxyhemoglobin concentrations were measured in the contralateral primary motor cortex and ventral premotor cortex using fNIRS. Simultaneously, heart rate, breathing rate, blood pressure and skin conductance response were measured. Hidden Markov models (HMM) were used to classify between active isometric pinching phases and rest. The classification performance (accuracy, sensitivity and specificity) was assessed for two types of input data: (i) fNIRS-signals only and (ii) fNIRS- and biosignals combined.ResultsfNIRS data were classified with an average accuracy of 79.4%, which increased significantly to 88.5% when biosignals were also included (p=0.02). Comparable increases were observed for the sensitivity (from 78.3% to 87.2%, p=0.008) and specificity (from 80.5% to 89.9%, p=0.062).ConclusionsThis study showed, for the first time, promising classification results with hemodynamic fNIRS data obtained from motor regions and simultaneously acquired biosignals. Combining fNIRS data with biosignals has a beneficial effect, opening new avenues for the development of brain-body-computer interfaces for rehabilitation applications. Further research is required to identify the contribution of each modality to the decoding capability of the subject’s hemodynamic and physiological state.

A new hand exoskeleton device for rehabilitation using a three-layered sliding spring mechanism

In this paper, a new hand exoskeleton device using a three-layered sliding spring mechanism is presented. In contrast to state of the art hand exoskeleton mechanisms (typically link, wire or pneumatically driven), the proposed mechanism is driven through large deformations of the compliant mechanism body. The mechanism can be made compact and lightweight by adequately positioning the compliant elements. In addition, the mechanism is designed to distribute 1-DOF actuated linear motion into three rotational motions of the finger joints, which translate into natural finger flexion/extension. The primary application of the proposed mechanism is to provide robotic support during physical therapy at the hospital (e.g. Continuous Passive Motion). However, thanks to its light and wearable structure, the proposed device could also be used at home as an assistive/therapeutic device to support activities of daily living. We introduce the mechanical structure of the three-layered sliding spring mechanism, present a prototype implementation as a hand exoskeleton device, and provide a preliminary evaluation.

A Haptic Knob for Rehabilitation of Stroke Patients

The strong impairment of motor functions in stroke survivors affects daily activities such as eating, manipulating objects or writing. Our goal is to induce long lasting improvements in such tasks by having patients perform systematic exercises using haptic interfaces. This paper describes a novel two-degrees-of-freedom interface which we have developed to help stroke patients gradually recover the ability to open and close the hand and manipulate knobs. Different solutions are studied and a design consisting of two parallelogram structures interacting with the fingers is proposed. The mechanical design offers the possibility to adapt the interface to various hand sizes and finger orientations, and to right or left-handed subjects. Design kinematics as well as actuation and system control are described. Several knobs are proposed to interact with patients, especially a cone mechanism to train a complete opening movement from a strongly contracted and closed hand to a large opened position. The interaction force with the subject is measured over four force sensors located close to the output of the interface. A preliminary study has been performed to evaluate the performances of the haptic interface

Rehabilitation of grasping and forearm pronation/supination with the Haptic Knob

This paper investigates robot-assisted rehabilitation after stroke using the Haptic Knob, a 2 degree-of-freedom end-effector based robotic device to train grasping and wrist pronation/supination. Nine chronic stroke subjects trained over a period of 6 weeks, with 3 one-hour sessions of robot-assisted therapy per week, consisting of two exercises requiring active participation promoted by therapeutic games. Results of standard clinical assessments demonstrate the positive effects of robot-assisted therapy with the Haptic Knob. Subjects improved by a mean of 4.3 points in the Fugl-Meyer assessment scale, together with a decrease in hand impairments such as abnormal muscle tone frequently observed in stroke subjects. Significant improvements were also observed in motor function of the upper arm as a result of the robot-assisted therapy, suggesting homogeneous improvement of upper limb function as a result of distal training.

Development of a Robot-Assisted Rehabilitation Therapy to train Hand Function for Activities of Daily Living

This paper presents the evaluation of a new two degree-of-freedom robotic interface, and the development of exercises to train movements and force control of wrist and hand. The Haptic Knob has two actuated parallelogram structures with a knob at the output, to interact with the fingers in a way to simulate grasping/releasing, in combination with pronation/supination movements of the forearm. Motivating game-like exercises have been designed according to a functional approach, where fundamental hand function required in activities of daily living (ADL) can be trained, while the device provides assistive or resistive forces. Preliminary testing has been performed with healthy subjects and three chronic stroke patients. Subjects found the exercises to be comfortable, and the robotic interface offers adequate range of motion and forces. A study with a group of chronic stroke patients will be conducted during the next months to determine the potential benefit of a therapy using our robotic equipment.

A Cable Driven Robotic System to Train Finger Function After Stroke

This paper presents a novel robotic interface to train intrinsic finger movements. The mechanical design, base on a cable system interacting with the fingers, offers the possibility of adapting the interface to accommodate various hand sizes and finger orientation. A main feature of the device is a clutch system, which consists of five clutches, one for each finger, that can be switched to three different modes: ( rest mode: the fingers are mechanically maintained at a fixed position, (ii) passive (from the view of the interface) mode: the finger is free to move along the path defined by the cable, and (iii) active mode: the force generated by the motor is applied to the finger.) With this mechanism, it is possible to train hand muscle function using only one actuator. The interaction wit the subject is measured by means of a position encoder an five force sensors located close to the output. We describe the human-oriented design of our underactuated robotic interface based on measured biomechanics. We detail the redundant safety mechanisms, the actuation, sensing and control system and report the performance and preliminary results obtained with this interface.