IEEE ... International Conference on Rehabilitation Robotics : [proceedings]最新文献

Motivation is crucial in stroke rehabilitation, as it enhances patient engagement, adherence, and recovery. Robots can be employed to improve motivation through multiplayer rehabilitation games, which allow patients to collaborate and interact in a virtual environment through multimodal sensory cues. This social interaction can provide social support and increase motivation, resulting in better therapy engagement. A hand rehabilitation robot (PLUTO) was used to investigate the potential of social interaction to implement haptic multiplayer games. Twelve unimpaired participants (6 dyads) played in solo, collaborative, and competitive game modes. Surprisingly, no difference was found in self-reported engagement, tension, or competence between solo and multiplayer games. However, the IMI scale indicated that engagement for multiplayer games was rated higher than for solo games. The collaborative game was preferred by 10 out of 12 participants, highlighting its potential for promoting behavioural involvement and engagement. This study indicates that using PLUTO with multiplayer game modes can enhance therapy engagement. This can potentially improve rehabilitation outcomes if translated to the patient population.

In the recent past, the development of lower-limb prostheses has taken a new turn with the emergence of active systems. However, their intrinsic wearable nature induces strict requirements regarding weight and encumbrance. In order to reduce the load - and thus the bulkiness - of their active part, several prototypes leverage the concept of compliant actuation, consisting in including an elastic element in parallel and/or in series with the actuator. In this paper, we explore the usability of polymer compliant ropes placed in parallel with the actuator of an ankle prosthesis. Ropes are intrinsically light and compact, and thus offer several advantages as compared to more traditional coil or leaf springs. Polymer materials were selected for their high energy density and yield strength. We conducted a set of experimental tests with several ropes, pretension levels, and periodic loading profiles. Results show that polymer-based ropes have a high potential for ankle assistance devices, since they can store the required energy in a low volume. However, further research should be conducted to improve their efficiency, since we estimated that only about 50% of the stored energy can be released, with few variations as a function of the rope preconditioning and loading profile.

Latest advances in wearable exoskeletons for the human lower extremity predominantly focus on minimising metabolic cost of walking. However, there currently is no robotic exoskeleton that gains control on the mechanics of biological tissues such as biological muscles or series-elastic tendons. Achieving robotic control of biological tissue mechanics would enable prevention of musculoskeletal injuries or the personalization of rehabilitation treatments following injury with levels of precisions not attained before. In this paper, we introduce a new framework that uses nonlinear model predictive control (NMPC) for the closed-loop control of peak tendon force in a simulated system of the human ankle joint with parallel exoskeletal actuation. We propose a computationally efficient NMPC's inner model consisting of explicit, closed-form equations of muscle-tendon dynamics along with those of the ankle joint with parallel actuation. The proposed formulation is tested and verified on movement data collected during dynamic ankle dorsiflexion/plantarflexion rotations executed on a dynamometer as well as during walking and running on a treadmill. The framework designed using the NMPC controller showed a promising performance in keeping the Achilles tendon force under a predefined threshold. Results indicated that our proposed model was generalizable to different muscles and gaits and suitable for real-time applications due to its low computational time.

This work describes the design and preliminary characterization of a novel portable hand exoskeleton for poststroke rehabilitation. The platform actively mobilizes the index-metacarpophalangeal (I-MCP) joint, and it additionally offers individual rigid support to distal degrees of freedom (DoFs) of the index and thumb. The test-bench characterization proves the capability of the device to render torques at the I-MCP level with high fidelity within frequencies of interest for the application (up to 3 Hz). The introduction of a feed-forward friction compensation at the actuator level lowers the output mechanical stiffness by 32%, contributing to a highly transparent behavior; moreover, the functionality of the platform in rendering different interaction strategies (patient/robot-in-charge) is tested with three healthy subjects, showing the potential of the device to provide assistance as needed.

Advancements in wearable robots aim to improve the users' motion, performance, and comfort by optimizing, mainly, energetic cost (EC). However, EC is a noisy measurement with a physiological delayed response that requires long evaluation periods and wearing an uncomfortable mask. This study aims to estimate and minimize an EMG-based objective function that describes the natural energetic expenditure of individuals walking. This objective is assessed by combining multiple electromyography (EMG) variables from the EMG intensity and muscle synergies. To evaluate this objective function simply and repeatedly, we prescribed step frequency (SF) via a metronome and optimized this frequency to minimize muscle activity demands. Further, a linear mixed-effects model was fitted for EC, with the EMG variables as fixed-effects and a random intercept that varies by participant. After the model was fitted to the data, a cubic polynomial was used to identify the optimal SF that reduces the overall EMG-based objective function. Our analysis outlines that the proposed objective function is comparable to the EC during walking, the primary objective function used in human-in-the-loop optimization. Thus, this EMG-based objective function could be potentially used to optimize wearable robots and improve human-robot interaction.

The sense of proprioception plays a critical role in motor function by providing a sense of body position and movement. Recent research has highlighted the impact of impaired proprioception on rehabilitation outcomes for stroke patients. To address this issue, various studies have explored the use of vibrotactile feedback to aid and enhance impaired proprioception. Since most studies focused on investigating the characteristics of human proprioceptive position or movement sense, the fixed and cumbersome equipment used for those studies is inappropriate for daily use where compact and portable device is preferred. To address this limitation, we propose a novel vibrotactile feedback method that provides joint-level state information using the cyclic vibrotactile funneling illusion. The proposed method was validated in first experiment with eleven healthy subjects, and the accuracy of proposed method in bi-directional scheme was evaluated through second experiments with three healthy subjects. Our methods demonstrated sufficient ability to transmit proprioceptive position information, making them potentially applicable to various wearable rehabilitation devices, thereby enabling more effective rehabilitation for patients with proprioceptive impairment.

One of the most frequent and severe aftermaths of a stroke is the loss of upper limb functionality. Therapy started in the sub-acute phase proved more effective, mainly when the patient participates actively. Recently, a novel set of rehabilitation and support robotic devices, known as supernumerary robotic limbs, have been introduced. This work investigates how a surface electromyography (sEMG) based control strategy would improve their usability in rehabilitation, limited so far by input interfaces requiring to subjects some level of residual mobility. After briefly introducing the phenomena hindering post-stroke sEMG and its use to control robotic hands, we describe a framework to acquire and interpret muscle signals of the forearm extensors. We applied it to drive a supernumerary robotic limb, the SoftHand-X, to provide Task-Specific Training (TST) in patients with sub-acute stroke. We propose and describe two algorithms to control the opening and closing of the robotic hand, with different levels of user agency and therapist control. We experimentally tested the feasibility of the proposed approach on four patients, followed by a therapist, to check their ability to operate the hand. The promising preliminary results indicate sEMG-based control as a viable solution to extend TST to sub-acute post-stroke patients.

Wearable robots show promise in addressing physical and functional deficits in individuals with mobility impairments. However, the process of learning to use these devices can take a long time. In this study, we propose a novel protocol to support the familiarization process with a wearable robot (the Myosuit) and achieve faster walking speeds. The protocol involves applying an anterior pulling force while participants perform a series of 10-meter Walking Tests (10mWT) with or without the Myosuit under various experimental conditions. We hypothesized that guiding the exploration of novel walking patterns can help the users learn to exploit the Myosuit's assistance faster by leading to larger step lengths and ultimately higher walking speeds. In this paper, we present the preliminary results of the protocol with seven participants with lower-limb mobility impairments. Participants who were assisted by the Myosuit showed a continuous increase in walking speed over the course of the pulling part of the experiment with a maximum increase of 41.3% (10.4%) when compared to the baseline 10mWT. Following the removal of the pulling force, these participants continued to show an increased walking speed while being supported by the Myosuit. This higher walking speed was primarily due to a significant increase in step length of 24% (16.6%) and cadence of 11% (8.9%). The results of this study may help the development of familiarization techniques for wearable robots.

In this study, we propose a shoe-type walking assist device that can control the inversion/eversion angle of the subtalar joint during heel contact, with the aim of improving the long-term quality of life of both elderly people and young healthy people. The proposed device enables the heel mechanism to rotate dynamically in the frontal plane to lead the subtalar joint alignment to the neutral position when the heel contacts the ground. The effectiveness of the proposed mechanism was demonstrated by comparing the amount of lateral thrust (lateral sway) during stepping movements with and without the mechanism assist in 5 healthy male subjects wearing the device.

This study implemented an electromyogram (EMG)-informed neuromusculoskeletal (NMS) model evaluating the volitional contributions to muscle forces and joint moments during functional electrical stimulation (FES). The NMS model was calibrated using motion and EMG (biceps brachii and triceps brachii) data recorded from able-bodied participants (n=3) performing weighted elbow flexion and extension cycling movements while equipped with an EMG-controlled closed-loop FES system. Models were executed using three computational approaches (i) EMG-driven, (ii) EMG-hybrid and (iii) EMG-assisted to estimate muscle forces and joint moments. Both EMG-hybrid and EMG-assisted modes were able estimate the elbow moment (root mean squared error and coefficient of determination), but the EMG-hybrid method also enabled quantifying the volitional contributions to muscle forces and elbow moments during FES. The proposed modelling method allows for assessing volitional contributions of patients to muscle force during FES rehabilitation, and could be used as biomarkers of recovery, biofeedback, and for real-time control of combined FES and robotic systems.