Neurorehabilitation From a Distance: Can Intelligent Technology Support Decentralized Access to Quality Therapy?

Current neurorehabilitation models primarily rely on extended hospital stays and regular therapy sessions requiring close physical interactions between rehabilitation professionals and patients. The current COVID-19 pandemic has challenged this model, as strict physical distancing rules and a shift in the allocation of hospital resources resulted in many neurological patients not receiving essential therapy. Accordingly, a recent survey revealed that the majority of European healthcare professionals involved in stroke care are concerned that this lack of care will have a noticeable negative impact on functional outcomes. COVID-19 highlights an urgent need to rethink conventional neurorehabilitation and develop alternative approaches to provide high-quality therapy while minimizing hospital stays and visits. Technology-based solutions, such as, robotics bear high potential to enable such a paradigm shift. While robot-assisted therapy is already established in clinics, the future challenge is to enable physically assisted therapy and assessments in a minimally supervized and decentralized manner, ideally at the patient’s home. Key enablers are new rehabilitation devices that are portable, scalable and equipped with clinical intelligence, remote monitoring and coaching capabilities. In this perspective article, we discuss clinical and technological requirements for the development and deployment of minimally supervized, robot-assisted neurorehabilitation technologies in patient’s homes. We elaborate on key principles to ensure feasibility and acceptance, and on how artificial intelligence can be leveraged for embedding clinical knowledge for safe use and personalized therapy adaptation. Such new models are likely to impact neurorehabilitation beyond COVID-19, by providing broad access to sustained, high-quality and high-dose therapy maximizing long-term functional outcomes.

Phase-Synchronized Assistive Torque Control for the Correction of Kinematic Anomalies in the Gait Cycle

Gait anomalies give rise to several clinical problems in stroke survivors, which restrict their functional mobility and have a negative impact on their quality of life. Robotics-aided gait training post-stroke has proven capable of improving patients' functional walking, but so far it has not performed significantly better than conventional therapy. We hypothesize that an exoskeleton-based training program, aimed at correcting deficits in the leg joints' movement, could produce greater improvements in gait function than conventional therapy. As a first step towards testing this hypothesis, we designed an exoskeleton control to correct a typical kinematic deficit post-stroke, namely, reduced knee flexion on the paretic side during swing. The proposed control attempts to minimize this deficit by delivering assistive torque synchronized with the continuous phase of the patient's gait. Nine healthy male participants walked in a unilateral cable-driven exoskeleton while subject to an artificial knee flexion impairment produced by a custom-made knee brace. The experiments employed a treadmill featuring a variable-velocity control to allow self-selected gait speed. The artificial impairment by itself caused a significant reduction in peak flexion angle (p = 0.000129). Exoskeleton assistance compensated most of the knee flexion deficit, yielding no significant difference with unrestricted flexion (p = 0.3393). No significant changes in self-selected gait speed or stride frequency were detected. The proposed control can be expanded to correct motion deficits in other joints at different stages of the gait cycle.

High mobility control of an omnidirectional platform for gait rehabilitation after stroke

We present a novel control method for an omnidirectional robotic platform for gait training. This mobile platform or "walker" provides trunk support and allows unrestricted motion of the pelvis simultaneously. In addition to helping the user maintain balance and preventing falls, the walker combines two types of therapeutic intervention: forward propulsion of the trunk and partial body weight support (BWS). The core of the walker's control is an admittance controller that maximizes the platform's horizontal mobility by optimizing the virtual mass of the admittance model. Said mass represents the best tradeoff between a low-frequency oscillation mode that becomes more damped as the virtual mass decreases, and a high-frequency mode that becomes less damped simultaneously and hence could destabilize the system. Forward propulsion of the trunk is aided by a horizontal force that is modulated with the patient's gait speed and turning rate to ensure easy adaptation. BWS is provided by a second, independent admittance controller that generates a spring-like upward force. In an initial study, a stroke patient was able to walk stably in the platform, as evidenced by the absence of oscillations associated with an excessively low virtual mass. A progressive increase in the patient's self-selected speed, along with greater uniformity in the instantaneous velocity, suggest that forward propulsion was effective in compensating the patient's own propulsion deficit.

Exoskeleton control for lower-extremity assistance based on adaptive frequency oscillators: Adaptation of muscle activation and movement frequency

In this article, we analyze a novel strategy for assisting the lower extremities based on adaptive frequency oscillators. Our aim is to use the control algorithm presented here as a building block for the control of powered lower-limb exoskeletons. The algorithm assists cyclic movements of the human extremities by synchronizing actuator torques with the estimated net torque exerted by the muscles. Synchronization is produced by a nonlinear dynamical system combining an adaptive frequency oscillator with a form of adaptive Fourier analysis. The system extracts, in real time, the fundamental frequency component of the net muscle torque acting on a specific joint. Said component, nearly sinusoidal in shape, is the basis for the assistive torque waveform delivered by the exoskeleton. The action of the exoskeleton can be interpreted as a virtual reduction in the mechanical impedance of the leg. We studied the ability of human subjects to adapt their muscle activation to the assistive torque. Ten subjects swung their extended leg while coupled to a stationary hip joint exoskeleton. The experiment yielded a significant decrease, with respect to unassisted movement, of the activation levels of an agonist/antagonist pair of muscles controlling the hip joint’s motion, which suggests the exoskeleton control has potential for assisting human gait. A moderate increase in swing frequency was observed as well. We theorize that the increase in frequency can be explained by the impedance model of the assisted leg. Per this model, subjects adjust their swing frequency in order to control the amount of reduction in net muscle torque.

A one-degree-of-freedom assistive exoskeleton with inertia compensation: the effects on the agility of leg swing motion

Many of the current implementations of exoskeletons for the lower extremities are conceived to either augment the user's load-carrying capabilities or reduce muscle activation during walking. Comparatively little research has been conducted on enabling an exoskeleton to increase the agility of lower-limb movements. One obstacle in this regard is the inertia of the exoskeleton's mechanism, which tends to reduce the natural frequency of the human limbs. A control method is presented that produces an approximate compensation of the inertia of an exoskeleton's mechanism. The controller was tested on a statically mounted, single-degree-of-freedom (DOF) exoskeleton that assists knee flexion and extension. Test subjects performed multiple series of leg-swing movements in the context of a computer-based, sprint-like task. A large initial acceleration of the leg was needed for the subjects to track a virtual target on a computer screen. The uncompensated inertia of the exoskeleton mechanism slowed down the transient response of the subjects' limb, in comparison with trials performed without the exoskeleton. The subsequent use of emulated inertia compensation on the exoskeleton allowed the subjects to improve their transient response for the same task.

Design of an active one-degree-of-freedom lower-limb exoskeleton with inertia compensation

Limited research has been done on exoskeletons to enable faster movements of the lower extremities. An exoskeleton’s mechanism can actually hinder agility by adding weight, inertia and friction to the legs; compensating inertia through control is particularly difficult due to instability issues. The added inertia will reduce the natural frequency of the legs, probably leading to lower step frequency during walking. We present a control method that produces an approximate compensation of an exoskeleton’s inertia. The aim is making the natural frequency of the exoskeleton-assisted leg larger than that of the unaided leg. The method uses admittance control to compensate for the weight and friction of the exoskeleton. Inertia compensation is emulated by adding a feedback loop consisting of low-pass filtered acceleration multiplied by a negative gain. This gain simulates negative inertia in the low-frequency range. We tested the controller on a statically supported, single-degree-of-freedom exoskeleton that assists swing movements of the leg. Subjects performed movement sequences, first unassisted and then using the exoskeleton, in the context of a computer-based task resembling a race. With zero inertia compensation, the steady-state frequency of the leg swing was consistently reduced. Adding inertia compensation enabled subjects to recover their normal frequency of swing.