I don't understand, but then the only thing that will make my gait better is curing my spasticity. You could put a gun to my head and tell me to straighten my foot while walking and you'd have to kill me since I don't have control of that. I'm hoping that I never am pulled over by cops where they tell me to put both hands on the roof and spread your legs. I'd fail just like having to alternately touch your nose with the index finger of each hand as a sobriety test.
Exploiting telerobotics for sensorimotor rehabilitation: a locomotor embodiment
Journal of NeuroEngineering and Rehabilitation volume 18, Article number: 66 (2021)
Abstract
Background
Manual treadmill training is used for rehabilitating locomotor impairments but can be physically demanding for trainers. This has been addressed by enlisting robots, but in doing so, the ability of trainers to use their experience and judgment to modulate locomotor assistance on the fly has been lost. This paper explores the feasibility of a telerobotics approach for locomotor training that allows patients to receive remote physical assistance from trainers.
Methods
In the approach, a trainer holds a small robotic manipulandum that shadows the motion of a large robotic arm magnetically attached to a locomoting patient's leg. When the trainer deflects the manipulandum, the robotic arm applies a proportional force to the patient. An initial evaluation of the telerobotic system’s transparency (ability to follow the leg during unassisted locomotion) was performed with two unimpaired participants. Transparency was quantified by the magnitude of unwanted robot interaction forces. In a small six-session feasibility study, six individuals who had prior strokes telerobotically interacted with two trainers (separately), who assisted in altering a targeted gait feature: an increase in the affected leg’s swing length.
Results
During unassisted walking, unwanted robot interaction forces averaged 3−4 N (swing–stance) for unimpaired individuals and 2−3 N for the patients who survived strokes. Transients averaging about 10 N were sometimes present at heel-strike/toe-off. For five of six patients, these forces increased with treadmill speed during stance (R2 = .99; p < 0.001) and increased with patient height during swing (R2 = .71; p = 0.073). During assisted walking, the trainers applied 3.0 ± 2.8 N (mean ± standard deviation across patients) and 14.1 ± 3.4 N of force anteriorly and upwards, respectively. The patients exhibited a 20 ± 21% increase in unassisted swing length between Days 1−6 (p = 0.058).
Conclusions
The results support the feasibility of locomotor assistance with a telerobotics approach. Simultaneous measurement of trainer manipulative actions, patient motor responses, and the forces associated with these interactions may prove useful for testing sensorimotor rehabilitation hypotheses. Further research with clinicians as operators and randomized controlled trials are needed before conclusions regarding efficacy can be made.
Background
Locomotor impairments can arise from injuries or disease processes that disrupt sensorimotor operations, such as spinal cord injuries and stroke. Locomotor training may be incorporated into a rehabilitation program. One approach uses a treadmill because it allows tight control over walking speed and terrain and facilitates the use of a body-weight support system [1, 2]. During treadmill training, human trainers can provide physical assistance to facilitate limb movement and support trunk stabilization [3]. High-volumes of task-orientated practice can promote neuroplasticity [4]. Although treadmill training has shown positive results for patient populations, including individuals who have had strokes [5, 6] or incomplete spinal cord injuries [7, 8], the overall efficacy is not unambiguously superior to other methods such as over-ground training or general exercise regimens [2, 9,10,11,12,13]. Explaining the inability of manual treadmill training to consistently meet expectations presents a grand challenge due to high investigational variability (e.g., eligibility criteria and intervention parameters [14]).
When providing physical assistance to elicit targeted modifications of a patient’s locomotor pattern, human trainers must contend with relatively complex patient dynamics. This includes the gravitational and inertial forces associated with the large wobbling mass [15] of a patient’s upper body, which is alternately supported by multi-link segmental chains (the legs) during locomotion. Further, the joints spanning these segments are actuated by a redundant set of viscoelastic muscles [16] controlled by a possibly impaired nervous system. Trainers also face significant sensorimotor constraints. They often need to produce large forces while kneeling or sitting with a limited view of a patient’s body and need to keep up with rapidly swinging patient limbs to prevent unintended interaction forces, which demands predictive control processes due to sensorimotor delays [17]. The combination of complex interactive dynamics, high forces, and rapid movements creates a challenging task that may limit trainer effectiveness.
One way to address the physical limitations of human trainers is to enlist the help of robots [18,19,20]. However, in doing so, human trainers have been relegated to a supervisory role. At the same time, robotic gait training outcomes have not proven dependably better than conventional rehabilitation approaches for spinal cord injury [21, 22] or stroke [23,24,25,26,27]. Giving trainers more online control of the robotic system (trainer-in-the-loop) could improve rehabilitation outcomes. The rationale is that trainers can use their experience and judgment to customize locomotor assistance on the fly, and their relatively high degree of motor execution variability could be a feature instead of a bug. Self-generated (intrinsic) variability can promote the exploration of novel motor actions that drive learning [28, 29]. Could this also hold for variability injected from an external source, i.e., from a trainer to a patient? If so, these advantages could be masked by trainer fatigue or other sensorimotor encumbrances. These points lead to the principal question: Would treadmill training outcomes improve if trainers remained in control, were relieved of high physical demands, and received augmented feedback about their patient interactions? Telerobotics, or robotics with a human operator in the control loop [30], may provide a viable approach to answering this question.
Although telerobotics has been broadly researched, for example, in areas related to telesurgery (see [30] for a review), rehabilitation applications with continuous physical interaction between clinicians and patients are more limited. Most existing telehealth approaches only permit visual and auditory communication [31,32,33,34]. One study investigated the feasibility of remote haptic communication using an exoskeleton to record the movements of patients who have had strokes; these movements were subsequently played back using an exoskeleton worn by therapists [35]. By feeling the patients' movements through the exoskeleton, the therapists were able to identify abnormal movement patterns. Although the results are promising, the therapists did not command the robotic system to apply forces to patients. Others have recently explored impedance-based telerobotics approaches for upper-extremity rehabilitation [36, 37], but such techniques have yet to be tested in clinical populations. In general, there is a significant need for telerobotics approaches that allow real-time bidirectional physical interaction between trainers and patients [38], which, in addition to benefits associated with human–human interaction (see previous paragraph) may be useful with heightened disease transmission risks.
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