A brain–computer-interface driven forearm exoskeleton with adaptive neuroregulation-based feedback for stroke rehabilitation

This paper investigates the effect of adaptive auditory feedback on continued player performance for stroke patients in a reaction time tablet game. The feedback sound pitch followed a saw-tooth shape that cumulatively increased for fast reaction times and flying back to the base pitch after a single slow reaction time. The analysis was based on data obtained in a field trial with lesion patients during their regular rehabilitation. The auditory feedback events were categorized by feedback type (positive/negative) and the associated pitch change of either high or low magnitude. Both feedback type and magnitude significantly affected on players performance. Negative feedback improved patients reaction times in subsequent hits by 0.42 s and positive feedback impaired their performance by 0.15 s.

BackgroundRepetitive TMS is used in stroke rehabilitation with predefined passive low and high-frequency stimulation. Brain State-Dependent Stimulation (BSDS)/Activity-Dependent Stimulation (ADS) using bio-signal has been observed to strengthen synaptic connections. Without the personalization of brain-stimulation protocols, we risk a one-size-fits-all approach.MethodsWe attempted to close the ADS loop via intrinsic-proprioceptive (via exoskeleton-movement) and extrinsic-visual-feedback to the brain. We developed a patient-specific brain stimulation platform with a two-way feedback system, to synchronize single-pulse TMS with exoskeleton along with adaptive performance visual feedback, in real-time, for a focused neurorehabilitation strategy to voluntarily engage the patient in the brain stimulation process.ResultsThe novel TMS Synchronized Exoskeleton Feedback (TSEF) platform, controlled by the patient’s residual Electromyogram, simultaneously triggered exoskeleton movement and single-pulse TMS, once in 10 s, implying 0.1 Hz frequency. The TSEF platform was tested for a demonstration on three patients (n = 3) with different spasticity on the Modified Ashworth Scale (MAS = 1, 1+, 2) for one session each. Three patients completed their session in their own timing; patients with (more) spasticity tend to take (more) inter-trial intervals. A proof-of-concept study on two groups—TSEF-group and a physiotherapy control-group was performed for 45 min/day for 20-sessions. Dose-matched Physiotherapy was given to control-group. Post 20 sessions, an increase in ipsilesional cortical-excitability was observed; Motor Evoked Potential increased by ~48.5 μV at a decreased Resting Motor Threshold by ~15.6%, with improvement in clinical scales relevant to the Fugl-Mayer Wrist/Hand joint (involved in training) by 2.6 units, an effect not found in control-group. This strategy could voluntarily engage the patient.ConclusionA brain stimulation platform with a real-time two-way feedback system was developed to voluntarily engage the patients during the brain stimulation process and a proof-of-concept study on three patients indicates clinical gains with increased cortical excitability, an effect not observed in the control-group; and the encouraging results nudge for further investigations on a larger cohort.

Stroke patients with severe motor deficits of the upper extremity may practice rehabilitation exercises with the assistance of a multi-joint exoskeleton. Although this technology enables intensive task-oriented training, it may also lead to slacking when the assistance is too supportive. Preserving the engagement of the patients while providing “assistance-as-needed” during the exercises, therefore remains an ongoing challenge. We applied a commercially available seven degree-of-freedom arm exoskeleton to provide passive gravity compensation during task-oriented training in a virtual environment. During this 4-week pilot study, five severely affected chronic stroke patients performed reach-to-grasp exercises resembling activities of daily living. The subjects received virtual reality feedback from their three-dimensional movements. The level of difficulty for the exercise was adjusted by a performance-dependent real-time adaptation algorithm. The goal of this algorithm was the automated improvement of the range of motion. In the course of 20 training and feedback sessions, this unsupervised adaptive training concept led to a progressive increase of the virtual training space (p < 0.001) in accordance with the subjects' abilities. This learning curve was paralleled by a concurrent improvement of real world kinematic parameters, i.e., range of motion (p = 0.008), accuracy of movement (p = 0.01), and movement velocity (p < 0.001). Notably, these kinematic gains were paralleled by motor improvements such as increased elbow movement (p = 0.001), grip force (p < 0.001), and upper extremity Fugl-Meyer-Assessment score from 14.3 ± 5 to 16.9 ± 6.1 (p = 0.026). Combining gravity-compensating assistance with adaptive closed-loop feedback in virtual reality provides customized rehabilitation environments for severely affected stroke patients. This approach may facilitate motor learning by progressively challenging the subject in accordance with the individual capacity for functional restoration. It might be necessary to apply concurrent restorative interventions to translate these improvements into relevant functional gains of severely motor impaired patients in activities of daily living.

This paper presents a novel mixed reality rehabilitation system used to help improve the reaching movements of people who have hemiparesis from stroke. The system provides real-time, multimodal, customizable, and adaptive feedback generated from the movement patterns of the subject's affected arm and torso during reaching to grasp. The feedback is provided via innovative visual and musical forms that present a stimulating, enriched environment in which to train the subjects and promote multimodal sensory-motor integration. A pilot study was conducted to test the system function, adaptation protocol and its feasibility for stroke rehabilitation. Three chronic stroke survivors underwent training using our system for six 75-min sessions over two weeks. After this relatively short time, all three subjects showed significant improvements in the movement parameters that were targeted during training. Improvements included faster and smoother reaches, increased joint coordination and reduced compensatory use of the torso and shoulder. The system was accepted by the subjects and shows promise as a useful tool for physical and occupational therapists to enhance stroke rehabilitation.

Today’s commercial forced exercise platforms had been validated not as a well-designed rehabilitation environment for rats with a stroke, for the reason that rat with a stroke cannot take exercise at a constant intensity for a long period of time. In light of this, this work presented an adaptive, fall-free ischemic stroke rehabilitation mechanism in an animal model, which was implemented in an infrared-sensing adaptive feedback control running wheel (IAFCRW) platform. Consequently, rats with a stroke can be safely rehabilitated all the time, and particularly at full capacity for approximately one third of a training duration, in a completely fall-free environment according to individual physical differences by repeated use of an acceleration/deceleration mechanism. The performance of this platform was assessed using an animal ischemic stroke model. The IAFCRW therapy regimen was validated to outperform a treadmill and a conventional running wheel counterpart with respect to the reduction in the neurobehavioral deficits caused by middle cerebral artery occlusion (MCAo). IAFCRW is the first adaptive forced exercise training platform short of electrical stimulation-assistance in the literature, and ischemic stroke rats benefit more in terms of the behavioral tests run at the end of a 3-week rehabilitation program after a stroke thereby.