Validating attentive locomotion training using interactive treadmill: an fNIRS study

Effects of Training with a Powered Exoskeleton on Cortical Activity Modulation in Hemiparetic Chronic Stroke Patients: A Randomized Controlled Pilot Trial

OBJECTIVES

To investigate the effects of exoskeleton-assisted gait training in stroke patients.

DESIGN

Prospective randomized controlled trial.

SETTING

Rehabilitation department in a single tertiary hospital.

PARTICIPANTS

Thirty (N=30) chronic stroke patients with Functional Ambulatory Category scale (FAC) between 2 and 4.

INTERVENTION

Patients were randomly assigned to 1 of 2 groups: training with Healbot G, a wearable powered exoskeleton (Healbot G group; n=15), or treadmill training (control group; n=15). All participants received 30 minutes of training, 10 times per week, for 4 weeks.

OUTCOME MEASUREMENTS

The primary outcome was oxyhemoglobin level changes, representing cortical activity in both motor cortices using functional near-infrared spectroscopy. The secondary outcomes included FAC, Berg Balance Scale, Motricity Index for the lower extremities (MI-Lower), 10-meter walk test, and gait symmetry ratio (spatial step and temporal symmetry ratio).

RESULTS

Compared to the control group, during the entire training session, the pre-training and post-training mean cortical activity, and the amount of increment between pre- and post-training were significantly higher in the Healbot G group (∆mean ± SD; pre-training, 0.245±0.119, post-training, 0.697±0.429, between pre- and post-training, 0.471±0.401μmol, P<.001). There was no significant difference in cortical activity between affected- and unaffected hemispheres after Healbot G training. FAC (∆mean ± SD; 0.35 ± 0.50, P=.012), MI-Lower (∆mean ± SD; 7.01 ± 0.14, P=.001), and spatial step gait symmetry ratio (∆mean ± SD; -0.32 ± 0.25, P=.049) were improved significantly in the Healbot G group.

CONCLUSION

Exoskeleton-assisted gait training induces cortical modulation effect in both motor cortices, a balanced cortical activation pattern with improvements in spatial step symmetry ratio, walking ability, and voluntary strength.

A robotic treadmill system to mimic overground walking training with body weight support

Introduction

Body weight support overground walking training (BWSOWT) is widely used in gait rehabilitation. However, existing systems require large workspace, complex structure, and substantial installation cost for the actuator, which make those systems inappropriate for the clinical environment. For wide clinical use, the proposed system is based on a self-paced treadmill, and uses an optimized body weight support with frame-based two-wire mechanism.

Method

The Interactive treadmill was used to mimic overground walking. We opted the conventional DC motors to partially unload the body weight and modified pelvic type harness to allow natural pelvic motion. The performance of the proposed system on the measurement of anterior/posterior position, force control, and pelvic motion was evaluated with 8 healthy subjects during walking training.

Results

We verified that the proposed system was the cost/space-effective and showed the more accurate anterior/posterior position than motion sensor, comparable force control performance, and natural pelvic motion.

Discussion

The proposed system is cost/space effective, and able to mimic overground walking training with body weight support. In future work, we will improve the force control performance and optimize the training protocol for wide clinical use.

Cortical activation in robot-assisted dynamic and static resistance training combining VR interaction: An fNIRS based pilot study

BACKGROUND

There are few isometric training systems based on upper limb rehabilitation robots. Its efficacy and neural mechanism are not well understood.

OBJECTIVE

This study aims to investigate the cortex activation of dynamic resistance and static (isometric) training based on upper limb rehabilitation robot combined with virtual reality (VR) interaction by using functional near-infrared spectroscopy (fNIRS).

METHODS

Twenty subjects were included in this study. The experiment adopts the block paradigm design. Experiment in dynamic and static conditions consisted of three trials, each consisting of task (60 s)-rest (40 s). The neural activities of the sensorimotor cortex (SMC), premotor cortex (PMC) and prefrontal cortex (PFC) were measured. The cortex activation and functional connectivity (FC) were analyzed.

RESULTS

Both the dynamic and static training can activate SMC, PMC, and PFC. In SMC and PMC, the activation of static training was stronger than dynamic training, there were significant differences between the two modes of each region of interest (ROI) (p <  0.05) (SMC: p = 0.022, ES = 0.72, PMC: p = 0.039, ES = 0.63). Besides, the FC between all ROIs of the static training was stronger than that of the dynamic training.

CONCLUSION

The static training based on upper limb rehabilitation robot may better facilitate the cortical activation associated with motor control.

Relation between Cortical Activation and Effort during Robot-Mediated Walking in Healthy People: A Functional Near-Infrared Spectroscopy Neuroimaging Study (fNIRS)

Force and effort are important components of a motor task that can impact rehabilitation effectiveness. However, few studies have evaluated the impact of these factors on cortical activation during gait. The purpose of the study was to investigate the relation between cortical activation and effort required during exoskeleton-mediated gait at different levels of physical assistance in healthy individuals. Twenty-four healthy participants walked 10 m with an exoskeleton that provided four levels of assistance: 100%, 50%, 0%, and 25% resistance. Functional near-infrared spectroscopy (fNIRS) was used to measure cerebral flow dynamics with a 20-channel (plus two reference channels) device that covered most cortical motor regions bilaterally. We measured changes in oxyhemoglobin (HbO₂) and deoxyhemoglobin (HbR). According to HbO₂ levels, cortical activation only differed slightly between the assisted conditions and rest. In contrast, bilateral and widespread cortical activation occurred during the two unassisted conditions (somatosensory, somatosensory association, primary motor, premotor, and supplementary motor cortices). A similar pattern was seen for HbR levels, with a smaller number of significant channels than for HbO₂. These results confirmed the hypothesis that there is a relation between cortical activation and level of effort during gait. This finding should help to optimize neurological rehabilitation strategies to drive neuroplasticity.

The effect of robot-assisted gait training on cortical activation in stroke patients: A functional near-infrared spectroscopy study

OBJECTIVE

To investigate the effects of the robot-assisted gait training on cortical activation and functional outcomes in stroke patients.

METHODS

The patients were randomly assigned: training with Morning Walk® (Morning Walk group; n = 30); conventional physiotherapy (control group; n = 30). Rehabilitation was performed five times a week for 3 weeks. The primary outcome was the cortical activation in the Morning Walk group. The secondary outcomes included gait speed, 10-Meter Walk Test (10MWT), FAC, Motricity Index-Lower (MI-Lower), Modified Barthel Index (MBI), Rivermead Mobility Index (RMI), and Berg Balance Scale (BBS).

RESULTS

Thirty-six subjects were analyzed, 18 in the Morning Walk group and 18 in the control group. The cortical activation was lower in affected hemisphere than unaffected hemisphere at the beginning of robot rehabilitation. After training, the affected hemisphere achieved a higher increase in cortical activation than the unaffected hemisphere. Consequently, the cortical activation in affected hemisphere was significantly higher than that in unaffected hemisphere (P = 0.036). FAC, MBI, BBS, and RMI scores significantly improved in both groups. The Morning Walk group had significantly greater improvements than the control group in 10MWT (P = 0.017), gait speed (P = 0.043), BBS (P = 0.010), and MI-Lower (P = 0.047) scores.

CONCLUSION

Robot-assisted gait training not only improved functional outcomes but also increased cortical activation in stroke patients.

Effects of passive and active training modes of upper-limb rehabilitation robot on cortical activation: a functional near-infrared spectroscopy study

OBJECTIVE

The purpose of this study is to investigate the cortical activation during passive and active training modes under different speeds of upper extremity rehabilitation robots.

METHODS

Twelve healthy subjects completed the active and passive training modes at various speeds (0.12, 0.18, and 0.24 m/s) for the right upper limb. The functional near-infrared spectroscopy (fNIRS) was used to measure the neural activities of the sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and prefrontal cortex (PFC).

RESULTS

Both the active and passive training modes can activate SMC, PMC, SMA, and PFC. The activation level of active training is higher than that of passive training. At the speed of 0.12 m/s, there is no significant difference in the intensity of the two modes. However, at the speed of 0.24 m/s, there are significant differences between the two modes in activation levels of each region of interest (ROI) (P < 0.05) (SMC: F = 8.90, P = 0.003; PMC: F = 8.26, P = 0.005; SMA: F = 5.53, P = 0.023; PFC: F = 9.160, P = 0.003).

CONCLUSION

This study mainly studied on the neural mechanisms of active and passive training modes at different speeds based on the end-effector upper-limb rehabilitation robot. Slow, active training better facilitated the cortical activation associated with cognition and motor control.See Video Abstract, http://links.lww.com/WNR/A621.

Motor Training Using Mental Workload (MWL) With an Assistive Soft Exoskeleton System: A Functional Near-Infrared Spectroscopy (fNIRS) Study for Brain-Machine Interface (BMI)

Mental workload is a neuroergonomic human factor, which is widely used in planning a system's safety and areas like brain-machine interface (BMI), neurofeedback, and assistive technologies. Robotic prosthetics methodologies are employed for assisting hemiplegic patients in performing routine activities. Assistive technologies' design and operation are required to have an easy interface with the brain with fewer protocols, in an attempt to optimize mobility and autonomy. The possible answer to these design questions may lie in neuroergonomics coupled with BMI systems. In this study, two human factors are addressed: designing a lightweight wearable robotic exoskeleton hand that is used to assist the potential stroke patients with an integrated portable brain interface using mental workload (MWL) signals acquired with portable functional near-infrared spectroscopy (fNIRS) system. The system may generate command signals for operating a wearable robotic exoskeleton hand using two-state MWL signals. The fNIRS system is used to record optical signals in the form of change in concentration of oxy and deoxygenated hemoglobin (HbO and HbR) from the pre-frontal cortex (PFC) region of the brain. Fifteen participants participated in this study and were given hand-grasping tasks. Two-state MWL signals acquired from the PFC region of the participant's brain are segregated using machine learning classifier-support vector machines (SVM) to utilize in operating a robotic exoskeleton hand. The maximum classification accuracy is 91.31%, using a combination of mean-slope features with an average information transfer rate (ITR) of 1.43. These results show the feasibility of a two-state MWL (fNIRS-based) robotic exoskeleton hand (BMI system) for hemiplegic patients assisting in the physical grasping tasks.

Toward Comparison of Cortical Activation with Different Motor Learning Methods Using Event-Related Design: EEG-fNIRS Study

Recently, motor imagery brain-computer interface (MI-BCI) has been studied as a motor learning method and evaluated by comparing with conventional passive and active training. Most functional near-infrared spectroscopy (fNIRS) studies adopted block design for comparing those motor learning methods, including MI-BCI. Compared to the block design, event-related design would be more appropriate for estimating cortical activation in MI-BCI which provides feedback for each trial. This paper is a preliminary study to check the feasibility whether event-related design can be applicable for MI-BCI. To this end, three different motor learning methods involving MI-BCI were compared. In hemodynamic response, MI-BCI showed significantly stronger cortical activation than passive training (PT), and weaker than active training (AT), which conforms most existing studies. The results demonstrate that event-related design could be applied to investigate cortical effects of MI-BCI and comparing hemodynamic responses of different motor learning methods.

Simulation and in vivo investigation of light-emitting diode, near infrared Gaussian beam profiles

Near infrared spectroscopy is an optical imaging technique which offers a non-invasive, portable, and low-cost method for continuously measuring the oxygenation of tissues. In particular, it can provide the brain activation through measuring the blood oxygenation and blood volume in the cortex. Understanding and then improving the spatial and depth sensitivity of near infrared spectroscopy measurements to brain tissue are essential for designing experiments as well as interpreting research findings. In this study, we investigate the effect of applying two common light beam profiles including Uniform and Gaussian on the penetration depth of an LED-based near infrared spectroscopy. In this regard, two Gaussian profiles were produced by adjusting plano-convex and bi-convex lenses and the Uniform profile was provided by applying a flat lens. Two experiments were conducted in this study. First, a simulation experiment was carried out based on scanning the intra space of a liquid phantom by using static and pulsating absorbers to compare the penetration depth of the configurations applied on the LED-based near infrared spectroscopy with that of a laser-based near infrared spectroscopy. Second, to show the feasibility of the best proposed configuration applied, an in vivo experiment of stress assessment has been performed and its results have been compared with that results obtained by laser one. The results showed that the LED-based near infrared spectroscopy equipped with bi-convex lens provides a penetration depth and hence quality measurements of near infrared spectroscopy and its extracted heart rate variability signals as well as laser-based near infrared spectroscopy especially in the application of stress assessment.

A two-wire body weight support system for interactive treadmill

Body weight support (BWS) system is widely used for patients to help their gait training. However, that existing systems require large workspace and elastic component in actuation makes the systems inappropriate for wide clinical use. The interactive treadmill was reported to be cost/space effectively simulate overground walking, but there was no suitable BWS system for the treadmill. We proposed a new concept of body weight support system for interactive treadmill. For wide clinical use, we applied a two-wire driven mechanism with simple actuator and a custom pelvic-type harness. With three healthy subjects, the performance of the proposed BWS system on unloading force control was evaluated, and the result showed that the feasibility of the proposed BWS system.