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1. Navigating the FDA Medical Device Regulatory Pathways for Pediatric Lower Limb Exoskeleton Devices

   https://doi.org/10.1109/JSYST.2020.3025111  

   Eguren, David ; Contreras-Vidal, Jose Luis ( October 2020 , IEEE Systems Journal)

   null (Ed.)

   There have been significant advances in the technologies for robot-assisted lower-limb rehabilitation in the last decade. However, the development of similar systems for children has been slow despite the fact that children with conditions such as cerebral palsy (CP), spina bifida (SB) and spinal cord injury (SCI) can benefit greatly from these technologies. Robotic assisted gait therapy (RAGT) has emerged as a way to increase gait training duration and intensity while decreasing the risk of injury to therapists. Robotic walking devices can be coupled with motion sensing, electromyography (EMG), scalp electroencephalography (EEG) or other noninvasive methods of acquiring information about the user’s intent to design Brain-Computer Interfaces (BCI) for neuromuscular rehabilitation and control of powered exoskeletons. For users with SCI, BCIs could provide a method of overground mobility closer to the natural process of the brain controlling the body’s movement during walking than mobility by wheelchair. For adults there are currently four FDA approved lower-limb exoskeletons that could be incorporated into such a BCI system, but there are no similar devices specifically designed for children, who present additional physical, neurological and cognitive developmental challenges. The current state of the art for pediatric RAGT relies on large clinical devices with high costs that limit accessibility. This can reduce the amount of therapy a child receives and slow rehabilitation progress. In many cases, lack of gait training can result in a reduction in the mobility, independence and overall quality of life for children with lower-limb disabilities. Thus, it is imperative to facilitate and accelerate the development of pediatric technologies for gait rehabilitation, including their regulatory path. In this paper an overview of the U.S. Food and Drug Administration (FDA) clearance/approval process is presented. An example device has been used to navigate important questions facing device developers focused on providing lower limb rehabilitation to children in home-based or other settings beyond the clinic. 

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2. Characterization and real-time removal of motion artifacts from EEG signals

   https://doi.org/10.1088/1741-2552/ab2b61  

   Kilicarslan, Atilla ; Contreras-Vidal, Jose Luis ( October 2019 , Journal of Neural Engineering)

   Objective: Accurate implementation of real-time non-invasive Brain-Machine / Computer Interfaces (BMI / BCI) requires handling physiological and non-physiological artifacts associated with the measurement modalities. For example, scalp electroencephalographic (EEG) measurements are often considered prone to excessive motion artifacts and other types of artifacts that contaminate the EEG recordings. Although the magnitude of such artifacts heavily depends on the task and the setup, complete minimization or isolation of such artifacts is generally not possible. Approach: We present an adaptive de-noising framework with robustness properties, using a Volterra based non-linear mapping to characterize and handle the motion artifact contamination in EEG measurements. We asked healthy able-bodied subjects to walk on a treadmill at gait speeds of 1-to-4 mph, while we tracked the motion of select EEG electrodes with an infrared video-based motion tracking system. We also placed Inertial Measurement Unit (IMU) sensors on the forehead and feet of the subjects for assessing the overall head movement and segmenting the gait. Main Results: We discuss in detail the characteristics of the motion artifacts and propose a real-time compatible solution to filter them. We report the effective handling of both the fundamental frequency of contamination (synchronized to the walking speed) and its harmonics. Event-Related Spectral Perturbation (ERSP) analysis for walking shows that the gait dependency of artifact contamination is also eliminated on all target frequencies. Significance: The real-time compatibility and generalizability of our adaptive filtering framework allows for the effective use of non-invasive BMI/BCI systems and greatly expands the implementation type and application domains to other types of problems where signal denoising is desirable. Combined with our previous efforts of filtering ocular artifacts, the presented technique allows for a comprehensive adaptive filtering framework to increase the EEG Signal to Noise Ratio (SNR). We believe the implementation will benefit all non-invasive neural measurement modalities, including studies discussing neural correlates of movement and other internal states, not necessarily of BMI focus. 

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3. Ankle-targeted exosuit resistance increases paretic propulsion in people post-stroke

   https://doi.org/10.1186/s12984-023-01204-w  

   Swaminathan, Krithika ; Porciuncula, Franchino ; Park, Sungwoo ; Kannan, Harini ; Erard, Julien ; Wendel, Nicholas ; Baker, Teresa ; Ellis, Terry D. ; Awad, Louis N. ; Walsh, Conor J. ( June 2023 , Journal of NeuroEngineering and Rehabilitation)

   Individualized, targeted, and intense training is the hallmark of successful gait rehabilitation in people post-stroke. Specifically, increasing use of the impaired ankle to increase propulsion during the stance phase of gait has been linked to higher walking speeds and symmetry. Conventional progressive resistance training is one method used for individualized and intense rehabilitation, but often fails to target paretic ankle plantarflexion during walking. Wearable assistive robots have successfullyassistedankle-specific mechanisms to increase paretic propulsion in people post-stroke, suggesting their potential to provide targetedresistanceto increase propulsion, but this application remains underexamined in this population. This work investigates the effects of targeted stance-phase plantarflexion resistance training with a soft ankle exosuit on propulsion mechanics in people post-stroke.

   We conducted this study in nine individuals with chronic stroke and tested the effects of three resistive force magnitudes on peak paretic propulsion, ankle torque, and ankle power while participants walked on a treadmill at their comfortable walking speeds. For each force magnitude, participants walked for 1 min while the exosuit was inactive, 2 min with active resistance, and 1 min with the exosuit inactive, in sequence. We evaluated changes in gait biomechanics during the active resistance and post-resistance sections relative to the initial inactive section.

   Walking with active resistance increased paretic propulsion by more than the minimal detectable change of 0.8 %body weight at all tested force magnitudes, with an average increase of 1.29 ± 0.37 %body weight at the highest force magnitude. This improvement corresponded to changes of 0.13 ± 0.03 N m kg^− 1in peak biological ankle torque and 0.26 ± 0.04 W kg^− 1in peak biological ankle power. Upon removal of resistance, propulsion changes persisted for 30 seconds with an improvement of 1.49 ± 0.58 %body weight after the highest resistance level and without compensatory involvement of the unresisted joints or limb.

   Targeted exosuit-applied functional resistance of paretic ankle plantarflexors can elicit the latent propulsion reserve in people post-stroke. After-effects observed in propulsion highlight the potential for learning and restoration of propulsion mechanics. Thus, this exosuit-based resistive approach may offer new opportunities for individualized and progressive gait rehabilitation.

    

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4. NeuroExo: A Low cost Non Invasive Brain Computer Interface for upper-limb stroke neurorehabilitation at home

   Gonzalez-Espana, Jose ; Craik, Craik ; Alamir, Ayman ; Feng, Jeff ; and Contreras-Vidal, Jose L. ( July 2023 , Proceedings of the 10th International Brain-Computer Interface Meeting 2023)

   The use of scalp electroencephalography (EEG) signals for brain-computer interface (BCI) to control end effectors in real time, while providing mobile capabilities for use at home neurorehabilitation, requires of software and hardware robust solutions. Moreover, to ensure democratized access to these systems, low cost, interoperability, and ease of use are essential. These challenges were addressed in the design, development and validation of the NeuroExo BCI System. As a proof of concept, the system was tested with an exoskeleton system for upper-limb stroke rehabilitation as the end effector. 

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5. Effects of high-intensity gait training with and without soft robotic exosuits in people post-stroke: a development-of-concept pilot crossover trial

   https://doi.org/10.1186/s12984-023-01267-9  

   Porciuncula, Franchino ; Arumukhom Revi, Dheepak ; Baker, Teresa C. ; Sloutsky, Regina ; Walsh, Conor J. ; Ellis, Terry D. ; Awad, Louis N. ( December 2023 , Journal of NeuroEngineering and Rehabilitation)

   High-intensity gait training is widely recognized as an effective rehabilitation approach after stroke. Soft robotic exosuits that enhance post-stroke gait mechanics have the potential to improve the rehabilitative outcomes achieved by high-intensity gait training. The objective of thisdevelopment-of-conceptpilot crossover study was to evaluate the outcomes achieved by high-intensity gait training with versus without soft robotic exosuits.

   In this 2-arm pilot crossover study, four individuals post-stroke completed twelve visits of speed-based, high-intensity gait training: six consecutive visits of Robotic Exosuit Augmented Locomotion (REAL) gait training and six consecutive visits without the exosuit (CONTROL). The intervention arms were counterbalanced across study participants and separated by 6 + weeks of washout. Walking function was evaluated before and after each intervention using 6-minute walk test (6MWT) distance and 10-m walk test (10mWT) speed. Moreover, 10mWT speeds were evaluated before each training visit, with the time-course of change in walking speed computed for each intervention arm. For each participant, changes in each outcome were compared to minimal clinically-important difference (MCID) thresholds. Secondary analyses focused on changes in propulsion mechanics and associated biomechanical metrics.

   Large between-group effects were observed for 6MWT distance (d = 1.41) and 10mWT speed (d = 1.14). REAL gait training resulted in an average pre-post change of 68 ± 27 m (p = 0.015) in 6MWT distance, compared to a pre-post change of 30 ± 16 m (p = 0.035) after CONTROL gait training. Similarly, REAL training resulted in a pre-post change of 0.08 ± 0.03 m/s (p = 0.012) in 10mWT speed, compared to a pre-post change of 0.01 ± 06 m/s (p = 0.76) after CONTROL. For both outcomes, 3 of 4 (75%) study participants surpassed MCIDs after REAL training, whereas 1 of 4 (25%) surpassed MCIDs after CONTROL training. Across the training visits, REAL training resulted in a 1.67 faster rate of improvement in walking speed. Similar patterns of improvement were observed for the secondary gait biomechanical outcomes, with REAL training resulting in significantly improved paretic propulsion for 3 of 4 study participants (p < 0.05) compared to 1 of 4 after CONTROL.

   Soft robotic exosuits have the potential to enhance the rehabilitative outcomes produced by high-intensity gait training after stroke. Findings of thisdevelopment-of-conceptpilot crossover trial motivate continued development and study of the REAL gait training program.

    

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