Brain–Computer Interface-Controlled Exoskeletons in Clinical Neurorehabilitation: Ready or Not?

Abstract

The development of brain–computer interface-controlled exoskeletons promises new treatment strategies for neurorehabilitation after stroke or spinal cord injury. By converting brain/neural activity into control signals of wearable actuators, brain/neural exoskeletons (B/NEs) enable the execution of movements despite impaired motor function. Beyond the use as assistive devices, it was shown that—upon repeated use over several weeks—B/NEs can trigger motor recovery, even in chronic paralysis. Recent development of lightweight robotic actuators, comfortable and portable real-world brain recordings, as well as reliable brain/neural control strategies have paved the way for B/NEs to enter clinical care. Although B/NEs are now technically ready for broader clinical use, their promotion will critically depend on early adopters, for example, research-oriented physiotherapists or clinicians who are open for innovation. Data collected by early adopters will further elucidate the underlying mechanisms of B/NE-triggered motor recovery and play a key role in increasing efficacy of personalized treatment strategies. Moreover, early adopters will provide indispensable feedback to the manufacturers necessary to further improve robustness, applicability, and adoption of B/NEs into existing therapy plans.

Synchronous motor imagery and visual feedback of finger movement elicit the moving rubber hand illusion, at least in illusion-susceptible individuals

“…From an applied neuroscience and neuroengineering perspective, the current findings provide valuable support for the idea that motor imagery can be used to elicit illusory sensations of body ownership and agency in BCI control over virtual and robotic limbs, as suggested by earlier studies (Alimardani et al 2013 , 2016 ; Braun et al 2016 ; Perez-Marcos et al 2009 ; see Colucci et al 2022 for a review on exoskeleton applications). Specifically, our findings add to this literature by demonstrating significant differences in the experience of ownership over a robotic rubber hand between synchronous and asynchronous kinesthetic motor imagery and visual feedback conditions and by providing evidence for significant proprioceptive drift effects in line with the classic rubber hand illusion literature (Botvinick and Cohen 1998 ; Kalckert and Ehrsson 2012 ; Tsakiris and Haggard 2005 ).…”

Personalized Brain–Computer Interface and Its Applications

“…(2) Motion replacement Annalisa Colucci et al mentioned in the literature published in 2022 [71] that the brain/neural exoskeleton (B/NE) will play a key role in improving the effectiveness of personalized treatment strategies. Coscia M et al [61] adjusted and improved the control parameters of B/NE training according to the patient's individual ability by monitoring the physiological biomarkers that predict mental exhaustion, such as heart rate variability, galvanic skin response, or respiratory rate.…”

The Berlin Bimanual Test for Tetraplegia (BeBiTT): development, psychometric properties, and sensitivity to change in assistive hand exoskeleton application

“…The BeBiTT does not only allow to monitor individual therapeutic success but also facilitates the comparison between different training approaches in occupational therapy and physiotherapy. In addition to its use in individuals with tetraplegia, the BeBiTT can be used as a template for assessing bimanual function in other patient groups, such as stroke survivors [12,13,30,31], although adjustments may need to be made according to the population's level of impairment. The BeBiTT might be also a useful tool to evaluate recovery of bimanual task performance secondary to neuroplasticity, e.g., triggered by repeated use of assistive exoskeletons [10,…”