Linear approaches to low-dimensional feature extraction may not be appropriate when statistical data are generated by a nonlinear interaction of parameters. Equally inadequate are linear methods for determining the dimension of the feature space. This article estimates the intrinsic dimension of extracellular action potentials (EAPs), which can be viewed as the minimum number of nonlinearly interacting parameters sufficient to describe the data. When combined with nonlinear feature extraction methods, this information may lead to a more faithful, low-dimensional EAP representation. These points are demonstrated using EAPs recorded experimentally by a multisensor electrode.

Gait impairment due to foot drop is a common outcome of stroke, and current physiotherapy provides only limited restoration of gait function. Gait function can also be aided by orthoses, but these devices may be cumbersome and their benefits disappear upon removal. Hence, new neuro-rehabilitative therapies are being sought to generate permanent improvements in motor function beyond those of conventional physiotherapies through positive neural plasticity processes. Here, the authors describe an electroencephalogram (EEG) based brain-computer interface (BCI) controlled functional electrical stimulation (FES) system that enabled a stroke subject with foot drop to re-establish foot dorsiflexion. To this end, a prediction model was generated from EEG data collected as the subject alternated between periods of idling and attempted foot dorsiflexion. This prediction model was then used to classify online EEG data into either "idling" or "dorsiflexion" states, and this information was subsequently used to control an FES device to elicit effective foot dorsiflexion. The performance of the system was assessed in online sessions, where the subject was prompted by a computer to alternate between periods of idling and dorsiflexion. The subject demonstrated purposeful operation of the BCI-FES system, with an average cross-correlation between instructional cues and BCI-FES response of 0.60 over 3 sessions. In addition, analysis of the prediction model indicated that non-classical brain areas were activated in the process, suggesting post-stroke cortical re-organization. In the future, these systems may be explored as a potential therapeutic tool that can help promote positive plasticity and neural repair in chronic stroke patients.

Background: Many stroke survivors have significant long-term gait impairment, often involving foot drop. Current physiotherapies provide limited recovery. Orthoses substitute for ankle strength, but they provide no lasting therapeutic effect. Brain-computer interface (BCI)-controlled functional electrical stimulation (FES) is a novel rehabilitative approach that may generate permanent neurological improvements. This study explores the safety and feasibility of a foot-drop-targeted BCI-FES physiotherapy in chronic stroke survivors. Methods: Subjects (n=9) operated an electroencephalogram-based BCI-FES system for foot dorsiflexion in 12 one-hour sessions over four weeks. Gait speed, dorsiflexion active range of motion (AROM), six-minute walk distance (6MWD), and Fugl-Meyer leg motor (FM-LM) scores were assessed before, during, and after therapy. The primary safety outcome measure was the proportion of subjects that deteriorated in gait speed by ≥0.16 m/s at one week or four weeks post-therapy. The secondary outcome measures were the proportion of subjects that experienced a clinically relevant decrease in dorsiflexion AROM (≥2.5˚), 6MWD (≥20 %), and FM-LM score (≥10 %) at either post-therapy assessment. Results: No subjects (0/9) experienced a clinically significant deterioration in gait speed, dorsiflexion AROM, 6MWT distance, or FM-LM score at either post-therapy assessment. Five subjects demonstrated a detectable increase (≥0.06 m/s) in gait speed, three subjects demonstrated a detectable increase (≥2.5) in dorsiflexion AROM, five subjects demonstrated a detectable increase (≥10 %) in 6MWD, and three subjects demonstrated a detectable increase (≥10 %) in FM-LM. Five of the six subjects that exhibited a detectable increase in either post-therapy gait speed or 6MWD also exhibited significant (p<0.01 using a Mann-Whitney U test) increases in electroencephalogram event-related synchronization/desynchronization. Additionally, two subjects experienced a clinically important increase (≥0.16 m/s) in gait speed, and four subjects experienced a clinically important increase (≥20 %) in 6MWD. Linear mixed models of gait speed, dorsiflexion AROM, 6MWD, and FM-LM scores suggest that BCI-FES therapy is associated with an increase in lower motor performance at a statistically, yet not clinically, significant level. Conclusion: BCI-FES therapy is safe. If it is shown to improve post-stroke gait function in future studies, it could provide a new gait rehabilitation option for severely impaired patients. Formal clinical trials are warranted.