Exposure Therapy With Personalized Real-Time Arousal Detection and Feedback to Alleviate Social Anxiety Symptoms in an Analogue Adult Sample: Pilot Proof-of-Concept Randomized Controlled Trial.

BACKGROUND: Exposure therapy is highly effective for social anxiety disorder. However, there is room for improvement. OBJECTIVE: This is a first attempt to examine the feasibility of an arousal feedback-based exposure therapy to alleviate social anxiety symptoms in an analogue adult sample. METHODS: A randomized, pilot, proof-of-concept trial was conducted to evaluate the acceptability, safety, and preliminary efficacy of our treatment program. Sessions were administered once a week for 4 weeks (1 hour each) to an analogue sample of 50 young adults who reported at least minimal social anxiety symptoms. Participants in both intervention and waitlist control groups completed assessments for social anxiety symptoms at the baseline, week 5, and week 10. RESULTS: Most participants found the intervention acceptable (82.0%, 95% CI 69.0%-91.0%). Seven (14.9%, 95% CI 7.0%-28.0%) participants reported at least one mild adverse event over the course of study. No moderate or serious adverse events were reported. Participants in the intervention group demonstrated greater improvements on all outcome measures of public speaking anxiety from baseline to week 5 as compared to the waitlist control group (Cohen d=0.61-1.39). Effect size of the difference in mean change on the overall Liebowitz Social Anxiety Scale was small (Cohen d=0.13). CONCLUSIONS: Our results indicated that it is worthwhile to proceed to a larger trial for our treatment program. This new medium of administration for exposure therapy may be feasible for treating a subset of social anxiety symptoms. Additional studies are warranted to explore its therapeutic mechanisms. TRIAL REGISTRATION: ClinicalTrials.gov NCT02493010; https://clinicaltrials.gov/ct2/show/NCT02493010.

Detection of motor imagery of brisk walking from electroencephalogram.

Rehabilitation of lower limbs is equally as important as that of upper limbs. This paper presented a study to detect motor imagery of walking (MI-Walking) from background idle state. Broad overlapping neuronal networks involved in reorganization following motor imagery introduce redundancy. We hypothesized that MI-Walking could be robustly detected by constraining dependency among selected features and class separations. Hence, we proposed to jointly select channels and frequency bands involved in MI-Walking by optimizing/regularizing the objective function formulated on the dependency between features and class labels, redundancy between to-be-selected with selected features, and separations between classes, namely, "regularized maximum dependency with minimum redundancy-based joint channel and frequency band selection (RMDR-JCFS)". Evaluated on electroencephalography (EEG) data of 11 healthy subjects, the results showed that the selected channels were mainly located at premotor cortex, mid-central area overlaying supplementary motor area (SMA), prefrontal cortex, foot area sensory cortex and leg and arm sensorimotor representation area. Broad frequencies of alpha, mu and beta rhythms were involved. Our proposed method yielded an averaged accuracy of 76.67%, which was 9.08%, 5.03%, 7.03%, 14.15% and 3.88% higher than that obtained by common spatial pattern (CSP), filter-bank CSP, sliding window discriminate CSP, filter-bank power and maximum dependency and minimum redundancy methods, respectively. Further, our method yielded significantly superior performance compared with other channel selection methods, and it yielded an averaged session-to-session accuracy of 70.14%. These results demonstrated the potentials of detecting MI-Walking using proposed method for stroke rehabilitation.

A pilot randomized controlled trial using EEG-based brain-computer interface training for a Chinese-speaking group of healthy elderly.

BACKGROUND: There is growing evidence that cognitive training (CT) can improve the cognitive functioning of the elderly. CT may be influenced by cultural and linguistic factors, but research examining CT programs has mostly been conducted on Western populations. We have developed an innovative electroencephalography (EEG)-based brain-computer interface (BCI) CT program that has shown preliminary efficacy in improving cognition in 32 healthy English-speaking elderly adults in Singapore. In this second pilot trial, we examine the acceptability, safety, and preliminary efficacy of our BCI CT program in healthy Chinese-speaking Singaporean elderly. METHODS: Thirty-nine elderly participants were randomized into intervention (n=21) and wait-list control (n=18) arms. Intervention consisted of 24 half-hour sessions with our BCI-based CT training system to be completed in 8 weeks; the control arm received the same intervention after an initial 8-week waiting period. At the end of the training, a usability and acceptability questionnaire was administered. Efficacy was measured using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), which was translated and culturally adapted for the Chinese-speaking local population. Users were asked about any adverse events experienced after each session as a safety measure. RESULTS: The training was deemed easily usable and acceptable by senior users. The median difference in the change scores pre- and post-training of the modified RBANS total score was 8.0 (95% confidence interval [CI]: 0.0-16.0, P=0.042) higher in the intervention arm than waitlist control, while the mean difference was 9.0 (95% CI: 1.7-16.2, P=0.017). Ten (30.3%) participants reported a total of 16 adverse events - all of which were graded "mild" except for one graded "moderate". CONCLUSION: Our BCI training system shows potential in improving cognition in both English- and Chinese-speaking elderly, and deserves further evaluation in a Phase III trial. Overall, participants responded positively on the usability and acceptability questionnaire.

Detection of motor imagery of swallow EEG signals based on the dual-tree complex wavelet transform and adaptive model selection.

OBJECTIVE: Detection of motor imagery of hand/arm has been extensively studied for stroke rehabilitation. This paper firstly investigates the detection of motor imagery of swallow (MI-SW) and motor imagery of tongue protrusion (MI-Ton) in an attempt to find a novel solution for post-stroke dysphagia rehabilitation. Detection of MI-SW from a simple yet relevant modality such as MI-Ton is then investigated, motivated by the similarity in activation patterns between tongue movements and swallowing and there being fewer movement artifacts in performing tongue movements compared to swallowing. APPROACH: Novel features were extracted based on the coefficients of the dual-tree complex wavelet transform to build multiple training models for detecting MI-SW. The session-to-session classification accuracy was boosted by adaptively selecting the training model to maximize the ratio of between-classes distances versus within-class distances, using features of training and evaluation data. MAIN RESULTS: Our proposed method yielded averaged cross-validation (CV) classification accuracies of 70.89% and 73.79% for MI-SW and MI-Ton for ten healthy subjects, which are significantly better than the results from existing methods. In addition, averaged CV accuracies of 66.40% and 70.24% for MI-SW and MI-Ton were obtained for one stroke patient, demonstrating the detectability of MI-SW and MI-Ton from the idle state. Furthermore, averaged session-to-session classification accuracies of 72.08% and 70% were achieved for ten healthy subjects and one stroke patient using the MI-Ton model. SIGNIFICANCE: These results and the subjectwise strong correlations in classification accuracies between MI-SW and MI-Ton demonstrated the feasibility of detecting MI-SW from MI-Ton models.

A brain-computer interface based cognitive training system for healthy elderly: a randomized control pilot study for usability and preliminary efficacy.

UNLABELLED: Cognitive decline in aging is a pressing issue associated with significant healthcare costs and deterioration in quality of life. Previously, we reported the successful use of a novel brain-computer interface (BCI) training system in improving symptoms of attention deficit hyperactivity disorder. Here, we examine the feasibility of the BCI system with a new game that incorporates memory training in improving memory and attention in a pilot sample of healthy elderly. This study investigates the safety, usability and acceptability of our BCI system to elderly, and obtains an efficacy estimate to warrant a phase III trial. Thirty-one healthy elderly were randomized into intervention (n = 15) and waitlist control arms (n = 16). Intervention consisted of an 8-week training comprising 24 half-hour sessions. A usability and acceptability questionnaire was administered at the end of training. Safety was investigated by querying users about adverse events after every session. Efficacy of the system was measured by the change of total score from the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) before and after training. Feedback on the usability and acceptability questionnaire was positive. No adverse events were reported for all participants across all sessions. Though the median difference in the RBANS change scores between arms was not statistically significant, an effect size of 0.6SD was obtained, which reflects potential clinical utility according to Simon's randomized phase II trial design. Pooled data from both arms also showed that the median change in total scores pre and post-training was statistically significant (Mdn = 4.0; p<0.001). Specifically, there were significant improvements in immediate memory (p = 0.038), visuospatial/constructional (p = 0.014), attention (p = 0.039), and delayed memory (p<0.001) scores. Our BCI-based system shows promise in improving memory and attention in healthy elderly, and appears to be safe, user-friendly and acceptable to senior users. Given the efficacy signal, a phase III trial is warranted. TRIAL REGISTRATION: ClinicalTrials.gov NCT01661894.