Bedside patient engagement monitor for rehabilitation in disorders of consciousness – demonstrative case-reports

Reducing Driving Risk Factors in Adolescents with Attention Deficit Hyperactivity Disorder (ADHD): Insights from EEG and Eye-Tracking Analysis

Adolescents with attention deficit hyperactivity disorder (ADHD) face significant driving challenges due to deficits in attention and executive functioning, elevating their road risks. Previous interventions targeting driving safety among this cohort have typically addressed isolated aspects (e.g., cognitive or behavioral factors) or relied on uniform solutions. However, these approaches often overlook this population's diverse needs. This study introduces the "Drive-Fun" innovative intervention (DFI), aimed at enhancing driving skills among this vulnerable population. The intervention was tested in a pilot study including 30 adolescents aged 15-18, comparing three groups: DFI, an educational intervention, and a control group with no treatment. Assessments included a driving simulator, EEG, and Tobii Pro Glasses 2. Evaluation was conducted pre- and post-intervention and at a 3-month follow-up. Results indicated that the DFI group significantly improved in the simulated driving performance, attentional effort, and focused gaze time. The findings underscore that holistic strategies with personalized, comprehensive approaches for adolescents with ADHD are particularly effective in improving driving performance. These outcomes not only affirm the feasibility of the DFI but also highlight the critical role of sensor technologies in accurately measuring and enhancing simulator driving performance in adolescents with ADHD. Outcomes suggest a promising direction for future research and application.

Intraoperative EEG-based monitors: are we looking under the lamppost?

PURPOSE OF REVIEW

While electroencephalogram (EEG)-based depth of anesthesia monitors have been in use clinically for decades, there is still a major debate concerning their efficacy for detecting awareness under anesthesia (AUA). Further utilization of these monitors has also been discussed vividly, for example, reduction of postoperative delirium (POD).It seems that with regard to reducing AUA and POD, these monitors might be applicable, under specific anesthetic protocols. But in other settings, such monitoring might be less contributive and may have a 'built-it glass ceiling'.Recent advances in other venues of electrophysiological monitoring might have a strong theoretical rationale, and early supporting results, to offer a breakthrough out of this metaphorical glass ceiling. The purpose of this review is to present this possibility.

RECENT FINDINGS

Following previous findings, it might be concluded that for some anesthesia protocols, the prevailing depth of anesthesia monitors may prevent incidences of AUA and POD. However, in other settings, which may involve other anesthesia protocols, or specifically for POD - other perioperative causes, they may not. Attention-related processes measured by easy-to-use real-time electrophysiological markers are becoming feasible, also under anesthesia, and might be applicable for more comprehensive prevention of AUA, POD and possibly other perioperative complications.

SUMMARY

Attention-related monitoring might have a strong theoretical basis for the prevention of AUA, POD, and potentially other distressing postoperative outcomes, such as stroke and postoperative neurocognitive disorder. There seems to be already some initial supporting evidence in this regard.

Evaluating a Novel EEG-Based Index for Stroke Detection Under Anesthesia During Mechanical Thrombectomy

BACKGROUND

The rapid identification of acute stroke (AS) during and after anesthesia might lead to early interventions and improved outcomes. We investigated a novel 2-channel electroencephalogram (EEG)-based marker for stroke detection-the lateral interconnection ratio (LIR)-in AS patients having endovascular thrombectomy (EVT) with general anesthesia (GA) or sedation. The LIR in 2 reference groups of patients without postoperative neurological complications was used for comparison.

METHODS

The National Institutes of Health stroke scale score was assessed before and after thrombectomy in 100 patients having EVT with GA or sedation. The EEG was monitored during and for 4 hours following EVT in the AS group and during surgery in the 2 reference groups. We compared: (1) LIR between AS and reference groups; (2) LIR and stroke dynamics (clinical improvement or deterioration after EVT assessed by the National Institutes of Health stroke scale score); (3) the impact of stroke site (anterior vs. posterior circulation) and anesthesia type (GA vs. sedation) on the LIR.

RESULTS

Median (interquartile range) LIR was lower in patients with AS compared with reference patients (0.09, 0.05 to 0.16 vs. 0.39, 0.24 to 0.52, respectively; P <0.000002), and LIR increased in AS patients whose clinical status recovered after EVT compared with nonrecovered patients (0.20, 0.12 to 0.29 vs. 0.09, 0.05 to 0.11, respectively; P <0.007). The LIR might be more sensitive to anterior circulation stroke but is not impacted by anesthesia type.

CONCLUSIONS

We demonstrated the utility of using AS patients undergoing EVT as a platform for assessing a novel EEG marker for the identification of stroke during anesthesia. Further, large-scale studies in AS patients during EVT and in patients undergoing different surgeries and anesthesia are required to validate the LIR.

Identifying Recall Under Sedation by a Novel EEG Based Index of Attention—A Pilot Study

Overview

Recall is an accepted consequence of sedation. But due to the very low prevalence of the more devastating awareness under anesthesia (AUA), it might be of value to assess first the efficacy of new markers for AUA by their efficacy in discovering the more prevalent recall under sedation (RUS). In this pilot study we assessed whether a novel index for attentional effort, the cognitive effort index (CEI), derived in real-time from one forehead EEG channel, could differentiate between patients with or without RUS.

Methods

EEG was sampled from 2 groups: (1) Patients who underwent deep sedation (n = 25) (using drugs according to the anesthesiologist preference, but generally combining either Midazolam or Propofol together with either Fentanyl or Remifentanil). (2) Patients who underwent general anesthesia (GA, n = 13, a negative control for recall). In recovery, recall was assessed using the BRICE questionnaire.

Results

Of the 25 sedated patients, 11 experienced recall. The CEI marker was high during significantly longer periods in patients with recall, compared to sedated patients, or patients under GA, without recall. Moreover, the increase in CEI was evident mainly toward the end of the procedure.

Conclusion

RUS seems to associate with higher level of attention, which is identified in real-time by the easy-to-extract CEI marker.

Music Stimulation for People with Disorders of Consciousness: A Scoping Review

Music stimulation is considered to be a valuable form of intervention for people with severe brain injuries and prolonged disorders of consciousness (i.e., unresponsive wakefulness/vegetative state or minimally conscious state). This review was intended to provide an overall picture of work conducted during the last decade to assess the impact of music on behavioral and non-behavioral responses of people with disorders of consciousness. Following the PRISMA-ScR checklist, a scoping review was carried out to identify and provide a synthesis of eligible studies published in English during the 2010–2021 period. Three databases (i.e., PubMed, PsycINFO, and Web of Science) were employed for the literature search. Thirty-four studies met the inclusion criteria. Those studies were grouped into three categories based on whether they assessed the effects of: (i) recorded music, (ii) interactive music, or (iii) response-contingent music. A narrative synthesis of the studies of each of the three categories was eventually provided. While the studies of all three categories reported fairly positive/encouraging results, several methodological questions make it difficult to draw conclusions about those results and their implications for intervention programs in daily contexts.

Real-time monitoring of barriers to patient engagement for improved rehabilitation: a protocol and representative case reports

PURPOSE

There is ample evidence that patient engagement is of major clinical importance in rehabilitation, and it seems this engagement is based upon effective allocation of attention to the tasks during the rehabilitation session. It is possible to discern two types of barriers which hinder attentive engagement: (1) dysfunctional affective coping and (2) limited cognitive recruitment and specifically attention deficit. These barriers might be general for a given patient, due to pre-morbid or co-morbid dysfunctions. But more often they are evoked by tasks or challenges during the rehabilitation session which might be too complicated or stressing for the specific patient who copes with potentially grave impairments. These barriers hinder rehabilitation progress and should be monitored and overcome, by the therapist, throughout the session.

METHODS

We have developed an easy-to-use tool for monitoring a patient's attentive engagement in real-time throughout a rehabilitation session based on analysing the electrophysiological signal sampled from a simple headset. The tool then analyzes the dynamics of the marker over time to identify cognitive and affective barriers during the session. It enables the therapist to insert feedback regarding the patient's functional performance and to combine it with the analysed barriers, in order to derive automatic recommendations for overcoming the cognitive and affective barriers (if identified) for significant enhancement of the rehabilitation session.

RESULTS AND CONCLUSIONS

In this work we present the principles of the tool as well as three detailed case reports to demonstrate its potential usefulness.IMPLICATIONS FOR REHABILITATIONCognitive and affective barriers hinder patient engagment and rehabilitation success.In this work we present an easy to use electrophysiology-based tool which monitors these barriers.Based on the measured barriers and patient's performance, the tool derives treatment suggestions.