Effect of brain alpha oscillation on the performance in laparoscopic skills simulator training

Enhancing touch sensibility with sensory electrical stimulation and sensory retraining

A large proportion of stroke survivors suffer from sensory loss, negatively impacting their independence, quality of life, and neurorehabilitation prognosis. Despite the high prevalence of somatosensory impairments, our understanding of somatosensory interventions such as sensory electrical stimulation (SES) in neurorehabilitation is limited. We aimed to study the effectiveness of SES combined with a sensory discrimination task in a well-controlled virtual environment in healthy participants, setting a foundation for its potential application in stroke rehabilitation. We employed electroencephalography (EEG) to gain a better understanding of the underlying neural mechanisms and dynamics associated with sensory training and SES. We conducted a single-session experiment with 26 healthy participants who explored a set of three visually identical virtual textures-haptically rendered by a robotic device and that differed in their spatial period-while physically guided by the robot to identify the odd texture. The experiment consisted of three phases: pre-intervention, intervention, and post-intervention. Half the participants received subthreshold whole-hand SES during the intervention, while the other half received sham stimulation. We evaluated changes in task performance-assessed by the probability of correct responses-before and after intervention and between groups. We also evaluated differences in the exploration behavior, e.g., scanning speed. EEG was employed to examine the effects of the intervention on brain activity, particularly in the alpha frequency band (8-13 Hz) associated with sensory processing. We found that participants in the SES group improved their task performance after intervention and their scanning speed during and after intervention, while the sham group did not improve their task performance. However, the differences in task performance improvements between groups only approached significance. Furthermore, we found that alpha power was sensitive to the effects of SES; participants in the stimulation group exhibited enhanced brain signals associated with improved touch sensitivity likely due to the effects of SES on the central nervous system, while the increase in alpha power for the sham group was less pronounced. Our findings suggest that SES enhances texture discrimination after training and has a positive effect on sensory-related brain areas. Further research involving brain-injured patients is needed to confirm the potential benefit of our solution in neurorehabilitation.

Beyond the Square knot: A validation study for a novel knot-tying method named "inverse 9"

Purpose

We compared the "inverse 9" laparoscopic suturing and knot-tying (LSKT) method to the traditional LSKT method in a validation study to demonstrate the "inverse 9" method's superiority and effectiveness in laparoscopy.

Methods

On the basis of their experience in laparoscopic surgery, 78 trainees were divided into two groups, with 52 inexperienced trainees in group A and 26 experienced trainees in group B. In group A, 52 trainees were randomly allocated to either group A1 ("inverse 9" LSKT training) or group A2 (traditional LSKT training). In group B, experienced trainees were randomly assigned to receive "inverse 9" LSKT training (group B1) or continuing training in the traditional LSKT method (group B2). All trainees received the same instruction and assessment and were asked to provide a subjective assessment of the two training methods at the end of the training.

Results

The trainees in groups A1, A2, and B had similar average ages and were mostly male. After training, all showed preliminary mastery of LSKT (P < 0.05). The trainees in groups A1 and B1 achieved learning proficiency in the fifth assessment, while those in group A2 achieved it in the sixth assessment. The trainees in groups A1 and B1 showed lower difficulty in achieving mastery and lower operation fatigue scores (P < 0.05), and 61.50 % of the trainees in group B preferred the "inverse 9" method in subjective evaluation.

Conclusion

As a novel LSKT technique, "inverse 9" offers a multitude of benefits. In addition to ensuring a simpler operation and effectively reducing the knot-tying time, it also involves a shorter learning curve than traditional LSKT methods. As such, it can be easily mastered and widely adopted as a standard LSKT technique.

Electroencephalography can provide advance warning of technical errors during laparoscopic surgery

BACKGROUND

Intraoperative adverse events lead to patient injury and death, and are increasing. Early warning systems (EWSs) have been used to detect patient deterioration and save lives. However, few studies have used EWSs to monitor surgical performance and caution about imminent technical errors. Previous (non-surgical) research has investigated neural activity to predict future motor errors using electroencephalography (EEG). The present proof-of-concept cohort study investigates whether EEG could predict technical errors in surgery.

METHODS

In a large academic hospital, three surgical fellows performed 12 elective laparoscopic general surgeries. Audiovisual data of the operating room and the surgeon's neural activity were recorded. Technical errors and epochs of good surgical performance were coded into events. Neural activity was observed 40 s prior and 10 s after errors and good events to determine how far in advance errors were detected. A hierarchical regression model was used to account for possible clustering within surgeons. This prospective, proof-of-concept, cohort study was conducted from July to November 2021, with a pilot period from February to March 2020 used to optimize the technique of data capture and included participants who were blinded from study hypotheses.

RESULTS

Forty-five technical errors, mainly due to too little force or distance (n = 39), and 27 good surgical events were coded during grasping and dissection. Neural activity representing error monitoring (p = .008) and motor uncertainty (p = .034) was detected 17 s prior to errors, but not prior to good surgical performance.

CONCLUSIONS

These results show that distinct neural signatures are predictive of technical error in laparoscopic surgery. If replicated with low false-alarm rates, an EEG-based EWS of technical errors could be used to improve individualized surgical training by flagging imminent unsafe actions-before errors occur and cause patient harm.

Use of neuroimaging to measure neurocognitive engagement in health professions education: a scoping review

PURPOSE

To map the current literature on functional neuroimaging use in medical education research as a novel measurement modality for neurocognitive engagement, learning, and expertise development.

METHOD

We searched PubMed, Embase, Cochrane, ERIC, and Web of Science, and hand-searched reference lists of relevant articles on April 4, 2019, and updated the search on July 7, 2020. Two authors screened the abstracts and then full-text articles for eligibility based on inclusion criteria. The data were then charted, synthesized, and analyzed descriptively.

RESULTS

Sixty-seven articles published between 2007 and 2020 were included in this scoping review. These studies used three main neuroimaging modalities: functional magnetic resonance imaging, functional near-infrared spectroscopy, and electroencephalography. Most of the publications (90%, n = 60) were from the last 10 years (2011-2020). Although these studies were conducted in 16 countries, 68.7% (n = 46) were from three countries: the USA (n = 21), UK (n = 15), and Canada (n = 10). These studies were mainly non-experimental (74.6%, n = 50). Most used neuroimaging techniques to examine psychomotor skill development (57%, n = 38), but several investigated neurocognitive correlates of clinical reasoning skills (22%, n = 15).

CONCLUSION

This scoping review maps the available literature on functional neuroimaging use in medical education. Despite the heterogeneity in research questions, study designs, and outcome measures, we identified a few common themes. Included studies are encouraging of the potential for neuroimaging to complement commonly used measures in education research and may help validate/challenge established theoretical assumptions and provide insight into training methods. This review highlighted several areas for further research. The use of these emerging technologies appears ripe for developing precision education, establishing viable study protocols for realistic operational settings, examining team dynamics, and exploring applications for real-time monitoring/intervention during critical clinical tasks.

SSVEP-Based Brain Computer Interface Controlled Soft Robotic Glove for Post-Stroke Hand Function Rehabilitation

Soft robotic glove with brain computer interfaces (BCI) control has been used for post-stroke hand function rehabilitation. Motor imagery (MI) based BCI with robotic aided devices has been demonstrated as an effective neural rehabilitation tool to improve post-stroke hand function. It is necessary for a user of MI-BCI to receive a long time training, while the user usually suffers unsuccessful and unsatisfying results in the beginning. To propose another non-invasive BCI paradigm rather than MI-BCI, steady-state visually evoked potentials (SSVEP) based BCI was proposed as user intension detection to trigger the soft robotic glove for post-stroke hand function rehabilitation. Thirty post-stroke patients with impaired hand function were randomly and equally divided into three groups to receive conventional, robotic, and BCI-robotic therapy in this randomized control trial (RCT). Clinical assessment of Fugl-Meyer Motor Assessment of Upper Limb (FMA-UL), Wolf Motor Function Test (WMFT) and Modified Ashworth Scale (MAS) were performed at pre-training, post-training and three months follow-up. In comparing to other groups, The BCI-robotic group showed significant improvement after training in FMA full score (10.05±8.03, p=0.001), FMA shoulder/elbow (6.2±5.94, p=0.0004) and FMA wrist/hand (4.3±2.83, p=0.007), and WMFT (5.1±5.53, p=0.037). The improvement of FMA was significantly correlated with BCI accuracy (r=0.714, p=0.032). Recovery of hand function after rehabilitation of SSVEP-BCI controlled soft robotic glove showed better result than solely robotic glove rehabilitation, equivalent efficacy as results from previous reported MI-BCI robotic hand rehabilitation. It proved the feasibility of SSVEP-BCI controlled soft robotic glove in post-stroke hand function rehabilitation.

Effect of Simulation-Based Training and Neurofeedback Interventions on Radiation Technologists' Workload, Situation Awareness, and Performance

PURPOSE

Our purpose was to assess the effect of a combined intervention - simulation-based training supported by neurofeedback sessions - on radiation technologists' (RTs') workload, situation awareness, and performance during routine quality assurance and treatment delivery tasks.

METHODS AND MATERIALS

As part of a prospective institutional review board approved study, 32 RTs previously randomized to receive versus not receive simulation-based training focused on patient safety were again randomized to receive versus not receive a 3-week neurofeedback intervention (8 sessions of alpha-theta protocol) focused on stress reduction as well as conscious precision, strong focus, and ability to solve arising problems. Perceived workload was quantified using the NASA Task Load Index. Situation awareness was quantified using the situation awareness rating technique. Performance score was calculated using procedural compliance with time-out components and error detection.

RESULTS

RTs randomized to simulation-based training followed by neurofeedback sessions demonstrated no significant changes in perceived workload or situation awareness scores, but did have better performance compared with other study groups (P < .01).

CONCLUSIONS

This finding is encouraging and provides basis for using neurofeedback as means to possibly augment performance improvements gained during simulation-based training.