A Visuo-Haptic System for Nodule Detection Training: Insights From EEG and Behavioral Analysis

Area of Science:

• Biomedical Engineering
• Neuroscience
• Medical Simulation

Background:

• Medical palpation is a crucial clinical skill.
• Current training methods using animal or synthetic models present ethical and waste concerns.
• Visuo-haptic simulations offer a potential alternative, but their efficacy requires validation.

Purpose of the Study:

• To develop a visuo-haptic system for training nodule detection using a haptic device and simulation software.
• To evaluate the system's potential for objective training and assessment of palpation skills.
• To investigate the correlation between electroencephalography (EEG) data and palpation performance.

Main Methods:

• Development of a visuo-haptic system integrating a Geomagic Touch haptic device and SOFA framework simulation.
• Collection of performance metrics and EEG data from 19 subjects performing a nodule detection task.
• Analysis of EEG alpha power and its relationship with palpation strategy and errors.

Main Results:

• Participants were categorized into low and high performers based on their palpation technique and EEG data.
• Low performers used greater pressure and exhibited higher resting EEG alpha power.
• High performers explored the surface with less pressure and showed lower alpha power, which correlated negatively with palpation depth and positively with errors.

Conclusions:

• EEG alpha power may serve as an objective indicator of cognitive engagement and performance in palpation tasks.
• The combination of EEG and performance data provides a robust method for assessing palpation abilities.
• This visuo-haptic system holds promise for effective and objective training of clinical palpation skills.