New framework uses EEG and AR to assess ocular response times for mTBI

Researchers have developed a novel framework that integrates electroencephalogram (EEG) data with augmented reality (AR)-based Vestibular/Ocular Motor Screening (VOMS) tasks to assess ocular response times. This system utilizes a Redundant Discrete Wavelet Transform (RDWT)-driven deep neural network to process EEG signals, with wavelet-domain filtering proving effective for denoising and improving prediction accuracy. Dynamic Time Warping (DTW) is then employed to estimate ocular response times, revealing task-dependent differences and highlighting the potential of this multimodal approach for assessing mild traumatic brain injury (mTBI). AI

IMPACT This research could lead to more objective and accessible diagnostic tools for mild traumatic brain injury.

RANK_REASON The cluster contains a research paper detailing a new methodology for assessing ocular response times using EEG and AR. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

• augmented reality
• dynamic time warping
• electroencephalogram
• Mann-Whitney U tests
• RDWT
• Shantanu Sarkar
• VOMS

• paper
• other

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →