TeleAutoHINTS: A Virtual or Augmented Reality (VR/AR) System for Automated Tele-Neurologic Evaluation of Acute Vertigo
Wei, H.; Bosley, J.; Kuwera, E.; Kazanzides, P.; Green, K. E.
Show abstract
Annually, several million patients in the United States visit the emergency room (ER) with symptoms of vertigo or dizziness. Rapidly distinguishing between benign causes, such as inner ear disease, and more severe conditions, like strokes, necessitates performing and interpreting a three-step bedside head and eye movement assessment called HINTS (head impulse, nystagmus, and test of skew). This test is more accurate than state-of-the-art brain imaging, especially early in the diseases course when there is a limited window for safely conducting lifesaving stroke interventions. A significant barrier to its widespread adoption is the shortage of experts trained to safely perform and interpret this test in the ER. This highlights the need for automated remote assessments. In response, we developed TeleAutoHINTS as a two-part solution: (1) a head-mounted display-based head and eye tracking platform, using Microsoft Hololens2, for automated tele-sensing and (2) an interconnected interface for real-time data visualization and analysis. We tested TeleAutoHINTS on three subjects to assess the feasibility of automated testing and evaluate the head and eye movement recordings. Preliminary results suggest that a head-mounted display-based remote self-assessment platform for acute vertigo diagnosis is technically feasible.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Influence of open-source virtual-reality based gaze training on navigation performance in Retinitis pigmentosa patients in a crossover randomized controlled trial 95%
- Salzburg Visual Field Trainer (SVFT): A virtual reality device for (the evaluation of) neuropsychological rehabilitation 95%
- What do blind people "see" with retinal prostheses? Observations and qualitative reports of epiretinal implant users 93%
Similar papers in this journal
- Automated Image Transcription for Perinatal Blood Pressure Monitoring Using Mobile Health Technology 93%
- Use of assistive technology to assess distal motor function in subjects with neuromuscular disease 91%
- Implementation and prospective real-time evaluation of a generalized system for in-clinic deployment and validation of machine learning models in radiology 91%
Similar papers in this journal
- Accurate detection of non-proliferative diabetic retinopathy in optical coherence tomography images using convolutional neural networks 92%
- The Role of the Eyes: Investigating Face Cognition Mechanisms Using Machine Learning and Partial Face Stimuli 89%
- Reliable data collection in participatory trials to assess digital healthcare apps. 89%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.