GPT Sonograpy: Hand Gesture Decoding from Forearm Ultrasound Images via VLM

Keshav Bimbraw, Ye Wang, Jing Liu, Toshiaki Koike-Akino

Keywords: GPT, LLM, VLM, Ultrasound Imaging, Human-Machine Interface, Gesture Decoding

TL;DR: In-Context Learning of Forearm Ultrasound Images to predict Hand Gesture

Abstract: Large vision-language models (LVLMs), such as the Generative Pre-trained Transformer 4-omni (GPT-4o), are emerging multi-modal foundation models which have great potential as powerful artificial-intelligence (AI) assistance tools for a myriad of applications, including healthcare, industrial, and academic sectors. Although such foundation models perform well in a wide range of general tasks, their capability without fine-tuning is often limited in specialized tasks. However, full fine-tuning of large foundation models is challenging due to enormous computation/memory/dataset requirements. We show that GPT-4o can decode hand gestures from forearm ultrasound data even with no fine-tuning, and improves with few-shot, retrieval augmented in-context learning.

Submission Number: 87