collaborators

6 papers

cs.RO2025

Simultaneous Estimation of Manipulation Skill and Hand Grasp Force from Forearm Ultrasound Images

Keshav Bimbraw, Srikar Nekkanti, Daniel B. Tiller +4

Accurate estimation of human hand configuration and the forces they exert is critical for effective teleoperation and skill transfer in robotic manipulation. A deeper understanding…

cs.CV2024

Hand Gesture Classification Based on Forearm Ultrasound Video Snippets Using 3D Convolutional Neural Networks

Keshav Bimbraw, Ankit Talele, Haichong K. Zhang

Ultrasound based hand movement estimation is a crucial area of research with applications in human-machine interaction. Forearm ultrasound offers detailed information about muscle…

cs.CV2024

Improving Intersession Reproducibility for Forearm Ultrasound based Hand Gesture Classification through an Incremental Learning Approach

Keshav Bimbraw, Jack Rothenberg, Haichong K. Zhang

Ultrasound images of the forearm can be used to classify hand gestures towards developing human machine interfaces. In our previous work, we have demonstrated gesture classificatio…

cs.CV2024

Forearm Ultrasound based Gesture Recognition on Edge

Keshav Bimbraw, Haichong K. Zhang, Bashima Islam

Ultrasound imaging of the forearm has demonstrated significant potential for accurate hand gesture classification. Despite this progress, there has been limited focus on developing…

cs.HC2024

Random Channel Ablation for Robust Hand Gesture Classification with Multimodal Biosignals

Keshav Bimbraw, Jing Liu, Ye Wang +1

Biosignal-based hand gesture classification is an important component of effective human-machine interaction. For multimodal biosignal sensing, the modalities often face data loss…

cs.CV2024

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

Keshav Bimbraw, Ye Wang, Jing Liu +1

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 power…