Publications

Preprints, manuscripts, and journal submissions from my research work.

Featured paper

Published on arXiv and currently submitted to IEEE.

arXiv 2512.22690 Dec 2025
Submitted to IEEE

Mesquite MoCap: Democratizing Real-Time Motion Capture with Affordable, Bodyworn IoT Sensors and WebXR SLAM

Authors: Poojan Vanani, Darsh Patel, Danyal Khorami, Siva Munaganuru, Pavan Reddy, Varun Reddy, Bhargav Raghunath, Ishrat Lallmamode, Romir Patel, Assegid Kidané, Tejaswi Gowda

Mesquite is an open-source, low-cost inertial motion capture system that pairs a 15-node IMU suit with a hip-worn smartphone for position tracking. A web-native stack (WebGL, WebXR SLAM, WebSerial, WebSockets) enables real-time visualization in the browser. Benchmarks report 2-5 degree joint-angle error, ~15 ms latency, and 99.7% packet delivery at roughly 5% of the cost of commercial optical systems.

Motion Capture IoT Sensors WebXR WebGL Open Source