This work explores the use of Augmented Reality as a tool to measure the malalignment of the lower limbs, reducing the dependence on radiographic exams and at the same time increasing the objectivity of the measurement through the automatic identification of the position of the joints in the patient’s body.

A wearable hand tracking glove built with ESP32, MPU IMUs, and an I2C multiplexer for precise real-time motion capture. Developed by Noviera Technologies as a foundation for next-gen VR/AR interaction, gesture recognition, and haptic integration. Open for experimentation, research, and collaboration.

Final project repository for Summer 2017 REU @ Clemson University.

KiCAD source files for Manuvr's motion capture glove.

A working posture dataset with full-body kinematics 3-D marker data

Self-supervised Learning of Motion Capture

Validation of Leap Motion Controller for finger kinematics

Datasets from THU-3DHuman

Arduino based table tennis shot predictor. Prediction is made in terms of probability, where the 4 type of gestures are assigned a probability. It can also be viewed as an accuracy score on your intended gesture if your training data is accurate enough.

This simple function permits to import properly all data stored in a txt file exported with Vicon Nexus

Automatically exported from code.google.com/p/ponyo-svn

A hardware design(PCB only) for SlimeVR Tracker

Tries to clean your dense mocap graphs like an animator would! So it will produce a usable artist friendly result while maintaining the original graph.

A clumnsy version of software aimed at evaluating the performance of a motion, supported by Myo armband.

A home surveillance system that will record video only when there is some kind of motion happens. This will help us to save the storage.

Motion detection based on Pythagorean-distance between consecutive frames & standard deviation of the frame.

Neurological Injury Motion Sensing (NIMS) Project

All my research findings, code and papers are available here

3D Scanning & Spatial Learning course: Volumetric Fusion project

Software tool for clinicians to better understand and evaluate bilateral coordination in children with cerebral palsy and other asymmetrical movement impairments. Work is ongoing.