NaveGo: an open-source MATLAB/GNU Octave toolbox for processing integrated navigation systems and performing inertial sensors analysis.

LiDAR-Inertial 3D Plane Simulator

ROS driver for all of MicroStrain's current G and C series products. To learn more visit

Deep Learning-Based Gait Recognition Using Smartphones in the Wild

MicroStrain Communication Library

Neural-Kalman GNSS/INS Navigation for Precision Agriculture

Human whole-body pose estimation using MARG multi-sensor data

Robot Motion Estimate: Tools, Variables, and Factors for SLAM in robotics; also see Caesar.jl.

TinyOdom: Hardware-Aware Efficient Neural Inertial Navigation

Vision Benchmark in Rome Development Kit

Intelligent Vehicle Perception Based on Inertial Sensing and Artificial Intelligence

sbgECom is a C library used to communicate with SBG Systems IMU, AHRS and INS

MATLAB implementation of dual foot-mounted inertial navigation system.

Auritus: An Open-Source Optimization Toolkit for Training and Development of Human Movement Models and Filters Using Earables

This repository was written to help analyze the Virginia Tech Natural Motion Dataset. The dataset contains 40 hours of unscripted human motion collected in the open world using XSens MVN Link. The dataset, metadata and more information is available through the Virginia Tech University Libraries: https://data.lib.vt.edu/articles/dataset/Virginia_…

PyJama is a friendly python library for analyzing human kinematics data. Aimed at analyzing data from IMU's, MIMU's, data from optical devices and in the future tracking data from deeplearning models.

MATLAB implementation of gait cycle validation and segmentation using inertial sensors.

CircuitPython code to detect motion of the Seeed XIAO nRF52840 Sense and send Bluetooth Low Energy (BLE) advertisements in the BTHome format when it's moving

Master Thesis - Continuous Authentication using Inertial-Sensors of Smartphones and Deep Learning

A python DIgital Signal ProcEssing Library developed to standardize extraction of sensor-derived measures (SDMs) from wearables or smartphones data.