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iNEMO engine software libraries

iNEMO engine features multi-sensor data fusion.

The iNEMO engine sensor fusion suite is a filtering and predictive software. It uses advanced algorithms to integrate outputs from multiple MEMS sensors in a smart way, independently of environmental conditions, to reach the best performance. Real-time motion-sensor data fusion is set to significantly improve the user experience, increasing accuracy, resolution, stability and response time in advanced motion-based applications in consumer, computer, industrial and medical fields. The iNEMO engine can be combined with ST’s iNEMO inertial modules to create the industry’s first complete and customizable hardware/software multi-axis MEMS sensor solutions for enhanced motion and accurate heading recognition. Equipment manufacturers across different market segments can now easily and quickly deploy robust and reliable high-performance motion detection systems with up to 10 degrees of freedom, comprising 3-axis sensing of linear, angular, and magnetic motion with barometer/altitude readings from a pressure sensor, enabling true augmented-reality applications.


  • Absolute point tracking and motion tracking accuracy
  • Immunity to magnetic interference for high performance in real-world conditions
  • Few user-calibration interruptions, enabling innovative and longer game play
  • Reliable compass heading for accurate navigation
  • Accurate direction, enabling true augmented-reality applications

 Software version


iNEMO-ENG-M1LI3 LITE version for
M1 System on Board

iNEMO Engine LITE version for iNEMO-M1: Based on the Kalman filter theory applied to MEMS sensors,
the iNEMO-M1 lite software library is a free source code that could be used for the STM32 and for
customizable HW/SW solutions.

iNEMOEngine_PW8 PRO version for Windows 8

This firmware running on the STM32 manages sensors on Windows 8 using the standard human interface devices (HID) over USB/I²C (compatible with Intel x86 and ARM processors). Allows sensor plug-and-play recognition and new application development using Windows 8 standard APIs.

It includes the PRO version of iNEMO Engine.

iNEMOEngine_PI3P PRO version for STM32

This firmware allows you to develop new custom applications running on the STM32 or to collect real-time sensor fusion data thorough Virtual COM from any platform (platform independent).

It includes the PRO version of iNEMO Engine.

iNEMOEngine_PAAP PRO version for Android

This is a complete solution to support Android platforms by providing the hardware abstraction layer, sensor drivers and sensor fusion library.

It includes the PRO version of iNEMO Engine.

iNEMOEngine PRO version Platform independent

iNEMO Engine PRO version compiled for 32bit microcontrollers.

It includes the PRO version of iNEMO Engine.

Game rotation vector (6-axis sensor fusion, Accelerometer + Gyroscope)

iNEMO Engine sensor fusion library based on accelerometer and gyroscope giving output in quaternion format.

It includes the PRO version of iNEMO Engine.

Geomagnetic vector (6-axis sensor fusion, Accelerometer + Magnetometer)

iNEMO Engine sensor fusion library based on accelerometer and magnetometer giving output in quaternion format.

6-axis Virtual Gyro (Accelerometer + Magnetometer)

This library simulate the output of a gyroscope using accelerometer and magnetometer data in order to reduce the overall power consumption of the system.

Tilt compensated eCompass

The library implements a tilt compensated  compass using Accelerometer and Magnetometer and include basic hard iron calibration.

Calibration is performed using defined movement to calibrate the sensor: rotation of 360° on horizontal plane and on orthogonal plane.

Dynamic Magnetometer Calibration

Hard and Soft Iron calibration library for magnetometer.

It supports two functional mode: Triggered Calibration or Always on calibration (Background Calibration) allowing auto-calibration through 8-movement.


The library implements the pedometer function (steps counting, distance and speed calculation, calories burned) using the output data of a MEMS accelerometer.


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