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一歩先へ:センサ・フュージョン内蔵の6軸IMU / AI / Qvarセンサ

An advanced inertial module with intelligent on-chip functionalities for high-end applications, including UI support

 

With a triple core, 6-axis architecture, the LSM6DSV16X Inertial Measurement Unit can handle advanced processing in the edge, making it ideal for advanced 3D phone mapping, context awareness in laptops and tablets, reliable and precise gesture recognition in AR and VR headsets, and always-on tracking in wearables.

LSM6DSV16X enables sensor fusion low power (SFLP), on-the-fly self-configuration, and AI algorithms. The IMU performs the data processing directly in the MEMS sensor, which enables significant energy savings in the system.

Thanks to its triple sensing core, the LSM6DSV16X can address the needs of user-interface controls and optical/electronic image stabilization (OIS/EIS).

Stay one step ahead with the LSM6DSV16X, enabling the Onlife Era.

 

Embedded features

  • 3-axis digital accelerometer and a 3-axis digital gyroscope 
  • Finite State Machine (FSM) to quickly detect events
  • Machine Learning Core (MLC) for accurate and reliable AI algorithms
  • Automatic System Configuration (ASC) for device self-configuration
  • Sensor Fusion Low Power (SFLP) for always-on spatial orientation
  • Configurable pedometer to accurately track footsteps
  • Qvar®, electrical potential sensing channel for advanced UIs
  • Three cores that can be configured to address the requirements of:
    • User interfaces
    • Optical Image Stabilization
    • Electrical Image Stabilization

 

Augmented with our ST Qvar sensor that detects electrostatic variations.

 

 

 

  LSM6DSV16X application examples

 

 

 

 

 

Personal electronics

Did you know that carrying a laptop in a backpack that is not properly shut down can drain your battery? ST’s new 6-axis sensor is the first of its kind to offer context recognition, bringing a whole new level of experience to users, while preserving the battery.

 

 

 

Smartphones

While 3-axis MEMS sensors enable various basic functionalities, such as wake up modes or screen orientation, ST’s 6-axis motion-tracking sensor provides additional information on the environment. Developers can now create new services or improve existing ones, without draining the battery.


 

 


Wearables

Do not take customers for granted! After years of double-digit growth, questions remain about how reliable wearables are. Ultralow-power, ST’s always-on 6-axis sensor has been designed to boost accuracy in power-constraint applications, including wearables.

 

 

Metaverse

Easily enter the metaverse and create lifelike animated avatars with ST’s new AI-enabled 6-axis motion sensor. Build a fully immersive experience with ST’s ecosystem and replicate body gestures in real time.

 

 

 

 

 

Discover our latest generation IMU sensor: LSM6DSV16X

Need to design with a 6-axis MEMS? Are you wondering how low the power consumption is? Or how small the package is? Our latest 6-axis IMU LSM6DSV16X will help you overcome engineering challenges …. And not just power and size!

  Recommended resources

User-friendly LSM6DSV16X evaluation board with Qvar electrostatic sensor

This flexible adapter board comes with the complete LSM6DSV16X pinout and is ready-to-use with the required decoupling capacitors on the VDD power supply line. Compatible with our ready-to-use MEMS motherboard (STEVAL-MKI109V3) development platform, it includes three different electrodes for finger swipe and hold gestures.


 

 

 

 

 

 

 

AlgoBuilder graphical design software for quickly building and deploying algorithms

Quickly implement proofs of concept using an easy and intuitive graphical interface for programming sensors without having to write code and visualizing data using in real time using plot and display functions.

 

 

X-CUBE-MEMS1: Sensor and motion algorithm expansion software package for STM32Cube

Comprehensive solution with drivers that recognize the sensors and collect temperature, humidity, pressure, and motion data. Package includes sample applications and a wide range of advanced motion libraries.

 

 

 

GitHub projects

 
Configuration examples for embedded Machine Learning Core feature
 
Configuration examples for embedded Finite State Machine feature