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New AI-enhanced Smart Accelerometers from ST

New sensors integrate advanced processing engines for reliable activity detection and gesture sensing

STMicroelectronics has introduced three new accelerometers with advanced processing engines built-in to extend sensor autonomy, enabling systems to respond more quickly to external events while reducing power consumption.

New AI-enhanced Smart Accelerometers from ST

The LIS2DUX12 and LIS2DUXS12 leverage ST’s third-generation MEMS technology, adding programmable capabilities including machine-learning core (MLC), advanced finite state machine (FSM), and an enhanced pedometer. A third entry-level accelerometer, LIS2DU12, is also available for less demanding applications. All three new products are complete with the latest industry standard I3C interface. The three devices integrate the common digital features for detecting events, as well as an anti-aliasing filter for high accuracy at lower sampling frequencies with performance benefits for accurate gesture detection at negligible power consumption.

The integrated machine-learning core in the LIS2DUX12 and LIS2DUXS12 enables artificial-intelligence (AI) algorithms to perform reliable activity detection and the finite state machine enhances movement recognition. Together, they provide autonomous processing in the sensor, which offloads host interaction and processing, significantly lowering power consumption and enables faster system responses. In addition, by deploying an adaptive self-configuration (ASC) capability, the accelerometers adjust their own settings (such as measurement range and frequency) independently to further optimize performance making each milliampere count.

The LIS2DUXS12 also features ST’s unique Qvar® sensing channel that senses changes in the ambient electrostatic environment to provide presence and proximity detection. This capability lets developers add value to their products such as user-interface control, liquid detection, and biometric sensing such as heart-rate monitors. In user-interface applications, Qvar® combined with an acceleration signal removes potential false positive detection in two-tap and multi-tap events.

The smart accelerometers provide context sensing for state-of-the-art wearables devices, True Wireless Stereo (TWS) speakers and earbuds, smartphones, hearing aids, game controllers, smart watches, asset trackers, robotic appliances, and IoT devices. All three products leverage on STMicroelectronics latest ultra-low-power architecture, which combines inherently extremely low power consumption with the anti-alias filter that helps to boost application performance, removing unwanted noise from the signal. Ready-to-use MLC and FSM algorithms are available through ST’s MEMS GitHub model zoo, which facilitates complex gestures, asset tracking, and many other use cases.

Features of the LIS2DUX12 Accelerometer include:

  • Supply voltage range from 1.62 V to 3.6 V
  • Four operating power modes
  • Ultralow power consumption
  • Low noise: 220 µg/ √Hz
  • Programmable full scale: ±2/±4/±8/±16 g
  • ODR from 1.6 Hz to 800 Hz
  • Embedded machine learning core
  • Programmable finite state machine
  • Adaptive self-configuration
  • Embedded temperature sensor
  • Embedded FIFO: up to 512 samples of accelerometer and temperature data in high resolution or up to 768 samples of acceleration data at low resolution
  • High-speed I²C/SPI/MIPI I3C® digital output interface
  • Advanced pedometer, step detector and step counter
  • Significant motion detection, tilt detection
  • Self-test

More information on the LIS2DUX12 Accelerometer with AI is available on the ST website at STMicroelectronics LIS2DUX12 product page.

The STMicroelectronics website address is www.st.com
[Reprinted with kind permission from STMicroelectronics - Release Date, 21st March, 2023]