STMicroelectronics' Motion Sensor has Improved Activity Tracking
February 21, 2019
The LSM6DSOX iNEMO sensor contains a machine learning core to classify motion data based on recognizable patterns.
STMicroelectronics has integrated machine learning technology into its advanced inertial sensors to improve activity-tracking performance and battery life in mobiles and wearables. The LSM6DSOX iNEMO sensor contains a machine learning core to classify motion data based on recognizable patterns.
The LSM6DSOX contains a 3D MEMS accelerometer and 3D MEMS gyroscope and has a common current consumption of 0.55mA. The machine learning core uses the sensor’s integrated finite-state machine logic to handle motion pattern recognition or vibration detection. Users can train the core for decision-tree-based classification using Weka to generate settings and limits from sample data such as acceleration, speed, and magnetic angle.
Support for free-fall, wakeup, 6D/4D orientation, click and double-click interrupts enable a wide variety of applications such as user-interface management and laptop protection in addition to activity tracking.
For more information, visit www.st.com.