Motion Sensor Uses Machine Learning For Activity Tracking

STMicroelectronics is integrating machine-learning technology into its 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 known patterns. Relieving this first stage of activity tracking from the main processor saves energy and accelerates motion-based apps such as fitness logging, wellness monitoring, personal navigation, and fall detection.

 

The LSM6DSOX sensor also has more internal memory than conventional sensors, and a state-of-the-art high-speed I3C digital interface. It is said to be easy to integrate with popular mobile platforms such as Android and iOS, simplifying use in smart devices for consumer, medical, and industrial markets.

Free Newsletter

Like this article? Subscribe to FierceSensors!

The sensors industry is constantly changing as innovation runs the market’s trends. FierceSensors subscribers rely on our suite of newsletters as their must-read source for the latest news, developments and analysis impacting their world. Register today to get sensors news and updates delivered right to your inbox.

 

The LSM6DSOX is in full production and available now, priced from $2.50 each/1,000. For more information, checkout the LSM6DSOX datasheet.

Suggested Articles

MarketsandMarkets says the low-light imaging market is expected to grow from $10.04 billion in 2019 to $18.36 billion by 2024.

SiC can make medical devices more perceptive, it can make electronics more energy-efficient, and it can help sensors perform in higher temperatures.

Components supplier CTS Corporation has acquired temperature sensor supplier Quality Thermistor, Inc. (QTI), for $75 million in cash.