Software simplifies human activity detection on mobile and wearable devices

April 7, 2016

Geneva, Switzerland. STMicroelectronics has introduced three additions to its Open.MEMS portfolio of free and easy-to-use software libraries for the development of best-in-class motion-sensing applications. The new libraries allow designers to combine the power of ST’s motion-sensing technology with the array of price/power/performance options offered by the STM32 ARM Cortex-M 32-bit microcontroller family. The libraries provide a route to implementing contextual awareness in mobile, wearable, and Internet of Things applications.

The new software allows the detection of human activities from data acquired by inertial sensors embedded in the end-user equipment. Optimized to minimize power consumption, they are particularly suited for fitness and healthcare applications in portable or wearable platforms that monitor human physical activities in real time over long periods.

Here are the three new software packages:

  • The osxMotionARActivity Recognition package is a high-performance algorithm that identifies the user activity from a wide range of movements and transportation scenarios such as stationary, walking, fast walking, jogging, cycling, and driving. Exploiting the high precision of ST’s LSM6DS3, LSM6DS3H, and LSM6DSL inertial modules, the Activity Recognition algorithm manages the data acquired from the sensors at a low sampling frequency and returns the identified activity in real time with a very low power consumption.
  • The osxMotionCPCarry Position package detects how the device containing the motion sensors is being carried. For example, the algorithm can detect whether a portable device such as a mobile phone is placed on a desk, held in hand to view the display, in a swinging arm, near the user’s head, or put in a shirt or trouser pocket. To minimize power consumption, sensor data is acquired at a low sampling frequency (50 Hz).
  • The osxMotionGRGesture Recognition package recognizes the actions carried out on a mobile or handheld device, including pick-up, glance, or wake-up, which allows designers to develop controls for different functions on the device. This algorithm acquires data from inertial modules with a sampling frequency of 100 Hz and recognizes the gestures carried out by the user platform in real time.

Based on the comprehensive STM32Cube software development tool, Open.MEMS libraries are part of the X-CUBE-MEMS1 expansion software package designed to run on the X-NUCLEO-IKS01A1 motion MEMS and environmental sensor expansion board.

Each Open.MEMS software package includes pre-compiled libraries for the most common development environments and examples expressly designed to quickly evaluate the outstanding features and performances of ST’s MEMS motion sensors.

The easy-to-use application programming interface (API) allows software developers to rapidly build and customize leading-edge motion-driven applications for the different use cases.

The new Open.MEMS packages are available now, free, to customers through a simple click-through license agreement.

About the Author

Rick Nelson | Contributing Editor

Rick is currently Contributing Technical Editor. He was Executive Editor for EE in 2011-2018. Previously he served on several publications, including EDN and Vision Systems Design, and has received awards for signed editorials from the American Society of Business Publication Editors. He began as a design engineer at General Electric and Litton Industries and earned a BSEE degree from Penn State.

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