STMicroelectronics Releases New MEMS Libraries For Detection of Human Activities
New Software Can Identify Movements, such as Running, Walking, Cycling and Driving
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
world-leading motion-sensing technology with the huge array of price/power/performance options offered by the STM32,
the world's most popular ARM®Cortex®-M 32-bit microcontroller family. This provides an ideal route to
implementing contextual awareness in mobile, wearable, and IoT (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.
The three new software packages are:
- The osxMotionAR Activity 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 osxMotionCP Carry 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 or 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 (50Hz).
- The osxMotionGR Gesture 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 100Hz 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 allows software developers to rapidly build and customize leading-edge motion-driven applications for the different use cases.
This software has now been replaced by the X-CUBE-MEMS1 software, for more information visit the ST website at
ST X-CUBE-MEMS1 software main page.
The company's Web site address is www.st.com.
[Reprinted with kind permission from STMicroelectronics - Release Date, 7th April, 2016]