04.08.16
STMicroelectronics has introduced three additions to its Open.MEMS portfolio of free software libraries for the development of motion-sensing applications. The new libraries allow designers to combine ST’s world-leading motion-sensing technology with an array of price/power/performance options offered by the STM32, ARM Cortex-M 32-bit microcontroller family. This provides a 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 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. • 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
• 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.
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 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. • 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
• 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.