Unicleo-GUI is a graphical user interface (GUI) for the X-CUBE-MEMS1 and X-CUBE-MEMS-XT1 software expansions and STM32 Nucleo expansion boards (X-NUCLEO-IKS01A1, X-NUCLEO-IKS01A2 and X-NUCLEO-IKS01A3).
The main objective of this application is to demonstrate the functionality of ST sensors and algorithms.
Unicleo-GUI is able to cooperate with firmware created by AlgoBuilder application and display data coming from the running firmware.
The application is also able to establish Bluetooth connection with BLE connectivity-equipped devices such as SensorTile (STEVAL-STLKT01V1), BlueCoin (STEVAL-BCNKT01V1), and STM32 Nucleo with X-NUCLEO-IDB05A1 expansion board, BlueTile (STEVAL-BCN002V1B) or WESU1 (STEVAL-WESU1) and read data from various device characteristics.
The supported firmware for these devices can be found at FP-SNS-ALLMEMS1, FP-SNS-MOTENV1, STSW-BLUETILE-DK and STSW-WESU1.
- Displays data from connected sensors in various views (time plot, scatter plot, 3D plot)
- Saves data to tab separated (TSV) or comma separated (CSV) files
- Configurable output data rate and full scale
- Directly reads from and writes to sensor registers
- Demonstrate sensor Finite State Machine (FSM) and Machine Learning Core (MLC) embedded features
- Works with X-CUBE-MEMS1 and X-CUBE-MEMS-XT1 sensor sample applications (Datalog, DatalogExtended, FFT Demo, DatalogLite)
- Works with sample applications for algorithms (Activity Recognition, Carry Position, Gesture Recognition, Sensor Fusion, Pedometer, Magnetometer Calibration, Accelerometer Calibration, Gyroscope Calibration, Activity Recognition for Wrist, Pose Estimation, Motion Intensity Detection, Fitness Activity, eCompass, Active Time, Fall Detection, Pedometer for Wrist, Standing vs Sitting Desk Detection, Tilt Sensing, Vertical Context)
- Works with firmware created by AlgoBuilder
- Windows®-based application
Unicleo-GUI is a graphical user interface (GUI) for the X-CUBE-MEMS1 software expansion and STM32 Nucleo expansion boards (X-NUCLEO-IKS01A1 and X-NUCLEO-IKS01A2). The main objective of this application is to demonstrate the functionality of ST sensors and algorithms supported by X-CUBE-MEMS1.