This application supports three different sets of ST hardware boards:

• STEVAL-STLKT01V1 (aka SensorTile)
• X-NUCLEO-IDB05A1 and X-NUCLEO-IKS01A2 expansion boards
• B-L475E-IOT01A IoT Discovery board
  
  and runs over four different target configurations:
  
  
• Nucleo F401RE + X-NUCLEO-IDB05A1 + X-NUCLEO-IKS01A2 (set target NUCLEO_F401RE)
• DISCO_L475VG_IOT01A (set target DISCO_L475VG_IOT01A)
• Nucleo L476RG + CRADLE + SENSORTILE (set target NUCLEO_L476RG)
• Nucleo L476RG + CRADLE_EXPANSION_BOARD + SENSORTILE (set target NUCLEO_L476RG, remove macro MINI_CRADLE from mbed_app.json)

The first 2 configurations do not require any HW modifications (just use the above indicated targets).

Third configuration (CRADLE ) only requires to remove the two ST-LINK jumpers and JP6 from the Nucleo board in order to allow flashing the SensorTile through the Nucleo Jtag controller. Once flashed, if the battery is properly plugged and charged, the SensorTile could be mounted in the plastic enclosure being able to run as a small stand alone wearable device. Please note that this configuration do not provide a serial console for printf.

To enable last configuration (CRADLE_EXPANSION_BOARD), follow the steps below:

• On Nucleo L476RG
  • open the two "ST-LINK" jumpers
  • open the MCU power supply jumper JP6
  • close the solder bridges SB63 and SB62 (to enable the serial console)
• O SensorTile Arduino Cradle close the solder bridges SB21 and SB10 (to enable the serial console)
• Plug the Sensor Tile on the Arduino Cradle
• Plug the Cradle on the Nucleo Arduino connector and connect the debug flat cable between Cradle and Nucleo Jtag connector (the cradle pin1 -identified by a dot- must be connected to the Nucleo pin1 (dot) of SWD CN4 jtag connector)
• Plug the Nucleo USB cable on PC (a new COM port should appear)
• Open a PC terminal to see the messages
• Compile from mbed CLI or on-line compiler removing macro MINI_CRADLE from mbed_app.json file and selecting NUCLEO_ L476RG target
• Flash the board with the binary

For all configurations on an Android or iOS device download and open the ST BlueMS application and connect to "MotEnvMbedOS" BLE device to see the sensor data.

For all configurations is possible to add a 9 axysis MotionFX sensor fusion library, to do so download the library from http://www.st.com/content/st_com/en/products/embedded-software/mcus-embedded-software/stm32-embedded-software/stm32cube-embedded-software-expansion/x-cube-mems1.html The library comes in three flavours, choose your preferred according to the toolchain used (IAR, Keil or GCC) and copy it in the Middlewares\ST\STM32_MotionFX_Library\Lib directory changing the file extension according to the toolchain used.
In the file mbed_app.json add the macro definition "USE_SENSOR_FUSION_LIB" to the choosen target.
If compiling from CLI, in the file \mbed-os\tools\toolchains\gcc.py change the compiling option from

if target.core == "Cortex-M4F": self.cpu.append("-mfpu=fpv4-sp-d16") self.cpu.append("-mfloat-abi=softfp") to
if target.core == "Cortex-M4F": self.cpu.append("-mfpu=fpv4-sp-d16") self.cpu.append("-mfloat-abi=hard")

and recompile with "mbed compile" after having selected the target and the ARM_GCC toolchain