SparkFun 6DoF IMU Breakout - BMI270 (Qwiic)

The SparkFun BMI270 6DoF IMU Breakout is a versatile, Qwiic-enabled breakout board, offering a highly integrated, low-power IMU from Bosch. It is designed to deliver precise acceleration and angular rate measurements, making it an optimal choice for wearable tech. The BMI270 is not just a simple accelerometer and gyroscope combo, but it also boasts a range of intelligent, on-chip, motion-triggered interrupt features.

This Qwiic BMI270 IMU Breakout measures 2.54cm x 2.54cm, allowing for easy integration into your projects with the use of solderless Qwiic cables and compatible controllers. For those who prefer traditional breadboards, all IO pins have been broken out to 2.54mm spaced pin headers on the sides of the board. The board also features on-board solder jumpers for easy selection of the device address, removal of the I²C pull-ups, and disabling of the power LED if required.

The 6-axis sensor combines a 16-bit tri-axial gyroscope and a 16-bit tri-axial accelerometer, using Bosch’s automotive-proven gyroscope technology. The BMI270 offers several functionalities, such as an integrated step counter/detector and gesture detection, making it ideal for wrist-worn devices. This IMU is perfect for wearables, smart clothes, smart shoes, smart glasses, and ankle bands.

The SparkFun Qwiic Connect System is an ecosystem of I²C sensors, actuators, shields, and cables designed to make prototyping faster and less error-prone. All Qwiic-enabled boards use a common 1mm pitch, 4-pin JST connector, reducing the amount of required PCB space and ensuring polarized connections for foolproof hook-ups.

The SparkFun Qwiic BMI270 6DoF IMU Breakout comes with a range of features including a 16-bit 3-axis accelerometer with a range of ±2g/±4g/±8g/±16g, a 16-bit 3-axis gyroscope with a range of ±125dps/±250dps/±500dps/±1000dps/±2000dps, and a 400kHz AUX sensor interface with hardware synchronization. It operates at 1.8V and 3.3V and has ultra-low current consumption. It also offers smart features like significant motion, any motion, motion detect, no motion, stationary detect, wrist wear wakeup, wrist-worn step counter, activity change recognition, and wrist gesture recognition.