Smart sensor from Bosch unlocks high-impact motion tracking
Bosch’s latest BHI385 sensor provides accurate acceleration measurement up to ±28 g – enabling it to capture peak movement, such as a golf swing or tennis smash, and provide the most precise insights.
With a measurement range of up to ±28 g, the BHI385 enables precise motion analysis for high-impact events across sports, fitness, and gaming. The sensor combines a gyroscope and accelerometer with embedded AI software and an integrated 32bit microprocessor, creating a complete programmable system based on Bosch Sensortec’s field-proven IMU platform.
The BHI385 builds on the successful BHI360 sensor generation and adds advanced programmability and self-learning AI – making it ideal for applications such as personalized coaching, sport-specific feedback or gesture-controlled interfaces.
The BHI385’s embedded AI supports key motion functions including 6DoF/9DoF sensor fusion, step counting, activity recognition, and gesture detection (single/double/triple tap). Self-learning cyclic gesture recognition allows it to detect repeated motion patterns and adapt them to the individual – not only recognizing what is being done, but also how well it is being performed. This enables advanced use cases such as quality-of-movement evaluation in sports or rehabilitation training.
All processing runs on the integrated low-power processor, avoiding wake-up calls to the host CPU. Typical current consumption is less than 500 μA at 50 Hz for sensor fusion, and under 50 μA for simpler accelerometer-based algorithms.
The BHI385 is offered in a compact 20-pin LGA package measuring 2.5 x 3.0 x 0.95 mm³. Its low power consumption and embedded intelligence make it a perfect fit for wearables, hearables, and edge AI systems. To support fast time-to-market, Bosch Sensortec provides developers with Motion AI Studio and an Open SDK for custom ML model integration.
The BHI385 is particularly suited to applications such as sport activity tracking, detailed movement evaluation including technique analysis, and embedded ML processing for wearables. Its high acceleration range and smart algorithms also make it ideal for impact and collision detection as well as intuitive human-machine interaction via motion control.
Target devices include smartwatches and fitness bands, specialised sports wearables such as smart clothing, head-mounted devices for AR/VR and audio use, and connected fitness or gaming equipment. These devices benefit from the BHI385’s compact design, embedded intelligence, and advanced motion tracking capabilities.
