LSM6DSL for Motion Tracking—Best Power Optimization Techniques?

[ahsrabrifat]

Hey everyone,

I’m working on a low-power motion tracking project using an LSM6DSL IMU to capture 3D acceleration and gyroscope data. This sensor is interesting because it has an "Always-On" mode, which is supposed to keep motion detection running with minimal power consumption.

I came across this article: LSM6DSL iNEMO Inertial Module – Always-On 3D Accelerometer and 3D Gyroscope, which explains the features and power management modes, but I still have some questions:

• What’s the most efficient way to configure the power modes to maximize battery life while maintaining good motion tracking performance?

• Has anyone used the embedded finite state machine (FSM) or machine learning core (MLC) in this IMU to reduce processing overhead on the MCU?

• Any real-world tips for reducing noise and drift when using this sensor in a wearable or mobile setup?

Looking forward to insights from anyone who has worked with LSM6DSL or similar IMUs!

[Federica Bossi]

Hi @ahsrabrifat ,

You can use the low power mode to reduce power consumption by lowering the output data rate (ODR) and disabling certain features. It is suitable for applications where high-frequency data is not critical.

Alternatively, you can choose Normal Mode that provides a balance between power consumption and performance. It is suitable for most motion tracking applications.

If you want to use FSM and MLC you need to choose another product, for example LSM6DSV16X. In the documentation you can find AN5882 and AN5804 which explain how to set them.

To reduce noise and drift you can:

1. Calibrate the sensor by placing the sensor in a known orientation and adjusting the readings accordingly.

2. Apply filters such as low-pass filters to reduce high-frequency noise. The LSM6DSL has built-in filtering options that can be configured to suit your needs.

3.  Mount the sensor on a stable platform and minimize vibrations from external sources. Be aware of temperature changes and other environmental factors that can affect sensor performance.