LSM6DSL for Motion Tracking—Best Power Optimization Techniques

[bidrohini]

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!

[JamesMVictoria]

On 4/4/2025 at 11:17 PM, bidrohini said:

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!
 
Optimizing power with the LSM6DSL is essential for motion tracking in embedded systems. Pairing it with components like the IMX324-AAUG, known for its automotive-grade performance, can enhance motion accuracy while keeping power draw in check—especially in edge AI or smart vision applications.

I am replying here so that I can keep track of this thread.