LSM6DSV16X datasheet(7/196 Pages) STMICROELECTRONICS

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2.6

Machine learning core

The LSM6DSV16X embeds a dedicated core for machine learning processing that provides system flexibility,

allowing some algorithms run in the application processor to be moved to the MEMS sensor with the advantage of

consistent reduction in power consumption.

Machine learning core logic allows identifying if a data pattern (for example motion, pressure, temperature,

magnetic data, and so forth) matches a user-defined set of classes. Typical examples of applications could be

activity detection like running, walking, driving, and so forth.

The LSM6DSV16X machine learning core works on data patterns coming from the accelerometer and gyro

sensors, but it is also possible to connect and process external sensor data (like magnetometer or pressure

sensor) by using the sensor hub feature (mode 2).

The input data can be filtered using a dedicated configurable computation block containing filters and features

computed in a fixed time window defined by the user. Computed feature values and filtered data values can also

be read through the FIFO buffer.

Machine learning processing is based on logical processing composed of a series of configurable nodes

characterized by "if-then-else" conditions where the "feature" values are evaluated against defined thresholds.

Figure 4. Machine learning core in the LSM6DSV16X

Machine

Learning Core

Logical processing

Sensor

Data

Computation

Block

Decision

Tree

Accelerometer

Results

Gyroscope

External

Sensor

Features

Filters

Meta-classifier

The LSM6DSV16X can be configured to run up to 4 decision trees simultaneously and independently and every

decision tree can generate up to 16 results. The total number of nodes can be up to 128.

The results of the machine learning processing are available in dedicated output registers readable from the

application processor at any time.

The LSM6DSV16X machine learning core can be configured to generate an interrupt when a change in the result

occurs.

2.7

Adaptive self-configuration (ASC)

The LSM6DSV16X supports the adaptive self-configuration (ASC) feature, which allows the FSM to automatically

reconfigure the device in real time based on the detection of a specific motion pattern or based on the output of a

specific decision tree configured in the MLC, without any intervention from the host processor. The FSM can write

a subset of the device registers using the SETR command, which allows indicating the register address and the

new value to be written in such a register. The access to these device registers is mutually exclusive to the host.

LSM6DSV16X

Machine learning core

DS13510 - Rev 1

page 7/196

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