<p>There could be multiple possible ways to extract the features. One would be to use RNNs for a temporal relationship as the input data is time-series.</p>

CC BY-SA 4.0
2020-09-02T10:48:03.590Z
2020-09-02T10:48:03.590Z
Karan Dhingra
<p>I have IMU (Inertial Measurment Unit- 6 axis) sensor data. The sensor attached on a car and 7 different drivers wipe on same path. I want to extract features and classify drivers. Which type of feature extractor do you guys suggest? I am planning to use PCA and Autoencoders but what do you think about classical signal properties to classify drivers?</p>

<classification><autoencoders><time-series><feature-extraction><signal-processing>
Which type of feature extractor do you suggest to classify sensor data?
dasmehdix
# Which type of feature extractor do you suggest to classify sensor data?

(Asked by: username_0 on 2020-09-01)

I have IMU (Inertial Measurment Unit- 6 axis) sensor data. The sensor attached on a car and 7 different drivers wipe on same path. I want to extract features and classify drivers. Which type of feature extractor do you guys suggest? I am planning to use PCA and Autoencoders but what do you think about classical signal properties to classify drivers?

**Tags:** classification, autoencoders, time-series, feature-extraction, signal-processing


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## 1 answers

### Answer by username_1 on 2020-09-02. Score: 1 | Accepted answer

There could be multiple possible ways to extract the features. One would be to use RNNs for a temporal relationship as the input data is time-series.


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