Skip to content


Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?

Latest commit


Git stats


Failed to load latest commit information.
Latest commit message
Commit time

Feature-based time-series classification

Here, we consider a time series as a sequence of its segments approximated by parametric models (e.g. autoregressive model, discrete Fourier transform, discrete wavelet transform). The parameters of the approximating models are used as time-series' features.
Then, we generalize this approach and use the distributions of the parameters estimated for models approximating different time-series' segments.

The proposed approach is applied to the problem of human activity recognition from accelerometer data.


M. E. Karasikov, V. V. Strijov, Feature-based time-series classification, Inform. Primen., 2016, Volume 10, Issue 4, 121–131.
DOI: 10.14357/19922264160413
pdf: full text

Matlab code

Matlab code resides in code.

Python code

All code rewritten in Python for reproducing experiments from the paper can be found in code/python.

Interactive human activity recognition application

An interactive online application is running on The source code resides in code/activity_prediction.


The full code of the demonstration server can be found in code/activity_prediction/server.

Android client application

To get the full code of the android application, unpack ActivityPrediction.rar in code/activity_prediction/android.