DOI: 10.5281/zenodo.18789091
title: Dataset for RehabApp

description: ----------------------------------------------------------------------------------------------------------------------------------------Dataset for RehabApp----------------------------------------------------------------------------------------------------------------------------------------

* ReadMe version: 1.1 (2026-02-27)* Dataset version: 1.0 (2026-02-25)* Dataset DOI: 10.5281/zenodo.18789091

--------------------------------------------------------------------CONTACT--------------------------------------------------------------------* Jan Kohout* jan.kohout@vscht.cz* +420 220 44 027* ORCID: 0000-0003-1591-2777* Department of Mathematics, Informatics and Cybernetics, Faculty of Chemical Engineering, University of chemistry and Technology, Prague* Technicka 5, 166 28, Prague 6, Czech Republic

______Creators______* Karel Štícha (0000-0003-0518-4702), University of chemistry and Technology, Prague* Jan Kohout (0000-0003-1591-2777), University of chemistry and Technology, Prague* Jan Mareš (0000-0003-4693-2519), University of chemistry and Technology, Prague--------------------------------------------------------------------DATA AVAILABILITY AND ACCESS INSTRUCTIONS--------------------------------------------------------------------Given the sensitive nature of the dataset, ethical and legal reasons prevent us from publishing the dataset openly. However, access to the dataset may be requested through the contact person listed above, pending verification, decision of the ethical committee and NDA.--------------------------------------------------------------------LICENSE--------------------------------------------------------------------______ReadMe file licence______* ReadMe by [Name Surname] is licensed under CC BY 4.0* Licence information: https://creativecommons.org/licenses/by/4.0/

______Dataset licence______* N/A--------------------------------------------------------------------DESCRIPTION AND METHODOLOGY--------------------------------------------------------------------

______About the dataset______This dataset contains time-series recordings of facial movements captured using a Kinect stereo-vision camera (Microsoft, USA) in patients after head and neck surgery who developed facial paresis. The purpose of the dataset is to support objective assessment of rehabilitation progress using a simplified House–Brackmann (HB) scale. Each sample consists of complex 3D trajectories of facial landmarks measured over time.

______Sample preparation______Patients performed standardized facial tasks while being recorded with the Kinect system (Microsoft, USA). Each measurement includes sequences of 3D landmark positions. To balance class frequencies, HB4 samples were merged into HB3 and HB5 samples into HB6, resulting in four final HB categories for analysis.

______Methods of data collection______Data were collected using a Kinect stereo-vision camera (Microsoft, USA), capturing 3D spatial coordinates of facial landmarks over time. The dataset contains 122 measurements from 93 study participants who signed an informed consent form. Each measurement includes multiple time curves representing the movement of facial points.

______Methods of data processing______Processing involves extracting time-dependent trajectories of facial landmarks. Several supervised learning methods were tested for HB scale classification:Neural networks.- --------------------------------------------------------------------FILE TYPES & FORMATS, SW TO OPEN AND DIMENSIONS & UNITS--------------------------------------------------------------------File format: The dataset is provided as a single exported data file derived from our internal database (CSV).

______Content______ Time-series of 3D facial landmark coordinates as used in the referenced study (collections of time curves).

Units:- Spatial coordinates: meters (according to Kinect measurement conventions).- Time: seconds or frame indices.

______Software compatibility______Python (NumPy/Pandas), MATLAB, R — for numerical analysis.Any standard tool capable of reading structured text data.