2.2.1. Training and Validation Data Acquisition

For the purpose of training and validating the trained model, XC-skiing data from 3 professional skiers (Table 2) from the Korea National Sport University was collected. They performed the classical and skating XC-skiing techniques on outdoor flat and natural courses in Pyeongchang, South Korea, where the 2018 Winter Olympic Games took place. All of them were informed of the purpose of this study and they participated voluntarily in the experiment after reading the research guidelines and signing consent forms. The study was ethically approved by the Korea National Sport University Institutional Review Board (IRB Number 20170424-004).


3 Male 23 69 176

**Table 2.** General characteristics of the three professional skiers that participated in the study.

In the training dataset, each skier performs only one technique of either the classical or skating styles on the flat course repeatedly. Each subject performs 5–6 laps of each technique on a 500 m long track. As there are 8 techniques (4 classical and 4 skating) and 3 skiers, a total of 24 such files are obtained. In the validation dataset, each skier is allowed to perform either all the 4 classical or skating techniques on either a 2.5 km long flat or natural course, similar to what he/she would perform under competitive conditions. The skiers are free to make transitions from one technique to the other; however, the skiing style remains the same. A total of 11 files are obtained in this manner (1 file could not be obtained due to unavailability of the tracks). For both the datasets, a video recording of the skiers while performing the skiing techniques is also shot. Table 3 lists the type of data collected for each subject. In order to examine whether our developed model could classify skiing techniques for skiers with different skill levels, we allowed the skiers to freely choose their own preferred skiing speeds and exercise intensities during the data collection.

**Table 3.** Training and validation data collected for three professional skiers characterized by the type of course (flat/natural) and the number and type of skiing techniques (classical/skating) that the subject is allowed to perform simultaneously.


X: The classical style data on the natural course for skier 1 is not available.

Each file in the training data exclusively contains the data of one of the techniques of one of the skiing styles, and hence does not require any labelling. However, the 4 techniques of each XC-skiing style in validation data are performed in a combined way and hence have to be labelled after data collection. The ground truth labels for the validation data are developed by professional cross-country skiing players from the Korea National Sport University by simultaneously watching the recorded video from a digital camera, human model video from the *XSens MVN Analyze*, and marking the frames corresponding to each technique in the raw data files. Labelling follows a 0–9 convention for each file: 0: start/end of the recording, 1: DS, 2: P-Off, 3: KDP, 4: DP, 5: V2, 6: V2A, 7: V1, 8: FS, 9: descending). The labels have been double checked by a professional XC skiing coach at the Korea National Sport University.
