Preliminary Dataset for the evaluation of a framework designed for dataset creation for monitoring simultaneously the operator and remotely operated vehicle for anomalous command detection

Preliminary Dataset for the evaluation of a framework designed for dataset creation for monitoring simultaneously the human and remotely operated vehicle for anomalous command detection General Information: This dataset consists of data from 6 subjects during a mission with an unmanned aerial vehicle (UAV). Data fusion includes data from the human operator and the UAV following a predefined course. Our goal is the classification of abnormal/involuntary movements of the operator given on the controller of the UAV. Movements were annotated manually based on the videos collected. This dataset was constructed for a preliminary analysis, prior to constructing a larger dataset and the design of the framework for creating such datasets. Data monitored from the human-operator are the: - heart rate (HR, Polar HR Sensor OH1 was used for signal collection)- surface electromyography signals (sEMG) from the right hand only (MYO Armband was used for signals collection). Data from the inertial measurement unit (IMU) of the UAV consists of: - Accelerometer x, y, z- Gyroscope x, y, z- Magnetometer x, y, z- Altitude- Relative height The procedure followed for the data acquisition is described in: Elia, R., Plastiras, G., Pettemeridou, E., Savva, A., & Theocharides, T. (2022). A real-world data collection framework for a fused dataset creation for joint human and remotely operated vehicle monitoring and anomalous command detection. CAAI Transactions on Intelligence Technology, 7(3), 432-445. Dataset In total there are three items that should be downloaded: (1) the zip folder 'Dataset.zip' containing the data, (2) the text file 'Dataset Description.txt' with all the necessary information for each folder, and (3) the text file 'Readme.txt' which contains the same information as those included in this section. Citing the Dataset The dataset is released under a Creative Commons Attribution license, so please cite the dataset if it is used in your work in any form. Published academic papers should use the academic paper citation for our paper. Personal works, such as projects or blog posts, should provide a URL to this Zenodo page, though a reference to our paper would also be appreciated. Academic paper citation: Elia, R., Plastiras, G., Pettemeridou, E., Savva, A., & Theocharides, T. (2022). A real-world data collection framework for a fused dataset creation for joint human and remotely operated vehicle monitoring and anomalous command detection. CAAI Transactions on Intell