Datos de Investigación (Arquitectura y Tecnología de Computadores)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/163805

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  • Miniatura
    Acceso AbiertoDataset
    Dataset of PaGER-Sync: Player Affective Gaming Experience and Responses - Synchronized ADICVIDEO
    (2025-07-16) Civit Masot, Javier; Luna Perejón, Francisco; Muñoz Saavedra, Luis; Civit Masot, Miguel; Domínguez Morales, Manuel Jesús; Miró Amarante, María Lourdes; Arquitectura y Tecnología de Computadores; Miró Amarante, María Lourdes; Civit Masot, Javier; Luna Perejón, Francisco; Muñoz Saavedra, Luis; Miró Amarante, María Lourdes; Civit Masot, Javier; Luna Perejón, Francisco; Miró Amarante, María Lourdes; Ministerio de Ciencia e Innovación (MICIN). España; TEP108: Robótica y Tecnología de Computadores
    The PaGER-Sync ADICVIDEO dataset is a multimodal, temporally synchronized repository of physiological and facial expression data recorded during controlled, immersive video game sessions designed to simulate realistic home gaming environments. It integrates biosignals from the Empatica E4 wristband —including Electrodermal Activity (EDA), Blood Volume Pulse (BVP), and Skin Temperature (TEMP) — with facial expression features extracted from video recordings using FaceReader software. Additionally, the dataset includes scores from pre-session psychometric questionnaires (Gaming Addiction Scale, Scale of Positive and Negative Experience, Emotion Regulation Questionnaire) and demographic gender data, providing psychological and individual difference context. A summary file detailing the two strongest emotions expressed by each participant with their respective percentages is included. A total of 25 participants played three commercial video games (Tetris, Sonic Racing, and Fall Guys) under controlled conditions, while their physiological responses were continuously recorded and their facial expressions captured on video for subsequent analysis. All data streams were precisely aligned using a common video-based timestamp, enabling frame-level synchronization across modalities, and the data were segmented by game. The dataset supports a wide range of research applications in affective computing, human-computer interaction, and behavioral analysis, and is particularly well-suited for the development and evaluation of multimodal affect detection models, as well as for exploring the interplay between psychological traits and real-time emotional responses.
  • Miniatura
    Acceso AbiertoDataset
    Neuromorphic Audio for Predictive Maintenance in Peristaltic Pumps [Dataset]
    (2025-01-23) Montes-Sánchez, Juan Manuel; Domínguez Morales, Juan Pedro; Vicente Díaz, Saturnino; Jiménez Fernández, Ángel Francisco; Arquitectura y Tecnología de Computadores; Montes-Sánchez, Juan Manuel; Agencia Estatal de Investigación. España; Ministerio de Ciencia, Innovación y Universidades (MICINN). España; TEP108: Robótica y Tecnología de computadores
    This dataset contains processed audio samples coming from a hydraulic block from a biomedical equipment. The block mounts 3 Thomas SR10/30 DC standard perisltaltic pumps, which were filled with distilled water. Only one pump was running at the same time during these recordings. There are two different predictive maintenance scenarios. In the first one, the cassettes of the pumps were changed before each recording. We used cassettes with 2 different levels of degradation: NEW (unused) and OLD (lifetime already expired). We defined 3 different classes: Class 1 is STOP (no pump running), class 2 is NEW (one pump running with a new cassette), and class 3 is OLD (one pump running with an old cassette). In the second scenario, air bubbles were introduced into the tube. This second scenario also has 3 classes: Class 1 is STOP (no pump running), class 2 is NORMAL (no air bubbles), and class 3 is BUBBLE (air bubbles present). A single microphone was used for all recordings. The .wav audio files were processed using a 64 channel Neuromorphic Auditory Sensor (NAS) into .aedat files, which are the present in this dataset. This neuromorphic audio data were also converted into cochleogram images using the software pyNAVIS, and they are also present in this format (.png files).
  • Miniatura
    Acceso AbiertoDataset
    Peristaltic pump aging detection dataset
    (2024-09-25) Montes-Sánchez, Juan Manuel; Uwate, Yoko; Nishio, Yoshifumi; Vicente Díaz, Saturnino; Jiménez Fernández, Ángel Francisco; Arquitectura y Tecnología de Computadores; Montes-Sánchez, Juan Manuel; Agencia Estatal de Investigación. España; Ministerio de Ciencia, Innovación y Universidades (MICINN). España; TEP-108: Robótica y tecnología de computadores
    This dataset contains samples coming from a hydraulic block from a biomedical equipment. The block mounts 3 Thomas SR10/30 DC standard perisltaltic pumps, which were filled with distilled water. Only one pump was running at the same time during these recordings, always at maximum constant speed. The cassettes of the pumps were changed before each recording. We used cassettes with 2 different levels of degradation: NEW (unused) and OLD (lifetime already expired). We defined 3 different classes: Class 1 is STOP (no pump running), class 2 is NEW (one pump running with a new cassette), and class 3 is OLD (one pump running with an old cassette). The classified samples were recorded using several sensors: 3 accelerometers, 1 gyroscope, 1 magnetometer and 1 microphone. All data were recorded at the same time at the maximum available frequency using the device "ST SensorTile.box". The raw data has already been processed into sepparate different .csv files (.wav files for audio) using python code.