Biophysiological Signals
One of the grand challenges in neuroscience is to understand the developing brain ‘in action and in context’ in complex natural settings. To address this challenge, it is imperative to acquire brain data from freely-behaving children to assay the variability and individuality of neural patterns across gender and age.
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Recent advances in scalp electroencephalography (EEG) as a neuroimaging tool have now allowed researchers to overcome technical challenges and movement restrictions typical in traditional neuroimaging studies. Fortunately, recent mobile EEG devices have enabled studies involving cognition and motor control in natural environments that require mobility, such as during art perception and production in a museum setting, and during locomotion tasks.
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This dataset is associated with the paper, Jackson & Hall 2016, which is open source, and can be found here: http://ieeexplore.ieee.org/document/7742994/
The DataPort Repository contains the data used primarily for generating Figure 1.
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The large number and scale of natural and man-made disasters have led to an urgent demand for technologies that enhance the safety and efficiency of search and rescue teams. Semi-autonomous rescue robots are beneficial, especially when searching inaccessible terrains, or dangerous environments, such as collapsed infrastructures. For search and rescue missions in degraded visual conditions or non-line of sight scenarios, radar-based approaches may contribute to acquire valuable, and otherwise unavailable information.
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This dataset is associated with the manuscript entitled "Data-efficient Human Walking Speed Intent Inference". The data represent the measurements taken from 15 able-bodied human subjects as the made speed changes while walking on a treadmill. Each subject is associated with a .mat file that contains 8 variables. Four variables are associated with the training dataset while four are associated with the experimental testing protocol.
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The signals of a recording belonging to the Frontside task are shown, the first two corresponding to the electromyography sensors while the others correspond to the infrared and red LED readings of the pulse oximetry sensor.
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Physiological database including 7 pairs of facial surface EMG (left/right frontalis, left/right zygomaticus, left/right orbicularis and centre corrugator) muscles, forehead PPG, IMU (Accelerometer, Gyroscope, Magnetometer) and continuous self-ratings of arousal and valence while watching video stimuli. 37 participants watched an average of 23 minutes worth of videos. This included blocks of positive, negative and neutral segments. Each segment included 10 videos, 30 seconds long each. Relaxation video was played between each segment.
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10 soccer supporters gathered to watch a live broadcasted Premier League
match between Liverpool and Manchester United (4 - 0) on 19th of March 2022, all
equipped with wrist-worn accelerometers. All participants were aware of the purpose of this experiment and consented to participate
by attendance at the event, and by wearing the accelerometer. No personally sensitive
information was collected, all data is fully anonymised following the GDPR guidelines
and all procedures were in accordance with the recommendations of the data protection
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IREYE4TASK is a dataset for wearable eye landmark detection and mental state analysis. Sensing the mental state induced by different task contexts, where cognition is a focus, is as important as sensing the affective state where emotion is induced in the foreground of consciousness, because completing tasks is part of every waking moment of life. However, few datasets are publicly available to advance mental state analysis, especially those using the eye as the sensing modality with detailed ground truth for eye behaviors.
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The formation and changes of the pulse wave areaffected by the functional status of the heart, blood, and arterial vessels. The pulse signal covers pathological information in the cardiovascular system, and the doctor of traditional Chinese medicine (TCM) can diagnose diseases by feeling the pulse. The diagnosis of diseases through feeling the pulse of TCM primarily relies on the doctor’s feelings and subjective experience, and it lacks objectified data.
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