Brain

This dataset provides measurements of cerebral blood flow using Radio Frequency (RF) sensors operating in the Ultra-Wideband (UWB) frequency range, enabling non-invasive monitoring of cerebral hemodynamics. It includes blood flow feature data from two arterial networks, Arterial Network A and Arterial Network B. Statistical features were manually extracted from the RF sensor data, while autonomous feature extraction was performed using a Stacked Autoencoder (SAE) with architectures such as 32-16-32, 64-32-16-32-64, and 128-64-32-16-32-64-128.

This is a videoconference between a witness about murders who is a victim of many crimes and a law firm. This witness is called Colin Paul Gloster. This law firm is called Pais do Amaral Advogados.

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With the continuous advancement of technology, small and portable physiological sensors that can be worn on the body are quietly integrating into our daily lives, and are expected to greatly enhance our quality of life. In order to further enrich and expand the emotional physiological signals captured by portable wearable devices, we utilized the 14-channel portable EEG acquisition device Emotiv EPOC X, and with emotional video clips as the stimulus source, we collected two sets of emotional EEG signals from two groups of 10 participants each, named EmoX1 and EmoX2.

Stress became a common factor of individuals in this competitive work environment, especially in academics. To address and assess this issue, this MUSEI-EEG dataset provides the Electroencephalogram (EEG) data of 20 undergraduate individuals in the 18-24 years age group (both male and female). Raag Darbari's music-based three-stage paradigm is designed for the subjects for cognitive stress assessment. Through this paradigm, physiological signal-based monitoring of stress level reduction can be observed in reference to stress and anxiety forms filled by the individual.