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.


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.


This dataset is associated with the paper, Jackson & Hall 2016, which is open source, and can be found here:

The DataPort Repository contains the data used primarily for generating Figure 1.


Globally, respiratory diseases are the leading cause of death, making it essential to develop an automatic respiratory sounds software to speed up diagnosis and reduce physician workload. A recent line of attempts have been proposed to predict accurately, but they have yet been able to provide a satisfactory generalization performance. In this contest, we invited the community to develop more accurate and generalized respiratory sound algorithms. A starter code is provided to standardize the submissions and lower the barrier.

Last Updated On: 
Sat, 02/24/2024 - 08:02

It has proved that the auscultation of respiratory sound has advantage in early respiratory diagnosis. Various methods have been raised to perform automatic respiratory sound analysis to reduce subjective diagnosis and physicians’ workload. However, these methods highly rely on the quality of respiratory sound database. In this work, we have developed the first open-access paediatric respiratory sound database, SPRSound. The database consists of 2,683 records and 9,089 respiratory sound events from 292 participants.


To understand the role of myo-inositol oxygenase (miox) in the osmotic regulation of Nile tilapia, its expression was analyzed in various tissues. The results showed that the expression of miox gene was highest in the kidney, followed by the liver, and was significantly upregulated in the kidney and liver under 1 h hyperosmotic stress. The relative luminescence efficiency of the miox gene transcription starting site (-4617 bp to +312 bp) under hyperosmotic stress was measured.


The Ground Reaction Forces are generated when walking, specifically when the foot contacts the ground, this information is directly related to the physical characteristics of each person, on the other hand, the growth that has the implementation of artificial intelligence algorithms for the diagnosis or evaluation of both pathologies and rehabilitation that occur in the lower limb are a very large area of opportunity.



Electromyography is useful for those interested in the study of biological signals and their processing, identifying the characteristics of these signals is valuable for the design of prosthetic and robotic systems or in rehabilitation for patients with pathologies of the lower limb. In this case, in particular, the EMG signals of the biceps femoris generated during the gait cycle are intended to characterize the muscle activation signals during walking. For the development of this database, one hundred users were invited to participate.


This data set consists of EEG data from 9 subjects. The cue-based BCI paradigm consisted of four di erent motor imagery tasks, namely the imag ination of movement of the left hand (class 1), right hand (class 2), both feet (class 3), and tongue (class 4). Two sessions on di erent days were recorded for each subject. Each session is comprised of 6 runs separated by short breaks. One run consists of 48 trials (12 for each of the four possible classes), yielding a total of 288 trials per session.


This dataset is developed to support research on early warning of pilots' cognitive collapse. It encompasses the recordings of 10 participants over 3 separate sessions in the simulated flight experiment paradigm. The experiment aims to elicit the pilots' cognitive collapse state and to early warn of the tipping points, for details you can refer to the paper "An Early Warning Approach for Pilots’ Cognitive Tipping Points Based Multi-modal Signals". Each trial consists of 3 stages that can induce cognitive states at low, medium, and high level with a cognitive collapse.