BioSig: The Free and Open Source Software Library for Biomedical Signal Processing

BioSig is an open source software library for biomedical signal processing. The aim of the BioSig project is to foster research in biomedical signal processing by providing free and open source software tools for many different application areas. Some of the areas where BioSig can be employed are neuroinformatics, brain-computer interfaces, neurophysiology, psychology, cardiovascular systems, and sleep research. Moreover, the analysis of biosignals such as the electroencephalogram (EEG), electrocorticogram (ECoG), electrocardiogram (ECG), electrooculogram (EOG), electromyogram (EMG), or respiration signals is a very relevant element of the BioSig project. Specifically, BioSig provides solutions for data acquisition, artifact processing, quality control, feature extraction, classification, modeling, and data visualization, to name a few. In this paper, we highlight several methods to help students and researchers to work more efficiently with biomedical signals

Driving Big Data – Integration and Synchronization of Data Sources for Artificial Intelligence Applications with the Example of Truck Driver Work Stress and Strain Analysis

This paper contributes to the issue of big data analysis and data quality with the specific field of time synchronization. As a highly relevant use case, big data analysis of work stress and strain factors for driving professions is outlined. Drivers experience work stress and strain due to trends like traffic congestion, time pressure or worsening work conditions. Although a large professional group with 2.5 million (US) and 3.5 million (EU) truck drivers, scientific analysis of work stress and strain factors is scarce. Driver shortage is growing into a large-scale economic and societal challenge, especially for small businesses. Empirical investigations require big data approaches with sources like physiological and truck, traffic, weather, planning or accident data. For such challenges, accurate data is required, especially regarding time synchronization. Awareness among researchers and practitioners is key and first solution approaches are provided, connecting to many further Machine Learning and big data applications

Emotions in context: examining pervasive affective sensing systems, applications, and analyses

Pervasive sensing has opened up new opportunities for measuring our feelings and understanding our behavior by monitoring our affective states while mobile. This review paper surveys pervasive affect sensing by examining and considering three major elements of affective pervasive systems, namely; “sensing”, “analysis”, and “application”. Sensing investigates the different sensing modalities that are used in existing real-time affective applications, Analysis explores different approaches to emotion recognition and visualization based on different types of collected data, and Application investigates different leading areas of affective applications. For each of the three aspects, the paper includes an extensive survey of the literature and finally outlines some of challenges and future research opportunities of affective sensing in the context of pervasive computing

Melanin-Concentrating Hormone (MCH): Role in REM Sleep and Depression.

The melanin-concentrating hormone (MCH) is a peptidergic neuromodulator synthesized by neurons of the lateral sector of the posterior hypothalamus and zona incerta. MCHergic neurons project throughout the central nervous system, including areas such as the dorsal (DR) and median (MR) raphe nuclei, which are involved in the control of sleep and mood. Major Depression (MD) is a prevalent psychiatric disease diagnosed on the basis of symptomatic criteria such as sadness or melancholia, guilt, irritability, and anhedonia. A short REM sleep latency (i.e., the interval between sleep onset and the first REM sleep period), as well as an increase in the duration of REM sleep and the density of rapid-eye movements during this state, are considered important biological markers of depression. The fact that the greatest firing rate of MCHergic neurons occurs during REM sleep and that optogenetic stimulation of these neurons induces sleep, tends to indicate that MCH plays a critical role in the generation and maintenance of sleep, especially REM sleep. In addition, the acute microinjection of MCH into the DR promotes REM sleep, while immunoneutralization of this peptide within the DR decreases the time spent in this state. Moreover, microinjections of MCH into either the DR or MR promote a depressive-like behavior. In the DR, this effect is prevented by the systemic administration of antidepressant drugs (either fluoxetine or nortriptyline) and blocked by the intra-DR microinjection of a specific MCH receptor antagonist. Using electrophysiological and microdialysis techniques we demonstrated also that MCH decreases the activity of serotonergic DR neurons. Therefore, there are substantive experimental data suggesting that the MCHergic system plays a role in the control of REM sleep and, in addition, in the pathophysiology of depression. Consequently, in the present report, we summarize and evaluate the current data and hypotheses related to the role of MCH in REM sleep and MD