Alzheimer's disease is the most prevalent cause of dementia. Mild Cognitive Impairment (MCI) is defined as a grey area between intact cognitive functioning and clinical dementia. Electroencephalography (EEG) has been used to identify biomarkers in dementia. Currently, there is a great interest in translating the study from raw signals to signal generators, trying to keep the relationship with neurophysiology. In the current study, EEG recordings during an encoding task were acquired in MCI subjects and healthy controls. Data was decomposed using group Independent Component Analysis (gICA) and the most neuronal components were analyzed using Phase Intertrial Coherence (PIC) and Phase shift Intertrial Coherence (PsIC). MCI subjects exhibited an increase of PIC in the theta band, while controls showed increase in PsIC in the alpha band. Correlation between PIC and PsIC and clinical scales were also found. Those findings indicate that the methodology proposed based in gICA can help to extract information from EEG recordings with neurophysiological meaning.

This article includes the phases of conceptualization and validation of a picosatellite prototype named Simple-2 for remote sensing activities using COTS (Commercial-Off-The-Shelf) components and the modular design methodology. To evaluate its performance and ensure the precision and accuracy of the measurements made by the satellite prototype, a methodology was designed and implemented for the characterization and qualification of CanSats (soda can satellites) through statistical tests and techniques of DoE (Design of Experiments) based on CubeSat aerospace standards and regulations, in the absence of official test procedures for these kinds of satellite form factor. For the above, two experimental units were used, and all the performance variables of the different satellite subsystems were discriminated. For the above, two experimental units were used, and all the performance variables of the different satellite subsystems were discriminated against. These were grouped according to the dependence of the treatments formulated in thermal and dynamic variables. For the tests of the first variables, a one-factor design was established using dependent samples on each of the treatments. Then, hypothesis tests were performed for equality of medians, using nonparametric analysis of the Kruskal-Wallis variance. Additionally, multivariate analysis of variance was carried out for nonparametric samples (nonparametric multivariate tests), and the application of post hoc multiple-range tests to identify the treatments that presented significant differences within a margin of acceptability. To know the dynamic response and ensure the structural integrity of the satellite module, shock, oscillation, and sinusoidal tests were applied through a shaker. Having applied the experimental methodology to the different units, the results of a real experiment are illustrated in which a high-altitude balloon was used through the application of nonparametric regression methods. This experiment’s interest measured thermodynamic variables and the concentration of pollutants in the stratosphere to corroborate the operating ranges planned in the above experiments using on-flight conditions and estimate the TLR (technology readiness level) of future prototypes.

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Respiratory muscles superficial electromyography (SEMG) is an important source of information in the monitoring of ventilated patients. One of the main problems in the acquisition of SEMG signals is the different sources of interference. The most common artifacts are the baseline wander (BW) normally generated by motion, and power line interference (PLI). In this paper, different methods were selected and evaluated for the removal of these artifacts in a simulated SEMG signal of the right diaphragm muscle. The best performance technique for the removal of each artifact was determined using frequency analysis and estimation of criteria such as the signal to noise ratio, relative error, cross-correlation, and coherence of the power spectrum density. The computational cost of each of the techniques was estimated to also assess how appropriate it is to implement in online applications and limited hardware. The study demonstrates that the spectral interpolation technique has a good performance in removing PLI from the SEMG signal but has a high computational cost, unlike the adaptive LMS filter. On the other hand, the SSA-based technique proved to be the best performing for BW removal and its computational cost is adequate in a more limited hardware system.

The densest network for measuring air pollutant concentrations in Colombia is in Medellin, where most sensors are located in the heavily polluted lower parts of the valley. Measuring stations in the higher elevations on the mountains surrounding the valley are not available, which limits our understanding of the valley’s pollutant dynamics and hinders the effectiveness of data assimilation studies using chemical transport models such as LOTOS-EUROS. To address this gap in measurements, we have designed a new network of low-cost sensors to be installed at altitudes above 2000 m.a.s.l. The network consists of custom-built, solar-powered, and remotely connected sensors. Locations were strategically selected using the LOTOS-EUROS model driven by diverse meteorology-simulated fields to explore the effects of the valley wind representation on the transport of pollutants. The sensors transmit collected data to internet gateways for posterior analysis. Various tests to verify the critical characteristics of the equipment, such as long-range transmission modeling and experiments with an R score of 0.96 for the best propagation model, energy power system autonomy, and sensor calibration procedures, besides case exposure to dust and water experiments, to ensure IP certifications. An inter-calibration procedure was performed to characterize the sensors against reference sensors and describe the observation error to provide acceptable ranges for the data assimilation algorithm (<10% nominal). The design, installation, testing, and implementation of this air quality network, oriented towards data assimilation over the Aburrá Valley, constitute an initial experience for the simulation capabilities toward the system’s operative capabilities. Our solution approach adds value by removing the disadvantages of low-cost devices and offers a viable solution from a developing country’s perspective, employing hardware explicitly designed for the situation.