Hypothermia in sepsis is generally perceived as something dysregulated and progressive although there has been no assessment on the natural course of this phenomenon in humans. This was the first study on the dynamics of hypothermia in septic patients not subjected to active rewarming, and the results were surprising. A sample of 50 subjects presenting with spontaneous hypothermia during sepsis was drawn from the 2005-2012 database of an academic hospital. Hypothermia was defined as body temperature below 36.0°C for longer than 2 h, with at least one reading of 35.5°C or less. The patients presented with 138 episodes of hypothermia, 21 at the time of the sepsis diagnosis and 117 with a later onset. However, hypothermia was uncommon in the final 12 h of life of the patients that succumbed. The majority (97.1%) of the hypothermic episodes were transient and self-limited; the median recovery time was 6 h; body temperature rarely fell below 34.0°C. Bidirectional oscillations in body temperature were evident in the course of hypothermia. Nearly half of the hypothermic episodes had onset in the absence of shock or respiratory distress, and the incidence of hypothermia was not increased during either of these conditions. Usage of antipyretic drugs, sedatives, neuroleptics, or other medications did not predict the onset of hypothermia. In conclusion, hypothermia appears to be a predominantly transient, self-limiting, and nonterminal phenomenon that is inherent to human sepsis. These characteristics resemble those of the regulated hypothermia shown to replace fever in animal models of severe systemic inflammation.

In this work, we proposed a novel way to estimate phase-lag synchronization in coupled systems. This approach was applied into two systems: a directed-coupled Rössler-Lorenz system and a network of Izhikevich neurons. For the former case, the phase-lag synchronization revealed an increase in complexity for the Lorenz subsystem components, when the coupling is activated. The opposite behavior was observed when the Izhikevich network were organized in a hierarchical way. Our results point out to emergent synchronism related to causal interactions in coupled complex systems.

No abstract

In this work, we propose changes in the structure of a neuronal network with the intention to provoke strong synchronization to simulate episodes of epileptic seizure. Starting with a network of Izhikevich neurons we slowly increase the number of connections in selected nodes in a controlled way, to produce (or not) hubs. We study how these structures alter the synchronization on the spike firings interval, on individual neurons as well as on mean values, as a function of the concentration of connections for random and non-random (hubs) distribution. We also analyze how the post-ictal signal varies for the different distributions. We conclude that a network with hubs is more appropriate to represent an epileptic state. BSM thanks the UNIEMP for their support. HAC thanks the FAPESP (process 2011/ 11973-4) for their support.

No abstract

The use of inertial measurement units (IMUs) is a low-cost alternative for measuring joint angles. This study aims to present a low-cost open-source measurement system for joint angle estimation. The system is modular and has hardware and software. The hardware was developed using a low-cost IMU and microcontroller. The IMU data analysis software was developed in Python and has three fusion filters: Complementary Filter, Kalman Filter, and Madgwick Filter. Three experiments were performed for the proof of concept of the system. First, we evaluated the knee joint of Lokomat, with a predefined average range of motion (ROM) of 60∘. In the second, we evaluated our system in a real scenario, evaluating the knee of a healthy adult individual during gait. In the third experiment, we evaluated the software using data from gold standard devices, comparing the results of our software with Ground Truth. In the evaluation of the Lokomat, our system achieved an average ROM of 58.28∘, and during evaluation in a real scenario it achieved an average ROM of 44.62∘. In comparing our software with Ground Truth, we achieved a root-mean-square error of 0.04 and a mean average percentage error of 2.95%. These results encourage the use of this system in other scenarios.

No abstract

No abstract