model

Statistical model improves analysis of skin conductance

Statistical model improves analysis of skin conductance
With electrodes strapped to two fingers, researchers can read out a signal of electrodermal activity. Credit: Sandya Subramanian/MIT Picower Institute

Electrodermal activity—the sweat-induced fluctuations of skin conductance made famous in TV dramatizations of lie-detector tests—can be a truly strong indicator of subconscious, or “sympathetic,” nervous system activity for all kinds of purposes, but only if it is analyzed optimally. In a new study in the Proceedings of the National Academy of Sciences, an MIT-based team of scientists provides a new, fast and accurate statistical model for analyzing EDA.

“Only so much of EDA is intuitive just by looking at the signal,” said Sandya Subramanian, a graduate student in the Harvard-MIT Health Sciences and Technology program and the study’s lead author. Meanwhile, existing mathematical methods of analysis either compute averages of the signal that obscure its instantaneous nature, or inefficiently force measurements into a fit with signal processing models that

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women

Women’s mental health improves after giving up alcohol, study finds

Many women drink alcohol to relax, feel good and take the edge off life, but recent evidence suggests skipping that daily glass of wine is a better way to boost their mental health.

With the start of Sober October — a month dedicated to going alcohol-free, much like Dry January — it may be another good reason to try a break from booze.

First, some sobering new statistics. Alcohol-related deaths are on the rise in the U.S., increasing by 43% from 2006 to 2018, a report published Thursday by the Centers for Disease Control and Prevention found. The impact was greatest on women.

Experts are also linking pandemic stress to a spike in alcohol use in 2020, with women’s stress drinking increasing significantly. The most problematic alcohol use happened around March and April of this year, one expert told NBC News.

The findings come as many Americans have been trying

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model

Innovative model improves Army human-agent teaming

ADELPHI, Md. — Army researchers developed a novel computational model for gathering cognitive data that may be a game changer in the fields of neuroscience and econometrics, and has broad relevance to networked and multi-agent systems.

At the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory and the University of Maryland, College Park, researchers developed what is known as the Autoregressive Linear Mixture, or ALM, a novel model for analyzing time-series data, or how things change over time.

For the Army, this comes in to play to assess the cognitive states of Soldiers to allow an intelligent adaptive system to balance the workload of the crew when completing challenging critical missions.

Employing recent advancements in optimization for nonconvex problems, the researchers adapted a proximal gradient algorithm and validated the proposed model and algorithm on an open-source electroencephalography, or EEG, dataset.

This work, recently featured in IEEE Xplore, innovates

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