AIMC Topic: Reflex, Startle

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Machine learning identification of tinnitus-related features in auditory peripheral spontaneous activity in a guinea pig noise-induced tinnitus model.

Hearing research
OBJECTIVES: Tinnitus affects millions globally, yet its clinical assessment relies on subjective reports, limiting diagnostic accuracy and treatment development. This study aimed to identify objective, tinnitus-related features within ensemble sponta...

Comparing statistical learning methods for complex trait prediction from gene expression.

PloS one
Accurate prediction of complex traits is an important task in quantitative genetics. Genotypes have been used for trait prediction using a variety of methods such as mixed models, Bayesian methods, penalized regression methods, dimension reduction me...

Enhancing Free-Living Fall Risk Assessment: Contextualizing Mobility Based IMU Data.

Sensors (Basel, Switzerland)
Fall risk assessment needs contemporary approaches based on habitual data. Currently, inertial measurement unit (IMU)-based wearables are used to inform free-living spatio-temporal gait characteristics to inform mobility assessment. Typically, a fluc...

Investigating the Independent and Combined Effects of Startle and Surprise in a Simulated Flight Task.

Human factors
ObjectiveWe aimed to characterize the impact of startle and surprise, both independently and in combination, on subjective feelings, behavior (task performance and gaze behavior), and several physiological parameters.BackgroundThe effects of startle ...