Publications by authors named "Marc Bartholet"
Article Synopsis
- * The study used continuous glucose monitoring data from a sports camp to assess the risk of nighttime hypoglycemia in children with T1D, employing machine learning models like random forest and deep neural networks.
- * Findings showed that the random forest model had a sensitivity of 71.1% and specificity of 75.8% in predicting nocturnal hypoglycemia, which is essential for taking timely actions to minimize risks for these children and their families.
The capacity to recover after a perturbation is a well-known intrinsic property of physiological systems, including the locomotor system, and can be termed 'resilience' Despite an abundance of metrics proposed to measure the complex dynamics of bipedal locomotion, analytical tools for quantifying resilience are lacking. Here, we introduce a novel method to directly quantify resilience to perturbations during locomotion. We examined the extent to which synchronizing stepping with two different temporal structured auditory stimuli (periodic and 1/ structure) during walking modulates resilience to a large unexpected perturbation.
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