AIMC Topic: Energy Metabolism

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Deep CHORES: Estimating Hallmark Measures of Physical Activity Using Deep Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Wrist accelerometers for assessing hallmark measures of physical activity (PA) are rapidly growing with the advent of smartwatch technology. Given the growing popularity of wrist-worn accelerometers, there needs to be a rigorous evaluation for recogn...
Deep Learning Adult Wrist Humans Male Activities of Daily Living Female Exercise Young Adult Energy Metabolism Accelerometry
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The Relationship between Sparseness and Energy Consumption of Neural Networks.

Neural plasticity Nov 25, 2020
About 50-80% of total energy is consumed by signaling in neural networks. A neural network consumes much energy if there are many active neurons in the network. If there are few active neurons in a neural network, the network consumes very little ene...
Nerve Net Neural Networks, Computer Models, Neurological Neurons Energy Metabolism
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Deep Learning to Predict Energy Expenditure and Activity Intensity in Free Living Conditions using Wrist-specific Accelerometry.

Journal of sports sciences Oct 30, 2020
Wrist-worn accelerometers are more comfortable and yield greater compliance than hip-worn devices, making them attractive for free-living activity assessments. However, intricate wrist movements may require more complex predictive models than those a...
Female Adult Male Humans Energy Metabolism Accelerometry Fitness Trackers Middle Aged Wrist Joint Exercise Deep Learning
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Iterative Learning Control for a Soft Exoskeleton with Hip and Knee Joint Assistance.

Sensors (Basel, Switzerland) Aug 4, 2020
Walking on different terrains leads to different biomechanics, which motivates the development of exoskeletons for assisting on walking according to the type of a terrain. The design of a lightweight soft exoskeleton that simultaneously assists multi...
Hip Joint Exoskeleton Device Biomechanical Phenomena Knee Joint Walking Gait Torque Humans Energy Metabolism Machine Learning
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Discovery of different metabotypes in overconditioned dairy cows by means of machine learning.

Journal of dairy science Jul 31, 2020
Using data from targeted metabolomics in serum in combination with machine learning (ML) approaches, we aimed at (1) identifying divergent metabotypes in overconditioned cows and at (2) exploring how metabotypes are associated with lactation performa...
Peripartum Period Metabolomics Metabolome Energy Metabolism Animals Cattle Machine Learning Female
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Moonlighting Proteins in the Fuzzy Logic of Cellular Metabolism.

Molecules (Basel, Switzerland) Jul 29, 2020
The numerous interconnected biochemical pathways that make up the metabolism of a living cell comprise a fuzzy logic system because of its high level of complexity and our inability to fully understand, predict, and model the many activities, how the...
Metabolic Networks and Pathways Models, Biological Energy Metabolism Protein Binding Humans Fuzzy Logic Animals Proteins
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Genes, the brain, and artificial intelligence in evolution.

Journal of human genetics Jul 27, 2020
Three important systems, genes, the brain, and artificial intelligence (especially deep learning) have similar goals, namely, the maximization of likelihood or minimization of cross-entropy. Animal brains have evolved through predator-prey interactio...
Genes Mitochondrial Diseases Brain Animals Evolution, Molecular Energy Metabolism Entropy Adaptation, Physiological Humans Artificial Intelligence
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Predicting children's energy expenditure during physical activity using deep learning and wearable sensor data.

European journal of sport science Jul 16, 2020
This study examined a series of machine learning models, evaluating their effectiveness in assessing children's energy expenditure, in terms of the metabolic equivalents (MET) of physical activity (PA), from triaxial accelerometery. The study also de...
Female Male Exercise Humans Wrist Energy Metabolism White People Deep Learning Wearable Electronic Devices Child Ankle Linear Models Accelerometry Calorimetry, Indirect
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Energy-efficient and damage-recovery slithering gait design for a snake-like robot based on reinforcement learning and inverse reinforcement learning.

Neural networks : the official journal of the International Neural Network Society Jun 16, 2020
Similar to real snakes in nature, the flexible trunks of snake-like robots enhance their movement capabilities and adaptabilities in diverse environments. However, this flexibility corresponds to a complex control task involving highly redundant degr...
Reinforcement, Psychology Algorithms Bayes Theorem Learning Gait Robotics Energy Metabolism
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Key components of mechanical work predict outcomes in robotic stroke therapy.

Journal of neuroengineering and rehabilitation Apr 21, 2020
BACKGROUND: Clinical practice typically emphasizes active involvement during therapy. However, traditional approaches can offer only general guidance on the form of involvement that would be most helpful to recovery. Beyond assisting movement, robots...
Movement Humans Upper Extremity Prognosis Middle Aged Stroke Rehabilitation Treatment Outcome Robotics Regression Analysis Female Models, Biological Energy Metabolism Aged Male
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