Peripheral Nervous System Responses to Food Stimuli: Analysis Using Data Science Approaches
In the field of food, as in other fields, the measurement of emotional responses to food and their sensory properties is a major challenge. In the present protocol, we propose a step-by-step procedure that allows a physiological description of odors, aromas, and their hedonic properties. The method rooted in subgroup discovery belongs to the field of data science and especially data mining. It is still little used in the field of food and is based on a descriptive modeling of emotions on the basis of human physiological responses.
Code (0)
등록된 구현이 없습니다.
Tasks
DescriptiveSubgroup DiscoverySimilar Papers 제목 키워드 기반
Coordinate-VAE: Unsupervised clustering and de-noising of peripheral nervous system data
The peripheral nervous system represents the input/output system for the brain. Cuff electrodes implanted on the peripheral nervous system allow observation and control over this system, however, the data produced by the…
ClusteringMuscle coactivation primes the nervous system for fast and task-dependent feedback control
Humans and other animals coactivate agonist and antagonist muscles in many motor actions. Increases in muscle coactivation are thought to leverage viscoelastic properties of skeletal muscles to provide resistance against…
Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological Rewards
As people learn to navigate the world, autonomic nervous system (e.g., "fight or flight") responses provide intrinsic feedback about the potential consequence of action choices (e.g., becoming nervous when close to a cli…
Navigatereinforcement-learningReinforcement LearningReinforcement Learning (RL)Optimal context separation of spiking haptic signals by second-order somatosensory neurons
We study an encoding/decoding mechanism accounting for the relative spike timing of the signals propagating from peripheral nerve fibers to second-order somatosensory neurons in the cuneate nucleus (CN). The CN is modele…
Visceral Machines: Reinforcement Learning with Intrinsic Physiological Rewards
The human autonomic nervous system has evolved over millions of years and is essential for survival and responding to threats. As people learn to navigate the world, ``fight or flight'' responses provide intrinsic feedb…
Navigatereinforcement-learningReinforcement LearningReinforcement Learning (RL)