Eating Bout Count
Number of discrete eating episodes
ConductVision · Behavioral Analysis
Eating Detection
Automated food consumption tracking with temporal precision for metabolic and circadian feeding research.
TrainableRodentMetabolismAuto Export
ConductVision / Eating Detection
Recording / Trial 3subject tracked
Eating Bout Count14
Eating Duration27%
Mean Bout Duration27%
Key Parameters
Metrics automatically extracted by ConductVision.
Total Eating Duration
Cumulative time spent eating
Mean Bout Duration
Average length per eating episode
Eating Latency
Time to first eating event from session start
Food Zone Time
Total time spent in designated food zone
Eating Frequency by Hour
Temporal distribution of eating events
What is Eating Detection?
Eating behavior in rodents is a critical endpoint for metabolic disorder research, appetite regulation studies, and circadian feeding pattern analysis. Automated eating detection replaces labor-intensive manual food weighing and video scoring with continuous, objective quantification of feeding events.
ConductVision's extensible behavior classifier uses pose estimation features fed into a Random Forest pipeline. Trained on labeled video of feeding behavior, the system detects eating bouts with high accuracy by recognizing characteristic head-down posture at food hoppers, paw manipulation of food pellets, and rhythmic jaw movements — matching human observer reliability.
Research Applications
Metabolic Research
- Obesity models — hyperphagia quantification in ob/ob and db/db mice
- Anorexia models — activity-based anorexia feeding suppression
- Diabetes — feeding pattern disruption in STZ and HFD models
Appetite Regulation
- Ghrelin and leptin pathway pharmacology
- GLP-1 receptor agonist anorectic effects
- Hypothalamic circuit manipulation effects on feeding
Circadian Feeding
- Light/dark cycle feeding distribution
- Restricted feeding schedule entrainment
- Meal pattern analysis — size, frequency, and timing
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