FoodLoop is built on decades of research in exercise physiology, nutritional science, sleep medicine, and cognitive neuroscience.
FoodLoop's training algorithms are based on periodization principles, progressive overload, and recovery science. We integrate research on muscle protein synthesis, glycogen replenishment, and neuromuscular adaptation to optimize training outcomes.
Our nutrition engine applies evidence from metabolic research, nutrient timing studies, and macro/micronutrient optimization. We consider energy availability, protein distribution, and micronutrient density to support performance and recovery.
FoodLoop evaluates sleep architecture, heart rate variability (HRV), and autonomic nervous system balance to assess recovery readiness. We apply findings from circadian biology and sleep medicine to optimize training load and recovery strategies.
Mental performance features are grounded in research on attention, executive function, and stress regulation. We integrate mindfulness research, cognitive load theory, and neuroplasticity principles to enhance focus and mental resilience.
FoodLoop's AI continuously learns from your data to deliver increasingly personalized recommendations. Our machine learning models analyze patterns in training response, nutrition adherence, recovery metrics, and performance outcomes to adapt your program in real-time.
Unlike static programs, FoodLoop adjusts to your individual response, accounting for factors like stress, sleep quality, menstrual cycle phases (for women), and lifestyle demands. The system becomes more accurate over time, creating a truly personalized health optimization experience.
FoodLoop prioritizes peer-reviewed research over fitness trends. Our recommendations are grounded in established scientific principles, not marketing hype. We continuously review emerging research to refine our algorithms while maintaining a foundation in proven methodologies.
Every feature in FoodLoop—from training periodization to nutrient timing to recovery protocols—is backed by scientific evidence. We believe in transparency and will always prioritize what works over what's trendy.