Description
How Does Personal Greatness Index works?
Current health and wellness app have traditionally been focused on physiological approach, Personal Greatest Index (“PGI”) is taking the different approach and studying the role of human body as brain fuel, to enable the thriving of all people – from a neuroscience approach.
For the BrianFuel Index, PGI is pioneering new generations of computational models of the biorhythms hierarchy system.
The goal is to bring these computation models "to life" by collecting biometric, lifestyle and mental well-being data so that a person’s neuro-cognitive model can change and adapt over time to reflect neuroscience based predictions like multitasking and rational decision making abilities.
BrainFuel index aims to weave insights from 7 daily lifestyle data, sleep, breakfast, lunch, dinner, cardio exercise, digestive system and daily summary, into brain performance mathematical models.
One of the goals of BrainFuel Index is to provide useful insights and predictions that are based on what happened in the past 72 hours, in terms of 3 main health pillars, hormonal, psychological and neurological science.
Is Personal Greatness Index effective?
Personal Greatness Index uses micro habit & selfie therapy (“MHST”), the most effective form of therapy to improve self care. Working with MHST does not require an in-person professional and therefore gives uers the power to do it in a guided and self-experimented way at their own time.
PGI APP unique algorithm provides a glimpse of user estimated cognitive condition based on lifestyle choices
- getting resting heart rate from Apple HealthKit, provides a glimpse of body allostasis load level
- getting cardio data from Apple HealthKit, provides a glimpse of our brain oxygen intake
- getting sleep data from Apple HealthKit, provides a glimpse of our brain healing level
- getting mental wellbeing data provides a glimpse of tonicity of our brain neuron Intracellular fluid
- getting digestive system data, provides a glimpse of body pH level
- getting occupation data, enables algorithm to classify into different performance category
- getting dominant side data, enables algorithm to classify into different performance category
- getting age data, enables algorithm to classify into different performance category
- getting gender data, enables algorithm to classify into different performance category
- getting ethnicity data, enables algorithm to classify into different performance category
- getting hobby data, enables algorithm to classify into different performance category
- getting music preference data, enables algorithm to classify into different performance cate