Weight Prediction
Data Type | Health Indicator |
|---|---|
Scan Requirements | BodyScan |
AHI Weight Prediction offers a way to check self-reported weight through a BodyScan. As weight is a major component in calculating Total Body Fat determining health risks, an incorrect body weight can lead to miscalculation.
Bias exists in a lot of individuals to some degree. Most people do not weight themselves eveery day and will recall the last time their weighed themselves. Some overweight and obese individuals might under-report their weight, leading to a lower risk. Similaraly, there are cases where individuals are underweight and over-report their weight.
BMI remains an important indicator for underwriting pricess in Life & Health Insurance. Misreported weight will lead to higher premiums as individuals will be miscategorized and lead to incorrect premium pricing. Intervention will not be possible to help those individuals, leading to late claims and increased risk of mortality.
Weight Prediction allows partners to compare self-reported weight with a prediction and flag the result as a mis-reported value.
Agreement of anthropometric and body composition measures predicted from 2D smartphone images and body impedance scales with criterion methods
Body composition and anthropometry assessment from two-dimensional smartphone images is possible through advancement of computational hardware and artificial intelligence (AI) techniques. This study established agreement of a novel smartphone assessment, compared with traditional bioelectrical impedance analysis (BIA), and criterion measures.