BodyScan dev team fact sheet.
- Scan: BodyScan
- Duration: <60 seconds
- Data Returned: Body circumference and composition (body fat %), and health indicators such as waist-hip ratio and Type-2 Diabetes risk.
- Processing: On-Device
- Platforms: iOS, Android
- iOS submodule size: <10MB.
- Android submodule Size: <10MB.
- Min. Requirements: iPhones: iOS 12.1 or above. Android: Android 8 or above, 64-bit, and OpenGL 3.1 support.
- Requirements to Operate: Internet connection, Remote Assets, User Input
What is BodyScan?
BodyScan is a scan technology where a front and side capture of a user's body is used to determine body circumference and body composition measurements.
BodyScan provides a process to capture a person's front and side image which is then used to calculate their anthropometric measurements. BodyScan includes inspection technology of the captured images to confirm that the user adheres to a minimum set of conditions, such as checking that the user is within frame and in the expected pose position, so that a high degree of accuracy can be maintained when using the technology.
How it Works
- BodyScan is hardware accelerated to run on-device for a near real-time experience.
- Front and side images undergo proprietary computer vision and machine learning processing modules.
- Individuals receive composition, dimensioning, and health risk results, while partners can benefit from aggregated data points.
- Overall Circumference Accuracy: 97.5%
- Chest Circumference Accuracy: 98%
- Hip Circumference Accuracy: 97%
- Waist Circumference Accuracy: 98%
- Thigh Circumference Accuracy: 97%
- Weight Inference (avg): 96.6%
- Repeatability: 98%
User Input Data
- Height, Weight, Sex
Direct scan outputs
Derived data based on Layer 1 outputs
- Waist-Hip Ratio
- Waist-Height Ratio
- Body Fat Percentage
Contextual data derived by comparing Layer 1 and 2 outputs and comparing them against public datasets or health studies.
Additional user input required to provide contextual data - Age, Ethnicity, Question Survey