Scientific Sources

Shen AI (Link)

Technology

This app uses the framework of Shen.AI for analysing the video capture session.

What is Shen.AI

Shen AI is a camera-based health monitoring SDK that enables our mobile applications to measure physiological parameters from a short face scan. By combining computer vision and artificial intelligence, it transforms the smartphone or tablet into a contactless health assessment tool, no wearables or external devices required.

The SDK is designed to be integrated directly into our application, allowing our users to complete a health scan in 30 seconds and receive results immediately. Processing runs on the user's device, helping deliver a fast experience while keeping video data local.

How does Shen AI work?

At a high level, every measurement follows the same flow:

  1. The user starts a health scan in our application.
  2. The camera captures a short video of the user's face.
  3. Shen AI analyzes subtle physiological signals from the video feed.
  4. AI models process these signals and estimate health measurements.
  5. Our application receives the results and decides how to present or use them.
The core technologies behind Shen AI are remote photoplethysmography (rPPG) and remote ballistocardiography (rBCG). rPPG is a method that detects tiny changes in light reflected from the skin that correspond to blood flow, while rBCG tracks the micro-movements caused by blood being ejected from the heart. Shen AI combines this multimodal approach (rPPG + rBCG) with advanced computer vision and AI models to produce reliable measurements across different devices, lighting conditions, and skin tones.

The following provides the sources and permit as a medical device IIa in the EU for this framework.

EU Permit and Scientific Sources

Values calculated directly as a result from the video capture session

  • Heart Rate
  • Breathing Rate
  • Heart Rate Variability
  • Blood Pressure

Additional values - calculated by Shen.AI based on results of the video session

Cardiac Workload

Cardiac workload is calculated as the product of heart rate and systolic blood pressure (measured in mmHg/s), also known as the rate-pressure product (RPP)—a key indicator of cardiac oxygen consumption. The higher the systolic arterial blood pressure, the harder the heart must work to eject a given amount of blood with each heartbeat. Similarly, at higher heart rates, cardiac oxygen demand increases, even if the work performed per heartbeat remains unchanged, as the cardiac muscles consume more oxygen during their excitation-contraction processes.

  1. Hetzenecker A, Buchner S, Greimel T, Satzl A, Luchner A, Debl K, et al. Cardiac workload in patients with sleep-disordered breathing early after acute myocardial infarction. Chest. 2013;143:1294-301.
  2. Westerhof N. Cardiac work and efficiency. Cardiovasc Res. 2000;48:4-7.
  3. Baller D, Bretschneider HJ, Hellige G. Validity of myocardial oxygen consumption parameters. Clin Cardiol. 1979;2:317-27.
  4. Kitamura K, Jorgensen CR, Gobel FL, Taylor HL, Wang Y. Hemodynamic correlates of myocardial oxygen consumption during upright exercise. J Appl Physiol. 1972;32:516-22.

Parasympathetic Activity (PA)

PA is a measure of parasympathetic nervous system activity based on spectral analysis of heart rate variability (HRV).
It is calculated as follows:

  1. Signal Processing – The RR interval tachogram is low-pass filtered (up to 0.4 Hz) to remove high-frequency noise.
  2. Spectral Analysis – Power spectral density (PSD) is computed, and power is extracted from two frequency bands:
    Low Frequency (LF): 0.04–0.15 Hz
    High Frequency (HF): 0.15–0.4 Hz
  3. PA Calculation – The relative contribution of HF power (associated with parasympathetic activity) to the total power in both bands: HF / (LF + HF) × 100%

PA reflects the dominance of parasympathetic modulation in heart rate control, with higher values indicating greater parasympathetic influence.

  1. Olivieri F, Biscetti L, Pimpini L, Pelliccioni G, Sabbatinelli J, Giunta S. Heart rate variability and autonomic nervous system imbalance: Potential biomarkers and detectable hallmarks of aging and inflammaging. Ageing Res Rev. 2024 Nov;101:102521. doi: 10.1016/j.arr.2024.102521. Epub 2024 Sep 27. PMID: 39341508.

Stress Index (SI)

SI is a metric derived from heart rate variability (HRV) analysis, reflecting the overall state and functional reserve of cardiovascular regulatory systems, particularly the balance between the sympathetic and parasympathetic branches of the autonomic nervous system.
SI is calculated using a modified version of Baevsky’s method, which analyzes the distribution of heartbeat intervals rather than relying solely on traditional statistical measures. This approach incorporates quartile-based dispersion measures and the overall shape of the histogram of interbeat intervals.
More on Baevsky's method:
https://ieeexplore.ieee.org/document/10782708

Additional values - calculated by Shen.AI based on given personal information

Waist-to-Height Ratio (WHtR)

Waist-to-Height Ratio (WHtR) is a metric that estimates the risk of obesity-related conditions, such as cardiovascular diseases, diabetes, and metabolic syndrome, by assessing abdominal fat distribution through the ratio of waist circumference to height. Higher WHtR values indicate greater abdominal fat, which is associated with increased health risks.

Note: WHtR may either be directly calculated from waist circumference and height or estimated using regression models based on demographic data.
Data needed to compute WHtR:

  • age
  • gender
  • height
  • weight
  • ethnicity

Resources

  1. Gibson, Sigrid & Ashwell, Margaret. (2019). A simple cut-off for waist-to-height ratio (0·5) can act as an indicator for cardiometabolic risk: Recent data from adults in the Health Survey for England. British Journal of Nutrition. 123. 1-26. 10.1017/S0007114519003301.
  2. Eslami M, Pourghazi F, Khazdouz M, Tian J, Pourrostami K, Esmaeili-Abdar Z, Ejtahed HS, Qorbani M. Optimal cut-off value of waist circumference-to-height ratio to predict central obesity in children and adolescents: A systematic review and meta-analysis of diagnostic studies. Front Nutr. 2023 Jan 4;9:985319. doi: 10.3389/fnut.2022.985319. PMID: 36687719; PMCID: PMC9846615.

Body Fat Percentage (BFP)

Body Fat Percentage (BFP) estimates the proportion of fat in the body relative to total body weight. It is an important indicator of overall health and fitness, helping to assess the risk of obesity-related conditions such as heart disease, diabetes, and metabolic syndrome. A higher body fat percentage is associated with an increased risk of cardiovascular disease. Understanding BFP helps users monitor their health status and encourages lifestyle changes to reduce fat levels.
Data needed to compute Body Fat Percentage (BFP):

  • age
  • gender
  • height
  • weight
Resources
  1. Ideal Body Fat Percentage chart (American Council on Exercise)
  2. Hodgdon, J.A.; Beckett, M.B. (1984). Prediction of Percent Body Fat for U.S. Navy Men and Women from Body Circumferences and Height. Naval Health Research Center.

Body Mass Index

Data needed to compute Body Mass Index:

  • height
  • weight
Resources
  1. World Health Organization. (2000). Obesity: Preventing and managing the global epidemic (WHO Technical Report Series No. 894). https://apps.who.int/iris/handle/10665/42330
  2. World Health Organization. (2005). The SuRF Report 2: The Surveillance of Risk Factors Report Series. World Health Organization. p. 22. https://iris.who.int/handle/10665/43190

Basal Metabolic Rate (BMR)

Basal Metabolic Rate (BMR) is the number of calories your body requires at rest to maintain basic physiological functions, such as breathing, circulation, and cell production. BMR accounts for a significant portion of total daily energy expenditure (TDEE) and is influenced by factors such as age, gender, weight, height, and body composition.
BMR doesn’t have strict “normal ranges” like some other health metrics (e.g., blood pressure or cholesterol levels) because it is highly individual. However, understanding your BMR helps assess whether your energy needs are typical for your age, gender, and body composition.
Data needed to compute Basal Metabolic Rate (BMR):

  • age
  • gender
  • weight
  • height

Total Daily Energy Expenditure (TDEE)

The Total Daily Energy Expenditure (TDEE) represents the total number of calories your body uses in a day to perform all activities, including basic physiological functions (BMR), physical activity, digestion, etc. TDEE is crucial for understanding calorie requirements and planning dietary/fitness goals (weight loss, maintenance, or muscle gain).
Data needed to compute TDEE:

  • age
  • gender
  • weight
  • height
  • physical activity level
Resources
  1. https://www.mdcalc.com/calc/25/basal-energy-expenditure#evidence
  2. https://www.google.com/books/edition/A_Biometric_Study_of_Basal_Metabolism_in/5A7ug_oiBHYC?hl=en&gbpv=0

Last updated: 14. Sep 2026

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