Basic info:
Presage vitals by video analysis generates heart rate variability, specifically the root mean square of successive NN differences from a video clip containing a subject’s face. An API has also been developed to allow users easy access to compute this metric for commercial and scientific applications.
Organization developing model: Presage Technologies
Model date: 20250911t173240
Model version: 1.6.0
Model type:A deterministic computer vision model with two primary stages. The first identifies and tracks key feature points on the subject’s face, and aggregates the image intensity into a set of means for specific regions of interest. The second stage uses signal processing to analyze the temporal fluctuations of these means to isolate and quantify the aggregate photoplethysmogram, from which HRV is computed. Heart rate variability (HRV) is reported as the RMSSD (Root Mean Square of Successive Differences) of NN intervals. NN interval is defined as the remote photoplethysmograph peak to peak interval, measured in milliseconds.
License: The algorithm is currently proprietary, and licenses are granted with predefined agreement.
Where to send questions: Questions can be sent to: support@presagetech.com
Model uses:
This HRV model was intended for use by qualified clinicians, polygraphers and researchers for the analysis and non-diagnostic utility of HRV quantification and derivative metrics. It was intended to be used with a video from a stationary device (such as a handheld, mobile or laptop camera), that contains the subject’s face in view, and be of 60 consecutive seconds in length and acquired at a minimum of 25 frames per second. The user’s face must be visible and unobstructed for at least 60 consecutive seconds within the video, and the user must not make sudden large motions or move their face beyond 90 degrees of optical axis during this time. It is only intended to measure on participants with pulse rate values in the range of 40-180 bpm.
Out-of-scope uses:
The Presage HRV model is not intended for diagnostic purposes. Do not self-diagnose or self-medicate on the basis of the measurements. No alarms are provided, and it is not an arrhythmia detection or monitoring model. It is currently not intended for use in highly dynamic environments, or with a highly moving camera. We ensure all users have acknowledged and agreed to our license agreement and terms of service for usage prior to use.
The HRV model first requires Mediapipe’s face detection algorithm to identify the face and 468 key feature points on the face (mesh model). Thus, if these features are not identifiable by Mediapipe’s algorithm, then HRV will not be calculable. Reference the Mediapipe model cards can be found here: Full Range Face detection model card.
These factors can affect model performance:
Other factors:
The evaluation data consists of a set of 231 videos. Corresponding quantities of HRV were measured from a Biopac 3 lead ECG. A clip of 60s from each video was run through the Presage HRV model for evaluation, leading to a total number of 356 samples. Videos were acquired on users covering a range of demographic variability, including age, gender and Fitzpatrick scale.
Distribution of error figures:
Skin Tone (Fitzpatrick) | % of Dataset (num samples) | RMSD | MAE [95% CI] | Mean Return Rate |
---|---|---|---|---|
1 | 0.17 (73) | 36.94 | 24.20 [16.68, 31.71] | 0.79 |
2 | 0.14 (60) | 36.87 | 23.31 [13.87, 32.75] | 0.75 |
3 | 0.09 (38) | 22.20 | 14.81 [9.19, 20.43] | 0.79 |
4 | 0.15 (65) | 56.95 | 41.49 [28.17, 54.82] | 0.62 |
5 | 0.14 (60) | 90.83 | 65.31 [42.70, 87.92] | 0.55 |
6 | 0.15 (66) | 53.76 | 38.91 [26.17, 51.65] | 0.48 |
Sex | % of Dataset (num samples) | RMSD | MAE [95% CI] | Mean Return Rate |
---|---|---|---|---|
M | 0.36 (161) | 37.96 | 25.80 [20.33, 31.26] | 0.71 |
F | 0.45 (201) | 62.56 | 40.45 [32.06, 48.84] | 0.62 |
Camera Type | % of Dataset (num samples) | RMSD | MAE [95% CI] | Mean Return Rate |
---|---|---|---|---|
Android | 0.48 (212) | 40.04 | 24.64 [19.38, 29.89] | 0.74 |
Econ | 0.52 (230) | 59.00 | 41.55 [34.56, 48.53] | 0.59 |