Mental Stress
The Mental Stress metric is a powerful parameter to quantify the mental stress status of the user, using key biomarker and facial micro expression metrics. An all-in-one, scientifically-backed index to personalise the mental health guidance on your platform and increase the self-awareness of your users.
The Mental Stress metric is calculated based on a combination of machine learning algorithms informed by selected HRV (Heart Rate Variability) metrics alongside context-based reasoning. The calculation uses an exponential weighting average, which accounts for historical data while prioritising recent Face Scans to provide a current snapshot of mental stress.
When is the first reading available? To obtain an initial reading, users must complete at least one Face Scan. The first result will be available the day after the first Face Scan is completed, and the value is further finetuned as more Face Scans are performed.
This unique all-in-one biomarker can help assess the stress load and the user's capacity to cope with stress. It serves as a valuable indicator to detect whether a person is potentially heading towards burnout or chronic stress. For a comprehensive evaluation of mental fitness, utilize this metric in combination with the Mental Health Risk and Sleep Quality metrics.
Use the Mental stress metric to offer hyper-personalized actionables to the user. Guide the user to relevant stress-relieving activities/offerings on your online platform. High Mentral Stress values serve as warnings and can be the starting point to introduce preventive measures for individuals engaged in prolonged stressful activity that may lead to burnout.
Mental Stress is returned as an integer on a scale of 0 to 5 and can be requested as a Widget or via the Rest API.
Name | Unit | Range | programmatic name | Health Profile |
|---|---|---|---|---|
Mental Stress | NA / Score between 0 and 5 | 0 - 5 | mental_stress | Mental Health |
Value | Meaning | Zone | Example User Text |
|---|---|---|---|
0 and 1 | Minimal | Green | You have a very low stress level. Keep going like this! |
2 | Normal | Green-Yellow | You're stress levels are normal. You're ready for the day! |
3 | Elevated | Yellow | You may be feeling a little more stressed than usual. You could consider implementing some stress management activities today like breathing exercises, meditation, or yoga. |
4 and 5 | High | Red | It seems like you are feeling quite stressed out. It's time to prioritize relaxation, recovery, and self-love. Activities like light stretching, journaling, and taking a hot bath can bring some mental relief. For better sleep, give yourself a little extra time to decompress before bed. |
The table above shows
- Value: The possible values for the health insight
- Meaning: What does the value mean
- Zone: We distinguish three zones, useful – for example - when creating a widget to clarify the feel towars the user
- Green = Optimal to normal
- Yellow = Normal to average
- Red = Outside the typical range; may require attention
- Example user text: An example of what could be communicated to the user in case this value is measured.
Add actionables to the Mental Stress output to hyper-personalize the user journey on your platform or app. The following actionables are the result of in-depth analyzes of observational studies performed by IntelliProve.
Impact sleep
On average, one good night's rest will decrease your stress level with 5,1%.
Impact stress-relieving activities
On average, relaxation will decrease your stress level with 32,9%.
Impact work
On average, stressful work increases your stress level with 30,3%
- McDuff D, Gontarek S, Picard R. 2014. Remote measurement of cognitive stress via heart rate variability. Conf Proc IEEE Eng Med Biol Soc. 2014:2957–2960.
- Taelman J, Vandeput S, Spaepen A, Van Huffel S. 2009. Influence of mental stress on heart rate and heart rate variability. Conf Proc IEEE Eng Med Biol Soc. 2009:2196–2199.
- Melillo P, Bracale M, Pecchia L. 2011. Nonlinear heart rate variability features for real-life stress detection. Case study: students under stress due to university examination. Biomed Eng Online. 10:96.
- Shaffer F, Ginsberg JP. 2017. An overview of heart rate variability metrics and norms. Front Public Health. 5:258.