Frequently Asked Questions

Based on our experience, a first integration of the IntelliProve software can be performed in less than 1 day. For developers, we kindly refer to the technical documentation for more information on how to integrate our software into your solution.

During the integration process, we offer full support to guide you to a successful launch.

Yes, it is possible to white label IntelliProve. For solutions that want a seamless experience, internally and externally, IntelliProve is the perfect option.

Health checks will be an integral part of your offering, without the need to refer to a third party.

The price is based on the number of health checks per month, so tailored to the volume of your platform. If you are interested in a price proposal completely according to your needs, reach out to us via [email protected] or schedule a meeting with our team.

At IntelliProve, we take privacy and security seriously. Our policies, technical controls and organizational controls have been designed to ensure the highest level of confidentiality and integrity when processing your data. IntelliProve undergoes regular penetration testing and security reviews and has been designed from the ground up to be GDPR compliant.

We would like to refer you to our Privacy policy for measures that IntelliProve has taken to ensure complete pseudonymization of the data. Our Data Processing Agreement (which includes our list of subprocessors) is available upon request. Please email [email protected] for more information.

There are various ways to use IntelliProve's health and well-being biomarkers within your online solution:

Biomarkers can easily be linked to your specific offering. In general, the value of a certain biomarker (or combination of biomarkers) defines which part of your offering is recommended to your user. Clear examples:

For more information, check out the 'How can it be used?' sections of every biomarker on our product documentation. Additionally, a workshop is offered as part of our product to establish the linkage of the biomarkers to your specific solution.

One of the significant advantages of our API offering is the complete customization of the returned values and follow-up based on the preferences and logic of the platform itself. Our clients employ various methods to interpret the measured values, some concrete examples are:

In our documentation portal, you can find definitions, examples of color coding, and qualitative information for each value bracket. In addition, during a short workshop (offered as part of our product), you will be guided in the interpretation of the biomarker according to your specific solution.

An analysis of at least 20 seconds is required to perform a qualitative measurement.

IntelliProve provides a comprehensive .json file containing all available biomarkers. It allows you to manually select the specific biomarkers you want to use and determine their optimal use. This level of customization empowers you to personalize your solution even further.

All biomarkers and parameters, except for the Mental Health Risk, are sent back immediately and represent a unique objective snapshot of that moment of time. By conducting frequent measurements, a trend/progress over time can be obtained.

To calculate Mental Health Risk, the user needs to have performed health scans for the past three weeks. At least two health scans per week are required. This is because our machine learning model has been trained to make a prediction based on a trend over time.

The evaluation of the performance of the algorithms is performed by step-by-step comparative analyses with the current state-of-the-art medical devices (pulse oximeter, sphygmomanometer,…) or questionnaires (e.g. PHQ-9, GAD-7). The accuracy and precision are checked by calculating for example the Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE) and Correlation Coefficient (R).

Currently, more than 1 million datapoints (resulting from various collaborations with clinical organisations) are actively used for testing and validating our models.

We kindly refer to our validation and precision report for an in-depth analysis on how our software is tested and validated. In short, the accuracy and precision levels of our product can be found in the table below.

IntelliProve makes use of photoplethysmography (PPG), an optical method to measure cardiac-synchronous blood volume change in body extremities such as the face, fingers and earlobes. As the heart pumps blood, the volume of blood in the arteries and capillaries changes by a small amount in sync with the cardiac cycle. This change in blood volume in the arteries and capillaries underneath the skin leads to small changes in the skin colour (visible in the Red/Green/Blue spectrum), from which a PPG waveform is estimated.

Traditionally, the PPG signal is captured using a device (e.g. pulse oximeter) that emits light and measures the amount of light that is absorbed or reflected by the tissue. In our approach, we use ambient light from the environment (the light source) and the camera from a smart device (the sensor) to measure the ‘remote’-PPG. The face serves as the region of interest due to its thin tissue and optimal blood perfusion.

Relying on modern computer vision technology, facial dynamics and microexpression patterns can be detected and extracted, reflecting the hemifacial asymmetry in emotion expressions. This makes it possible to objectively detect and predict mental disorders, such as anxiety or mood disorders.

Typical patterns are raised eyebrows, leaden gazes, swollen faces and hang-dog mouth expressions.

Heart Rate Variability, or HRV for short, is a non-invasive measure of your autonomic nervous system, which is the body’s main control center. It is widely considered as one of the best objective metrics for physical fitness and determining your body’s readiness to perform. HRV is literally the variance in time between the beats (NN interval) of your heart.

Heart rate variability (HRV) can be derived from a ECG or PPG signal. A commonly used statistical metric for representing short-time HRV (over a time duration of the order of 10s to 1 min) is the Standard Deviation of NN intervals (SDNN).

The intimate connection between the heart and the brain is well described. HRV is known to be regulated by the prefrontal cortex (i.e., brain regions involved in the regulation of ANS activity). It is considered to indirectly reflect complex patterns of brain activation and provides information on the central nervous system (CNS) functional organization and the bidirectional interaction between the CNS and the ANS. There is substantial evidence that HRV is not only a risk marker for cardiovascular disease, but that also decreases in HRV have close associations with depression, schizophrenia, and post-traumatic stress disorder. On the other hand, high HRV is generally associated with a relaxed and resilient mental state.

While we often associate biomarkers with physical illness, it is crucial to recognize their relevance in assessing mental well-being as well. We kindly refer to our comprehensive blog post about the use of biomarkers and how they can give professionals unique insights from a patient and provide valuable information for personalized care and treatment plans.

At IntelliProve, ensuring the effectiveness of our product across the population is a top priority. Due to continuous training and testing of our model with test subjects with different skin colours, no reduced performance can currently be observed in people with a dark skin colour.

To illustrate, the graph below represents the margin of error of the heart rate (which is a direct derivative of our signal quality) in the function of skin colour. The smaller this margin of error, the greater the signal quality. For each group, this margin of error remains nicely below the threshold of 5bpm (=clinical acceptability criteria). We kindly refer to our validation and precision report for more infomation.