The Science Behind

Because every person is individually different,
the BioRICS technology only compares you with yourself

Improve with data and science

BioRICS has 14 years of experience with developing wearable software, based on 30 years of scientific research. BioRICS has developed algorithms and built a sound expertise to apply them in the field of human health tracking (physical condition, mental status, sleep quality and drowsiness). These algorithms are application-specific and have been made fit for integration into new, cutting-edge products of BioRICS and in those of their customers.

The BioRICS methodology

For aerobic energy production to happen, we breath air which the lungs bring into the blood. The heart pumps the oxygen-rich blood to cell level where metabolic energy is produced. Consequently, level of heartbeat is a measure for aerobic energy production. The BioRICS approach has focused on the decomposition of the heartbeat’s main components. By measuring continuously and monitoring the dynamic response of the heart rate throughout the day and the night, the basal metabolism and thermoregulation components are estimated whilst the physical component is measured using the accelerometer in the wearable.

The mental component is calculated thereof using the adaptive models which allow to distinguish the physical from the mental component. This principle has been validated in several scientific studies on humans (see pdf).

So, we monitor the distribution of heart rate (aerobic energy production) over the different components: basal metabolism, thermal component, physical and mental component. The unique strength of BioRICS is the fact that this monitoring is done:

  • in real-time
  • on moving subjects
  • with individualised algorithms.

Basic principles

The methodology starts from the principle that an individual living organism (human, animal, plant) is considered a CITD system, which stands for:

  • Complex
    Each biological organism consists of numerous sub processes and interacts with numerous other processes in the same living organism and its micro-environment.
  • Individually different
    Similar to looks and personalities, each living organism is biologically different and responds in an individual way.   
  • Time-varying
    The response of a living organism is very variable in time and depends on both external (e.g. temperature, other people, etc.) and internal (e.g. current state of mind, age, etc.) factors. Unlike a machine, a living organism is expected, and can respond differently to the same stimulus provided at different moments in time, even if they are very close to each other.
  • Dynamic
    Nothing in a living organism is constant. There are continuous changes in the pursuit of a balanced situation. Steady states will not be achieved, but rather dynamic changes to reach a balance between 1. a person’s environment (homeostatis), 2. the ability to perform actions and 3. the individual goals.
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Requirements for qualitative monitoring

Continuous measurements

If we want to collect information about the actual state of a living organism, we need to measure biological responses. Moreover, since the living organism is constantly varying, to capture the variation, continuous measurement of the relevant variables is necessary.

Automatic and real-time adaptation of the models

There is no single model that can describe the monitoring process that is used. Therefore, constant adaptation of the model in real-time is necessary. In the BioRICS algorithms, this is done in an automated way.

There is no single model that can describe the monitoring process that is used. Therefore, constant adaptation of the model in real-time is necessary. In the BioRICS algorithms, this is done in an automated way.

Individual, accurate metrics

An average of a population is a theoretical concept that has been developed to reach conclusions on populations. However, in order to differentiate and conclude on the individual’s state in a correct and accurate way, all metrics used need to come from the individual.

Dynamic models

There is no such concept as a steady state in a living organism. As such, the use of dynamic models to explain the underlying processes is the only way forward.

Monitoring Mental State: an Energy Balance Approach 

The living human body is all about energy. Our body needs energy to perform any type of function, from the very basic of maintaining our bodily functions to physical performance and more complex activities such as problem solving. From a macroscopic or biosystems analysis point of view, our body needs energy for the following:

Basal Metabolism

There is no single model that can describe the monitoring process that is used. Therefore, constant adaptation of the model in real-time is necessary. In the BioRICS algorithms, this is done in an automated way.

Thermoregulation

Humans are homoeothermic organisms and therefore need to keep their core body temperature constant. To do so, the body performs a number of actions, that require energy, such as producing more energy to increase the body temperature or vasodilation to lose heat and reduce body temperature.

Physical activity/performance

Any physical activity that we perform, from the smallest move of the finger to more intense activities such as running a marathon, requires energy.

Mental activity

Our brain is one of the most valuable parts of our body and as such it gets special treatment by our body. Still, for the brain to function energy is required.

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For all these energy-intensive aspects, food (proteins, carbohydrates and lipids) and energy (e.g. Adenosine Triphosphate, fat) stored in the body, need to be transformed to energy available to the body.

This transformation happens either in an aerobic way (e.g. using the oxygen we breath to metabolise organic compounds into energy) or in an anaerobic way (e.g. anaerobic glycolysis that is happening in the muscle when not enough oxygen is available).

The BioRICS methodology versus HRV

HRV measures the variation in the time interval between consecutive heartbeats. As scientifically described,  these variations relate to 16 possible reasons of which ‘stress’ is only one. However, to detect whether a variation in HRV relates to stress, is impossible without including other information. To exclude HRV variation due to movement, the subject needs to be inactive during the measurement, consequently HRV cannot be measured correctly on moving people.

The BioRICS methodology focuses on the real time measurement of the metabolic energy balance and more specifically on the energy  use for mental tasks. In this respect, energy recovery over a period is much more important to prevent mental health issues than just looking at stress alone. For example, being engaged in mental activities such as talking to friends or having fun also takes metabolic energy. The BioRICS algorithms run in real time (every second), whilst the person is moving and take time-varying characteristics of the individual into account.

 

 

Mental Energy Use and Recovery

As BioRICS uses individualised algorithms, the BioRICS products need to adapt and get to know the individual’s physiology when starting to monitor for the first time, 

The mental energy use is monitored from the distribution of heart rate. It represents all metabolic energy used for mental activities. This can be the result of different states such as positive or negative emotions, stress, focus, concentration, etc.  Therefore, context information is important to create awareness of positive experiences and negative stressors and let the user discover how his/her body responds to the many impulses it needs to absorb every day.  

Recovery is that part of the dynamics which is not used by the body for extra mental expenditure. Mental recovery can happen when relaxing or working without time pressure for example during the day but most recovery is built during the night when sleeping. This is why a 24-hour monitoring is important. 

Validation of the BioRICS algorithms

Table 1: examples of validation studies conducted by BioRICS in collaboration with KU Leuven or industrial partners

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Table 1: validation studies conducted by BioRICS in collaboration with KU Leuven or industrial partners

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