Science behind the algorithm

That is why we must understand their mechanisms in depth and how they really work. Emotions serve as a crucial role in our daily lives, from the way we respond to how we make decisions. They have an impact on our physical and mental health. If we take a peek under the hood, our emotions, ranging from the most pleasant to the most stressful ones, are generated and regulated by the Limbic System in our brain. This creates a matching physical response in our body, controlled by the Autonomic Nervous System (ANS). Both of these systems have evolved significantly since our ancient mammal ancestors, to the sophisticated and complex human species we are today.

Examining the Limbic System closely, we understand that it is a collection of small sections in our brain, each one with serving its very own unique role. The Hypothalamus, the Hippocampus and the Amygdala are just a few examples of the parts making up the Limbic System that are responsible for a diverse set of emotions such as pleasure, anger, fear, stress, aggression and many more.

On the contrary, the ANS consists of two sub-systems, the Sympathetic and Parasympathetic systems. The Sympathetic nervous system prepares our body for the “fight, flight or freeze” response, while the Parasympathetic system is in charge of returning our body back to its normal state.

Scientific Team & Partners

The scientific team boats the director of the Department of Stress Neurobiology and Neurogenetics at Max Planck Institute of Psychiatry (Germany). The Head of the Neurobiology Department at Weizmann Institute of Science (Israel), and medical experts in different field related to stress and research.

We process and analyze data has evolved significantly over the past few years. The use of complex deep learning networks is bringing us closer to understanding human emotions and the effect they have on our body. But there are still many obstacles to overcome.

GSR is arguably the most useful index of changes in sympathetic arousal that are tractable to emotional and cognitive states as it is the only autonomic psychophysiological variable that is not contaminated by parasympathetic activity.

The most common approach for representing affective states is a dimension approach, presenting valence, arousal and dominance dimensions. This can be done by using the Self-Assessment Manikin (SAM), individuals can assess their own emotional responses.

HRV is a useful index for assessing human emotions, due to its connection and reflection by the ANS, thus this makes the HRV (together with the analysis measurements), a strong and valid objective tool for measuring human emotions.

To build a versatile machine learning algorithm, a large amount of data is required. For this task we planned two different experiments, one focused on stress specifically and the other focused on affective responses.

Seamlessly integrate with our algorithm

Countries involved in our research

Data samples collected to date, processed and analyzed as the foundation of Kenko's AI algorithm and the base for validating it's superiority

Lab experiments conducted in various academic protocols

Reaction events induced, recorded and investigated

Habituation To Stress As A Performance Factor

KENKO TECHNOLOGY

Science behind the algorithm

Emotions matter

Scientific Team & Partners

Data Analysis

GSR

Measuring Emotions

HRV

Experiments

Measuring Emotions

Seamlessly integrate with our algorithm

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