Our mission

Understanding human nature

 

To become the standard in measuring and understanding human emotions to drive business success we build on the latest science and technology.

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We rely on the best sensors

We use biometric sensors that are used thoroughly in academic and applied research settings. They have been validated using meticulous tests, and validations are published in peer-reviewed journals.

 

We build on the most robust methodology

Our methodology is based on the latest advancements in psychophysiological research. Our metrics are refined using our database that contains measurements from tens of thousands of participants, using thousands of video stimuli.

 
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We leverage the cloud & open-source

By cooperating with Google and basing all of our data-intensive tasks and web-based services on their cloud offerings we can focus on development as we don't have to worry about infrastructure and are able to scale up our operations as soon as it is needed. Investing in the state-of-the-art scientific computing ecosystem of Python helps us in constantly improving our results and rate of productivity.

 

We learn & improve constantly

Basing our research and development processes on battle tested agile methodologies and by constantly collecting user feedback we are able to react to customer needs and iterate product development quickly.

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We proudly collaborate with

Budapest University of Technology and Economics, Hungary

Budapest University of Technology and Economics, Hungary

Vrije Universiteit, Netherlands

Vrije Universiteit, Netherlands

University of Augsburg, Germany

University of Augsburg, Germany

Eötvös Loránd University, Hungary

Eötvös Loránd University, Hungary

Featured scientific publications

 
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Predicting arousal with machine learning of EEG signals

In this study, we investigated how different biometric sensors can predict the arousal of participants while they watched a diverse set of short videos. We found that electrodermal activity (i.e. the conductivity of the skin) can be more reliably used than electrical activity from the surface of the skull.

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Comparison between wireless and wired EEG recordings in a virtual reality lab: Case report

This case study examined if traditional, wired laboratory EEG devices (that are used to measure the electric activity of the brain) and wireless counterparts are comparable. It was found that the slower electric oscillations of the brain — that are more relevant to brain research — can be reliably measured using wireless devices.

 
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A fluid response: Alpha-amylase reactions to acute laboratory stress are related to sample timing and saliva flow rate

In this study, heart rate based metrics were used to understand how experimental stressors (cold water pain and mental arithmetic calculations) affect participants stress level, measured by salivary analytes. It was found that the autonomous nervous system has different response latency, therefore timing should be especially important for the measurement of psychophysiological activity.

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Lateralized Rhythmic Acoustic Stimulation during Daytime NREM Sleep Enhance Slow Waves

This study investigated if a rhythmic sound during sleep can differentially induce better sleep — measured by the electric activity from the skull — in the two brain hemispheres. It was found that although the acoustic stimulation did lead to better sleep, this effect was not specific for the two hemispheres.

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