HNL is a tool for measuring emotional commitment that relies on the advanced analysis of the electrocardiogram of people exposed to a stimulus: audiovisual content for example.
Simple and non-invasive, the patches connected to a computer allow the HNL software to capture even the smallest cardiac variations in a person.
Our technology is based on several patents and scientific publications, including automatic detection of R peaks, signal normalization, quantification of parasympathetic tone and transformation into exploitable emotional information.
Two points differentiate our technology: interindividual normalization and calibration of the emotional scale.
Interindividual normalization reduces the number of needed participants and avoids parasites variables such as age, gender and so on.
Calibration of the emotional scale: HNL degrees (°HNL) provide clear and directly exploitable information about the second-to-second emotional impact of participants’ experiences because they have been calibrated. Four emotional temperatures are proposed: not significant, low, medium or high emotional intensity.
To enable the translation of recorded emotions, HNL has created a simple degree of emotional intensity on a scale of 0 to 100, the HNL degree. (° HNL)
between 0 and 8, the emotion is not considered significant.
– ° HNL min is the smallest emotional intensity felt over the duration of the content.
– ° HNL max corresponds to the highest emotional intensity felt over the duration of the content.
– ° HNL i (index) thus corresponds to the emotional average felt over the duration of the content.
In order to simplify the reading of the data, the results are classified according to a simple indicator:
– Hot if the °HNL is greater than 32
– Medium if the °HNL is between 16 and 32
– Cold if the °HNL is between 8 and 16
The greater the emotional intensity, the more the measured panelist is involved in the content, we can say that they are engaged, touched by the content. When an individual is emotionally affected, they will be interested in the content, they will understand it better (or will make efforts or additional research to understand it), they will retain it more easily, but also perennially.
The valence of an emotion (that is, whether it is positive or negative) will be determined by the panelist them self, or will be easily deductible by the study operator.
The worst thing that can happen for content is that it generates indifference, that is to say that the message does not get through. HNL allows you to detect empty content.