Optimizing biosensor software with biosensors
![](https://mir-s3-cdn-cf.behance.net/project_modules/max_1200/ce616d96310339.5eab354ce911d.png)
![](https://mir-s3-cdn-cf.behance.net/project_modules/max_1200/d77be096310339.5eab354ce8bfd.png)
![](https://mir-s3-cdn-cf.behance.net/project_modules/max_1200/00869c96310339.5eab354ce8679.jpg)
For my current project, my master thesis, my thesis group and I chose to work with one of most rapidly emerging technology, biosensors. Biosensors come in many forms, from simple things such as heart rate monitors, to high tech electrodermal activity (also called EDA). The case given to us were from one of the leading companies in biosensor techonology and biosensor software is iMotions, a software which allows all kind of biosensor data to be collected and analyzed in the same software.
![Image may contain: screenshot and clipart](https://mir-s3-cdn-cf.behance.net/project_modules/disp/3e248896310339.5eab354d74bd2.png)
Our involvement revolved that the iMotions software is an advanced software as it can be used for up to six different biosensors. As such, it is complex to learn the functionalities of the software without being overwhelmed by all the information. This is where my competencies for user experience and information studies come in, in addition to that I am also a certified iMotions user. Our approach to the case was to combine the use of eye tracking, facial expression analysis and EDA to measure users gaze behavior, their irritation and their engagement when using the software, with these sensors.
![Image may contain: screenshot and person](https://mir-s3-cdn-cf.behance.net/project_modules/max_1200/4d6cdc96310339.5eab354d73b88.png)
In above picture, the use of eye tracking are shown. With such technology, you are able to creat heatmaps of what the user look at first, how long they look at it, what catches their attention. For this case, it also allows us to see where the participant look when asked to complete a task, showing where they expect the contet to be, and where they look if they can't find the content.
![Image may contain: human face, smile and person](https://mir-s3-cdn-cf.behance.net/project_modules/max_1200/9d148b96310339.5eab354d74792.png)
Facial expression analysis is less intruding biosensor, as it just needs a camera to work. The use of capturing users faces during a test gives valuable insight towards if the user feel irritated, discomfort or joy during the task, especially highlighting if the users are frustrated by the tasks.
![Image may contain: map](https://mir-s3-cdn-cf.behance.net/project_modules/max_1200/c455f396310339.5eab354d74257.jpg)
The last sensor we want to apply is the electrodermal activity sensor (EDA). EDA is a sensor placed on two fingers and stricly technically speaking, it measures the sweat level of the user. However, the sweat conductance can tell a lot more than you think as it is not normal sweat levels it register, but tiny chemical signals the body is sending the brain. Thus, it is a sensor that can be used to see emotional intensity the user register. However, it cannot tell if what this emotion is.
By combining all three sensors, we would be able to get very accurate insights into what is working in the current software, what's not and how the user react to to different tasks. Unfortunately, due to COVID-19, our above approach were not possible, and we needed to find adjust our approach to be solely digital data collection