A Method to Filter Electrodermal Activity Through Accelerometer Data
Skin gives away information about how a person feels when they are emotionally aroused, whether they feel stressed, fearful, nervous, excited, happy, etc. When a person is emotionally aroused, the electrical conductivity of the skin changes, known as electrodermal activity (EDA). Changes in EDA can be studied via sensor devices. This technology is an algorithm that removes the movement noise from EDA data received from various devices, providing more accurate data for those studying EDA.
There are many devices that collect electrodermal activity data. As devices are becoming less cumbersome and better suited for everyday activity (some sensors can even be worn on the wrist), movement due to everyday activities introduces noise into the data. The movement of these devices and the corresponding noise introduced to the data make the data difficult to interpret with accuracy.
This technology is an algorithm that can be used to filter out noise due to movement from electrodermal activity data gathered from various devices. It allows those using the algorithm to see what is really happening in the data without extra noise from movement. This helps them to study only the relevant data and to come to better conclusions regarding EDA responses to various stimuli.
Being able to exclude noise due to movement from EDA data will open doors to researchers trying to better understand the relationship between various stimuli and people’s emotional responses to them. The field of electrodermal activity is a relatively new one; the subject invention marks a significant step forward in data analysis and interpretation.
At present the application of this technology is primarily research-based, but improved versions of movement noise exclusion are likely to be included in new devices as technology continue to be developed in general sensor and EDA areas.
Idalis Villanueva, Ph.D.
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