Physiological measurements form an integral part of science and have a growing role in social research. These measurements provide an insight in some of the body’s and nervous system’s responses to stimuli, often in real-time. The developments in the field of physiological measurements and the myriad of devices that are capable of them follow each other in quick succession. This is where the experience and expertise of the BMS lab is often needed. A research collaboration involving researchers from the University of Twente, Tactus addiction care and The Netherlands Organization for applied science, recently developed and published a method for the validation of new physiological measurement devices and measurements. Their work will aid in further developing the field, the devices and the adoption of physiological measurements in social research.
Physiological measurements can provide a window in the participant’s experience or mind through the measurable responses their body gives. One’s skin conductivity might for example be indicative of someone’s excitement or stress levels, similar to one’s heart rate. The potential of these measurements and the devices that support them is however limited by the little amount of information that is available on the scientific validity of a lot of the devices used for physiological measurements. In this study the researchers aimed to do more than fill the current need for information. Through careful testing using the BMS lab’s Empatica E4 wrist sensors, they were able to develop a procedure with which to validate both the E4’s measurements and that of physiological measurements in general. Their study included work on biases, errors and criteria for valid measurements and have been published. You can read their work using the reference below and link below.
van Lier, H. G., Pieterse, M. E., Garde, A., Postel, M. G., de Haan, H. A., Vollenbroek-Hutten, M. M., … & Noordzij, M. L. (2019). A standardized validity assessment protocol for physiological signals from wearable technology: Methodological underpinnings and an application to the E4 biosensor. Behavior research methods, 1-23.