Biomarker of long-term stress

Description

Stress is experienced by people every day as a consequence of the many different factors . This results in an increased difficulty for the individual to notice when a prolonged period of stress manifest into health problems, as well as a difficulty in understanding the environmental factors responsible for it.

Current approaches to monitoring stress are mostly based on self-assessment through questionnaires or by a personal meeting with a psychologist. The former is not ideal since it relies on the subjects ability to recall past experiences and can be experienced as being obtrusive, and the latter due to the costs related to fomal interviewing. Therefore, the past decades have seen comprehensive research into finding a quantifiable biological parameter (a so called biomarker) to objectively measure stress. One of the main candidates is heart rate variability (HRV), which has already been proven useful in sequencing the daily life of individuals into periods of low and high stress levels. Therefore, the is a growing intest in using HRV for estimating indications of excessive stress loads causing an individual to be in risk of developing associated health problems. The fact that HRV baseline measurements have been proven to be highly sensitive to environmental factors as well as past activities during the day of the measurement adds to the complexity of measuring it, which is something past studies have not taken into account.

The purpose of the research program is therefore to create an experimental protocol for a study testing HRV measured from smartphones as a biomarker for longterm trends of stress levels in individuals, using the vast knowledge of HRV to ensure that it is acquired in the best possible way for it to reflect longterm stress trends. This includes developing methods around the acquisition of the biomarker as well as the development of all software necessary for processing and analysing the data.

Contact persons: Naja Hulvej Rod (nahuro@sund.ku.dk) and Mathias Pinto Bonnesen (mathias.bonnesen@ku.sund.dk)