Improving real-life, heart rate based estimates of emotion by taking metabolic heart rate into account – a perspective and an example in cooking

Abstract

Physiological variables such as heart rate carry information about mental state (cognitive and emotional state - here we simply refer to ‘emotion’). An important advantage over verbal methods as a way to probe emotion, is that heart rate is an implicit measure that can be measured continuously. Extracting information about emotion from heart rate in real life is challenged by the concurrent effect of physical activity on heart rate caused by metabolic need. “Non-metabolic heart rate”, which refers to the heart rate that is caused by factors other than physical activity, would be a more sensitive and more universally applicable correlate of emotion than heart rate itself. To precisely determine non-metabolic heart rate is a challenge. We explored evidence from the literature that non-metabolic heart rate, as it has been determined up until now, indeed reflects emotion. We focused on methods using accelerometry since these sensors are readily available in devices suitable for daily life usage. We found no convincing evidence that these existing methods lead to estimates of non-metabolic heart rate that reflect emotion. This is probably caused by the fact that intensity of motion signals as recorded from accelerometers does not correspond one-on-one with muscle activity in cases that forces are exerted without much movement (isometric muscle activity). In addition, the placement of the sensors do not always match the currently moving body parts, leading to invalid estimates. Studies in the field of energy expenditure as measured through variables extracted from respiratory gas exchange, show that energy expenditure can be well estimated using accelerometry by first identifying the type of action that is performed, rather than (only) using the intensity of motion signals. We therefore suggest that for real-life cases, estimating the type and intensity of activities based on accelerometry (and other information), and in turn use those to determine the non-metabolic heart rate, is the most promising route to determining non-metabolic heart rate precisely enough in order for it to be useful in estimating emotional state. In a study on estimating emotion during real-life cooking, we determined non-metabolic heart rate by correcting heart rate in an activity specific way. Rather than using a model that estimates specific activities based on accelerometry, we made an effort to estimate a baseline metabolic heart rate from participants performing movements that occur during cooking, without the emotion that occurs during cooking. The aim was to investigate the potential of non-metabolic heart rate to reflect emotionally salient phases during the process of cooking a dish.