Using "big data" from sensors worn continuously outside the lab, researchers have observed patterns of objective physiology that challenge some of the long-standing theoretical concepts of emotion and its measurement. One challenge is that emotional arousal, when measured as sympathetic nervous system activation through electrodermal activity, can sometimes differ significantly across the two halves of the upper body. We show that traditional measures on only one side may lead to misjudgment of arousal. This article presents daily life and controlled study data, as well as existing evidence from neuroscience, supporting the influence of multiple emotional substrates in the brain causing innervation on different sides of the body. We describe how a theory of multiple arousals explains the asymmetric EDA findings. Keywordsaffective computing, ambulatory measurement, electrodermal activity (EDA), emotional arousal, idiographic research, sympathetic nervous system (SNS)

We respond to the commentaries of Critchley and Nagai, Mendes, Norman, Sabatinelli, and Richter. We agree that a theory needs to make predictions and we elaborate on the predictions we made so far. We do not agree that arousal has to have a precise definition in order to present theory about it; however, we do provide concrete answers to questions raised about multiple arousal theory.

Abstract-The wide availability of low-cost wearable biophysiological sensors enables us to measure how the environment and our experiences impact our physiology. This creates a challenge: in order to interpret the longitudinal data, we require the matching contextual information as well. Collecting continuous biophysiological data makes it unfeasible to rely solely on our memory for contextual information. In this paper, we first present an architecture and implementation of a system for the acquisition, processing, and visualization of biophysiological signals and contextual information. Next, we present the results of a user study: users wore electrodermal activity wrist sensors that measured their autonomic arousal. These users uploaded the sensor data at the end of each day. At first, they annotated their events at the end of each day; then, after a two-day break, they annotated the data from two days earlier. One group of users had access to both the signal and the contextual information collected by the mobile phone and the other group could only access the biophysiological signal. At the end of the study, the users filled in a system usability scale and user experience surveys. Our results show that the system enables the users to annotate biophysiological signals at a greater effectiveness than the current state of the art while also providing very good usability.

This work proposes a system for the automatic annotation and monitoring of cell phone activity and stress responses of users. While mobile phone applications (e.g., e-mail, voice, calendar) are used to non-intrusively extract the context of social interactions, a non-intrusive and comfortable biosensor is used to measure the electrodermal activity (EDA). Then, custom stress recognition software analyses the streams of data in real-time and associates stress levels to each event. Both contextual data and stress levels are aggregated in a searchable journal where the user can reflect on his/her physiological responses.