Chapter 6 190 sensors directly. After a small preliminary study with main stakeholders and users on acceptable, usable, and nonstigmatizing hardware (unpublished), we decided to use a smartwatch and mobile phone. Next, we decided on developing an app for Google’s Android (including Wear) OS. As a mature, easy-to-access OS, it has a broad base of support by manufacturers, software developers, and users alike. Most smartwatches (at the time) came equipped with a photoplethysmogram (PPG) sensor and accelerometer. The PPG sensor is used for measuring heart rate (HR). After studying the literature on the use of biosignals for affect detection, we built an algorithm that takes the HR data of the user to calculate a physiological correlate of emotional arousal (PCEA). HR, similar to HR variability (HRV) and electrodermal activity (EDA), is triggered by the sympathetic nervous system [29,30]. Typical consumer wrist-based HR monitors provide a fairly accurate measurement of HR even when deployed during physical activity and movement [31]. The first version of the app was built by one of the authors (RK) and 2 graduate students in Human Media Interaction. The outcomes of previous design cycles served as the main sources of input for programming (refer to the study by Derks et al [28]). Visual design was kept low in complexity so that the app’s graphical user interface (GUI) is easy to interpret by the user yet remains nondescript to the environment (see Figure 1). To cater to the expressed need for discreet and unobtrusive coaching, audio signals were deliberately not implemented. Instead, the app was programmed to give tactile feedback via the vibration motor in the smartwatch. Users have direct access to a proxy of the current level of the PCEA via continuous HR measurements on both the smartwatch and mobile phone. On the smartwatch, users have the option to choose from 4 different watch faces. The mobile phone app provides an overview of the recent measurements. At higher levels of arousal (stages 4 and 5 out of 5), the user receives a textual prompt, intended to stimulate deliberate reflection on one’s current status of emotional arousal. See Figure 2 for an impression. An option to manually export recorded data to a server was also implemented. With this option, a primary user is able to transfer his or her data to a server. These data can then be accessed via an internet browser through a secured gateway. The data can be presented in raw form or plotted to provide a graph depicting the changes in PCEA over time. This option was built in to increase the number of ways the data could be used to support therapy. For example, it could provide an opportunity for the patients to get a better overview of the changes in their arousal over time or to let their therapists have a view (if they were granted access to the secured data by the patient). Although this functionality was built in, it could not be tested at the clinic because of limitations in the technical infrastructure at site and ethical limitations concerning the sending of personal data to servers outside the clinic. Figure 3 gives an overview of the setup of the app.
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