Wearables: An R Package With Accompanying Shiny Application for Signal Analysis of a Wearable Device Targeted at Clinicians and Researchers

Abstract

Physiological signals (e.g., heart rate, skin conductance) that were traditionally studied in neuroscientific laboratory research are currently being used in numerous real-life studies using wearable technology. Physiological signals obtained with wearables seem to offer great potential for continuous monitoring and providing biofeedback in clinical practice and healthcare research. The physiological data obtained from these signals has utility for both clinicians and researchers. Clinicians are typically interested in the day-to-day and moment-to-moment physiological reactivity of patients to real-life stressors, events, and situations or interested in the physiological reactivity to stimuli in therapy. Researchers typically apply signal analysis methods to the data by pre-processing the physiological signals, detecting artifacts, and extracting features, which can be a challenge considering the amount of data that needs to be processed. This paper describes the creation of a "Wearables" R package and a Shiny "E4 dashboard" application for an often-studied wearable, the Empatica E4. The package and Shiny application can be used to visualize the relationship between physiological signals and real-life stressors or stimuli, but can also be used to pre-process physiological data, detect artifacts, and extract relevant features for further analysis. In addition, the application has a batch process option to analyze large amounts of physiological data into ready-to-use data files. The software accommodates users with a downloadable report that provides opportunities for a careful investigation of physiological reactions in daily life. The application is freely available, thought to be easy to use, and thought to be easily extendible to other wearable devices. Future research should focus on the usability of the application and the validation of the algorithms.

Keywords: R Shiny application; electrodermal activity; heart rate; neuroscience; physiological reactivity; treatment; wearables.

FIGURE 1

An example of a session that contains physiological data on EDA, HR, temperature, and movement, but also provides information from HR, movement, and EDA on the number of artifacts.

FIGURE 2

Features that can be extracted from an EDA signal. Printed with permission from Taylor et al. (2015).

FIGURE 3

The data tab user interface, in which data can be read in from Empatica zip files.

FIGURE 4

The calendar tab that can be used to add text to the visualization and color shade activities.

FIGURE 5

The visualization tab has a Settings Tab that can be used to choose the settings to be displayed. Preset ranges for the physiological signal are: EDA (0–20 micro Siemens), HR (40–160 beats), temperature (24–38°C), and movement (0.98–1.25 mean acceleration).

FIGURE 6

The Plot Tab can be used to visualize the physiological signals and synchronize them with the calendar events. A session is displayed for approximately 1 h, in which one of the authors undertakes eight activities, each lasting 7 min, to indicate the differences in physiological reactivity during various activities and illustrates differences in physiological reactivity.

FIGURE 7

The Analysis Tab can be used to select a timeframe, for which the signal analysis should be performed and download a report.

FIGURE 8

Summary report of the analysis that can be read with your local browser.