Human emotion is inclusive of experiential, behavioural and physiological components. Research methodologies within the humanities have tended to over-emphasize the experiential component through assessments derived from self-report measures and interviews. With advances in unobtrusive wearable technologies the acquisition of moment-to-moment physiological data is now available to a wider audience than ever before. Using data collected with the Empatica E4 wristband, the the Situation Specific Arousal Analyzer (SSAA) application, available for both OS X and Windows, has been designed to support non-clinical research and analysis into the physiological measurement and tracking of autonomic nervous system arousal with a focus on state specific anxiety within the context of foreign language education. The data quantification and packaging of the SSAA represents innovation in accessible research methodology applicable to the study of foreign language education anxiety. SSAA data allows correlations and relationships to be analyzed with other affective variables of common interest such as motivation, achievement, personality and a willingness to communicate. Non-clinical researchers can incorporate medical grade physiological data into their repertoire and align research into foreign language education anxiety with the technological opportunities available.

Trait anxiety is a relatively stable feature of an individual’s personality profile and reflects a predisposition to psychopathological conditions and heightened states of arousal whereas state anxiety or experimentally-induced anxiety is a more temporal experience often occurring in the absence of underlying psychopathological conditions. State specific anxiety is therefore dependent on isolated environmental triggers meaning that researchers are able to exert a degree of control over the onset of autonomic nervous system arousal through situational manipulation. State specific anxiety episodes are dynamic and momentary fluctuations in arousal can be expected even within the broader context of exposure to a specific stimulus. Given that state specific anxiety corresponds to a specific environmental stimulus, it is incumbent upon researchers to establish clear data collection/analysis parameters to avoid the misattribution of arousal to uncontrolled stimuli. Within the domain of foreign language education research, fixed data collection/analysis parameters able to document real-time moment-to-moment fluctuations have not been documented due to methodological limitations. In response to technological developments in wearable research devices, new opportunities have arisen to expand the research methodologies used in the recording, assessment and analysis of foreign language education anxiety.

Using the Empatica E4 wristband, a "medical-grade wearable device that offers real-time physiological data acquisition, enabling researchers to conduct in-depth analysis and visualization” (Empatica Inc. 2021), high-integrity physiological data can now be captured with relative ease. However, the data captured by the Empatica E4 does not lend itself to application within foreign language education research due to raw data format and data complexity. A technical solution was therefore required to bring such useful physiological data into reach of educational practitioners. The Situation Specific Arousal Analyzer (SSAA) application has been designed to make Empatica E4 data accessible to foreign language education researchers, particularly those with an interest in state specific anxiety.  The SSAA permits access to practical data output relative to autonomic nervous system arousal in state specific situations through the quantification of indicators such as Heart Rate Variability (HRV) and Electrodermal Activity (EDA) under a range of user-defined experimental parameters. The SSAA aims to contribute to an expansion of current methodologies and push contemporary research beyond experiential self-report measures thereby allowing a wider demographic to benefit from innovations in physiological data capture, processing and analysis.

Using the files exported from E4 Connect, the SSAA extracts Heart Rate (HR), Heart Rate Variability (HRV) (time-domain methods, frequency-domain methods, non-linear domain methods) and Electrodermal Activity (EDA) relative to time interval parameters specified by the researcher. The user interface is therefore able to be tailored to meet a range of analytical conditions focused on either the micro analysis of arousal in time specific segments such as every few seconds during a foreign language spoken presentation, or relative to longer macro periods of analysis such as across an entire classroom period or activity. For the HRV time-domain, the beat-to-beat interval (NNMean) can be calculated up to once per 0.015625 (1/64) second while for the EDA mean (EDAMean) it is possible to capture data once per 0.25 (1/4) second. For HR, the mean value of the HR (HRMean) and the standard deviation of the HR (HRSD) are calculated. For the HRV time-domain, the mean value of the beat-to-beat interval (NNMean) and the standard deviation of the beat-to-beat interval (NNSD) are calculated. For the HRV frequency-domain, very low frequency (VLF), low frequency (LF), high frequency (HF), and the ratio of LF and HF (LF/HF) are calculated. For the HRV non-linear domain, SD1 and SD2 Poincaré Plots are calculated as follows:

• As X = {RR1, RR2, ..., RR(n - 1)}, and Y = {RR2, RR3, ..., RRn}
• PP SD1: The standard deviation of '(X - Y) / Sqrt(2)' in the condition range using the duration column of IBI.csv
• PP SD2: The standard deviation of '(X + Y) / Sqrt(2)' in the condition range using the duration column of IBI.csv

For the EDA analysis, the mean value of the EDA (EDAMean) and the standard deviation of the EDA (EDASD) are calculated. The SSAA exports the results relative to each experimental time interval as a single tabulated .csv file using the columns shown below. It also exports visualizations as Lomb-Scargle Periodograms and Poincaré Plots for each analysis interval parameter specified.