Validation of the EmotiBit wearable sensor for heart-based measures under varying workload conditions - Vorreuther, Anna; Tagalidou, Nektaria; Vukelić, Mathias (Frontiers in Neuroergonomics, 2025)
IntroductionThe EmotiBit photoplethysmography (PPG) device allows user-owned data collection for measures of cardiovascular activity (CVA) and electrodermal activity (EDA) in naturalistic settings. The aim of this study was to evaluate the validity of this device for collecting high-quality data while participants experience varying levels of cognitive workload.MethodsUsing a standardized criterion validity protocol, recordings of 15 participants performing a cognitive workload task were compared for the EmotiBit and a reference electrocardiography (ECG) device (BITalino PsychoBit). Multiple preprocessing pipelines and a signal quality check were implemented. Parameters of interest including heart rate (HR), heart rate variability (HRV) measures, skin conductance level (SCL), and skin conductance response (SCR) measures were assessed using Bland-Altman plot and ratio (BAr) analyses, as well as cross-correlations of the EDA signal time series of both devices.ResultsBAr results indicated good agreement between devices regarding HR with an average difference of 1–2 beats per minute (bpm). HRV measures yielded an insufficient BAr, albeit most data points lay within a priori boundaries of agreement. EDA measures yielded insufficient agreement for comparing SCL and SCR number and amplitude.DiscussionThe results are comparable to the validation of similar wearable PPG devices and extend the validation of the EmotiBit by assessing the acquired signals during varying levels of cognitive workload. While the device may be used to collect HR for scientific data analysis, its quality regarding HRV and EDA measures is not comparable to a standard ECG.SignificanceThis study provides the first systematic validation following a standardized protocol of the EmotiBit PPG device relative to an ECG when considering recordings collected during cognitive workload induction.