QoL_Stress: A Multimodal Dataset of Physiological and Self-Reported Stress Responses

A multimodal dataset containing ECG, EDA, heart rate, and self-reported stress/anxiety measures from 66 participants during relaxation and stress phases, designed for stress detection research.The QoL_Stress dataset is organized into collections exported as CSV files. Each file contains data for all participants; phase labels (RELAX/STRESS) and participant identifiers allow linking physiological signals with self-reported measures, enabling multimodal analyses. Collection Records Description Key Fields ecg 132 Continuous ECG during RELAX/STRESS phases, HR features and alerts waveform_samples, heart_rate (bpm), heart_rate_alert, phase eda 124 Electrodermal activity capturing SCL and SCR timestamp, scl_avg (µS), activation (SCR), valid_data, phase fitbit_heart_rate_per_second 66 HR per second time, value (bpm) fitbit_heart_rate_per_minute 66 HR averaged per minute time, value (bpm) fitbit_heart_rate_summary 66 Daily HR summaries including calories and HR zones heartRateZones, caloriesOut, min, max participants 66 Demographics and professional category sex, age, education, professional_category pss-14 66 Perceived Stress Scale total and item-level scores total_score, item-level responses stai 132 STAI-S by phase total_score, item-level responses, phase File Naming:Files are named after the collection, e.g.,ecg.csv, eda.csv, fitbit_heart_rate_per_second.csv, participants.csv. Each file contains all participants’ data for that collection. Phase labels (RELAX/STRESS) and participant identifiers allow linking physiological signals with self-reported measures. Data Format:All files are in CSV format, ready for analysis with standard tools such as Python (Pandas, NumPy), R, or MATLAB. Time stamps are provided where appropriate to enable precise temporal alignment between physiological and self-reported measures.