Resources

The project aims to understand occupants’ behaviour, engagement, emotion, and comfort indoors with heterogeneous sensors and wearables.

Comparison of HR values reported by ECG (Bittium Faros) and wearables including Biovotion Everion, Empatica E4, Apple Watch, Garmin, Fitbit, and Xiaomi Miband.

GLOBEM datasets contain the first released multi-year mobile and wearable sensing datasets from 2018 to 2021, containing 705 person-years and 497 unique participants.

The PADS dataset contains smartwatch-based records from interactive neurological assessments of Parkinsons disease patients, differential diagnoses and healthy controls. The data is complemented with non-motor symptoms and medical history information

Dataset used for development of an algorithm for on-line anxiety level detection from biosignals.

This dataset explores safe actuation (music, perfume, coffee) for enhancing cognitive states. It includes subjects’ responses, reaction times, and physiological data (EDA, HR, BVP, PPG, temperature, accelerometer, EEG) during n-back memory tasks.

Multimodal (ECG, EMG, EDA, PPG, TEMP, ACC) biosignal dataset of everyday activities. Created with 3 wearable devices based on ScientISST Sense and Empatica E4.

Multimodal (ECG, EMG, EDA, PPG, TEMP, ACC) biosignal dataset of everyday activities. Created with 3 wearable devices based on ScientISST Sense and Empatica E4.

This initial version of the PHASES dataset includes multimodal menstrual health data—hormone levels, wearable sensor metrics, and self-reported symptoms—collected across two study intervals from 42 young adults.

This initial version of the PHASES dataset includes multimodal menstrual health data—hormone levels, wearable sensor metrics, and self-reported symptoms—collected across two study intervals from 42 young adults.