Multimodal dataset from 24 participants with synchronized wrist-worn PPG from Galaxy Watch 5 and Empatica E4, plus chest ECG from Polar H10, collected during diverse activities in semi-naturalistic settings for evaluating consumer-grade wearable performance.
Large public dataset from Microsoft Research Aurora Project with ECG and PPG signals from wrist-worn wearables, balanced for gender, age, and hypertension status, enabling causal inference research for non-invasive blood pressure prediction with 205 extracted features.
Real operational electricity system records from ISO New England (ISONE) covering urban smart city energy activity including demand, generation, pricing, and grid operations across multiple metropolitan areas for energy analytics and forecasting.
Wearable IMU dataset from 22 Parkinson's disease patients performing standardized motor tasks, with four inertial sensors (ankles, wrist, lower back) capturing freezing of gait (FoG) episodes, designed for algorithm development and clinical gait analysis.
Multimodal dataset from 18 subjects with wearable IMUs (wrists, torso), Bluetooth indoor localization, and first-person video capturing 12 activity categories in realistic home/office scenarios for human activity recognition and fall detection research.
Dataset from wearable system integrating triaxial accelerometers with flexible haptic actuators for real-time body motion sensing and synchronized vibration feedback, including ML-classified motion data from diverse body placements for VR/AR and remote communication applications.
Continuous 4-week wearable dataset from 49 participants with smartwatch-based heart rate variability (HRV), motion sensors, daily sleep diaries, and biweekly clinical assessments of depression, anxiety, and insomnia for mental health research.
Novel dataset correlating real wearable device data (heart rate, steps, sleep, calories) with Self-Reported Quality of Life (SRQoL) measures using the WHOQOL-BREF questionnaire for health monitoring and QoL prediction research.
48 half-hour excerpts of two-channel ambulatory ECG recordings from 47 subjects (1975–1979), digitized at 360 Hz with expert annotations for approximately 110,000 heartbeats, widely used for arrhythmia detection research.[page:2][web:219]
Multimodal body motion and vital sign recordings from 10 volunteers performing 12 physical activities, collected with three body-worn sensor units (chest, wrist, ankle) including 2‑lead ECG.[web:124][web:130][web:148][web:153]
High-frequency wearable sensor data from 9 subjects performing 18 different daily and sports activities, recorded with three 100 Hz IMUs and a heart rate monitor.[web:125][web:128][web:138][web:142]
Multi-source healthcare dataset integrating Electronic Health Records, medical imaging (CT and MRI scans), and wearable IoT sensor data for personalized treatment optimization. Includes 5,008 brain imaging files and real-time physiological monitoring data.