1. Bar Crawl: Detecting Heavy Drinking: Accelerometer and transdermal alcohol content data from a college bar crawl. Used to predict heavy drinking episodes via mobile data.
2. Bar Crawl: Detecting Heavy Drinking: Accelerometer and transdermal alcohol content data from a college bar crawl. Used to predict heavy drinking episodes via mobile data.
3. Breath Metabolomics: Breath analysis is a pivotal method for biological phenotyping. In a pilot study, 100 experiments with four subjects have been performed to study the reproducibility of this technique.
4. Daphnet Freezing of Gait: This dataset contains the annotated readings of 3 acceleration sensors at the hip and leg of Parkinson's disease patients that experience freezing of gait (FoG) during walking tasks.
5. EEG Eye State: The data set consists of 14 EEG values and a value indicating the eye state.
6. EEG Steady-State Visual Evoked Potential Signals: This database consists on 30 subjects performing Brain Computer Interface for Steady State Visual Evoked Potentials (BCI-SSVEP).
7. EMG data for gestures: These are files of raw EMG data recorded by MYO Thalmic bracelet
8. Epileptic Seizure Recognition: This dataset is a pre-processed and re-structured/reshaped version of a very commonly used dataset featuring epileptic seizure detection.
9. Horton General Hospital: Horton General Hospital is in the town Banbury not far from Oxford, UK.
10. Hungarian Chickenpox Cases: A spatio-temporal dataset of weekly chickenpox cases from Hungary. The dataset consists of a county-level adjacency matrix and time series of the county-level reported cases between 2005 and 2015.
11. ICU: Data set prepared for the use of participants for the 1994 AAAI Spring Symposium on Artificial Intelligence in Medicine.
12. Localization Data for Person Activity: Data contains recordings of five people performing different activities. Each person wore four sensors (tags) while performing the same scenario five times.
13. sEMG for Basic Hand movements: The sEMG for Basic Hand movements includes 2 databases of surface electromyographic signals of 6 hand movements using Delsys' EMG System. Healthy subjects conducted six daily life grasps.
14. Simulated data for survival modelling: A variety of survival data, with carefully controlled event and censor rates, is available to allow people to develop and test new approaches to survival modelling.
15. Simulated Falls and Daily Living Activities Data Set: 20 falls and 16 daily living activities were performed by 17 volunteers with 5 repetitions while wearing 6 sensors (3.060 instances) that attached to their head, chest, waist, wrist, thigh and ankle.
16. Smartphone-Based Recognition of Human Activities and Postural Transitions: Activity recognition data set built from the recordings of 30 subjects performing basic activities and postural transitions while carrying a waist-mounted smartphone with embedded inertial sensors.