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12 Data Sets

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1. 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.

2. Diabetes: This diabetes dataset is from AIM '94

3. EEG Database: This data arises from a large study to examine EEG correlates of genetic predisposition to alcoholism. It contains measurements from 64 electrodes placed on the scalp sampled at 256 Hz

4. EEG Eye State: The data set consists of 14 EEG values and a value indicating the eye state.

5. 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).

6. EMG data for gestures: These are files of raw EMG data recorded by MYO Thalmic bracelet

7. Epileptic Seizure Recognition: This dataset is a pre-processed and re-structured/reshaped version of a very commonly used dataset featuring epileptic seizure detection.

8. ICU: Data set prepared for the use of participants for the 1994 AAAI Spring Symposium on Artificial Intelligence in Medicine.

9. 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.

10. 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.

11. 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.

12. 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.


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