%The data was generated with healthy participants simulating the
%class activities of performed. Data was collected from 6
%participants using a tri-axial accelerometer on the dominant wrist
%whilst conducting 4 different activities. The four tasks, each of
%different length, are: WALKING includes different paces and
%gestures: walking slowing while gesturing, walking slowly, walking
%normal and walking fast, each of 30 seconds long. RUNNING includes
%running a 40 meters long corridor. SAWING with a saw and during 30
%seconds. SEIZURE MIMICKING seated, with 5-6 sec before and 30 sec
%after the mimicked seizure. The seizure was 30 sec long.
%
%Each participant performs each activity 10 times at least. The
mimicked seizures were trained and controlled, following a protocol
defined by an medical expert. All the activities were carried out
indoors, either inside an office or in the corridor around it.

The sampling frequency was 16 Hz. Some activities lasted about 30
seconds, others are 1 minute long, others are about 2 minutes. Our
standard practice for the archive is to truncate data to the length
of the shortest series retained. We removed prefix and suffix flat
series and truncated to the shortest series (20 measurements,
approx 13 seconds), taking a random interval of activity for series
longer than the minimum. A single case
from the original (ID002 Running 16) was removed because the data
was not collected correctly. After tidying the data we have a total
of 275 cases. The train test split is divided into three
participants for training, three for testing, with the IDs removed
for consistency with the rest of the archive.

Relevant Papers:
[1] Villar JR, Vergara P, Menéndez M, de la Cal E, González VM, Sedano J.
Generalized Models for the Classification of Abnormal Movements in Daily Life and its Applicability to Epilepsy Convulsion Recognition. Int
J Neural Syst. 2016 Sep;26(6) 2016
