Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 1.0.2

File: <base>/training/georgia/g10/E09902.hea (729 bytes) 
E09902 12 500 5000
E09902.mat 16x1+24 1000.0(0)/mV 16 0 -29 -26962 0 I
E09902.mat 16x1+24 1000.0(0)/mV 16 0 -82 -14632 0 II
E09902.mat 16x1+24 1000.0(0)/mV 16 0 -53 12884 0 III
E09902.mat 16x1+24 1000.0(0)/mV 16 0 56 -12007 0 aVR
E09902.mat 16x1+24 1000.0(0)/mV 16 0 12 -20171 0 aVL
E09902.mat 16x1+24 1000.0(0)/mV 16 0 -68 32020 0 aVF
E09902.mat 16x1+24 1000.0(0)/mV 16 0 34 62 0 V1
E09902.mat 16x1+24 1000.0(0)/mV 16 0 24 -1101 0 V2
E09902.mat 16x1+24 1000.0(0)/mV 16 0 -9 25723 0 V3
E09902.mat 16x1+24 1000.0(0)/mV 16 0 -58 16106 0 V4
E09902.mat 16x1+24 1000.0(0)/mV 16 0 -102 30148 0 V5
E09902.mat 16x1+24 1000.0(0)/mV 16 0 -78 -6595 0 V6
# Age: 50
# Sex: Male
# Dx: 713426002,270492004,164889003
# Rx: Unknown
# Hx: Unknown