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Table 5 Performance of the classification rules based on single features and on the best subset of features

From: Nonlinear Heart Rate Variability features for real-life stress detection. Case study: students under stress due to university examination

Features ACC SEN SPE PPV NPV Classified as stress if
SD2 73% 79% 67% 70% 76% SD2<0.0646
D 2 73% 69% 76% 74% 71% D 2 <2.2533
REC 71% 67% 76% 74% 70% REC>0.3791
En(r chon ) 71% 64% 79% 75% 69% En(r chon )<1.0530
α 1 71% 57% 86% 80% 67% α 1 <1.2479
ShEn 68% 64% 71% 69% 67% ShEn>3.3060
l mean 67% 57% 76% 71% 64% l mean >13.2302
En(0.2) 64% 62% 67% 65% 64% En(0.2)<1.0517
l max 60% 62% 57% 59% 60% l max <250.6263
En(r max ) 58% 64% 52% 57% 59% En(r max )<1.1099
DET 56% 69% 43% 55% 58% DET>0.9870
α 2 40% 50% 31% 42% 38% α 2 <0.7711
SD1 39% 33% 45% 38% 40% SD1>0.0243
SD1,SD2, En(0.2) 90% 86% 95% 95% 87% See formula 15