TY - JOUR
T1 - Heart rate monitoring using human speech spectral features
AU - James, Alex Pappachen
N1 - Publisher Copyright:
© 2015, James.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2015/12/1
Y1 - 2015/12/1
N2 - This paper attempts to establish a correlation between the human speech, emotions and human heart rate. The study highlights a possible contactless human heart rate measurement technique useful for monitoring of patient condition from real-time speech recordings. The distance between the average peak-to-peak distances in speech Mel-frequency cepstral coefficients are used as the speech features. The features when tested on 20 classifiers from the data collected from 30 subjects indicate a non-separable classification problem, however, the classification accuracies indicate the existence of strong correlation between the human speech, emotion and heart-rates.
AB - This paper attempts to establish a correlation between the human speech, emotions and human heart rate. The study highlights a possible contactless human heart rate measurement technique useful for monitoring of patient condition from real-time speech recordings. The distance between the average peak-to-peak distances in speech Mel-frequency cepstral coefficients are used as the speech features. The features when tested on 20 classifiers from the data collected from 30 subjects indicate a non-separable classification problem, however, the classification accuracies indicate the existence of strong correlation between the human speech, emotion and heart-rates.
KW - Heart rate
KW - Human emotions
KW - Mel-frequency cepstral coefficients
KW - Speech signal
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U2 - 10.1186/s13673-015-0052-z
DO - 10.1186/s13673-015-0052-z
M3 - Article
AN - SCOPUS:84947209969
VL - 5
SP - 1
EP - 12
JO - Human-centric Computing and Information Sciences
JF - Human-centric Computing and Information Sciences
SN - 2192-1962
IS - 1
M1 - 33
ER -