Evaluation of Python HeartPy Tooklit for Heart Rate extraction from PPG
Date Issued
2021
Author(s)
Hristina, Mitrova
Madevska Bogdanova, Ana
Lehocki, Fedor
Ondrusova, Beata
Abstract
Handling the mass casualty emergency situations can be improved by introducing a chest patch sensor that is able to deliver the
main vital parameters: Heart Rate (HR), Respiration Rate (RR), SPO2
and Blood Pressure. The START triage procedure requires both HR and
RR parameters almost instantly.
In this paper we investigate the calculation of HR from a raw PPG
signal, using appropriate functions from the Python HeartPy Tooklit, by
comparing the calculated HR to the measured HR for the same patients,
recorded at the same time as the PPG signal. By using several evaluation
metrics, it was concluded that there is no significant difference between
the measured and the calculated HR (MAE = 0,3, MSE=0,3, R2 =0,99,
Pearson’s and the Spearman’s coefficient of correlation, 0.99). This result
is the same whether raw or filtered PPG signal was used for the HR
calculation.
main vital parameters: Heart Rate (HR), Respiration Rate (RR), SPO2
and Blood Pressure. The START triage procedure requires both HR and
RR parameters almost instantly.
In this paper we investigate the calculation of HR from a raw PPG
signal, using appropriate functions from the Python HeartPy Tooklit, by
comparing the calculated HR to the measured HR for the same patients,
recorded at the same time as the PPG signal. By using several evaluation
metrics, it was concluded that there is no significant difference between
the measured and the calculated HR (MAE = 0,3, MSE=0,3, R2 =0,99,
Pearson’s and the Spearman’s coefficient of correlation, 0.99). This result
is the same whether raw or filtered PPG signal was used for the HR
calculation.
Subjects
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