, Volume 21, Issue 2, pp 110–120 | Cite as

Extended algorithm for real-time pulse waveform segmentation and artifact detection in photoplethysmograms

Original Article



Photoplethysmography can be used for measuring oxygen saturation or assessing autonomic function. Artifacts can render the photoplethysmogram (PPG) useless. Thus, algorithms capable of identifying artifacts are important. However, the published algorithms are limited in their abilities and study design. Therefore, the authors developed a novel embedded algorithm for pulse waveform (PWF) segmentation and artifact detection in real-time.


The previous PWF analysis was not able to detect a diastolic peak, which prevents analyses like arterial stiffness. Furthermore, the algorithm shows room for improvements if the first part of the pulse wave is disturbed. To overcome these limitations, the authors extended the PWF analysis.

Materials and methods

The extended PWF analysis was validated as before with the data records from 63 subjects acquired in a sleep laboratory, ergometry laboratory, and intensive care unit. The output of the algorithm was compared with harmonized experts’ annotations with a total duration of 31.5 h.


The comparison of the artifacts detection performance between the extended and the original PWF analysis shows a reduced sensitivity from 99.6 to 99.5%, but increased specificity from 90.5 to 91.6%, precision from 98.5 to 98.6%, accuracy from 98.3 to 98.4%, Cohen’s kappa coefficient from 0.927 to 0.932, and F‑measure from 0.990 to 0.991. Furthermore, the PWF analysis is now able to detect diastolic peaks.


The proposed novel extended PWF analysis seems to be a suitable method for real-time annotation of the PPG, and detection of pulse wave amplitude, pulse wave duration, rise time, pulse propagation time as well as their variations.


Oxygen saturation Autonomic function Blood volume Diastolic peaks Vascular stiffness 

Erweiterter Algorithmus zur Echtzeit-Pulswellensegmentierung und Artefakterkennung in Photoplethysmogrammen



Die Photoplethysmographie kann verwendet werden, um die Sauerstoffsättigung zu messen oder das vegetative Nervensystem zu untersuchen. Artefakte können das Photoplethymogramm (PPG) bis zur Unkenntlichkeit verzerren. Daher sind Algorithmen wichtig, die in der Lage sind, Artefakte zu erkennen. Die bisher publizierten Algorithmen sind aber in ihren Fähigkeiten und ihrem Studiendesign limitiert. Deshalb entwickelten die Autoren einen neuartigen integrierten Algorithmus zur Segmentierung der Pulswellenform (PWF) und Artefakterkennung in Echtzeit.

Ziel der Arbeit

Die vorangegangene PWF-Analyse konnte keinen diastolischen Peak erkennen, wodurch z. B. Untersuchungen der arteriellen Steifigkeit nicht möglich waren. Zudem zeigte der Algorithmus Verbesserungspotenzial bei im Anfangsbereich gestörten Pulswellen. Um diese Einschränkungen zu beseitigen, erweiterten die Autoren die PWF-Analyse.

Material und Methoden

Die erweiterte PWF-Analyse wurde wie zuvor mit den Datensätzen von 63 Personen validiert, die in einem Schlaflabor, Ergometrielabor und auf Intensivstation erfasst worden waren. Die Ergebnisse des Algorithmus wurden mit den abgeglichenen Expertenauswertungen mit einer Gesamtdauer von 31,5 h verglichen.


Der Vergleich der Leistung bei der Artefakterkennung zwischen der erweiterten und der Original-PWF-Analyse zeigt eine reduzierte Sensitivität von 99,6 % auf 99,5 %, während sich die Spezifität von 90,5 % auf 91,6 %, der positive Vorhersagewert von 98,5 % auf 98,6 %, die Vertrauenswahrscheinlichkeit von 98,3 % auf 98,4 %, der Kappa-Koeffizient nach Cohen von 0,927 auf 0,932 und das F‑Maß von 0,990 auf 0,991 verbesserten. Darüber hinaus lassen sich nun mit der PWF-Analyse diastolische Peaks erkennen.


Die neue, erweiterte PWF-Analyse scheint eine brauchbare Methode für die Echtzeitauswertung von PPG und die Bestimmung der Pulswellenamplitude, Pulswellendauer, Anstiegszeit, Pulsausbreitungszeit sowie deren Variationen zu sein.


Sauerstoffsättigung Autonome Funktion Blutvolumen Diastolische Spitzenwerte Vaskuläre Steifigkeit 


Compliance with ethical guidelines

Conflict of interest

The development of the original PWF analysis was supported by the German Federal Ministry of Education and Research (BMBF) and MCC GmbH & Co. KG. During the database recording and the development of the original PWF analysis, C. Fischer was in an employment relationship with the company MCC GmbH & Co. KG. For the development of the extended PWF anlaysis C. Fischer, M. Glos, T. Penzel, and I. Fietze declare that they have no competing interests.

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national). Informed consent was obtained from all patients included in the study.


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Copyright information

© Springer Medizin Verlag GmbH 2017

Authors and Affiliations

  1. 1.Roche Diabetes Care GmbHMannheimGermany
  2. 2.Interdisziplinäres Schlafmedizinisches ZentrumCharité – Universitätsmedizin BerlinBerlinGermany
  3. 3.International Clinical Research CenterSt. Anne’s University Hospital BrnoBrnoCzech Republic
  4. 4.BruchsalGermany

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