An Automated Algorithm to Extract Time Plane Features from the PPG Signal and its Derivatives for Personal Health Monitoring Application

Abstract

Recently, photoplethysmogram (PPG) signal is widely adopted in health monitoring devices for automated assessment of different cardiovascular parameters. However, research in the area of computerized health analysis using PPG signal features is still lagging behind. In this paper, a robust, automated yet simple algorithm is proposed for accurate detection of characteristic points from the PPG signal and its derivatives. The methodology follows amplitude thresholding, slope-reversal, and an empirical formula based approach. Finally, Baseline modulation is removed from the PPG dataset and features are extracted from the amplitude normalized PPG signal and its derivatives. Performance of the proposed algorithm is evaluated over MIMIC database as well as over real PPG data acquired from both healthy volunteers and cardiac patients. The algorithm exhibits high efficiency for all detected fiducial points with an average sensitivity, positive predictivity and detection accuracy of 99.80%, 99.84%, and 99.65%, respectively. Compared to the existing methods, the proposed algorithm offers complete characterization of the PPG signal and its derivatives.

KEYWORDS:

• Amplitude threshold
• Biomedical signal processing
• Photoplethysmogram (PPG)
• PPG derivatives
• Slope reversal
• Time-domain feature extraction

Acknowledgements

The authors would like to express their deepest gratitude to Dr S Guha, MD, DM (cardiology) (Professor and HOD), other medical practitioners and the entire support staffs of the department of cardiology, Medical College and Hospital, Kolkata, for their valuable suggestions and assistance in the development of PPG database and validation of the proposed algorithm.

Additional information

Notes on contributors

Abhishek Chakraborty

Abhishek Chakraborty received his BSc (Hons) and MSc degrees in electronic science from the University of Calcutta, Kolkata, India in 2005 and 2007, respectively. Currently, he is pursuing his PhD degree in the Department of Applied Physics, University of Calcutta, India. He is also working as a part-time lecturer (Government approved) in the Department of Electronics, Dum Dum Motijheel College, Kolkata since 2009. He qualified the UGC –NET examination in the year 2013. His research interests include biomedical signal processing and analysis. Email: [email protected]

Deboleena Sadhukhan

Deboleena Sadhukhan received her BSc degree with major in physics in 2007. She then completed her BTech and MTech degrees in instrumentation engineering from the Department of Applied Physics, University of Calcutta, India, in 2010 and 2012, respectively, and stood 1^st class first (gold medalist) in both of them. She is currently pursuing her PhD degree from the same department with the prestigious DST INSPIRE fellowship provided by the Department of Science & Technology, Government of India. Her research interests include biomedical signal processing and pattern recognition. Email: [email protected]

Madhuchhanda Mitra

Madhuchhanda Mitra was born in Kolkata, India in 1961. She received her BTech, MTech and PhD (Tech) degrees in 1987, 1989 and 1998, respectively, from University of Calcutta, Kolkata, India. She is currently a professor with the Department of Applied Physics, University of Calcutta. Her current research interests include biomedical signal processing, machine fault analyses, and material science. Dr Mitra received the “Griffith Memorial Award” from the University of Calcutta. Corresponding author. Email: [email protected]