A review on wearable photoplethysmography sensors and their potential future applications in health care

Photoplethysmography (PPG) is an uncomplicated and inexpensive optical measurement method that is often used for heart rate monitoring purposes. PPG is a non-invasive technology that uses a light source and a photodetector at the surface of skin to measure the volumetric variations of blood circulation. Recently, there has been much interest from numerous researchers around the globe to extract further valuable information from the PPG signal in addition to heart rate estimation and pulse oxymetry readings. PPG signal’s second derivative wave contains important health-related information. Thus, analysis of this waveform can help researchers and clinicians to evaluate various cardiovascular-related diseases such as atherosclerosis and arterial stiffness. Moreover, investigating the second derivative wave of PPG signal can also assist in early detection and diagnosis of various cardiovascular illnesses that may possibly appear later in life. For early recognition and analysis of such illnesses, continuous and real-time monitoring is an important approach that has been enabled by the latest technological advances in sensor technology and wireless communications. The aim of this article is to briefly consider some of the current developments and challenges of wearable PPG-based monitoring technologies and then to discuss some of the potential applications of this technology in clinical settings.

[1]  Zhilin Zhang,et al.  TROIKA: A General Framework for Heart Rate Monitoring Using Wrist-Type Photoplethysmographic Signals During Intensive Physical Exercise , 2014, IEEE Transactions on Biomedical Engineering.

[2]  C. Heneghan,et al.  Continuous Blood Pressure Monitoring using ECG and Finger Photoplethysmogram , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[3]  Mohamed Elgendi,et al.  Detection of a and b waves in the acceleration photoplethysmogram , 2014, BioMedical Engineering OnLine.

[4]  Jianchu Yao,et al.  A novel algorithm to separate motion artifacts from photoplethysmographic signals obtained with a reflectance pulse oximeter , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[5]  Toshiyo Tamura,et al.  Wearable Photoplethysmographic Sensors—Past and Present , 2014 .

[6]  W. Zareba,et al.  Heart rate variability. , 2013, Handbook of clinical neurology.

[7]  Mohd Alauddin Mohd Ali,et al.  Analysis of the Effect of Ageing on Rising Edge Characteristics of the Photoplethysmogram using a Modified Windkessel Model , 2007, Cardiovascular engineering.

[8]  A. Murray,et al.  Effects of filtering on multisite photoplethysmography pulse waveform characteristics , 2004, Computers in Cardiology, 2004.

[9]  Jae Mok Ahn.  New Aging Index Using Signal Features of Both Photoplethysmograms and Acceleration Plethysmograms , 2017, Healthcare informatics research.

[10]  T. Kawada,et al.  Utility of second derivative of the finger photoplethysmogram for the estimation of the risk of coronary heart disease in the general population. , 2006, Circulation journal : official journal of the Japanese Circulation Society.

[11]  Joseph Wei,et al.  How Wearables Intersect with the Cloud and the Internet of Things : Considerations for the developers of wearables. , 2014, IEEE Consumer Electronics Magazine.

[12]  Philippe Renevey,et al.  Validation of a wrist monitor for accurate estimation of RR intervals during sleep , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[13]  I. Imanaga,et al.  Correlation between wave components of the second derivative of plethysmogram and arterial distensibility. , 1998, Japanese heart journal.

[14]  Alan Murray,et al.  A prospective comparison of bilateral photoplethysmography versus the ankle-brachial pressure index for detecting and quantifying lower limb peripheral arterial disease. , 2008, Journal of vascular surgery.

[15]  Kwang Suk Park,et al.  Second Derivative of Photoplethysmography for Estimating Vascular Aging , 2007, 2007 6th International Special Topic Conference on Information Technology Applications in Biomedicine.

[16]  M. Elgendi.  On the Analysis of Fingertip Photoplethysmogram Signals , 2012, Current cardiology reviews.

[17]  Insoo Kim,et al.  Lightweight wrist photoplethysmography for heavy exercise: motion robust heart rate monitoring algorithm , 2015, Healthcare technology letters.

[18]  Kemal Polat,et al.  Non-invasive prediction of hemoglobin level using machine learning techniques with the PPG signal's characteristics features , 2015, Appl. Soft Comput..

[19]  Walter Karlen,et al.  Multiparameter Respiratory Rate Estimation From the Photoplethysmogram , 2013, IEEE Transactions on Biomedical Engineering.

[20]  Cigdem Eroglu Erdem,et al.  An overview of non-contact photoplethysmography , 2017, 2017 25th Signal Processing and Communications Applications Conference (SIU).

[21]  Janis Spigulis,et al.  Simultaneous recording of skin blood pulsations at different vascular depths by multiwavelength photoplethysmography. , 2007, Applied optics.

[22]  Ying Bai,et al.  An ultra-wearable, wireless, low power ECG monitoring system , 2006, 2006 IEEE Biomedical Circuits and Systems Conference.

[23]  H Harry Asada,et al.  Mobile monitoring with wearable photoplethysmographic biosensors. , 2003, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[24]  M. AlGhatrif,et al.  A brief review: history to understand fundamentals of electrocardiography , 2012, Journal of community hospital internal medicine perspectives.

[25]  Shamim Nemati,et al.  Data Fusion for Improved Respiration Rate Estimation , 2010, EURASIP J. Adv. Signal Process..

[26]  A. Weissler,et al.  Systolic Time Intervals in Heart Failure in Man , 1968, Circulation.

[27]  Boreom Lee,et al.  Improved elimination of motion artifacts from a photoplethysmographic signal using a Kalman smoother with simultaneous accelerometry , 2010, Physiological measurement.

[28]  A Murray,et al.  Similarity in bilateral photoplethysmographic peripheral pulse wave characteristics at the ears, thumbs and toes , 2000, Physiological measurement.

[29]  Cheng Wang,et al.  Monitoring heart and respiratory rates at radial artery based on PPG , 2013 .

[30]  Zhilin Zhang,et al.  Photoplethysmography-Based Heart Rate Monitoring in Physical Activities via Joint Sparse Spectrum Reconstruction , 2015, IEEE Transactions on Biomedical Engineering.

[31]  Kostas Stylianou,et al.  Arterial Stiffness Alterations during Hemodialysis: The Role of Dialysate Calcium , 2007, Nephron Clinical Practice.

[32]  Alex Young,et al.  Characterization and reduction of motion artifacts in photoplethysmographic signals from a wrist-worn device , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[33]  M. Nitzan,et al.  The variability of the photoplethysmographic signal - a potential method for the evaluation of the autonomic nervous system , 1998, Physiological measurement.

[34]  Ki H. Chon,et al.  Estimation of Respiratory Rate From Photoplethysmogram Data Using Time–Frequency Spectral Estimation , 2009, IEEE Transactions on Biomedical Engineering.

[35]  Michael R. Neuman,et al.  Wearable sensors : fundamentals, implementation and applications , 2014 .

[36]  Friso De Boer,et al.  Measurement of a-a Intervals at Rest in the Second Derivative Plethysmogram , 2009 .

[37]  Arthur A M Wilde,et al.  Accurate electrocardiographic assessment of the QT interval: teach the tangent. , 2008, Heart rhythm.

[38]  Mohd. Alauddin Mohd. Ali,et al.  The Analysis of PPG Morphology: Investigating the Effects of Aging on Arterial Compliance , 2012 .

[39]  Hoon Ko,et al.  Wearable Photoplethysmographic Sensor Based on Different LED Light Intensities , 2017, IEEE Sensors Journal.

[40]  E. Hari Krishna,et al.  A Novel Approach for Motion Artifact Reduction in PPG Signals Based on AS-LMS Adaptive Filter , 2012, IEEE Transactions on Instrumentation and Measurement.

[41]  Emma Pickwell-MacPherson,et al.  Noninvasive cardiac output estimation using a novel photoplethysmogram index , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[42]  K. Takazawa,et al.  Assessment of vascular aging and atherosclerosis in hypertensive subjects: second derivative of photoplethysmogram versus pulse wave velocity. , 2000, American Journal of Hypertension.

[43]  Sun K. Yoo,et al.  Motion artifact reduction in photoplethysmography using independent component analysis , 2006, IEEE Transactions on Biomedical Engineering.

[44]  M. A. Mohd Ali,et al.  Second derivatives of photoplethysmography (PPG) for estimating vascular aging of atherosclerotic patients , 2012, 2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences.

[45]  K Budidha,et al.  The human ear canal: investigation of its suitability for monitoring photoplethysmographs and arterial oxygen saturation , 2014, Physiological measurement.

[46]  E. Hari Krishna,et al.  Estimation of respiration rate from ECG, BP and PPG signals using empirical mode decomposition , 2011, 2011 IEEE International Instrumentation and Measurement Technology Conference.

[47]  Ahmet Resit Kavsaoglu,et al.  A novel feature ranking algorithm for biometric recognition with PPG signals , 2014, Comput. Biol. Medicine.

[48]  B. Trenor,et al.  A computer based photoplethysmographic vascular analyzer through derivatives , 2008, 2008 Computers in Cardiology.

[49]  P. Gibbs,et al.  Active noise cancellation using MEMS accelerometers for motion-tolerant wearable bio-sensors , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[50]  T. Ushiroyama,et al.  Assessment of chilly sensation in Japanese women with lasor Doppler fluxmetry and acceleration plethysmogram with respect to peripheral circulation , 2005 .

[51]  Yun-Kyung Lee,et al.  Development of a wristwatch-type PPG array sensor module , 2011, 2011 IEEE International Conference on Consumer Electronics -Berlin (ICCE-Berlin).

[52]  Rosalind W. Picard,et al.  Motion-tolerant magnetic earring sensor and wireless earpiece for wearable photoplethysmography , 2010, IEEE Transactions on Information Technology in Biomedicine.

[53]  H. Nazeran,et al.  Comparison of Heart Rate Variability Signal Features Derived from Electrocardiography and Photoplethysmography in Healthy Individuals , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[54]  R. Simon Sherratt,et al.  Comparison of low-power wireless communication technologies for wearable health-monitoring applications , 2015, 2015 International Conference on Computer, Communications, and Control Technology (I4CT).

[55]  Mohamed Elgendi,et al.  Applying the APG to measure Heart Rate Variability , 2010, 2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE).

[56]  Roozbeh Jafari,et al.  BioWatch: A Noninvasive Wrist-Based Blood Pressure Monitor That Incorporates Training Techniques for Posture and Subject Variability , 2016, IEEE Journal of Biomedical and Health Informatics.

[57]  I. Oliva,et al.  Toe Pulse Wave Analysis in Obliterating Atherosclerosis , 1983, Angiology.

[58]  Ashley M. Mulchrone,et al.  Sleep apnea: a review of diagnostic sensors, algorithms, and therapies , 2017, Physiological measurement.

[59]  G. Lu,et al.  A comparison of photoplethysmography and ECG recording to analyse heart rate variability in healthy subjects , 2009, Journal of medical engineering & technology.

[60]  Robert Simon Sherratt,et al.  A Survey on Wireless Body Area Networks for eHealthcare Systems in Residential Environments , 2016, Sensors.

[61]  Thomas Penzel,et al.  An Algorithm for Real-Time Pulse Waveform Segmentation and Artifact Detection in Photoplethysmograms , 2017, IEEE Journal of Biomedical and Health Informatics.

[62]  Tom Page,et al.  A Forecast of the Adoption of Wearable Technology , 2015, Int. J. Technol. Diffusion.

[63]  C. M. Lee,et al.  Reduction of motion artifacts from photoplethysmographic recordings using a wavelet denoising approach , 2003, IEEE EMBS Asian-Pacific Conference on Biomedical Engineering, 2003..

[64]  Jean-Yves Fourniols,et al.  Smart wearable systems: Current status and future challenges , 2012, Artif. Intell. Medicine.

[65]  L. Lindberg,et al.  A New Probe for Ankle Systolic Pressure Measurement Using Photoplethysmography (PPG) , 2005, Annals of Biomedical Engineering.

[66]  Zhilin Zhang,et al.  Combining ensemble empirical mode decomposition with spectrum subtraction technique for heart rate monitoring using wrist-type photoplethysmography , 2015, Biomed. Signal Process. Control..

[67]  L. Nilsson,et al.  Respiration can be monitored by photoplethysmography with high sensitivity and specificity regardless of anaesthesia and ventilatory mode , 2005, Acta anaesthesiologica Scandinavica.

[68]  John D. Enderle,et al.  Introduction to Biomedical Engineering , 1999 .

[69]  T. Ohkubo,et al.  Pulse wave velocity and the second derivative of the finger photoplethysmogram in treated hypertensive patients: their relationship and associating factors , 2002, Journal of hypertension.

[70]  Sungmee Park,et al.  Enhancing the quality of life through wearable technology , 2003, IEEE Engineering in Medicine and Biology Magazine.

[71]  Changseok Bae,et al.  Adaptive Noise Cancellation Using Accelerometers for the PPG Signal from Forehead , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[72]  Radek Martinek,et al.  Design and prototyping of a wristband-type wireless photoplethysmographic device for heart rate variability signal analysis , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[73]  R. I. Kitney,et al.  Measurement of heart-rate variability: Part 1—Comparative study of heart-rate variability analysis methods , 1977, Medical and Biological Engineering and Computing.

[74]  K. Chon,et al.  Can Photoplethysmography Variability Serve as an Alternative Approach to Obtain Heart Rate Variability Information? , 2008, Journal of Clinical Monitoring and Computing.

[75]  Y. Mendelson,et al.  Measurement site and photodetector size considerations in optimizing power consumption of a wearable reflectance pulse oximeter , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[76]  Friso De Boer,et al.  Heart Rate Variability Measurement using the Second Derivative Photoplethysmogram , 2010, BIOSIGNALS.

[77]  K. Takazawa,et al.  Assessment of vasoactive agents and vascular aging by the second derivative of photoplethysmogram waveform. , 1998, Hypertension.

[78]  Chen Wei,et al.  Study on conditioning and feature extraction algorithm of photoplethysmography signal for physiological parameters detection , 2011, 2011 4th International Congress on Image and Signal Processing.

[79]  Kenshi Sakai,et al.  Human photoplethysmogram: new insight into chaotic characteristics , 2015 .

[80]  Kirk H. Shelley,et al.  The relationship between the photoplethysmographic waveform and systemic vascular resistance , 2007, Journal of Clinical Monitoring and Computing.

[81]  Ronald M. Aarts,et al.  Reducing motion artifacts in photoplethysmograms by using relative sensor motion: phantom study , 2012, Journal of biomedical optics.

[82]  P. Chowienczyk,et al.  Determination of age-related increases in large artery stiffness by digital pulse contour analysis. , 2002, Clinical science.

[83]  R. Stout,et al.  The Effect of Venous Pulsation on the Forehead Pulse Oximeter Wave Form as a Possible Source of Error in Spo2 Calculation , 2005, Anesthesia and analgesia.

[84]  A. Yli-Hankala,et al.  EEG spectral entropy, heart rate, photoplethysmography and motor responses to skin incision during sevoflurane anaesthesia , 2005, Acta anaesthesiologica Scandinavica.

[85]  Blaine A. Price,et al.  Wearables: has the age of smartwatches finally arrived? , 2015, Commun. ACM.

[86]  Kyung-Sup Kwak,et al.  The Internet of Things for Health Care: A Comprehensive Survey , 2015, IEEE Access.

[87]  E. Nemati,et al.  A wireless wearable ECG sensor for long-term applications , 2012, IEEE Communications Magazine.

[88]  Haruki Kawanaka,et al.  Estimating heart rate using wrist-type Photoplethysmography and acceleration sensor while running , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[89]  Nikolaos G. Bourbakis,et al.  A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[90]  John Allen.  Photoplethysmography and its application in clinical physiological measurement , 2007, Physiological measurement.

[91]  Yuan-Ting Zhang,et al.  Adaptive reduction of motion artifact from photoplethysmographic recordings using a variable step-size LMS filter , 2002, Proceedings of IEEE Sensors.

[92]  Friso De Boer,et al.  Heart Rate Variability and the Acceleration Plethysmogram Signals Measured at Rest , 2010, BIOSTEC.

[93]  Ilkka Korhonen,et al.  Application of Optical Heart Rate Monitoring , 2014 .

[94]  A Murray,et al.  Accuracy of four automatic QT measurement techniques in cardiac patients and healthy subjects. , 1996, Heart.