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In this article we analyze a number of observations obtained with the reflection-mode photoplethysmography (PPG), which can hardly be explained by commonly accepted model of the PPG-signal formation. It is shown that the physiologic model of light interaction with living tissue recently proposed by our group provides reasonable explanation of all observations. According to this model, it is pulsatile transmural pressure of the arteries, which compresses/decompresses the density of capillaries in the dermis, thus modulating the blood volume in the capillary bed, which in its turn modulates the power of remitted green light.
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Physics Procedia 86 ( 2017 ) 72 80
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1875-3892 © 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
Peer-review under responsibility of the organizing committee of PNBS-2015 and PNMS-2015.
doi: 10.1016/j.phpro.2017.01.024
International Conference on Photonics of Nano- and Bio-Structures, PNBS-2015, 19-20
June 2015, Vladivostok, Russia and the International Conference on Photonics of Nano-
and Micro-Structures, PNMS-2015, 7-11 September 2015, Tomsk, Russia
Origin of photoplethysmographic waveform at green light
Alexei A. Kamshilin
,Nikita B. Margaryants
Department of Computer Photonics and Videomatics, ITMO University, St. Petersburg, 197101, Russia
In this article we analyze a number of observations obtained with the reflection-mode photoplethysmography (PPG),
which can hardly be explained by commonly accepted model of the PPG
-signal formation. It is shown that the
physiologic model of light interaction with living tissue recently proposed by our group provides reasonable
explanation of all observations. According to this model, it is pulsatile transmural pressure of the arteries, which
compresses/decompresses the density of capillaries in the dermis, thus modulating the blood volume in the capillary
bed, which in its turn modulates the power of remitted green light.
© 2016 The Authors.Published by Elsevier B.V.
Peer-review under responsibility of the organizing committee of PNBS-2015 and PNMS-2015.
Keywords:photoplethysmography;blood pulsation imaging; amplitude distribution of blood pulsation
1. Introduction
The term “plethysmography” stems from two ancient Greek words “plethysmos” which means increase,
and “grapho” which is the word for write. In medicine this term is commonly used to define process of
determination and registration of blood volume changes in a live body. Hertzman was first who introduced
in 1938 the term of photoplethysmography (PPG) to describe a non-invasive optical technique capable for
transcutaneous registration of blood volume changes in the blood vessels (Hertzman(1938)). Underlying
principle of PPG is the empirical observation that the light transmitted through (or reflected from) the living
tissue obtains a modulation in time at the heartbeat frequency(Hertzman and Spealman(1937)). The
* Corresponding author. Tel.: +7-812-571-65-34
E-mail address:
© 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
Peer-review under responsibility of the organizing committee of PNBS-2015 and PNMS-2015.
Alexei A. Kamshilin and Nikita B. Margaryants / Physics Procedia 86 ( 2017 ) 72 – 80 73
technique is very simple and cost efficient because it requires only two elements, a source of incoherent
light (even natural illumination can be used) and a photoreceiver for implementation. Due to these
advantages, an optical device for measurements of arterial blood oxygen saturation (pulse oximeter) was
invented in 1972 by Takuo Aoyagi(Severinghaus and Honda (1987), Aoyaqi(2003)). Pulse oximeters
became commercially available since 1983. Today these devices are adopted for carrying out the standard
procedure of oxygen saturation estimation in numerous clinics worldwide. In addition, pulsatile variation of
the signal in PPG sensors is commonly used for measuring the heart rate. Notably that the heart-rate
estimations today can be provided by using ubiquitous smartphones (Jonathan and Leahy(2010)). Starting
from the year 2000, when the first system of noncontact imaging photoplethysmography (iPPG) was
proposed by (Wu et al.(2000)), there is rapid growth in the literature pertaining to PPG technique and its
applications motivated by advances in technology of optoelectronic devices and digital signal processing.
However, despite of the long history in PPG research, the detailed mechanism behind the phenomena of the
light modulation caused by cardiovascular activity is still a matter of debate. Is it change of blood volume
or blood pressure, which primarily affects the parameters of light?
In this paper we discuss existing models of light interaction with a biological tissue in-vivo drawing
attention to recent experimental observations using iPPG systems, which are hardly explained in frames of
the generally accepted model. Our opinion is that the recently proposed model(Kamshilin et al.(2015b)),
which takes into account elastic deformation of the dermis by big blood vessels, more correctly describes
the origin of light modulation.
2. Conventional model of PPG-waveform origin
2.1. Inverse relationship between blood volume and light intensity
In any PPG experiment, a biological tissue is illuminated by an incoherent light source, and the power
of light either transmitted through or reflected from the tissue is measured by a photo-detector.
Correspondingly, there are two modes of PPG systems: transmitting and reflectance(Nijboer et al.(1981)).
In the transmitting mode of operation, the light source and photoreceiver are situated opposite each other
with transilluminated vascular tissue between them. In the reflectance mode, the detector and light source
are placed side by side to monitor the light remitted from the tissue. Basing on the experimental
observations, the most of researchers is of the opinion that the light intensity registered by the
photodetector is inversely related to the blood volume in the tissue (Hertzman (1938), Nieveen et al.(1956),
Weinman et al.(1977), Roberts (1982), de Trefford and Lafferty (1984) Reisner et al.(2008)).This
mechanism is not difficult to understand in the transmitting-mode PPG in the case of using near-infrared
(NIR) light. Tissue is less opaque than the whole blood and, consequently less light goes through the
transilluminated tissue and reaches the photodetector when the blood volume increases and vice versa. It is
less obvious why the inverse relationship between remitted light power and blood volume should hold in
the reflectance-mode PPG although experimental evidence seems to support this standpoint. In the latter
mode, displacement of vessel wall may affect the light modulation (Weinman et al.(1977)). Moreover, it is
not clear how efficient is light interaction with arterial blood in the reflection mode. Nevertheless, it was
generally accepted that both modes of PPG measure blood volume variations in the vascular bed (Jago and
Murray, (1988), Nitzan et al.(1998), Loukogeorgakis et al.(2002), Khanoka et al.(2004), Shelley et
al.(2005)).Sometimes the PPG technology is even referenced to as pulse volume monitor(Kim et al. (1986),
Murray and Foster (1996), Millasseau et al. (2006), Selvaraj et al.(2008), Cenini et al.(2010)).
74 Alexei A. Kamshilin and Nikita B. Margaryants / Physics Procedia 86 ( 2017 ) 72 – 80
Typical waveform of the PPG signal is shown in Fig. 1a for several sequential pulses. As seen, it
consists of two different components: alternating (AC) which is varying in time with frequency of about
one Hz and slowly varying baseline (DC-level). In the frames of the commonly accepted model of PPG, the
AC-component stems from absorption because of pulse-added volume of arterial blood, while the baseline
(DC) with various lower frequency components is attributed to respiration, sympathetic nervous system
activity, and thermoregulation (Allen et al.(2005), Buchs et al.(2005)). It is believed that DC component is
due to (i) absorption by non-pulsatile arterial blood, (ii) absorption by blood in viens and capillaries (which
are not pulsating at the heartbeats), and (iii) absorption and scattering in all other tissues.
Fig. 1. (a) Typical waveform of the photoplethysmographic waveform: AC (red curve)ispulsatile component of the signal,DC(black
dashed curve) is slowly varying component; (b) ratio AC/DC(red curve) after detrending and inversion with simultaneously recorded
ECG (blue curve).
Red curve in Fig. 1b shows the same PPG waveform, but after normalization to the DC level,
detrending, and inversion the sign, to make the waveform proportional to change of the blood volume. One
can see that AC component oscillates synchronously with heartbeats, which are represented by R-peaks in
the electrocardiogram (ECG, blue curve) simultaneously recorded with PPG. It was noticed even in the first
paper devoted to PPG that inverted AC-component resembles the pressure pulse(Hertzman and
Spealman(1937)). Other researchers also share the view thatthe PPG waveform resembles that of the
arterial blood pressure but instead of pressure it is related to the volume changes in the measurement site
and hence contains information related to the peripheral blood circulation (Murray and Foster (1996),
Shelley et al.(2005), Korhonen and Yli-Hankala(2009)). The relationship of PPG signal with change of
blood volume was supported by observed similarity between PPG and simultaneously measured volume of
a limb by the strain gauge (de Trefford and Lafferty(1984)), and by correlation between PPG and arterial
diameter measured by Doppler ultrasound (Wang and Zheng (2010)).In the systole phase, when the arterial
blood pressure is in the maximum, vessels walls are expanded leading to the maximal momentary blood
volume, as well (Murray and Foster(1996)).Therefore, change of the blood pressure and blood volume are
related each other but correct interpretation of the experimental results requires more detailed explanation
of the mechanism of light-tissue interaction.
2.2. Pulse oximetry
The same basic idea of light modulation by pulsating arterial blood volume is behind the pulse oximetry,
a noninvasive technology for measuring the arterial oxygen saturation (Mannheimer(2007), Severinghaus
and Honda (1987)). In a pulse oximeter, a finger or toe is illuminated simultaneously at two different
wavelengths (red and infrared), and the light power at each wavelength is measured separately after
interaction with biological tissue. Since the blood absorption depends on the concentration of oxygenated
hemoglobin, the ratio of AC/DC (so called ratio of ratios) was found to be proportional to the level of blood
Alexei A. Kamshilin and Nikita B. Margaryants / Physics Procedia 86 ( 2017 ) 72 – 80 75
oxygen saturation after respective calibration(Aoyaqi (2003)).It is worth noting that all oximeters operate in
the contact with the skin under applied external pressure(Dassel et al., 1995). Successful application of
blood oximeters in clinical practice supported the model in which AC component of the PPG waveform
stems from pulsating volume of arterial blood.However, there were reports of signal instability and
erroneously low SpO2 values with some of reflectance-mode oximeters (Sami et al.(1991),Dassel et
al.(1995), Whitman et al. (2003), Redford et al. (2004)).
3. Conflicts of experimental data with the conventional model
3.1. Dependence on light wavelength
Pulse oximeters usually operate with red and near infrared light (wavelength band 660 900 nm). This
light penetrates relatively deep (0.8 1.5 mm) into a living tissue (Anderson and Parrish(1982)). Therefore,
it can be absorbed by blood flowing in deeply situated arteries. However, several groups reported that
AC/DC ratio of the PPG waveform is much higher at the green light (Verkruysse et al.(2008), Maeda et al.
(2011), Kamshilin et al.(2011), Sun et al. (2012), Teplov et al.(2014), Bal(2015)). Numerical modeling of
PPG waveform (Cui et al.(1990)) also showed that AC component of the PPG waveform is maximal at the
wavelength of 520 580 nm, which was attributed to stronger absorption of green light by
erythrocytes.Considering that the penetration depth of green light does not exceed 0.6 mm (Anderson and
Parrish (1982), Bashkatov et al.(2005)) while arteries are typically situated deeper than 3 mm below the
epidermis (Gray(2008)), one can hardly explain these observations in the frames of commonly accepted
PPG model.
3.2. Counter-phase light modulation in adjacent areas
Imaging photoplethysmography possesses an important advantage of offering detailed spatial
information simultaneously from different places of a tissue, thus allowing mapping of physiological
parameters. We developed modified iPPG system referred to as Blood Pulsation Imaging (BPI), which
allowed mapping of both the amplitude and relative phase of blood pulsations (Kamshilin et al. (2011)).
Using advantages of the BPI system, we recently observed that green light remitted from adjacent places at
a subject’s hand acquires a counter phase temporal modulation (Kamshilin et al. (2013), Teplov et al.
(2014)). An example of the spatial distribution of the phase of PPG waveform is shown in Fig. 2ain which
the phase difference is coded inpseudocolor. It is clearly seen that there are several adjacent areas atthe
wrist in which the phase difference of light modulation reaches 180q.The PPG waveforms recorded in two
adjacent regions of interest (ROI) are shown in Fig. 2b by black and red curves for ROI-1 and ROI-2,
respectively. Position of ROI-1 (black square in Fig. 2a) and ROI-2 (white square) were chosen to be in
areas with counter phase modulation. The distance between the centers of theseROIswas about 3 mm, and
the size of each ROI was 7 × 7 pixels or 1.7 × 1.7 mm2.Such areas with counter-phase light modulation
were found in all 58 studied subjects (Kamshilin et al.(2015b)).
One can see in Fig. 2b that the power of light remitted from ROI-1 and ROI-2 is modulated at the same
heartbeat frequency but shapes of the waveforms are completely different. While the PPG waveform in
ROI-1 (black curve) has the classical shape resembling typical dynamics of arterial blood pressure with fast
transitions from diastole to systole and with specific dicrotic notch in the backward transition, the inverted
waveform in ROI-2(red curve) cannot find any explanation in the frames of conventional PPG model. An
attempt to interpret coexistence of both waveforms assuming the origin of light modulation being the
change of arterial blood volume certainly fails because in this case the systole and diastole are observed
simultaneously in two neighboring regionsseparated by few millimeters only, which is impossible from the
physiological point of view. First observation of simultaneously occurring light modulation with inverted
shapes was reported by our group (Teplov et al.(2014)). It is worth noting, nevertheless, that almost 40
years ago inverted “blood-volume pulses” were observed in few places over carotid arteries by movable
reflection-mode PPG transducer (Weinman et al.(1977)). However, using single-point measuring
76 Alexei A. Kamshilin and Nikita B. Margaryants / Physics Procedia 86 ( 2017 ) 72 – 80
transducer,it was difficult to conclude whether the inverted waveform is due to physiological causes or to a
different transducer position (Weinman et al. (1977)). In contrast, visualization of blood pulsations by
modern BPI system with high spatial resolution unambiguously demonstrates physiological (not
instrumental) origin of these observations (Teplov et al.(2014), Kamshilin et al.(2015b)).
Fig. 2.Counter-phase light modulation. (a) Spatial distribution of the relative phase of the PPG signal (position of ROI-1 is shown by
black square while that of ROI-2 by white one). (b) PPG waveform recorded in these ROIs: black curve is the signal in ROI-1 and
the red curve is the signal in ROI-2. The color scales on the left shows the relative phase in degrees.
3.3. Influence of the skin contact
For accurate measurements, conventional PPG sensor should operate in a contact with the skin.
However, in spite of several studies of the contact-force effect on the amplitude and shape of the PPG
waveform, the physiological reason of external force influence has not been completely clarified. On the
one hand, the increasein contacting force (e.g., by applying the external pressure to the reflection-mode
PPG sensor by more than 80 mmHg)results in diminishing of the AC component (Nieveen et al. (1956),
Teng and Zhang(2004)) because such a pressure might significantly reduce the vessels diameter with
consequent diminishing of the pulsating blood volume. This scenario was supported by the theoretical
model which considered mechanical properties of arterial walls (Teng and Zhang(2007)). On the other
hand, there are reports (Dassel et al.(1995), Shelley et al.(2005), Fallow et al. (2013)) describing shape
improvement of the PPG waveform (which was transferred from a noise-like to one resembling the
dynamics of arterial blood pressure) after application of an external pressure below 60 mmHg to the
sensor.In this case, change of the signal shape is also accompanied by an increaseof the AC-component
amplitude. The effect of the contact force on the waveform shape was attributed to the influence of the
venous component: it is thought that pressure onto the sensor forces venous blood out of the tissue(Dassel
et al.(1995), Shelley et al.(2005), Shelley(2007)).However, the detailed mechanism remainsunclear how
does the venous component might lead to the noise-like signal In this sense, we completely agree with
conclusion of the recent reviewdevoted to plethysmography (Alian and Shelley(2014)) that the
physiologic source of the PPG waveform is still unknown.
All above-mentioned studies of the external pressure effect (Nieveen et al. (1956), Dassel et al. (1995),
Teng and Zhang (2004), Shelley et al.(2005)) were carried out using single-point PPG sensors operating
with near infrared light which relatively deep penetrates into the tissue and might interact with venous
blood. However, our recent study of blood pulsations in subjects’ palms using BPI system at green light
demonstrated that weak external pressure (less than 40 mmHg) results in both significant increase (up to 8
times) of the AC component and improvement of the waveform shape (Kamshilin et al.(2015a), Kamshilin
et al. (2015b)).Since green light does not penetrate deeply into the tissue (see Sect. 3.1) and cannot
efficiently interacts with veins, these observations cannot be explained in the frames of commonly accepted
PPG model.
Alexei A. Kamshilin and Nikita B. Margaryants / Physics Procedia 86 ( 2017 ) 72 – 80 77
4. New physiologic model of PPG
To resolve the conflict between the experimental data and conventional PPG model, our group recently
proposed a new model of light interaction with living tissue (Kamshilin et al.(2015b)). It is based on the
well-known physiologic postulate that considerable pulse-pressure oscillations occur only in arteries
(Guyton and Hall(2010)). These oscillations result in modulation at the heartbeat frequency of both the
blood volume in arteries and the transmural pressure. However, green light is not modulated by arterial
bloodvolume pulsations because of its small penetration into the tissue. Nevertheless, during the systole
phase, growingtransmural pressure compresses the connective tissue of the dermis in local places
depending on the particular anatomy of a subject. Dermis contains both blood and lymphatic capillaries
which are incompressible and they do not pulsate at the heartbeat rate (Reisner et al. (2008)). However, due
to dermis compression, the distance between adjacent capillaries diminishes(Chan et al.(1996)), which
results in modulation of capillaries density synchronously with the transmural pressure in the local place of
measurements.This variation of the density of capillaries leads to temporal modulation of the light
parameters because it affects both the absorption and scattering coefficients. In other words, PPG
waveform originates from the modulation of the blood volume in the capillary bed, which is induced by the
pulsatile transmural pressure of the arteries.
Fig. 3.New concept for the origin of PPG waveform. (a) Artery is in the diastole phase with the smallest compression of the capillary
bed. (b) Systole phase with slightly compressed capillaries because of elastic external boundary. (c) Strongly compressed capillary
bed in the case of external contact.
Simplified concept of the proposed model is shown in Fig. 3. In the end-diastole phase (Fig. 3a, the
dermis is in the minimal compression suggesting the minimal density of capillaries, as well. In this case the
green light remitted from the upper part of the dermis (due to small penetration depth) has the maximal
power because absorption and scattering are in their own minima. Thereafter, fast-growing transmural
pressure compresses the dermis leading to the maximal density of capillaries in the systole phase (Fig. 3b
and Fig. 3c). Correspondingly, the power of remitted light reaches its minimum in the systole phase.
Therefore, the inverted waveform of the remitted light power follows the changes of transmural blood
pressure, not arterial blood volume. However, the degree of dermis compression depends on the boundary
conditions of the skin. Without any external contact (Fig. 3b), an elastic skin (typical for youth)is reshaped
with moderate compression of the dermis, which results in small amplitude of the AC component.
Alternatively (Fig. 3c), for stiff skin (or when the skin displacement is limited by an external contact), the
dermis compression is much higher resulting in larger PPG signal.
Certainly, any variation of internal conditions (e.g., caused by change of venous pressure, mussel
constriction, or change of the lymph volume) affects the PPG waveform, as well. Frequently observed
improvement of the waveform shape byexternal contact force(Dassel et al.(1995), Shelley et al. (2005),
Kamshilin et al. (2015a)) may be explained in the following way. Noise-like PPG waveform observed
without external force may be caused by non-efficient mechanical links between the arterial walls and
capillary bed in dermis. By applying external force, the links are repaired and transmural pressure
efficiently modulates the capillary density.Prevalence of other than arterial transmural pressure factors on
78 Alexei A. Kamshilin and Nikita B. Margaryants / Physics Procedia 86 ( 2017 ) 72 – 80
the PPG signal formation in the case of noncontact plethysmography explains recently observed lack of
correlation between ECG and PPG signals (Kamshilin et al.(2015a)).The new model also explains
observed tendency of the PPG-signal amplitude being increased with subject’s age (Nippolainen et
Observations of the inverted PPG waveform (Weinman et al.(1977), Teplov et al.(2014)) can also be
explained in the frames of new model. Complexity of a body structure allows us to suggest that there are
selected areas in which mechanical connections of arterial walls with dermis may significantly vary even in
adjacent places. In such areas, dermis compression in one local place could result in i ts expansion in the
neighbor place (Kamshilin et al.(2015b)). An example of such behavior is an elastic rubber: application of
the pressure to the center of the peace of rubber leads to squeeze of its central part with the simultaneous
expansion of the peripheral part.In this specific area, both the light absorption and light scattering will vary
in the counter phase in adjacent places as it is shown in Fig. 2b and was recently reported in (Teplov et al.
(2014), Kamshilin et al.(2015b)).
The new model also modifies interpretation of the results obtained with pulse oximetry sensors
operating in the reflection mode. Since the PPG waveform originates from the modulation of the blood
volume in dermis, an oximeter does measure the oxygen saturation in the capillaries, not in the arteries.
Even though the reflection-mode oximeters operate at red and near infrared light, which penetrates much
deeper than green light, the influence of the dermis compression should be significant because any light
twice interacts with upper level of the dermis before reaching the photo-receiver.
5. Conclusion
Analysis of various experiments carried out with the reflection-mode photoplethysmographyshowed that
the number of observations failed in explanation by commonly accepted model of light interaction with
living biological tissue can be explained in new model recently developed by our group (Kamshilin et
al.(2015b)). According to this model, it is pulsatile transmural pressure of the arteries, which
compresses/decompresses the density of capillaries in the dermis, thus modulating the blood volume in the
capillary bed, which is read out by green light.
The research was financially supported by the Russian Science Foundation (grant 15-15-20012).
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... For transmission-based PPG measurements, red or near infrared (NIR) light is often used because this wavelength is sensitive to hemoglobin absorption and can penetrate through the finger for detection [3]. Reflection-based PPG measurements used in heart rate monitoring are typically performed using green light, whereas red or NIR light is typically used for oxygen saturation measurements [4]. There has been extensive research utilizing the PPG signal to estimate blood pressure, and various strategies have been applied. ...
... Wavelengths of 532 nm and 808 nm were chosen because they probe different tissue volumes. 532 nm is more strongly absorbed by tissue and penetrates less deeply, and has been used frequently in wrist PPG measurements [4]. In contrast, 808 nm will penetrate more deeply into tissue. ...
... For all subjects, pulses appeared most clearly near the radial artery, as confirmed by palpation. This is consistent with the literature suggesting that the reflective PPG signal on the wrist is strongest near the radial artery [4,34]. After the wrist measurement location was identified, an initial baseline measurement was taken. ...
Non-invasive continuous blood pressure monitoring remains elusive. There has been extensive research using the photoplethysmographic (PPG) waveform for blood pressure estimation, but improvements in accuracy are still needed before clinical use. Here we explored the use of an emerging technique, speckle contrast optical spectroscopy (SCOS), for blood pressure estimation. SCOS provides measurements of both blood volume changes (PPG) and blood flow index (BFi) changes during the cardiac cycle, and thus provides a richer set of parameters compared to traditional PPG. SCOS measurements were taken on the finger and wrists of 13 subjects. We investigated the correlations between features extracted from both the PPG and BFi waveforms with blood pressure. Features from the BFi waveforms were more significantly correlated with blood pressure than PPG features ( R = − 0.55, p = 1.1 × 10 ⁻⁴ for the top BFi feature versus R = − 0.53, p = 8.4 × 10 ⁻⁴ for the top PPG feature). Importantly, we also found that features combining BFi and PPG data were highly correlated with changes in blood pressure ( R = − 0.59, p = 1.7 × 10 ⁻⁴ ). These results suggest that the incorporation of BFi measurements should be further explored as a means to improve blood pressure estimation using non-invasive optical techniques.
... Recent advancements in image processing have made the extraction of vital signs from remote, contactless, photoplethysmographic (rPPG) signals possible [4]. The fundamental principle governing rPPG is similar to that of contact PPG; they both exploit the light absorption differences of oxygenated and deoxygenated hemoglobin in capillary blood vessels [5]. While PPG primarily uses visible and near-infrared light sources, rPPG merely acquires visible wavelength as modern video cameras compose images in the RGB color channels [6,7]. ...
... Several physiological models have been proposed in cPPG to explain the light interaction in reflective photoplethysmography [5]. While each model has its own advantages in justifying the signal morphology and behavior, more empirical analyses are needed for hypothesizing similar models in rPPG-based sensing applications. ...
Point-of-care remote photoplethysmography (rPPG) devices that utilize low-cost RGB cameras have drawn considerable attention due to their convenience in contactless and non-invasive vital signs monitoring. In rPPG, sufficient lighting conditions are essential for obtaining accurate diagnostics by observing the complete signal morphology. The effects of illuminance intensity and light source settings play a significant role in rPPG assessment quality, and it was previously observed that different lighting schemes result in different signal quality and morphology. This study presents a quantitative empirical analysis where the quality and morphology of rPPG signals were assessed under different light settings. Participants’ faces were exposed to the white LED spotlight, first when the sources were installed directly behind the video camera, and then when the sources were installed in a cross-polarized scheme. Hence, the effect of specular reflectance on rPPG signals could be observed in an increasing projection. The signal qualities were analyzed in each intensity level using a signal-to-noise (SNR) ratio metric. In 3 of 7 participants, placing the video camera on the same level as the light source led to signal quality loss of up to 3 dB for the range 30–60 Lux. In addition, two fundamental morphological features were analyzed, and the derivative-related feature was found to be increasing with illuminance intensity in 6 of 7 participants.
... blood, melanin) and scatters (collagen, keratin), which constitute the quite complex biological tissue. Several studies deal with the origin of PPG signal [15][16][17]; nevertheless, the most accredited theories identify as principal contributor factors the following ones [18]: (1) the different orientation of blood cells during the systolic and diastolic phases, resulting in changes of the overall light attenuation, (2) the volumetric distribution of the absorbers and (3) the mechanical movements of the capillaries and the elastic deformation of the skin during the vascular bed expansion. Beyond the increase of the overall capillary density, this phenomenon causes variations of the back-reflected light intensity due to local changes of both the scattering and the absorption coefficient of the light. ...
... On the other hand, PPG is a low-cost and noninvasive way to measure blood volume changes in a human during heart activity. PPG has two main components: incoherent light source and photoreceiver [35]. A typical PPG signal element is shown in Figure 2, complete with the systolic period associated with blood in-rush, the diastolic period associated with relaxation, and the dicrotic notch associated with pulse reflection [36]. ...
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Affective computing focuses on instilling emotion awareness in machines. This area has attracted many researchers globally. However, the lack of an affective database based on physiological signals from the Asian continent has been reported. This is an important issue for ensuring inclusiveness and avoiding bias in this field. This paper introduces an emotion recognition database, the Asian Affective and Emotional State (A2ES) dataset, for affective computing research. The database comprises electrocardiogram (ECG) and photoplethysmography (PPG) recordings from 47 Asian participants of various ethnicities. The subjects were exposed to 25 carefully selected audio–visual stimuli to elicit specific targeted emotions. An analysis of the participants’ self-assessment and a list of the 25 stimuli utilised are also presented in this work. Emotion recognition systems are built using ECG and PPG data; five machine learning algorithms: support vector machine (SVM), k-nearest neighbour (KNN), naive Bayes (NB), decision tree (DT), and random forest (RF); and deep learning techniques. The performance of the systems built are presented and compared. The SVM was found to be the best learning algorithm for the ECG data, while RF was the best for the PPG data. The proposed database is available to other researchers.
... From the reflected light, the BVP signal is extracted, which is processed further to compute the HR [31]. The first commercial oximeter based on PPG was introduced in 1983 [14]. Oximeters contain a photodiode sensor which measures the intensity of reflected light. ...
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With a surge in online medical advising remote monitoring of patient vitals is required. This can be facilitated with the Remote Photoplethysmography (rPPG) techniques that compute vital signs from facial videos. It involves processing video frames to obtain skin pixels, extracting the cardiac data from it and applying signal processing filters to extract the Blood Volume Pulse (BVP) signal. Different algorithms are applied to the BVP signal to estimate the various vital signs. We implemented a web application framework to measure a person's Heart Rate (HR), Heart Rate Variability (HRV), Oxygen Saturation (SpO2), Respiration Rate (RR), Blood Pressure (BP), and stress from the face video. The rPPG technique is highly sensitive to illumination and motion variation. The web application guides the users to reduce the noise due to these variations and thereby yield a cleaner BVP signal. The accuracy and robustness of the framework was validated with the help of volunteers.
... A change in the medium traveled distance �z (t) (Eq. 4) due to heart pulsation-induced arterial volume change 18,31,32 will be related to a change in the diffuse reflected light �R D(t) (Eq. 6). ...
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We describe a new method for remote emotional state assessment using multispectral face videos, and present our findings: unique transdermal, cardiovascular and spatiotemporal facial patterns associated with different emotional states. The method does not rely on stereotypical facial expressions but utilizes different wavelength sensitivities (visible spectrum, near-infrared, and long-wave infrared) to gauge correlates of autonomic nervous system activity spatially and temporally distributed across the human face (e.g., blood flow, hemoglobin concentration, and temperature). We conducted an experiment where 110 participants viewed 150 short emotion-eliciting videos and reported their emotional experience, while three cameras recorded facial videos with multiple wavelengths. Spatiotemporal multispectral features from the multispectral videos were used as inputs to a machine learning model that was able to classify participants’ emotional state (i.e., amusement, disgust, fear, sexual arousal, or no emotion) with satisfactory results (average ROC AUC score of 0.75), while providing feature importance analysis that allows the examination of facial occurrences per emotional state. We discuss findings concerning the different spatiotemporal patterns associated with different emotional states as well as the different advantages of the current method over existing approaches to emotion detection.
... IR and near-IR wavelengths are useful for measuring blood flow in deep tissues such as muscle, while green light allows for superficial blood flow measurement in the skin. Therefore, green light is most commonly used for wrist-worn devices as it offers the strongest modulation [30]. Furthermore, multi-wavelength PPG sensors are being developed to improve signal quality. ...
The inconvenience and risk associated with the regular use of invasive blood glucose measurements has led to tremendous research in this area. This paper proposes the design of a non-invasive blood glucose estimation system using novel Mel frequency cepstral coefficients features of wristband photoplethysmogram signal and physiological parameters. A dataset from 217 participants of a hospital in Cuenca Ecuador is used to validate the proposed model. The support vector regression (SVR) and extreme gradient boost regression (XGBR) techniques are used to estimate blood glucose levels (BGL). The XGBR technique achieves the least value for the standard error of prediction (SEP), 9.78 mg/dL. Further, 5 features are selected from the feature set based on the feature importance in XGBR. The XGBR model with the reduced feature set results in further reduction of SEP value (5.53 mg/dL) with a correlation coefficient of 0.99. Standard Clarke error grid analysis and Bland-Altman analysis shows that the predicted glucose values are in the clinically acceptable region. The results of the proposed model demonstrate the potential of wearable BGL monitoring technology.
With a surge in online medical advising remote monitoring of patient vitals is required. This can be facilitated with the Remote Photoplethysmography (rPPG) techniques that compute vital signs from facial videos. It involves processing video frames to obtain skin pixels, extracting the cardiac data from it and applying signal processing filters to extract the Blood Volume Pulse (BVP) signal. Different algorithms are applied to the BVP signal to estimate the various vital signs. We implemented a web application framework to measure a person’s Heart Rate (HR), Heart Rate Variability (HRV), Oxygen Saturation (SpO\(_{2}\)), Respiration Rate (RR), Blood Pressure (BP), and stress from the face video. The rPPG technique is highly sensitive to illumination and motion variation. The web application guides the users to reduce the noise due to these variations and thereby yield a cleaner BVP signal. The accuracy and robustness of the framework was validated with the help of volunteers, and their privacy was protected using face masking techniques.KeywordsRemote photoplethysmographyDeep learningVital signs measurementComputer vision
Conference Paper
PhotoPlethysmoGraphy (PPG) is ubiquitously employed in wearable devices for health monitoring. Photodiode signal inversion is observed in rare occasions, most of the time when the sensor is pressed against the skin. We report in this article such observations made at the right common carotid artery site. Indeed we have systematically observed a photodiode signal inversion when the PPG sensor is placed where the pulse is the best felt at the carotid. In addition to be inverted, the pulse is steeper during the systolic phase. Such inversion has implications in terms of pulse arrival time (PAT) measurements In our experiments, this causes a difference of 20 ms in the carotid PAT when measured at the absolute maximum slope. The mechanical and optical properties of tissues must be better accounted to explain the PPG signal morphology. Clinical Relevance- Understanding the role of mechanical tissue properties seems relevant in order to obtain more reproducible results in PPG signal analysis.
Sensors play an important role in measuring biosignals. These sensors evolved from analog form to current digital avatar. First formally known cardiovascular sensing device is a stethoscope. It has evolved from its earliest version of a wooden tube of specific dimensions to binaural stethoscope. to a digital stethoscope in which the sound of heart pulses can be digitized, annotated, and processed. ECGs have also evolved from room-size machines to small credit-card-sized wearable devices. This chapter will describe the basic building blocks of such many cardiovascular sensing devices, how they can be used to predict cardiovascular issues, and a point of view on how they will evolve further.
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We present experimental evidence that the parameters of green light remitted from a human tissue in-vivo strongly depend on skin contact status. In case when the skin is free of any contact, simultaneous recording of imaging photoplethysmogram (iPPG) and electrocardiogram revealed that contactless iPPG fails in correct estimates of the heart rate in almost half of the cases. Meanwhile, the number of successful correlations between ECG and iPPG is significantly increased when the skin is in contact with a glass plate. These observations are in line with the recently proposed model in which pulsatile arteries deform the connective-tissue components of the dermis thus resulting in temporal modulation of the capillary density interacting with slightly penetrating light.
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In this report we present the experimental study of imaging photoplethysmography in the area of the palm and wrist of fifty-six healthy subjects. We found that the amplitude of the PPG waveform is unevenly distributed over the studied area forming the hot spots with the elevated amplitude. There is clear tendency of the amplitude increasing in the hottest spots with the age of the subject. These observations support the recently proposed model of photoplethysmography in which pulse oscillations of the arterial transmural pressure deform the connective-tissue components of the dermis resulting in periodical changes of both the light scattering and absorption.
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Photoplethysmography (PPG) is a noninvasive optical method accepted in the clinical use for measurements of arterial oxygen saturation. It is widely believed that the light intensity after interaction with the biological tissue in vivo is modulated at the heartbeat frequency mainly due to pulsatile variations of the light absorption caused by arterial blood-volume pulsations. Here we report experimental observations, which are not consistent with this model and demonstrate the importance of elastic deformations of the capillary bed in the formation of the PPG waveform. These results provide new insight on light interaction with live tissue. To explain the observations we propose a new model of PPG in which pulse oscillations of the arterial transmural pressure deform the connective-tissue components of the dermis resulting in periodical changes of both the light scattering and absorption. These local changes of the light-interaction parameters are detected as variations of the light intensity returned to a photosensitive camera. Therefore, arterial pulsations can be indirectly monitored even by using the light, which slightly penetrates into the biological tissue.
Despite the many years since optical spectra from human skin were first obtained, only recently have quantitative models of cutaneous optics been applied. This chapter aims to present the optics of human skin conceptually and quantitatively, to examine the structures and pigments that modify cutaneous optics, and to discuss current research in this area and its applications to photomedicine. Introductory sections on the structure of skin and on optical phenomena in turbid media are included in addition to the general introduction below. This chapter does not offer an exhaustive review of all studies related to the optics of human skin, but attempts to include those reliable studies pertinent to its goals. The interested reader can find thorough and more historical reviews in (1–3).
We propose a robust method for automated computation of heart rate (HR) from digital color video recordings of the human face. In order to extract photoplethysmographic signals, two orthogonal vectors of RGB color space are used. We used a dual tree complex wavelet transform based denoising algorithm to reduce artifacts (e.g. artificial lighting, movement, etc.). Most of the previous work on skin color based HR estimation performed experiments with healthy volunteers and focused to solve motion artifacts. In addition to healthy volunteers we performed experiments with child patients in pediatric intensive care units. In order to investigate the possible factors that affect the non-contact HR monitoring in a clinical environment, we studied the relation between hemoglobin levels and HR estimation errors. Low hemoglobin causes underestimation of HR. Nevertheless, we conclude that our method can provide acceptable accuracy to estimate mean HR of patients in a clinical environment, where the measurements can be performed remotely. In addition to mean heart rate estimation, we performed experiments to estimate oxygen saturation. We observed strong correlations between our SpO2 estimations and the commercial oximeter readings.