Laser-speckle-based detection of fluid pulsation
in the presence of motion
artifacts:
in vitro and in vivo study
M. Nemati,1,* R. W. C. G. R. Wijshoff,2J. M. A. Stijnen,3S. van Tuijl,3J. W. M. Bergmans,2 N. Bhattacharya,1and H. P. Urbach1
1Optics Research Group, Department of Imaging Science and Technology, Delft University of Technology,
Lorentzweg 1, 2628 CJ Delft, The Netherlands
2Signal Processing Systems, Department of Electrical Engineering, Eindhoven University of Technology,
Den Dolech 2, 5612 AZ Eindhoven, The Netherlands
3LifeTec Group, Den Dolech 2, 5612 AZ Eindhoven, The Netherlands
*Corresponding author: m.nemati@tudelft.nl
Received September 2, 2013; revised November 7, 2013; accepted November 11, 2013; posted November 11, 2013 (Doc. ID 196826); published December 9, 2013
We have performed an in vitro and in vivo study, based on laser speckle contrast analysis, to detect fluid pulsation in the presence of artifacts caused by the relative motion between the sample and the illumination source. We observe that the pulsation signal is clearly detectable for a range of motion amplitudes and oscillation frequencies; however, for higher amplitudes and oscillation frequencies of motion, the signal, due to pulsation, becomes increasingly difficult to detect. © 2013 Optical Society of America
OCIS codes: (100.0100) Image processing; (170.0170) Medical optics and biotechnology; (230.0230) Optical devices; (290.0290) Scattering.
http://dx.doi.org/10.1364/OL.38.005334
The regular monitoring of vital body parameters is becom-ing increasbecom-ingly relevant, as population demographics in many countries lean toward aging. Recovery and rehabili-tation chances increase significantly with the early diagno-sis of disease. Noninvasive monitoring techniques have a huge advantage, since they cause no discomfort to the patient and avoid the risk of contamination and infection, besides other issues. Optical methods can contribute here significantly; already, many noninvasive techniques have been developed with them. One such portable noninvasive optical monitoring device that is widely used to monitor cardiovascular complications is the pulse oximeter. The pulse oximeter produces a photoplethysmogram (PPG) by measuring changes in light absorption in the presence of illumination. The device is commonly attached to the
patient’s finger, in a clinical environment. The major
diffi-culties faced by these measurements are low perfusion
and motion artifacts [1,2]. In spite of the fact that this
method has been in use for many years, the extraction of the signal in the presence of measurement errors caused by motion artifacts, are still at a developing stage. To deal with such artifacts, different research approaches address
the problem based on hardware [3], or software-based
sol-utions [4], to improve the signal quality; however, most of
the time, the precise source of artifacts is unknown. These approaches help to decrease the number of false alarms, but do not completely remove the influence of artifacts. In this Letter, we address the possibility of measuring a pulsatile flow in a noisy environment, using an approach based on speckle dynamics, which we have previously demonstrated in the measurement of pulsation, in flow,
in a scattering medium [5]. In this specific case we
mea-sure pulsation and heart rate, in the presence of motion between the illumination, in in vitro and in vivo samples, respectively. The main difference between speckle meas-urement and PPG is that, instead of measuring volume
changes, we measure the time-dependent velocity changes of the scattering particles, such as red blood cells (RBCs). Speckle is a random intensity pattern that is produced when monochromatic light is scattered from a rough sur-face, where inhomogeneity is not resolved. The addition of various scattered waves, with different phases and amplitudes, will define the overall intensity of the speckle images. By analyzing the speckle patterns, we can extract information about the medium, which can contain static or dynamic properties. In the case of blood flow measure-ments, a time-varying speckle is studied. The complexity of the situation arises from the presence of dynamic scatterers within several layers of static scatterers, with different composition and different scattering properties. Speckle techniques have demonstrated the capability
of monitoring retinal blood flow [6]. The possibility of
measuring hemodynamic parameters in the presence of relative motion between the optical components and
sample using speckles, is still an open question [7].
We initially did an in vitro study to investigate the in-fluence of artifacts arising due to motion on the signal. The schematic of the setup for in vitro and in vivo
measurements is shown in Fig.1. The experimental setup
is composed of three main parts: illumination, sample, and detection. For illumination, we used a vertical-cavity surface-emitting laser diode (VCSEL) with an emission wavelength of 850 nm and spectral bandwidth of 0.3 nm. The laser diode has a coherence length of 2.4 mm and an optical output power of 0.5 mW. The measurements have been done on a phantom that contains a flow cell with a top membrane made up of Delrin (polyoxymethylene, POM), which has scattering properties similar to skin
[8]. The flow cell has a rectangular channel with a length
of 20 mm and a depth of 1 mm, to represent a homog-enous thin layer of flow. We used a roller pump (Minipuls 3) with five rollers to generate a controlled frequency
5334 OPTICS LETTERS / Vol. 38, No. 24 / December 15, 2013
pulsatile flow in our flow cell. Milk was used as a scatter-ing fluid to mimic the blood flow, as the fat particles in
milk scatter light similarly to the RBCs in blood [9,10].
For our detection system, we used a high speed camera
(Photron Fastcam SA3) with a pixel size of 17 × 17 μm.
For magnification, we coupled the camera to a
stereo-microscope with overall magnification of 6.4×. In the
experiments, we simulated a scenario of measuring the pulse rate in a phantom case, where the artifacts are generated by systematic and random motions. We have used these two main categories to compare the system-atic motion with either rhythmic hand motion, which oc-curs, for instance, in sport activities, or random motion, which resembles the complex hand motions of patients in a clinical setting. To generate the motion, we used a mini-shaker, driven using a Labview-based program, and passed through an amplifier. The laser diode is attached to the shaker, which moves with a defined linear or random motion. The movement of the beam spot affects its position on the sample being illuminated and, thus, the separation distance between the laser beam and the detector. This continuous movement creates the main motion-induced artifacts by changing the optical path through the sample and changing the depth at which the sample is monitored.
One approach for analyzing the dynamic fluctuation of speckled images by moving scatterers, is based on the laser speckle contrast method, first introduced by Briers
and Webster [11]. In this method, the speckle images
were recorded using a camera with an exposure time
of, typically, 1–20 ms. In each acquisition, the
time-integrated speckle images were recorded with a blurry effect because of the longer integration time compared with the speckle decorrelation time induced by the
motion of the scatterers [12]. This blurring of the speckle
data is analyzed to study the motion. The images, or spe-cific parts of them, are quantified by the contrast term K, defined as the ratio of standard deviation σ over
the average intensity fluctuations hIi:
K hIiσ : (1)
The calculated contrast has a lower value in the case of a sample that has moving scatterers, due to the fact that the standard deviation of the intensity decreases while the average intensity remains constant. The main schemes of computing the speckle images from the raw data are considered as temporal, spatial, or a combination of these two techniques. A more detailed description can be found
in the literature [13]. In the present work, we have
calcu-lated the speckle contrast for each image with a spatial
window size of 7 × 7 camera pixels. The calculated
con-trast for the series of images was then Fourier-analyzed to obtain the frequency spectrum of the speckle contrast fluctuations arising due to the different processes, for the entire time of each measurement.
To simulate heart rate in vitro, a roller pump gener-ated a pulsation rate of 1 and 1.25 Hz, with amplitudes per stroke of 6.7 and 7.8 ml, respectively. The base flow
rate for 1 and 1.25 Hz was 40 ml∕ min and 47 ml∕ min,
respectively. The motion-induced artifacts were gener-ated using the shaker to move the illuminating laser at three different frequencies (0.7, 1.4, and 2.8 Hz) with two different amplitudes (0.5 and 2 mm). Each measure-ment was recorded for 45 s at 50 frames per second. The exposure time for each frame was 20 ms. The images
were recorded using the full camera frame of1024 px ×
1024 px.
The experimentally measured contrasts for the milk
pulsation at 1 and 1.25 Hz are shown in Fig.2. The left
panel displays the contrast calculated for the recorded images in time with the two different pulsation frequen-cies of milk flowing in the sample cell. The panel on the right is the spectral composition of the speckle contrast variation, arising due to the pulsation of the fluid in the sample, and the motion artifacts generated by the moving illuminating source and extracted from the images
Fig. 1. Experimental setup (a) in vitro and (b) in vivo. The motion artifacts are generated by the motion of the laser beam, which creates a different penetration depth, illumination spot, and distance to the detector. The speckle contrast has been calculated over the whole illuminated area.
Fig. 2. Speckle contrast variation over time on the left and spectral analysis of the contrast curve on the right. Milk pulsa-tion in the flow cell with frequencies of 1 Hz (upper plot) and 1.25 Hz (lower plot) for two displacements of the illuminating laser: 0.5 mm (upper continuous line) and 2 mm (lower dashed line) at the frequencies of (a) 0.7 Hz, (b) 1.4 Hz, and (c) 2.8 Hz. December 15, 2013 / Vol. 38, No. 24 / OPTICS LETTERS 5335
obtained by the camera. The measured signals are shown for the best and worst signal visibilities, which is the case for the 0.5 and 2 mm displacement amplitudes of the laser by the shaker, respectively. For each measurement, the signal has been low-pass filtered at 6 Hz and plotted for the same range of frequencies. As can be seen in the figure, the visibility of pulsation signal, compared with the motion signal on the laser, has decreased. The main reason for a larger drop in the case of 1.25 Hz pulsation is the flow rate. In the current setup, a higher pulsation rate also causes a higher flow rate. The measured signal qual-ity drops due to the speckle patterns being more blurry, which results in a lower contrast value. The main aim of these measurements is to distinguish and reliably detect the pulsatile signal, in spite of the noise elements around it. We must state that, in the current experimental setup with speckle imaging, we cannot distinguish between two opposite directions of laser motion. This leads to the double frequency signal of the laser motion (1.4, 2.8, and 5.6 Hz) being more prominent in our spectral decom-position graphs. In the in vitro case, we have the specific advantage of knowing the frequency of the signal we would like to detect, since it is the frequency of our pump. In this case, therefore, we can separate it from the other frequencies in our setup, e.g., the modulation frequency of the shaker that moves the laser. We have observed that, neglecting the spectral signal arising from the known frequency of the shaker, and calculating the signal-to-noise ratio for the signal arising from the pump, the average signal-to-noise ratio of 14 dB makes the measurement of the pulsation signal still feasible. A sur-prising point was that the signal was still distinguishable for the case of pulsation at 1.25 Hz and a laser oscillation frequency of 0.7 Hz, which has a larger amplitude at the double frequency of 1.4 Hz. In this case, the frequencies of the signals are even closer, or overlap, and it is prob-ably not possible to detect the pulsation frequency clearly. From the figure, we observe that, even for the case of maximum displacement at 2 mm and a shaker frequency of 2.8 Hz, we were still able to see the signal; however, we emphasize that the detection possibility of the signal deteriorates with increasing amplitude and/or the oscillation frequency of the shaker that moves the laser, because speckle contrast modulation decreases.
To quantify this, Table1 shows the ratios between the
amplitude of the pulsation signal from the spectral de-composition and the amplitude of the double frequency signal of the laser motion, seen in the same spectral decomposition. To extend our study to a more general case, we decided to move the shaker and, hence, the laser, randomly using a band limited white noise signal
with frequencies in the range of 0.1–10 Hz. The choice
of this frequency range was made based on literature that states the PPG pulsatile cardiac signal is in the range of
0.5–4 Hz, with the low frequency range of respiration
signal of 0.2–0.4 Hz. [14,15]. The results of this study are
shown in Fig.3, where we see that the pulsation signal is
clearly visible for the lowest amplitude of laser motion of the laser, which is 0.5 mm. For the white noise measure-ments, the signal was observable only up to the laser motion amplitude of 1 mm; above this amplitude, it is
dif-ficult to detect anything, as can be seen in Fig.3for the
case of a laser motion amplitude of 2 mm. In the case of random motion, therefore, the amplitude of the motion with respect to the illuminating source is the deciding factor for signal detection. We then implemented the measurement in vivo by placing the finger of a volunteer in the place of the flow cell. The volunteer also wore a commercial pulse oximeter on the thumb so that our
Fig. 3. Speckle contrast variation over time on the left and spectral analysis of the contrast curve on the right. Milk pulsa-tion in the flow cell with frequencies of 1 Hz (upper plot) and 1.25 Hz (lower plot) for random displacement of the illuminat-ing laser at the amplitudes: 0.5 mm (upper continuous line) and 2 mm (lower dashed line).
Table 1. Ratio of Pulsation Frequency Amplitude to Double Frequency of Laser Motion Signal in the
Spectral Decomposition Flow Pulse (Hz) Frequency Motion 1.4 Hz 2.8 Hz 5.6 Hz Amplitude (mm) 1 0.82 0.34 0.19 0.5 1 0.13 0.14 0.17 2 1.25 1.03 0.27 0.11 0.5 1.25 0.074 0.06 0.06 2
Fig. 4. Speckle contrast variation over time on the left and spectral analysis of the contrast curve on the right. Measure-ment with human finger for the illuminating laser displaceMeasure-ments of: 0.5 mm (upper continuous line) and 0.8 mm (lower dashed line) at the frequencies (a) 1 Hz, (b) 1.4 Hz, and (c) 2.8 Hz. 5336 OPTICS LETTERS / Vol. 38, No. 24 / December 15, 2013
measurements could be verified. The analog signal from the pulse oximeter was synchronized with the camera frames recorded for the measurement. To keep the heart rate values similar, the measurements for the two ampli-tudes of the shaker, which moves the illuminating laser at 0.5 and 0.8 mm, were performed sequentially in time. The
results of the measurements can be seen in Fig.4for the
three different motion frequencies of 1, 1.4, and 2.8 Hz of the illuminating laser, at the two different amplitudes. The results confirm our expectations from the in vitro measurements that the detectability of the signal drops for higher motion amplitudes and frequencies. We see this even more in the case of random motion of the
shaker moving the illuminating laser in Fig.5. The heart
rates indicated in Figs.4and5were those measured
inde-pendently by the commercial pulse oximeter.
We have performed an in vitro and an in vivo study, based on laser speckle contrast analysis, to detect fluid pulsation in the presence of artifacts caused by relative motion between the sample and the illumination source. We observe that the pulsation signal is clearly detectable for a range of motion amplitudes and oscillation frequen-cies. However, at higher amplitudes and oscillation frequencies of motion, the signal, due to pulsation,
becomes increasingly difficult to detect. The thresholds of detectability remain an interesting question for further research.
This work was funded by AgentschapNL under the
project IOP Photonic Devices, IPD083359 HIP
—Hemo-dynamics by Interferometric Photonics. The authors would also like to express gratitude to R. C. Horsten, T. Zuidwijk, and R. Pols of TUDelft, and L. G. Paroni of LifeTec Group, for their help and support with the experimental setup.
References
1. J. Allen, Physiol. Meas. 28, R1 (2007).
2. P. A. Kyriacou, S. Powell, R. M. Langford, and D. P. Jones, Physiol. Meas. 23, 533 (2002).
3. M. R. Ram, K. V. Madhav, E. H. Krishna, N. R. Komalla, and K. A. Reddy, IEEE Trans. Instrum. Meas. 61, 1445 (2012). 4. R. W. C. G. R. Wijshoff, M. Mischi, J. Veen, A. M. van der Lee,
and R. M. Aarts, J. Biomed. Opt. 17, 117007 (2012). 5. M. Nemati, L. Wei, M. G. Zeitouny, M. Stijnen, S. van Tuijl, N.
Bhattacharya, and H. P. Urbach, Proc. SPIE 8413, 84131D (2012).
6. H. Cheng and T. Q. Duong, Opt. Lett. 32, 2188 (2007). 7. D. Briers, D. D. Duncan, E. Hirst, S. J. Kirkpatrick, M.
Larsson, W. Steenbergen, T. Stromberg, and O. B. Thompson, J. Biomed. Opt. 18, 66018 (2013).
8. M. Vegfors and L. Lindberg, Med. Biol. Eng. Comput. 31, 135 (1993).
9. A. Gilman, Annu. Rev. Biochem. 56, 615 (1987).
10. M. Michalski, V. Briard, and F. Michel, LAIT 81, 787 (2001). 11. J. Briers and S. Webster, Opt. Commun. 116, 36 (1995). 12. M. Draijer, E. Hondebrink, T. van Leeuwen, and W.
Steenbergen, Lasers Med. Sci. 24, 639 (2009).
13. J. Qiu, P. Li, W. Luo, J. Wang, H. Zhang, and Q. Luo, J. Biomed. Opt. 15, 016003 (2010).
14. H. Lee, J. Lee, W.-G. Jung, and G. Lee, Int. J. Control Autom. 5, 701 (2007).
15. K. V. Madhav, M. R. Ram, E. H. Krishna, N. R. Komalla, and K. A. Reddy, IEEE Trans. Instrum. Meas. 62, 1094 (2013). Fig. 5. Speckle contrast variation over time on the left and
spectral analysis of the contrast curve on the right. Measure-ment with human finger for two random displaceMeasure-ments of the illuminating laser at the amplitudes: 0.2 mm (upper continuous line) and 0.8 mm (lower dashed line).
