A flexible organic reflectance oximeter array
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Edited by Cunjiang Yu, University of Houston, Houston, TX, and accepted by Editorial Board Member John A. Rogers October 12, 2018 (received for review July 30, 2018)

Significance
The optical method to determine oxygen saturation in blood is limited to only tissues that can be transilluminated. The status quo provides a single-point measurement and lacks 2D oxygenation mapping capability. We use organic printed optoelectronics in a flexible array configuration that senses reflected light from tissue. Our reflectance oximeter is used beyond conventional sensing locations and accurately measures oxygen saturation on the forehead. In a full system implementation, coupled with a mathematical model, we create 2D oxygenation maps of adult forearms under pressure-cuff–induced ischemia. Our skin-like flexible sensor system has the potential to transform oxygenation monitoring of tissues, wounds, skin grafts, and transplanted organs.
Abstract
Transmission-mode pulse oximetry, the optical method for determining oxygen saturation in blood, is limited to only tissues that can be transilluminated, such as the earlobes and the fingers. The existing sensor configuration provides only single-point measurements, lacking 2D oxygenation mapping capability. Here, we demonstrate a flexible and printed sensor array composed of organic light-emitting diodes and organic photodiodes, which senses reflected light from tissue to determine the oxygen saturation. We use the reflectance oximeter array beyond the conventional sensing locations. The sensor is implemented to measure oxygen saturation on the forehead with 1.1% mean error and to create 2D oxygenation maps of adult forearms under pressure-cuff–induced ischemia. In addition, we present mathematical models to determine oxygenation in the presence and absence of a pulsatile arterial blood signal. The mechanical flexibility, 2D oxygenation mapping capability, and the ability to place the sensor in various locations make the reflectance oximeter array promising for medical sensing applications such as monitoring of real-time chronic medical conditions as well as postsurgery recovery management of tissues, organs, and wounds.
Hemoglobin, a protein molecule in the blood, transports oxygen from the lungs to the body’s tissues. Oximeters determine oxygen saturation (
Recent progress in flexible and stretchable sensors has made them extremely promising for medical sensing and diagnostics because they enhance the signal-to-noise ratio (SNR) by establishing a conformal sensor–skin interface (3⇓⇓⇓⇓⇓⇓⇓–11). Consequently, novel flexible sensors using organic and inorganic optoelectronics for transmission and reflection-mode pulse oximetry show a higher SNR due to a reduction in ambient noise (12⇓⇓⇓⇓⇓–18). Lochner et al. (17) demonstrated
Overview and operation of the printed reflectance oximeter array (ROA). (A) Schematic of an application scenario of the ROA: 2D oxygenation mapping of a skin graft on the forearm. After surgery, the ROA is placed on the skin graft to map oxygenation of the reconstructed skin. (B) ROA sensor configuration. Red and NIR OLED arrays composed of
Here, we report a reflectance oximeter array (ROA), a flexible and printed electronic system realized by printing and integrating arrays of organic optoelectronics with conventional silicon integrated circuits for blood and tissue oximetry. The ROA is composed of four red and four NIR printed organic light-emitting diodes (OLEDs) and eight organic photodiodes (OPDs) (Fig. 1 B and C). We use red (612 nm) and NIR (725 nm) OLEDs, where the molar absorptivities of
Results
Analytical Models for Reflectance Oximetry.
Oximeters use the property that the molar extinction coefficients of
The operation of noninvasive reflectance oximetry can be grouped into two modes: (i) reflection-mode pulse oximetry (
In the case of low perfusion or in the absence of a pulsatile arterial blood signal, pulse oximetry in both transmission and reflection modes cannot be performed. In these scenarios, Eq. 1 can be rewritten to measure the time-varying light intensity attenuation,
Reflectance Oximeter Design and Placement on the Body.
Emitter–detector spacing (d) is an important design parameter for reflectance oximetry. To find the optimal d, we use a reflection-mode sensor board and measured the effect of d on PPG ac and dc signals at the eight locations on the body as depicted in SI Appendix, Fig. S4 A and B. The schematic of the sensor, containing three rings of four PDs spaced at 0.5 cm, 0.8 cm, and 1.1 cm away from the red and NIR LEDs at the center, is shown in SI Appendix, Fig. S4C. Both ac and dc signal magnitude drops exponentially with increasing d. SI Appendix, Fig. S4 D and E shows ac and dc signals for
An approach similar to obtaining the optimal d is used to find the optimal sensing location for
OLED and OPD Array Fabrication and Characterization.
We printed the organic optoelectronics of the ROA on separate substrates and then assembled them to form the sensor array. With 0.7 × 0.7 cm active area for both OLEDs and OPDs and 0.5 cm spacing between the OLEDs and OPDs, the dimension of the complete ROA is 4.3 cm in both length and width. The OLED arrays are fabricated on top of polyethylene naphthalate (PEN) substrates with patterned indium tin oxide (ITO) for contacts. A surface energy patterning (SEP) step is then performed that creates hydrophilic regions where poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) is blade coated, which is discussed in detail by Han et al. (15, 25) (Fig. 2A, Left). The interlayer and the emission layer are deposited using subsequent blade-coating steps (Fig. 2B, Left). Then, the dielectric and the silver traces are printed using a screen printer (Fig. 2C, Left). The purpose of printing the dielectric is to prevent shorts between the underlying ITO strips and the silver traces. Finally, thermal evaporation is used to deposit calcium/aluminum to finish the fabrication of OLED arrays (Fig. 2D, Left). Each OLED pixel is encapsulated with UV curable epoxy and a plastic film. The OLED device stack is shown in Fig. 2G. The same process steps apply for both red and NIR OLEDs; only the active materials are different.
Fabrication flow of the OLED and OPD arrays for the ROA. (A–D) The OLED and OPD array fabrication steps are shown side by side. For the OLED array, only one color consisting of 4 pixels is shown for simplicity—the same fabrication steps are used for red and NIR OLEDs. For the OPD array, the complete array consists of 8 pixels. (A) PEDOT:PSS is blade coated using surface energy patterning (SEP) on ITO-patterned PEN for the OLEDs and on a planarized PEN for the OPDs. (B) Active layers are blade coated—brick color indicates OLED active material and pink color indicates OPD active material. (C) Silver traces are screen printed on both OLEDs and OPDs. The OLEDs require an additional dielectric layer (blue) to prevent shorting of the anode to the cathode. (D) Aluminum cathode is evaporated, which defines the active area of the pixel. D, Insets show a zoomed-in view of the individual pixels. (E and F) The deposition techniques: Blade coating and screen printing are schematically shown and the color bars of the fabrication steps in A–C, Left indicate the deposition technique used for that respective layer: sky blue for blade coating and red for screen printing. (G and H) Device structure of the OLED and the OPD, respectively.
The OPD array is fabricated on a planarized PEN substrate. A PEDOT:PSS anode is blade coated using the SEP technique as shown in Fig. 2A, Right. The SEP process for OPDs is previously described by Pierre et al. (26, 27). A patterned anode is necessary because, without patterning, a large parasitic capacitance is formed between the PEDOT:PSS layer and the body, which obscures the signal in noise. The active layer is then blade coated (Fig. 2B, Right). Next, silver traces are screen printed to connect the anodes and cathodes of each pixel to external circuitry as shown in Fig. 2C, Right. Finally, an aluminum cathode is evaporated to complete the device stack, which is shown in Fig. 2H.
The OPD and OLED arrays are shown in Fig. 3 A and B, respectively. The OPD array comprises eight OPD pixels, where each OPD row contains two OPD pixels. Brown markers from darker to lighter shades are used to label rows 1–4 of the OPD array. The same markers are used to present the performance characteristics of the OPD pixels. As for the 2 × 2 red and NIR OLED arrays, rows 1 and 3 contain the four red OLED pixels, and rows 2 and 4 contain the four NIR OLED pixels. The ROA is formed by stacking the OLED and OPD arrays. The arrays are assembled such that emitter–detector spacing of 0.5 cm is maintained.
Photographs and performance parameters of the OPD and OLED arrays. (A) OPD array composed of 8 pixels with 2 pixels in each row. The rows are marked using different shades of brown markers, which represent the legends of performance data presented in C and D. (B) Red and NIR OLED arrays: 2 × 2 red OLED array in rows 1 and 3 and 2 × 2 NIR OLED array in rows 2 and 4. The rows are marked using red and gray markers, which represent the legends of performance data presented in F and G. (C) Current density vs. voltage bias (
The performance parameters of the OPD array are shown in Fig. 3 C–E. The shade of brown lines indicates the row position of the pixels in the array as shown in Fig. 3A. An average EQE of 30% is observed across the absorption spectrum (Fig. 3D) with dark currents of a few nanoamperes per square centimeter (Fig. 3C). The cutoff frequency is measured at over 5 kHz for OPDs as shown in Fig. 3E. Since the operation frequency of the pulse oximeters is generally less than 1 kHz, this bandwidth is sufficient for oximetry. The linear dynamic response of the OPDs is shown in SI Appendix, Fig. S7.
The OLEDs show turn-on voltages at around 3 V as designated in the J-V characteristics in Fig. 3F. The OLEDs are operated at 10 mA⋅cm−2 for oximetry, where the red OLEDs provide 0.9 mW of flux, while the NIR OLEDs provide 0.2 mW of flux. The EQE values at operating conditions are ∼8–10% for red OLEDs and ∼2–3% for NIR OLEDs (Fig. 3G). The OLEDs demonstrate a change in performance parameters, depending on the row position due to the decrease in active layer thickness in the blade-coating direction; this variability can be mitigated by continuously feeding ink in front of the blade coater (15, 28). The variability in the OLED and OPD performance can be accommodated by taking a calibration measurement before using the array for oximetry. The emission spectrum of the OLEDs is shown in Fig. 3H, where the red OLED has a peak emission at 612 nm and the NIR OLED has a peak emission at 725 nm.
System Setup and Single-Pixel Reflection-Mode Pulse Oximetry.
The full system implementation requires addressing individual pixels of the oximeter. Therefore, the hardware and software for the ROA are designed to support both single-pixel and array measurements (Fig. 4A). The printed ROA is interfaced with the control electronics using flexible flat cable (FFC) connectors. Each pixel of the ROA is composed of one red and one NIR OLED and two OPDs. Signals from the red and NIR channels are read out sequentially using the two OPDs, and the average of the OPDs is used for signal processing. Using this format, the
System design for reflectance oximetry and single-pixel reflection-mode pulse oximetry (
To test the reflectance oximeter in the single-pixel mode, we used a setup where oxygenation of a volunteer can be changed by varying the oxygen concentration of the inhaled air (Fig. 4B). An altitude simulator is used to change the oxygen concentration of the air the volunteer breathes in via a facemask. Depending on the oxygen concentration of the air, the volunteer’s oxygenation changes. This change in oxygenation is then picked up by a commercial finger probe sensor and using the reflection-mode sensor on the forehead. Calculated oxygen saturation using the commercial probe (
For the transmission-mode probe, oxygen saturation (
The pulse arrival times at the forehead and the fingers are different; the delay is on the order of 50 ms (29), which may slightly affect the pulse oxygenation calculations. Therefore, for a more direct comparison between the transmission- and reflection-mode pulse oximetry, we collected pulse oximetry data in both transmission and reflection mode from the fingers of the same hand as shown in SI Appendix, Fig. S10. In this experiment, the printed reflectance probe is placed under one finger and the commercial transmission-mode finger probe is worn on another finger. The commercial and reflectance finger probes provide almost identical
To investigate the temperature effects of the reflectance sensor, we operated the OLEDs of the device at different drive conditions and recorded the corresponding temperatures of the sensor on a volunteer’s forearm (SI Appendix, Fig. S11). We observed a negligible change in the temperature—the sensor temperature remained within
In Vivo 2D Oxygen Saturation Monitoring.
The pulse oximetry model is applicable when there is a pulsatile arterial blood signal. In the absence of a pulsatile arterial blood signal, we use the modified model (Eq. 5 and SI Appendix) to monitor local changes in tissue oxygenation of a volunteer’s arm under normal and ischemic conditions. By restricting blood supply to the arm with a pressure cuff, we induce temporary ischemia to the arm by inflating the pressure cuff to 50 mmHg over the systolic pressure. We use the ROA to monitor the change in oxygen saturation (
In vivo 2D oxygen saturation monitoring with the ROA. (A) The ROA is placed on a volunteer’s forearm to monitor the change in oxygen saturation (
The
In the 2D oxygenation mapping experiments, we monitored tissue oxygenation of the forearm with and without pressure-cuff–induced ischemia. When blood supply to the arm is occluded using the pressure cuff, oxygenated blood cannot circulate to the forearm, which results in a drop in tissue oxygenation. We recorded this change in oxygenation using the ROA. With the status quo, i.e., transmission-mode pulse oximetry, this change in oxygenation cannot be observed, because when blood circulation is cut off, the pulsatile arterial blood signal disappears, which is essential to calculate the pulse oxygenation using transmission-mode pulse oximetry. The ROA can measure the change in
Discussion
Existing techniques for measuring oxygen concentration in blood heavily rely on noninvasive transmission-mode pulse oximetry (
Flexible organic and inorganic optoelectronics enhance the SNR of oximetry by reducing the ambient noise signal. Our demonstration of the ROA in this paper increases the sensing locations of oximetry and enables measuring oxygenation in the absence of pulsatile arterial blood signal. Additionally, the use of printing techniques such as blade coating and screen printing to fabricate the sensor on flexible plastic substrates makes the sensor both comfortable to wear and efficient at extracting high-quality biosignal. This work presented an unprecedented level of control and integration in printed electronic systems. We hope that our demonstration of the flexible reflection oximeter array with 2D spatial mapping capability will encourage novel sensing schemes and aid in medical sensing applications such as 2D mapping of oxygenation in tissues, skin grafts, wounds, and transplanted organs.
Materials and Methods
Fabrication and Characterization of the OLED Arrays.
The OLED arrays were printed on 125-μm thick ITO patterned PEN substrates. Two 1-cm wide ITO strips were placed 1.1 cm apart from each other, for creating the two columns of the OLEDs. The substrate was placed on a hotplate at 80 °C for 3 h under vacuum. The sample was then taken out in the air and placed on a hotplate at 180 °C for 1 h. Then the substrate was treated with plasma for 10 s and the entire surface was treated with (heptadecafluoro1,1,2,2-tetrahydrodecyl) (Gelest SIH5841.0) for 20 min under light vacuum (0.1–1 Torr) to make the surface hydrophobic. The treated substrate was kept in a nitrogen-filled chamber overnight. The substrate was patterned, exposing the active area of the OLEDs by using plasma to selectively etch off the hydrophobic layer. Then PEDOT:PSS (Clevios AI4083; Heraeus), the interlayer, and the semiconducting polymers (Cambridge Display Technologies Ltd.) were subsequently blade coated to form the emissive layer of the OLEDs. Concentrations of 6 mg⋅m
Fabrication and Characterization of the OPD Array.
The OPD array was printed on top of planarized PEN substrates (TeiJin PQA1), using blade-coating techniques. The substrate was first plasma treated in Tegal Plasmod at 50 W for 10 s. The substrate was then placed in a vacuum with 40 μL of heptadecaflouropolymer for 20 min to render the substrate hydrophobic. A stainless steel stencil with cutouts of the desired PEDOT:PSS area was placed on top of the substrate and then treated for 1.2 min with oxygen plasma in a Diener Nano plasma system. A total of 30 μL of PEDOT:PSS was dispensed uniformly in front of the blade. Then ink was blade coated with a blade height of 100 μm and speed of 1 cm
Control Electronics for the ROA.
The control electronics were designed to support reflectance oximetry in the single-pixel and the array mode. Additionally, the system was designed to measure oxygenation with or without the pulsatile arterial blood signal. We used a Texas Instruments AFE (AFE4490) to sequentially drive the OLEDs and read out the OPD signal. The OLED and OPD arrays were interfaced with the control electronics using FFC connectors. The pixels in the array were selected using analog switches (Analog Devices ADG1608). The AFE was controlled with an Arduino Due microcontroller. Software control of the AFE allowed flexibility in choosing OLED driving parameters and allowed adjustments to the variable OPD gain circuitry. The OLEDs were driven at 10 mA⋅cm−2 with a 9-V battery in push–pull mode. A two-stage OPD gain circuitry was used to amplify the photocurrent. A 100-kΩ feedback resistor was used in the first stage, and unity gain was used in the second stage. Finally, the data were collected using a USB interface and were processed using custom in-house software.
Reflection-Mode Pulse Oximetry (S p O 2 r ) Data Collection and Processing.
For monitoring oxygenation in the presence of a pulsatile signal, the oxygenation of the volunteer was changed by using an altitude simulator (Everest Summit II Altitude Generator). Altitudes of 5,000 feet and 8,000 feet correspond to oxygen concentrations of 17.5% and 15%, respectively. The change in oxygen concentration changed oxygen saturation of the volunteer, which was monitored using a transmission-mode oximeter probe on the finger (
Reflectance Oximetry Data Collection and Processing.
For measuring oxygenation in the absence of a pulsatile arterial blood signal, forearm ischemia was induced in human volunteers, using a pressure cuff. After taking a baseline measurement, the pressure cuff was used to induce ischemia, using a pressure of 50 mmHg over the systolic pressure. The cuff was released after 2 min of ischemia. Data were recorded for 5 min to observe the change in oxygenation using the ROA. A raster scan from Px1 to Px9 was used to collect data from the tissue. A modified model as described in Eq. 5 was used to monitor oxygenation of tissue. Data from the 9 pixels were plotted using nearest-neighbor interpolation to create the 2D spatial maps of red and NIR channels and the change in oxygenation.
All reflectance oximetry experiments performed on human subjects were carried out with informed consent under the approval of the University of California, Berkeley Institutional Review Board, protocol ID 2014-03-6081.
Acknowledgments
We thank Cambridge Display Technology (CDT) for supplying OLED and OPD materials and Prof. Michel Maharbiz, Ramune Nagisetty, and Dr. Juan Pablo Duarte Sepulveda for helpful technical discussions. This work was supported in part by CDT (02672530) and by Intel Corporation via Semiconductor Research Corporation Grant 2014-IN-2571.
Footnotes
- ↵1To whom correspondence may be addressed. Email: yasser.khan{at}berkeley.edu or acarias{at}eecs.berkeley.edu.
Author contributions: Y.K., D.H., A.P., J.T., X.W., C.M.L., G.B., N.Y.-G., C.N., R.W., and A.C.A. designed research; Y.K., D.H., A.P., J.T., X.W., C.M.L., G.B., and N.Y.-G. performed research; Y.K., C.N., R.W., and A.C.A. contributed new reagents/analytic tools; Y.K., D.H., A.P., J.T., C.N., R.W., and A.C.A. analyzed data; and Y.K., D.H., A.P., J.T., and A.C.A. wrote the paper.
Conflict of interest statement: A provisional patent application has been filed based on the technology described in this work.
This article is a PNAS Direct Submission. C.Y. is a guest editor invited by the Editorial Board.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1813053115/-/DCSupplemental.
- Copyright © 2018 the Author(s). Published by PNAS.
This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
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