Photoelectronic technology has found extensive application due to its non-invasiveness, compact structure, and low cost. However, in semi-transparent media, the detection system based on reflection structure indiscriminately receives reflection light from different depths, resulting in the masking of target signals and a decrease in signal quality. To address this issue, selecting reflected light at different depths through polarization gates is an effective way. In this study, we analyzed a polarization gate-semi-infinite medium scattering model and investigated the impact of various factors on the reflected light filtering capability of the polarization gate, through Monte Carlo simulations and polystyrene microsphere scattering experiments. We found that the polarization gate can achieve a more effective control effect on the high polarization area on the reflective surface. Furthermore, the signal-to-noise ratio of the photoplethysmography sensor with an orthogonally polarized gate was improved from 0.72 to 2.36 dB. In other words, the polarization gate offers new insights into signal optimization through a structural design, which facilitates the development of wearable, low-power, and robust physiological signal measurement systems in the future.

Photoelectronic technology has widely been used in the field of biomedical detection due to its non-invasive ability to acquire extensive information acquisition characteristics,1–6 particularly in areas such as electronic skin and wearable devices.7–11 Biological tissues can modulate light information, including polarization, phase, and intensity, which leads to variations in the optical information carried by light propagating through them. Consequently, the changes in the light signal captured by the photoelectronic detection system reflect relevant biological information.6,8,12,13 Common photoelectronic detection system structures include transmissive14,15 and reflective1 configurations. Due to the geometric arrangement in which both the input and the acquisition ends are located on the same side of the medium, the reflective photoelectronic sensing system has fewer space constraints and, thus, has advantages in biomedical detection.16,17 Nonetheless, because of the aforementioned geometric arrangement and the semi-transparent and complex scattering nature of biological tissues,18 the signal acquisition end indiscriminately receives photons reflected from the superficial surface and those reflected from deeper layers within the tissue.19 The interference of multiple reflected photons from different depths reduces the signal quality of the detection system, which presents significant limitations on high-precision physiological measurements.20 Hence, extracting effective signals from the superimposed light remains the key challenge in constructing high-precision photoelectronic detection systems under complex scattering environments.

Given the continuous variations in optical information during propagation, previous research has utilized optical gating techniques, such as time gating,21–23 coherent gating, and polarization gating, for precise selection of light. These techniques help improve the signal-to-noise ratio (SNR) and achieve high-precision detection in complex scattering environments. Time gating and coherent gating are two methods used for the high-precision selection of photons, with the former based on flight time and the latter based on optical coherence. However, the high costs, large equipment sizes, and complex optical setups of these methods hinder the integrated implementation in wearable applications.24–30 In biological tissues, the polarization state of light undergoes continuous changes during its propagation.31,32 Polarized lights from different depths undergo different optical paths, leading to distinguished polarization states. Consequently, photon filtration can be achieved by incorporating simple polarization elements into the optical path.33,34 This characteristic renders polarization gates highly applicable in compact and resource-constrained optical systems. Previous studies have reported the differential modulation of reflected light from different paths through polarization gates, which endows the photoelectronic detection system with a signal filtering capability.1,35–41 The modulation of the polarization of light by scattering media is affected by factors such as incident light, scattering environment, and propagation path. These factors further affect the filtration effectiveness of polarization gating. To optimize the efficiency of polarization gates in signal filtering and expand their application in various scenarios, a crucial aspect lies in the accurate understanding of the impact of optical system structures and scattering model parameters on the differential modulation effects of polarization gates and the underlying physical mechanisms. Such an understanding will improve the system design to accommodate diverse application environments and enhance the interference suppression capabilities of polarization gates, thereby advancing their proficiency in signal optimization.

In this work, we investigate the impact of optical system structure and scattering model parameters on the improvement in the polarization gate signal from the perspective of changes in optical polarization information. We analyze a polarization gate-semi-infinite scattering model for solving the masking of target signals in the reflective photodetection system and study the effects of factors such as detection position, light source, and scattering environment on the polarization gate’s modulation performance through Monte Carlo simulations and scattering experiments. An “hourglass-shaped” high-polarization region is observed around the incident point, indicating that the polarization gate can achieve better differentiated modulation in the high-polarization region. This is attributed to the larger polarization differences among the reflected light at different depths within this region. Our research reveals the influence of incident light polarization state, wavelength, mass concentration, particle diameter, and scattering environment on the polarization gate’s modulation effect and the underlying physical mechanisms. Furthermore, we design a polarization-gated photoplethysmography (PG-PPG) device to demonstrate the improvement in the signal of reflective photonic devices achieved through orthogonal polarization gate control. The polarization gate offers a simple and resource-efficient approach, and this study further advances its application in physiological signal measurements, contributing to the development of wearable, low-power, and robust signal measurement systems.

To simulate the propagation of light in highly scattering media and the modulation effect of a polarization gate on light, this study designed a semi-infinite scattering medium model based on the range of optical parameters of biological tissues.18 The Mie–Monte Carlo ray-tracing algorithm was implemented using the MATLAB software, following Wang’s VMC algorithm,42 to simulate light propagation in Mie scattering media. To simplify the light–tissue interaction, we assumed that light scattered in a homogeneous scattering medium, with symmetric spherical particles as scattering agents, and the light rays were considered non-coherent. The scattering angle distribution and Mueller matrix calculations were based on the Mie theory.

An optical transformation matrix Rδ was employed to mimic the modulation of light by a polarizer; δ is the angle between the polarization axis of the polarizer and the polarization direction of the incident light. After multiple scattering of light in the model, it returns to the reflecting surface. We multiply the Stokes vector of light [I Q U V] left by Rδ. To obtain stable results, each simulation involved tracking over 20 × 106 light rays,
Rδ=1cos2δsin2δ0cos2δcos22δsin2δcos2δ0sin2δsin2δcos2δsin22δ00000.
(1)
The simulation follows the Stokes–Muller form, where the polarization state of light is represented by a 4 × 1 Stokes vector (S = [I Q U V]T) description. We calculate the average values of I, Q, and U for photons in the target area. Then, we substitute the average values of I, Q, and U into the following formula for calculating the degree of polarization (DOP):
DOP=Q2+U2I.
(2)
We employed an experimental setup to measure the Stokes vector of the laterally emitted light. This setup comprised a semiconductor laser (Changchun New Industries Optoelectronics Tech. Co., Ltd., MDL-III-633L, 633 nm, 30 mW), an imaging system (Basler acA4112-30uc USB 3.0, 4096 × 3000 pixels), two polarizers, and a scatter sample. The sample is water suspensions of polystyrene spheres packed in a 2 mm optical path colorimetric dish. The light emitted by the laser passed through the polarizers and aperture, resulting in a spot-shaped linearly polarized beam, which was incident from the top edge of the sample. The light scattered from the side of the sample was collected using a camera after passing through an analyzer. We rotated the analyzer to 0°, 45°, and 90° while recording the corresponding pixel intensities as P1(x, y), P2(x, y), and P3(x, y). x and y represent the pixel positions. Subsequently, these data were substituted into the following formula to calculate the Stokes parameters:
I(x,y)=P1(x,y)+P3(x,y),Qx,y=P1x,yP3x,y,U(x,y)=2P2(x,y)I(x,y).
(3)

The high-scattering medium sample used in the experiment was prepared by dispersing monodisperse polystyrene spheres (refractive index nsph = 1.59) in deionized water (refractive index nmed = 1.33) to form a suspension. According to the experimental setup, spheres with diameters of 1, 1.5, and 2 µm (Fig. S1) were prepared at different concentrations, as indicated in Table S1. The scattering coefficient μs and the Mueller matrix of the samples were calculated based on the Mie scattering theory.43 

A commercial reflective PPG sensor, MAX30102, was employed as the sensing device. The acquired signals were converted to digital signals through an analog front-end circuit and sent to an Arduino Uno R3 development board. To create orthogonal polarization pairs, a polarizing film (visible light biaxial color film, Nitto Inc.) was cut into sizes of 1 × 3 mm2 and 3 × 3 mm2, respectively, and mounted on the Light Emitting Diode (LED) and Photodiode (PD). The polarizing film at the LED end had its polarization axis perpendicular to the LED–PD connection line, while the polarizing film at the PD end had its polarization axis parallel to it, ensuring that the PD was positioned in a region of high polarization for backward scattered light.

To investigate the differential modulation of polarized light on reflected light at various depths, we designed a polarization gate-semi-infinite scattering model based on the range of biological tissue optical parameters18 (see Table S1) and performed Monte Carlo ray tracing to compute the modulation of reflected light by the polarization gate (see Sec. II A). The light is modulated by the polarizer to be polarized and then incident along the positive Z-axis, undergoing multiple scattering in the medium. A fraction of photons scatter inside the medium and exit from the top of the model in the opposite direction of the Z-axis. The penetration depth and the Stokes vector [I Q U V]T of the photons reaching the detector are recorded with an acceptance angle of 30°. The Stokes vector describes the intensity, polarization direction, DOP, and ellipticity of the incident light (see Sec. II B). We simulated the correlation between the intensity and penetration depth of light reaching the detector under three conditions: no analyzer [Fig. 1(a)]; incident light polarization parallel to the polarization axis of the analyzer [Fig. 1(b)]; and incident light polarization orthogonal to the polarization axis of the analyzer [Fig. 1(c)]. The spatial distribution of the reflected light in these cases is shown in Fig. S2.

FIG. 1.

Polarization gate-semi-infinite medium scattering model. (a) No analyzer. (b) Parallel polarization pairs. (c) Orthogonal polarization pairs.

FIG. 1.

Polarization gate-semi-infinite medium scattering model. (a) No analyzer. (b) Parallel polarization pairs. (c) Orthogonal polarization pairs.

Close modal

As shown in Fig. 2(a), the simulation result with no polarizer is defined as the control group, and half of the light intensity received by the detector with no polarizer is defined as the control light intensity (IControl). Under parallel polarization conditions, the detector receives a higher intensity from the shallow depth region (<1 mm) compared to the control group, while the intensity from the deep region (>1 mm) is comparable to the control group. The polarization of deep-reflected light degraded through multiple scattering; hence, the parallel polarization applies differential intensity modulation to shallow- and deep-reflected light, resulting in a higher proportion of shallow-reflected light. In contrast, orthogonal polarization suppresses the shallow-reflected light to a greater extent, leading to a higher proportion of deep-reflected light.

FIG. 2.

Effect of the polarization gate on different depth reflected light. (a) The correlation between the reflected light intensity and the penetration depth under no analyzer, parallel polarization pairs, and orthogonal polarization pairs. (b) The correlation between the ability of polarization gate to regulate light and penetration depth under parallel and orthogonal conditions, and the correlation between the DOP and penetration depth. (c) Experimental diagram for the measurement of side light polarization. (d) Lateral polarization distribution of water suspensions of polystyrene spheres (c = 0.25%, d = 1.5 µm, and λ = 633 nm).

FIG. 2.

Effect of the polarization gate on different depth reflected light. (a) The correlation between the reflected light intensity and the penetration depth under no analyzer, parallel polarization pairs, and orthogonal polarization pairs. (b) The correlation between the ability of polarization gate to regulate light and penetration depth under parallel and orthogonal conditions, and the correlation between the DOP and penetration depth. (c) Experimental diagram for the measurement of side light polarization. (d) Lateral polarization distribution of water suspensions of polystyrene spheres (c = 0.25%, d = 1.5 µm, and λ = 633 nm).

Close modal

To characterize the ability of the polarization gate to modulate the reflected light, the ratio of the light intensity with the analyzer to the control light intensity was used as a criterion to evaluate the modulation ability of the polarization gate. Compared to IControl, the parallel polarization gate leads to a slight enhancement (∼20%) in the intensity of shallow-reflected light reaching the detector. In contrast, the orthogonal polarization gate causes attenuation. In addition, the polarization gate has minimal modulation effects on deep-reflected light, mainly due to the low DOP exhibited by the deep-reflected light [Fig. 2(b)]. To further validate the correlation between the DOP and the penetration depth, this study employed the experimental setup depicted in Fig. 2(c) (see Sec. II C) to measure the spatial distribution of DOP for the laterally emitted light from the water suspensions of polystyrene spheres (see Sec. II D). As shown in Fig. 2(d), the DOP of the light decreases with increasing penetration depth, attributed to an increased occurrence of scattering events.

The preceding investigation revealed that the modulation effect of the polarization gate on the reflected light depends on the DOP. To identify the optimal modulation region of the polarization gate for enhancing the modulation efficacy of the polarization gate, we have explored the DOP distribution of the reflected light on the scattering medium model’s reflective surface. The detector is divided into a 200 × 200 grid and collects the average Stokes vector [I Q U] of the photons falling into each grid (Fig. S3). By substituting the acquired values into Eq. (2), the DOP of the photons in each grid can be obtained.

As shown in Fig. 3(a), an “hourglass-shaped” high-polarization region (black box) emerges in the region perpendicular to the incident light polarization direction. This is due to the anisotropic property of the backward-Muller matrix of the scattering model, which causes the polarization distribution in the scattering model to change with the azimuth.44,45 Within the black box, the DOP of the shallow-reflected light reaches 0.6, while within the ordinary region (red box), the DOP of the shallow-reflected light is only 0.4. Greater polarization differences appear between the reflected light at different depths within the black box [Fig. 3(b)]. As shown in Fig. 3(c), we compared the correlation between the modulation ability of the polarization gate to the reflected light in the black box and red box regions and the penetration depth. The polarizing gate exhibits its highest modulation efficiency of up to 60% for the shallow-reflected light in the black box region. Conversely, in the red box region, the modulation efficiency is less than 40%, and it nearly loses its ability to control the reflected light when the penetration depth exceeds 0.5 mm. The polarization gate exhibits a stronger modulation capability on the shallow-reflected light within the high-polarization region (black box), and this capability can be sustained for a longer period with increasing penetration depth. The data evidence that placing the polarization gate within the high-polarization region is more favorable for enhancing the differentiated modulation effect of the polarization gate and improving the quality of the reflected signal. As shown in Fig. S4, the modulation effect of the polarization gate on photons is significantly enhanced within the black box [compared to Fig. 2(a)], and the distribution of photon intensity with respect to depth also changes. In addition, we employ a Stokes vector measurement setup [Fig. 3(d)] to explore the polarization distribution of the scattered sample’s reflected surface emission. The presence of an “hourglass-shaped” high-polarization region perpendicular to the polarization direction of the incident light [Figs. 3(e) and 3(f)] is consistent with our simulation results and significantly bolsters the confidence in the validity of this study. Furthermore, by comparing the polarization distribution of the reflection surface in the scattering model with three different particle diameters, it is observed that the reflection surface’s polarization gradually transitions from “hourglass-shaped” [Fig. S5(a)] to “clover-shaped” [Fig. S5(b)] as the particle diameter increases.

FIG. 3.

Performance distribution of the polarization gate on the reflective surface. (a) DOP distribution on the model reflective surface. (b) Variation in the DOP of the reflected light with penetration depth in the highly polarized region and the ordinary region. (c) Comparison of the polarization gate modulation effect in the highly polarized region and the normal region. (d) Experimental setup for measuring the polarization state of the incident light on the reflective surface. (e) and (f) Polarization distribution of the reflected light measured when the direction of incident light polarization is along the X and Y axes, respectively.

FIG. 3.

Performance distribution of the polarization gate on the reflective surface. (a) DOP distribution on the model reflective surface. (b) Variation in the DOP of the reflected light with penetration depth in the highly polarized region and the ordinary region. (c) Comparison of the polarization gate modulation effect in the highly polarized region and the normal region. (d) Experimental setup for measuring the polarization state of the incident light on the reflective surface. (e) and (f) Polarization distribution of the reflected light measured when the direction of incident light polarization is along the X and Y axes, respectively.

Close modal

The polarization state variation of polarized light during propagation in scattering media is influenced by several factors, including the polarization type of the incident light,46 incident wavelength λ,47 particle diameter d,48 mass concentration c,49 and other environmental conditions [Fig. 4(a)]. It is highly demanded to investigate the impact of these factors for filtering signals through polarization gating. We discuss the polarization type and incident wavelength of the incident light from the perspective of the light source, which is important for photoelectronic device design. According to Fig. 4(b), the DOP of linearly polarized light decreases from 0.5 to 0.1 as the penetration depth increases from 0.5 to 2 mm, while the DOP of circularly polarized light decreases from ∼0.6 to 0.5 under the same conditions (λ = 633 nm, d = 1.5 µm, and c = 0.2%). The DOP of linearly polarized incident light decreases more rapidly with increasing penetration depth, implying larger polarization state differences in the reflected light at different depths. The depolarization effect of circularly polarized light is weaker than that of linearly polarized light in the Mie scattering regime.46 However, the optical path required to generate and analyze the circularly polarized light is more complex, which poses significant challenges for the design and integration of optoelectronic detection systems. This finding is advantageous for the differential control of polarization gates. The circularly polarized light, due to its weak depolarization, can be used to reflect information from deeper layers of the medium since its spin reverses when it is scattered at large angles. In the Mie scattering regime, which is primarily characterized by forward-scattered small-angle scattering, a significant portion of the light retains its original polarization state.50 

FIG. 4.

Effect of the incident light on polarization gate modulation performance. (a) Factors affecting polarization gate modulation. (b) Variation in the polarization of linearly and circularly polarized light with the depth of penetration. (c) Performance of the polarization gate for different incident light wavelengths. (d) The correlation between the DOP of different incident wavelengths and the penetration depth.

FIG. 4.

Effect of the incident light on polarization gate modulation performance. (a) Factors affecting polarization gate modulation. (b) Variation in the polarization of linearly and circularly polarized light with the depth of penetration. (c) Performance of the polarization gate for different incident light wavelengths. (d) The correlation between the DOP of different incident wavelengths and the penetration depth.

Close modal

Next, we investigated the variations in the polarization-gate modulation performance under different incident light wavelengths [Fig. 4(c)]. The parallel and orthogonal polarization gates, respectively, enhanced or attenuated the shallow reflectance light up to 60%, and this modulation effect decreased with increasing penetration depth. As the incident light wavelength λ increased, the polarization gate exhibited a stronger modulation capacity, which improved the signal quality by modulating the shallow reflectance light. This phenomenon can be mainly attributed to the variation in DOP. As shown in Fig. 4(d) (d = 1.5 µm and c = 0.2%), longer wavelengths resulted in a higher DOP for the shallow reflectance light (<1 mm), while beyond a penetration depth of 2 mm, the DOP of reflected light at different wavelengths became equivalent. On the one hand, according to Mie theory,43 the relative size parameter X = πdnmed/λ becomes smaller for longer incident wavelengths, weakening the depolarization effect of single-scattering events (Fig. S6). On the other hand, longer wavelengths increased the scattering coefficient (Table S1), which enhanced the probability of multiple scattering events for particles and strengthened the polarization depolarization effect of the model. These two mechanisms have competing effects, with the first mechanism dominating when the light penetration depth is shallow, while they counterbalance each other when the penetration depth is deep.

Differences in biological types, tissue locations, and even states of the same tissue can lead to different optical performances due to their distinct optical properties. To optimize the performance of the polarization gate in various environments, we discuss the effects of mass concentration and particle diameter from the perspective of scattering environments. Figure 5(a) illustrates the modulation capability of the polarization gate for the reflected light in water suspensions of polystyrene spheres in different mass concentrations (d = 1.5 µm and λ = 633 nm). It is evident that while the polarization gate has an effect on light penetration at different depths, its modulation capability becomes weaker in higher-concentration scattering environments for the same penetration depth. The attenuation of modulation capability accelerates, and the ratio IAnalyzer/INone tends to 1 for shallower penetration depths, indicating that the polarizer cannot modulate the reflected light. This is due to the proportionality correlation between the scattering coefficient and mass concentration, μsca = cQsca. Hence, as the mass concentration in the scattering environment increases, the scattering coefficient also increases, causing a faster decrease in polarization degree as the polarized light propagates within it [Fig. 5(b)]. Furthermore, we designed experiments to validate the differences in modulation effectiveness of the polarization gate under different mass concentrations (Fig. S7).

FIG. 5.

Modulation effect of the polarization gate on samples with different mass concentrations. (a) Variation in polarization gate modulation performance at different mass concentrations. (b) Variation in reflected light polarization with the depth of penetration at different mass concentrations (d = 1.5 µm and λ = 633 nm).

FIG. 5.

Modulation effect of the polarization gate on samples with different mass concentrations. (a) Variation in polarization gate modulation performance at different mass concentrations. (b) Variation in reflected light polarization with the depth of penetration at different mass concentrations (d = 1.5 µm and λ = 633 nm).

Close modal

As shown in Fig. S8(a), we have found that the correlation between the diameter of the scattering particle and the ability of the polarization gate to modulate the light is weak. This is because the pattern of light polarization with the depth of penetration does not change significantly in scattering environments with different scattering particle sizes [Fig. S8(b)]. When the scattering particle diameter increases, on the one hand, its relative size parameter X = πdnmed/λ increases, thus enhancing the depolarization effect of light per scattering; on the other hand, it decreases the particle density in the scattering environment. The mass concentration of the scattering environment is fixed, leading to a reduction in the scattering coefficient, which, in turn, diminishes the effect of the scattering environment on the depolarization of the polarized light. The effects of these two mechanisms cancel each other out so that the pattern of change in the polarization of light remains almost unchanged as the particle diameter changes, and thus, the ability of the polarization gate to modulate the light changes little.

We have explored the influence of various factors on the signal-filtering capability of polarization gates. The parameters of the polarization optical detection system can be optimized according to different application scenarios to enhance signal filtering. As shown in Fig. 6(a), we have designed a PG-PPG sensor to demonstrate the optimization effect of the polarization gate on the signal of the photoelectronic detection system (see Sec. II E). The PPG signal consists of two mixed components: one is the alternating current (AC) signal caused by the periodic changes in vessel volume, and the other is the direct current (DC) signal reflected from the skin surface and superficial tissues.51 When calculating target is physiological features such as heart rate52 and blood oxygen,17 we need to analyze the AC signal by measuring the vascular volume changes, while the DC is considered as noise and will reduce the signal-to-noise ratio (SNR). When measuring heart rate fluctuation signals from the vascular layer (>1 mm), we use linearly polarized light as the source and employ an orthogonal polarization gate to filter out the DC component reflected from the superficial tissue. Meanwhile, to enhance the modulation of the polarization gate, we set the detector in a highly polarized region perpendicular to the light source polarization direction, of which the principle is shown in Fig. 6(b). The reflected light from shallow tissues largely retains its original polarization characteristics, resulting in a greater degree of suppression by the orthogonal polarization filter. However, the AC signal from blood vessels undergoes multiple scattering, degrading into lower-polarized light, hence retaining ∼50% of the light intensity even after passing through the orthogonal polarization filter. We measured the pulse fluctuation signal from the radial artery using a normal PPG sensor and a PG-PPG sensor at rest and ±10° extension/flexion motion of the wrist, respectively [Fig. 6(c)].

FIG. 6.

Improvement in the PPG signal by the polarization gate. (a) Schematic diagram of a polarization gate configured on a PPG sensor. (b) Principle of the quadrature polarization gate. (c) Resting state test and wrist swing ±10°. (d) Comparison of normal PPG and PG-PPG signals at rest. (e) Comparison of normal PPG and PG-PPG signals when the wrist is swinging ±10°.

FIG. 6.

Improvement in the PPG signal by the polarization gate. (a) Schematic diagram of a polarization gate configured on a PPG sensor. (b) Principle of the quadrature polarization gate. (c) Resting state test and wrist swing ±10°. (d) Comparison of normal PPG and PG-PPG signals at rest. (e) Comparison of normal PPG and PG-PPG signals when the wrist is swinging ±10°.

Close modal
The PPG signal in a static state is shown in Fig. 6(d). We use SNR to characterize the signal quality, and the SNR is calculated as follows:
SNRdB=10log10AsignalAnoise=10log10ACDC.
(4)

The SNR of the PPG sensor with no analyzer is 0.72 dB, while that of the PPG sensor with an orthogonal analyzer is 2.36 dB, which increases the SNR by 1.64 dB. Comparative investigation when the wrist joint is extended/flexion at ±10° shows that the PPG signal with no analyzer exhibits much surface moving signals, primarily caused by the relative motion between the sensor and the skin during wrist movement, leading to the interference to discern the heartbeat signal. In contrast, the application of an orthogonal polarization gate effectively suppresses the surface signal by over 80%, enabling enhanced capture of the heartbeat signal even under dynamic conditions [Fig. 6(e)]. The experimental results show that the orthogonal polarization gate has a strong gating ability, and hence, it can filter the reflected light from shallow tissue, adjust the signal composition, and improve the sensing performance of PPG devices.

For solving the masking of target signals and a decrease in SNR in the reflective photoelectronic detection system, a novel design strategy by introducing a polarization gate-semi-infinite medium scattering model to select reflected light at different depths is proposed. To optimize the effect of polarization gates on the mixing of reflected signals, this work investigates the effect of detection position, incident light, and scattering environment on the effect of polarization gates on the modulation of reflected signals. We find that an “hourglass” high polarization region appears on the reflecting surface, where the polarization gate can more effectively modulate the reflected light at different depths differently, which is beneficial for solving the problem of signal mixing. We also investigate the effect of the incident light and scattering environment on the polarization gate’s modulation performance. To verify the signal improvement of the polarization gate, a PPG with an orthogonal analyzer is designed, and the SNR improved to 2.36 dB from 0.72 dB. Meanwhile, an orthogonal polarization gate enhances the heartbeat signal capture even under dynamic conditions. This study reveals the correlation between the polarization gate modulation effect and the system structure and parameters, which offers new insights into the signal optimization of the polarization gate through a structural design for various application scenarios. This structural design shows promises for the construction of wearable, low-power, and highly robust physiological signal measurement systems. Furthermore, this design method is also expected to be combined with other optical detection and imaging methods to achieve a more sensitive, precise, and multifunction system.

The supplementary material contains the spatial distribution of light on the reflection surface of the model, Stokes vector distribution on the reflection surface of the model, the correlation between the reflected light intensity and the penetration depth, the backscattering polarization distribution of polystyrene spheres with different diameters, the relation between the polarization degree of incident light with different wavelengths and the scattering event, an experiment to explore the ability of polarization gate to modulate the reflected light, the simulation of polarization gating performance of particles with different diameters, the SEM scans of particles with different diameters, and the parameters of the scattering model.

X. M. Li acknowledges the financial support from the Guangdong Basic and Applied Basic Research Foundation (Grant No. 2022A1515010136), the Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices, and the South China Normal University start-up fund. L. Tao acknowledges the financial support from the National Key Research and Development Program of China (Grant No. 2023YFB3208002), the National Natural Science Foundation of China (Grant No. 62005051), and the start-up fund of Beijing Institute of Technology. The authors thank Huan He, Guoyuan Zhou, Jiali Wang, and Yuanzhi Zhou for fruitful discussions.

The authors have no conflicts to disclose.

Quanyu Ji: Conceptualization (lead); Data curation (lead); Formal analysis (lead); Investigation (lead); Methodology (lead); Software (lead); Visualization (lead); Writing – original draft (lead); Writing – review & editing (lead). Yeshen Chen: Conceptualization (equal); Formal analysis (equal); Software (equal); Writing – review & editing (equal). Weiliang Xu: Formal analysis (equal); Investigation (equal); Writing – review & editing (equal). Zhibin Zou: Formal analysis (equal); Writing – review & editing (equal). Haihua Fan: Formal analysis (equal); Investigation (equal); Writing – review & editing (equal). Zefeng Chen: Formal analysis (equal); Investigation (equal); Writing – review & editing (equal). Li Tao: Formal analysis (lead); Investigation (lead); Writing – review & editing (equal). Xinming Li: Conceptualization (lead); Formal analysis (equal); Funding acquisition (lead); Investigation (equal); Methodology (lead); Project administration (lead); Resources (lead); Supervision (lead).

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Supplementary Material