In this paper, we propose a conceptually novel algorithm, namely "Spatial Subspace Rotation" (2SR), that improves the robustness of remote photoplethysmography. Based on the assumption of 1) ...spatially redundant pixel-sensors of a camera, and 2) a well-defined skin mask, our core idea is to estimate a spatial subspace of skin-pixels and measure its temporal rotation for pulse extraction, which does not require skin-tone or pulse-related priors in contrast to existing algorithms. The proposed algorithm is thoroughly assessed on a benchmark dataset containing 54 videos, which includes challenges of various skin-tones, body-motions in complex illuminance conditions, and pulse-rate recovery after exercise. The experimental results show that given a well-defined skin mask, 2SR outperforms the popular ICA-based approach and two state-of-the-art algorithms (CHROM and PBV). When comparing the pulse frequency spectrum, 2SR improves on average the SNR of ICA by 2.22 dB, CHROM by 1.56 dB, and PBV by 1.95 dB. When comparing the instant pulse-rate, 2SR improves on average the Pearson correlation and precision of ICA by 47% and 65%, CHROM by 22% and 23%, and PBV by 21% and 39%. ANOVA confirms the significant improvement of 2SR in peak-to-peak accuracy. The proposed 2SR algorithm is very simple to use and extend, i.e., the implementation only requires a few lines MATLAB code.
Remote photoplethysmography (rPPG) techniques can measure cardiac activity by detecting pulse-induced color variations on human skin using an RGB camera. State-of-the-art rPPG methods are sensitive ...to subject body motions (e.g., motion-induced color distortions). This study proposes a novel framework to improve the motion robustness of rPPG. The basic idea of this paper originates from the observation that a camera can simultaneously sample multiple skin regions in parallel, and each of them can be treated as an independent sensor for pulse measurement. The spatial redundancy of an image sensor can thus be exploited to distinguish the pulse signal from motion-induced noise. To this end, the pixel-based rPPG sensors are constructed to estimate a robust pulse signal using motion-compensated pixel-to-pixel pulse extraction, spatial pruning, and temporal filtering. The evaluation of this strategy is not based on a full clinical trial, but on 36 challenging benchmark videos consisting of subjects that differ in gender, skin types, and performed motion categories. Experimental results show that the proposed method improves the SNR of the state-of-the-art rPPG technique from 3.34 to 6.76 dB, and the agreement (±1.96σ) with instantaneous reference pulse rate from 55% to 80% correct. ANOVA with post hoc comparison shows that the improvement on motion robustness is significant. The rPPG method developed in this study has a performance that is very close to that of the contact-based sensor under realistic situations, while its computational efficiency allows real-time processing on an off-the-shelf computer.
The emergence of reconfigurable intelligent surfaces (RISs) enables us to establish programmable radio wave propagation that caters for wireless communications, via employing low-cost passive ...reflecting units. This work studies the non-trivial tradeoff between energy efficiency (EE) and spectral efficiency (SE) in multiuser multiple-input multiple-output (MIMO) uplink communications aided by a RIS equipped with discrete phase shifters. For reducing the required signaling overhead and energy consumption, our transmission strategy design is based on the partial channel state information (CSI), including the statistical CSI between the RIS and user terminals (UTs) and the instantaneous CSI between the RIS and the base station. To investigate the EE-SE tradeoff, we develop a framework for the joint optimization of UTs' transmit precoding and RIS reflective beamforming to maximize a performance metric called resource efficiency (RE). For the design of UT's precoding, it is simplified into that of UTs' transmit powers with the aid of the closed-form solutions of UTs' optimal transmit directions. To avoid the high complexity in computing the nested integrals involved in the expectations, we derive an asymptotic deterministic objective expression. For the design of the RIS phases, an iterative mean-square error minimization approach is proposed via capitalizing on the homotopy, accelerated projected gradient, and majorization-minimization methods. Numerical results illustrate the effectiveness and rapid convergence rate of our proposed optimization framework.
Electrocardiogram (ECG) reconstruction from contact photoplethysmogram (PPG) would be transformative for cardiac monitoring. We investigated the fundamental and practical feasibility of such ...reconstruction by first replicating pioneering work in the field, with the aim of assessing the methods and evaluation metrics used. We then expanded existing research by investigating different cycle segmentation methods and different evaluation scenarios to robustly verify both fundamental feasibility, as well as practical potential. We found that reconstruction using the discrete cosine transform (DCT) and a linear ridge regression model shows good results when PPG and ECG cycles are semantically aligned-the ECG R peak and PPG systolic peak are aligned-before training the model. Such reconstruction can be useful from a morphological perspective, but loses important physiological information (precise R peak location) due to cycle alignment. We also found better performance when personalization was used in training, while a general model in a leave-one-subject-out evaluation performed poorly, showing that a general mapping between PPG and ECG is difficult to derive. While such reconstruction is valuable, as the ECG contains more fine-grained information about the cardiac activity as well as offers a different modality (electrical signal) compared to the PPG (optical signal), our findings show that the usefulness of such reconstruction depends on the application, with a trade-off between morphological quality of QRS complexes and precise temporal placement of the R peak. Finally, we highlight future directions that may resolve existing problems and allow for reliable and robust cross-modal physiological monitoring using just PPG.
To control the spread of coronavirus disease 2019 (COVID-19), it is effective to perform a fast screening of the respiratory rate of the subject at the gate before entering a space to assess the ...potential risks. In this paper, we examine the potential of a novel yet cost-effective solution, called thermopile-based respiratory gating, to contactlessly screen a subject by measuring their respiratory rate in the scenario with an entrance gate. Based on a customized thermopile array system, we investigate different image and signal processing methods that measure respiratory rate from low-resolution thermal videos, where an automatic region-of-interest selection-based approach obtains a mean absolute error (MAE) of 0.8 breaths per minute. We show the feasibility of thermopile-based respiratory gating and quantify its limitations and boundary conditions in a benchmark (e.g., appearance of face mask, measurement distance and screening time). The technical validation provided by this study is helpful for designing and implementing a respiratory gating solution toward the prevention of the spread of COVID-19 during the pandemic.
Metal−organic framework (MOF) membranes have attracted considerable attention because of their striking advantages in small-molecule separation. The preparation of an integrated MOF membrane is still ...a major challenge. Depositing a uniform seed layer on a support for secondary growth is a main route to obtaining an integrated MOF membrane. A novel seeding method to prepare HKUST-1 (known as Cu3(btc)2) membranes on porous α-alumina supports is reported. The in situ production of the seed layer was realized in step-by-step fashion via the coordination of H3btc and Cu2+ on an α-alumina support. The formation process of the seed layer was observed by ultraviolet−visible absorption spectroscopy and atomic force microscopy. An integrated HKUST-1 membrane could be synthesized by the secondary hydrothermal growth on the seeded support. The gas permeation performance of the membrane was evaluated.
To achieve fast and secure information steganography in underwater acoustic channel scenarios, this paper proposes a PSO (Particle Swarm Optimization) and IWT (integer wavelet transform) based image ...steganography algorithm for underwater acoustic communication. Firstly, the underwater image to be embedded is interleaved and packed to generate the secret information code-stream to improve the detection and recovery performance of transmission errors. Secondly, the cover image is divided into non-overlapping blocks and IWT is applied to each block, which can save PSO search space and improve the optimal solution performance. Thirdly, the embedding position matrix of the high frequency sub-band coefficients is chaotic scrambled, and PSO is used to select the optimal key to obtain the optimal matching position for the secret information to produce the best stego-image quality. Finally, transmission error detection and recovery measures are applied to the extracted secret information to improve the reconstruction quality in underwater acoustic channel scenarios. Experimental results show that the proposed algorithm outperforms existing approaches in terms of information embedding capacity and steganographic visual quality, meeting the requirements of safety and real-time performance of underwater communication. Moreover, it also has the ability of error detection and recovery for harsh underwater acoustic channel.
Current rodent models of wound healing and scarring are flawed because of rapid wound contraction and inconspicuous scarring after healing, which is not closely parallel to the physiologic process in ...humans. This study aimed to establish a novel model of wound healing and scarring in rats.
Excisional wounds were generated in rat tail or dorsal skin and histologic changes and wound contraction were assessed 2, 10, and 16 days after injury. After healing, rat tail scar was investigated for 24 consecutive weeks by histologic and immunohistochemical staining. Finally, a stretched scar model was generated in rat tail with high or low strain after reepithelialization to mimic human hypertrophic scars. The tail hypertrophic scars were analyzed by histology, immunohistochemical staining, and mRNA quantification 0, 2, 6, 12, and 24 weeks after stretching.
Compared with the dorsal wounds, a larger dermal gap percentage (p < 0.05) and more pronounced granulation were found in rat tail wounds. Tail scars remained conspicuous and underwent maturation over 24 weeks after wound healing. In addition, high mechanical strain induced significantly increased scar area (p < 0.01), scar height (p < 0.05), vessel density (p < 0.01) and hypertrophic scar-related molecule expression, and distorted collagen arrangement in rat tail scars.
The rat tail model exhibits minor wound contraction and biological features analogous to both normotrophic and hypertrophic scar in humans when generated with or without stretching, respectively. It is a promising new model for studies of both cutaneous wound healing and scarring.
In this article, we propose a novel deep domain adaptation method based on graph neural network (GNN) for multitemporal hyperspectral remote sensing images. In GNN, graphs are constructed for source ...and target data, respectively. Then the graphs are utilized in each hidden layer to obtain features. GNN operates on graph structure and the relations between data samples can be exploited. It aggregates features and propagate information through graph nodes. Thus, the extracted features have an improved smoothness in each spectral neighborhood which is beneficial to classification. Furthermore, the domain-wise correlation alignment (CORAL) and class-wise CORAL are jointly embedded in GNN network to achieve a joint distribution adaptation performance. By introducing the joint CORAL strategy in GNN, the extracted features can not only be aligned between domains but also have a superior discriminability in each domain. This domain adaptation network is named as joint CORAL-based graph neural network. Experiments using multitemporal Hyperion and NSF-funded center for airborne laser mapping datasets demonstrate the effectiveness of the proposed method.
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