Multi-Modal Sleep Stage Classification With Two-Stream Encoder-Decoder.

Sleep staging serves as a fundamental assessment for sleep quality measurement and sleep disorder diagnosis. Although current deep learning approaches have successfully integrated multimodal sleep signals, enhancing the accuracy of automatic sleep staging, certain challenges remain, as follows: 1) optimizing the utilization of multi-modal information complementarity, 2) effectively extracting both long- and short-range temporal features of sleep information, and 3) addressing the class imbalance problem in sleep data. To address these challenges, this paper proposes a two-stream encode-decoder network, named TSEDSleepNet, which is inspired by the depth sensitive attention and automatic multi-modal fusion (DSA2F) framework. In TSEDSleepNet, a two-stream encoder is used to extract the multiscale features of electrooculogram (EOG) and electroencephalogram (EEG) signals. And a self-attention mechanism is utilized to fuse the multiscale features, generating multi-modal saliency features. Subsequently, the coarser-scale construction module (CSCM) is adopted to extract and construct multi-resolution features from the multiscale features and the salient features. Thereafter, a Transformer module is applied to capture both long- and short-range temporal features from the multi-resolution features. Finally, the long- and short-range temporal features are restored with low-layer details and mapped to the predicted classification results. Additionally, the Lovász loss function is applied to alleviate the class imbalance problem in sleep datasets. Our proposed method was tested on the Sleep-EDF-39 and Sleep-EDF-153 datasets, and it achieved classification accuracies of 88.9% and 85.2% and Macro-F1 scores of 84.8% and 79.7%, respectively, thus outperforming conventional traditional baseline models. These results highlight the efficacy of the proposed method in fusing multi-modal information. This method has potential for application as an adjunct tool for diagnosing sleep disorders.

Wound healing is promoted by Musa paradisiaca (banana) extract in diabetic rats.

Introduction: Impairments in wound healing commonly occur among patients with diabetes. Herbal medicines have a long history of usage in wound care management. Super green (SG) is a newly discovered natural product obtained from Musa paradisiaca. This study aimed to investigate the efficacy of the topical application of SG in healing surgical wounds in diabetic rats. Material and methods: Wistar rats received a one-time intraperitoneal injection of streptozotocin to induce type 1 diabetes. Full-thickness excisional skin wounds were created on the backs of the rats. The relevant groups were topically treated with the indicated concentrations of SG or vehicle dressing throughout the study duration. Histological analysis was performed and the mRNA levels of proinflammatory cytokines were measured to evaluate the improvement of wound closure. Results: The wound area ratio of the SG (1/6000 dilution)-treated group was greatly reduced compared to that of the vehicle-treated group. The histological analysis showed fewer inflammatory cells, accelerated re-epithelialization, and increased collagen deposition in SG 1/6000-treated wounds. The gene expression levels of tumor necrosis factor-α, interleukin-1ß, and interleukin-6 were decreased and the levels of type I and type III collagen were increased after SG treatment. Conclusions: These results show that the most therapeutically efficacious concentration of SG (1/6000 dilution) can enhance wound repair in diabetic rats. SG has the potential to be a new treatment strategy for diabetic wounds.

Prognostic impact of cortactin in patients with hypopharyngeal cancer and its role for tegafur-uracil maintenance after adjuvant chemoradiotherapy.

The prognosis of patients with hypopharyngeal cancer (HPC) remains poor. Our study aims to investigate the prognostic impact of cortactin in patients with HPC and its role for tegafur-uracil (UFUR) maintenance after adjuvant chemoradiotherapy (CRT). Patients who were diagnosed to have HPC and underwent laryngopharyngectomy followed by adjuvant CRT were enrolled into our study. Immunohistochemical staining was performed for cortactin evaluation. Kaplan-Meier curves were depicted for recurrence-free survival (RFS) and overall survival (OS). A total of 157 patients were enrolled into our study. After stratified by cortactin, 53 patients were cortactin (+) and 104 patients were cortactin (-). The median RFS was 86.7 months in cortactin (-) and 10.2 months in cortactin (+) (P < 0.001). The median OS was 93.4 months in cortactin (-) and 16.9 months in cortactin (+) (P < 0.001). Patients were further classified according to UFUR maintenance or not after adjuvant CRT. In cortactin (+) patients, the median RFS and OS were 13.6 months versus 7.0 months (P = 0.006) and 24.0 months versus 10.0 months (P < 0.001) in UFUR (+) and UFUR (-), respectively. In cortactin (-) patients, the median RFS and OS were 96.0 months versus 72.2 months (P = 0.262) and 98.5 months versus 105.0 months (P = 0.665) in UFUR (+) and UFUR (-), respectively. Cortactin has a significantly impact in HPC patients. UFUR maintenance provided survival benefits in patients with cortactin (+) after adjuvant CRT.

An Entropy-Balanced Orthogonal Learning Bamboo Forest Growth Optimization Algorithm with Quasi-Affine Transformation Evolutionary and Its Application in Capacitated Vehicle Routing Problem.

The bamboo forest growth optimization (BFGO) algorithm combines the characteristics of the bamboo forest growth process with the optimization course of the algorithm. The algorithm performs well in dealing with optimization problems, but its exploitation ability is not outstanding. Therefore, a new heuristic algorithm named orthogonal learning quasi-affine transformation evolutionary bamboo forest growth optimization (OQBFGO) algorithm is proposed in this work. This algorithm combines the quasi-affine transformation evolution algorithm to expand the particle distribution range, a process of entropy increase that can significantly improve particle searchability. The algorithm also uses an orthogonal learning strategy to accurately aggregate particles from a chaotic state, which can be an entropy reduction process that can more accurately perform global development. OQBFGO algorithm, BFGO algorithm, quasi-affine transformation evolutionary bamboo growth optimization (QBFGO) algorithm, orthogonal learning bamboo growth optimization (OBFGO) algorithm, and three other mature algorithms are tested on the CEC2017 benchmark function. The experimental results show that the OQBFGO algorithm is superior to the above algorithms. Then, OQBFGO is used to solve the capacitated vehicle routing problem. The results show that OQBFGO can obtain better results than other algorithms.

A Deep Learning-Based Chair System That Detects Sitting Posture.

Long-term poor sitting posture leads to physical injuries such as muscle soreness and waist and neck alignment problems. In this study, we proposed an intelligent sitting posture detection system that uses depth cameras fixed on a chair to capture depth images of the user's sitting posture, and then applies a trained artificial intelligence (AI) model on an embedded Raspberry Pi board to recognize the user's sitting posture from the image data. Finally, through Bluetooth on the Raspberry Pi, the results are sent to the user's smartphone application for display and recording to achieve rapid detection of sitting posture and warning of poor sitting posture. The contribution of this study is its use of two depth cameras mounted on a chair, thereby eliminating the problem of cumbersome sensors that compromise user comfort or are prone to damage. The detection of the user's entire sitting posture was completed on an edge computing platform, which leads to power savings and offers privacy protection. Furthermore, because of the low battery power usage, the system is portable. To perform quick AI calculations, we developed a lightweight EfficientNet model and programmed it for the Raspberry Pi. The system achieved an accuracy of 99.71% and an execution speed of almost one posture result per second.

The quantitative analysis of low-concentration (2%) ALA-PDT assisted with Q-switch 1064-nm Nd:YAG laser for acne vulgaris treatment.

Conventional 5-aminolevulinic acid-photodynamic (ALA-PDT) therapy (10-20%) has been widely applied for moderate-to-severe acne. The aim of this study is to investigate the effects of non-ablative Q-switched 1064-nm Nd:YAG laser-assisted ALA-PDT with low concentration (2%) on the treatment of acne vulgaris. Enrolled patients were randomly assigned to 2 groups. One group received combined therapy of 2% ALA-PDT and non-ablative Q-switched 1064-nm Nd:YAG laser, and the other received only 2% ALA-PDT. Patients in each group had received 3-session treatments with 4-week intervals (week 0, 4, and 8). Sebum secretion, melanin index, erythema index, and transepidermal water loss (TEWL) were assessed at week 2, 8, 12, and 24. VISIA® skin image system score and global esthetic improvement scale (GAIS) were also evaluated. Twenty-four participants were enrolled and evenly randomized to two groups. Significant improvement in sebum secretion was noted in combined therapy group compared to the monotherapy group at week 12 (37.5% versus 16.3%), and the improvement would still be noted until week 24 (18.3% versus 17.4%). Combined group also showed more severe melanin index and erythema index after treatment. For VISIA® skin analysis, patients in combined group had better percentile ranking in porphyrins and red-light images. There were no significant differences in GAIS at the end of the follow-up between each group, whereas higher proportion of satisfaction was noted in combined group at week 2. With the assistance of laser, low concentrations (2%) of 5-ALA can provide effective phototoxic reactions in treating acne vulgaris. The satisfaction of patients is high with acceptable adverse effects.

Adaptability of melanocytes post ultraviolet stimulation in patients with melasma.

BACKGROUND: Dynamic in vivo changes in melanin in melasma lesions after exposure to ultraviolet (UV) irradiation have not been described. OBJECTIVES: To determine whether melasma lesions and nearby perilesions demonstrated different adaptive responses to UV irradiation and whether the tanning responses were different among different locations on face. METHODS: We collected sequential images from real-time cellular resolution full-field optical coherence tomography (CRFF-OCT) at melasma lesions and perilesions among 20 Asian patients. Quantitative and layer distribution analyses for melanin were performed using a computer-aided detection (CADe) system that utilizes spatial compounding-based denoising convolutional neural networks. RESULTS: The detected melanin (D) is melanin with a diameter >0.5 µm, among which confetti melanin (C) has a diameter of >3.3 µm and corresponds to a melanosome-rich package. The calculated C/D ratio is proportional to active melanin transportation. Before UV exposure, melasma lesions had more detected melanin (p = 0.0271), confetti melanin (p = 0.0163), and increased C/D ratio (p = 0.0152) in the basal layer compared to those of perilesions. After exposure to UV irradiation, perilesions have both increased confetti melanin (p = 0.0452) and the C/D ratio (p = 0.0369) in basal layer, and this effect was most prominent in right cheek (p = 0.030). There were however no significant differences in the detected, confetti, or granular melanin areas before and after exposure to UV irradiation in melasma lesions in all the skin layers. CONCLUSIONS: Hyperactive melanocytes with a higher baseline C/D ratio were noted in the melasma lesions. They were "fixed" on the plateau and were not responsive to UV irradiation regardless of the location on face. Perilesions retained adaptability with a dynamic response to UV irradiation, in which more confetti melanin was shed, mainly in the basal layer. Therefore, aggravating effect of UV on melasma was mainly due to UV-responsive perilesions rather than lesions.

System Based on Artificial Intelligence Edge Computing for Detecting Bedside Falls and Sleep Posture.

Bedside falls and pressure ulcers are crucial issues in geriatric care. Although many bedside monitoring systems have been proposed, they are limited by the computational complexity of their algorithms. Moreover, most of the data collected by the sensors of these systems must be transmitted to a back-end server for calculation. With an increase in the demand for the Internet of Things, problems such as higher cost of bandwidth and overload of server computing are faced when using the aforementioned systems. To reduce the server workload, certain computing tasks must be offloaded from cloud servers to edge computing platforms. In this study, a bedside monitoring system based on neuromorphic computing hardware was developed to detect bedside falls and sleeping posture. The artificial intelligence neural network executed on the back-end server was simplified and used on an edge computing platform. An integer 8-bit-precision neural network model was deployed on the edge computing platform to process the thermal image captured by the thermopile array sensing element to conduct sleep posture classification and bed position detection. The bounding box of the bed was then converted into the features for posture classification correction to correct the posture. In an experimental evaluation, the accuracy rate, inferencing speed, and power consumption of the developed system were 94.56%, 5.28 frames per second, and 1.5 W, respectively. All the calculations of the developed system are conducted on an edge computing platform, and the developed system only transmits fall events to the back-end server through Wi-Fi and protects user privacy.

Novel Smart Assistance System for Arteriosclerosis Evaluation.

Arteriosclerosis is a cardiovascular disease that can cause calcification, sclerosis, stenosis, or obstruction of blood vessels and may further cause abnormal peripheral blood perfusion or other complications. In clinical settings, several approaches, such as computed tomography angiography and magnetic resonance angiography, can be used to evaluate arteriosclerosis status. However, these approaches are relatively expensive and require an experienced operator and often the injection of a contrast agent. In this article, a novel smart assistance system based on near-infrared spectroscopy was proposed that can noninvasively assess blood perfusion and thus indicate arteriosclerosis status. In this system, a wireless peripheral blood perfusion monitoring device simultaneously monitors changes in hemoglobin parameters and the cuff pressure applied by a sphygmomanometer. Several indexes extracted from changes in hemoglobin parameters and cuff pressure were defined and can be used to estimate blood perfusion status. A neural network model for arteriosclerosis evaluation was constructed using the proposed system. The relationship between the blood perfusion indexes and arteriosclerosis status was investigated, and the neural network model for arteriosclerosis evaluation was validated. Experimental results indicated that the differences in many blood perfusion indexes for different groups were significant and that the neural network model could effectively evaluate arteriosclerosis status (accuracy = 80.26%). By using a sphygmomanometer, the model can be employed for simple arteriosclerosis screening and blood pressure measurements. The model offers real-time noninvasive measurement, and the system is relatively inexpensive and easy to operate.

Intelligent Headband System for Evaluating Rehabilitation Effectiveness.

Stroke is an acute cerebrovascular condition causing damage to cranial nerves and requires subsequent rehabilitation treatment. In clinical practice, the effectiveness of rehabilitation is usually subjectively assessed by experienced physicians or using global prognostic scales. Several brain imaging techniques, such as positron emission tomography, functional magnetic resonance imaging, and computed tomography angiography, can be applied in rehabilitation effectiveness evaluation, but their complexity and long measurement times limit the activity of patients during measurement. This paper proposes an intelligent headband system based on near-infrared spectroscopy. An optical headband continuously and noninvasively monitors changes in hemoglobin parameters in the brain. The system's wearable headband and wireless transmission provide convenience of use. According to the change of hemoglobin parameters during rehabilitation exercise, several indexes were also defined to evaluate the state of cardiopulmonary function and further build the neural network model of the cardiopulmonary function evaluation. Finally, the relationship between the defined indexes and the cardiopulmonary function state were investigated and the neural network model for the cardiopulmonary function evaluation was also applied in the rehabilitation effect evaluation. The experimental results show the cardiopulmonary function state could reflect on most of the defined indexes and the output of neural network model, and the rehabilitation therapy could also improve the cardiopulmonary function.

Serum vascular endothelial growth factor affects tissue fluid accumulation and is associated with deteriorating tissue perfusion and oxygenation in severe sepsis: a prospective observational study.

BACKGROUND: Positive fluid balance and tissue fluid accumulation are associated with adverse outcomes in sepsis. Vascular endothelial growth factor (VEGF) increases in sepsis, promotes vascular permeability, and may affect tissue fluid accumulation and oxygenation. We used near-infrared spectroscopy (NIRS) to estimate tissue hemoglobin (Hb) oxygenation and water (H2O) levels to investigate their relationship with serum VEGF levels. MATERIAL AND METHODS: New-onset severe sepsis patients admitted to the intensive care unit were enrolled. Relative tissue concentrations of oxy-Hb ([HbO2]), deoxy-Hb ([HbR]), total Hb ([HbT]), and H2O ([H2O]) were estimated by near-infrared spectroscopy (NIRS) for three consecutive days and serum VEGF levels were measured. Comparisons between oliguric and non-oliguric patients were conducted and the correlations between variables were analyzed. RESULTS: Among 75 eligible patients, compared with non-oliguric patients, oliguric patients were administrated more intravascular fluids (median [IQR], 1926.00 [1348.50-3092.00] mL/day vs. 1069.00 [722.00-1486.75] mL/day, p < 0.001) and had more positive daily net intake and output (mean [SD], 1,235.06 [1303.14] mL/day vs. 313.17 [744.75] mL/day, p = 0.012), lower [HbO2] and [HbT] over the three-day measurement (analyzed by GEE p = 0.01 and 0.043, respectively) and significantly higher [H2O] on the third day than on the first two days (analyzed by GEE p = 0.034 and 0.018, respectively). Overall, serum VEGF levels were significantly negatively correlated with [HbO2] and [HbT] (rho = - 0.246 and - 0.266, p = 0.042 and 0.027, respectively) but positively correlated with [H2O] (rho = 0.449, p < 0.001). Subgroup analysis revealed a significant correlation between serum VEGF and [H2O] in oliguric patients (rho = 0.532, p = 0.003). Multiple regression analysis determined the independent effect of serum VEGF on [H2O] (standardized coefficient = 0.281, p = 0.038). CONCLUSIONS: In severe sepsis, oliguria relates to higher positive fluid balance, lower tissue perfusion and oxygenation, and progressive tissue fluid accumulation. Elevated serum VEGF is associated with worsening tissue perfusion and oxygenation and independently affects tissue fluid accumulation.

Noncontrast MRI in assessing venous reflux of legs using QFlow analysis and radial basis function neural network technique.

Since venous reflux is difficult to quantify, triggered angiography non-contrast-enhanced (TRANCE)-magnetic resonance imaging (MRI) is a novel tool for objectively evaluating venous diseases in the lower extremities without using contrast media. This study included 26 pre-intervention patients with superficial venous reflux in the lower extremities and 15 healthy volunteers. The quantitative flow (QFlow) analyzed the phase shift information from the pixels within the region of interest from MRI. The fast and simple radial basis function neural network (RBFNN) learning model is constructed by determining the parameters of the radial basis function and the weights of the neural network. The input parameters were the variables generated through QFlow, while the output variables were morbid limbs with venous reflux and normal limb classification. The stroke volume, forward flow volume, absolute stroke volume, mean flux, stroke distance, and mean velocity of greater saphenous veins from QFlow analysis could be used to discriminate the morbid limbs of pre-intervention patients and normal limbs of healthy controls. The neural network successfully classified the morbid and normal limbs with an accuracy of 90.24% in the training stage. The classification of venous reflux using the RBFNN model may assist physicians in clinical settings.

Aberration analysis of a projection-type CGH display with an expanded FOV based on the HOE screen.

This paper proposed a holographic optical element as a see-through screen for the computer-generated hologram projection system with 3D images. The proposed holographic screen consisted of a linear grating and a lens phase. The linear grating is used to redirect the information light and guide information into the observer's eye and achieve the see-through function. The lens phase is used to magnify the field of view of the holographic projection system. The aberration caused by the screen was analyzed in this paper and the aberration can be pre-corrected in the hologram calculation algorithm. Finally, the proposed system achieved 20.3 by 14.3 degrees field of view at 532 nm laser based on the spatial light modulator with 6.4 µm pixels.

Increased tissue water in patients with severe sepsis affects tissue oxygenation measured by near-infrared spectroscopy: a prospective, observational case-control study.

Background: Tissue oedema affects tissue perfusion and interferes with the monitoring of tissue oxygenation in patients with severe sepsis. However, the underlying mechanisms remain unclear. We used a wireless near-infrared spectroscopy (NIRS) device that transmits tri-wavelength light to quantify tissue haemoglobin (Hb) and water (H2O) content. We estimated tissue H2O in severe sepsis patients and healthy controls, compared their difference, and investigated the correlation of tissue H2O with systemic haemodynamics and its impact on tissue oxygenation. Methods: Seventy-seven adult patients with new-onset severe sepsis admitted to the intensive care unit within 72 h and 30 healthy volunteers (controls) were enrolled. The NIRS device was placed on the participant's leg to estimate the relative tissue concentrations of oxy-Hb ([HbO2]), deoxy-Hb ([HbR]), total Hb ([HbT]), and H2O ([H2O]) at rest for three consecutive days. Two-sample t-test or Mann-Whitney U test, chi-square test, and generalised estimating equations (GEEs) were used for comparisons. Results: In severe sepsis patients, the [H2O] in the anterior tibia was higher [mean (standard deviation, 95% confidence interval), 10.57 (3.37, 9.81-11.34) vs. 7.40 (1.89, 6.70-8.11)] and the [HbO2], [HbT], and tissue Hb oxygen saturation (StO2) were lower [0.20 (0.01, 0.20-0.20) vs. 0.22 (0.01, 0.22-0.23), 0.42 (0.02, 0.42-0.43) vs. 0.44 (0.02, 0.44-0.45), and 47.25% (1.97%, 46.80-47.70%) vs. 49.88% (1.26%, 49.41-50.35%), respectively] than in healthy controls in first-day measurements. GEE analysis revealed significant differences in [H2O], [HbO2], [HbT], and StO2 between groups over three consecutive days (all P≤0.001). In addition, [HbO2] and StO2 levels gradually decreased over time in the patient group. A negative correlation was observed between [H2O] and [HbO2] and StO2, which became more obvious over time (day 1: r=-0.51 and r=-0.42, respectively; both P<0.01; day 3: r=-0.67 and r=-0.63, respectively, both P<0.01). Systolic arterial pressure was positively related to [H2O] (r=0.51, P<0.05, on day 1) but was not associated with tissue oxygenation parameters. Conclusions: NIRS can be used to quantify tissue H2O. Severe sepsis patients have increased tissue H2O, which responds to changes in arterial blood pressure and affects tissue oxygenation.

Molecular Characteristics and Distribution of Virulence Genes among Staphylococcus aureus Complex Isolates Derived from Vascular Access Infections.

Staphylococcus aureus is a major human pathogen that produces various virulence factors which promote the binding of bacteria to tissues and medical devices such as vascular access devices, thereby developing a wide range of invasive infections. Vascular access serves as an entry site for S. aureus and elevates the risk of infection in the hemodialysis population. Nevertheless, the distribution of virulence genes in Staphylococcus spp. associated with vascular access infections (VAIs) has not been studied previously. In this study, we determined the relationship between the molecular characteristics and virulence profiles of S. aureus isolates obtained from VAIs. We collected isolates from patients with VAIs between August 2017 and December 2020 and further analyzed the molecular characteristics, antimicrobial resistance profiles, and virulence gene distribution in the isolates. Overall, 15 sequence types (STs), including a new ST (ST6892) and 19 spa types, were identified among the 56 isolates. Of the 53 S. aureus isolates, ST8, ST239, ST45, and ST59 were the predominant STs, whereas ST2250 was the only ST in 3 S. argenteus isolates. ST45-SCCmecIV-t026 (abbreviated as ST45-IV-t026), ST59-V-t437, and ST8-IV-t008 were the predominant clones that belonged to agr type I. All isolates harbored clfB and eno, whereas all S. aureus isolates harbored clfA. In addition, 10 Panton-Valentine leucocidin-positive isolates belonged to ST8 and ST59, with ST8-IV-t008 and ST59-V-t437 being the predominant clones. In brief, the distribution of virulence genes associated with STs may assist in the spread of molecular types of Staphylococcus spp.

Design of Waveguide Polarization Convertor Based on Asymmetric 1D Photonic Crystals.

Photonic crystals possess metastructures with a unique dispersion relation. An integrated optical circuit plays a crucial role in quantum computing, for which miniaturized optical components can be designed according to the characteristics of photonic crystals. Because the stable light transmission mode for a square waveguide is transverse electric or transverse magnetic polarization, we designed a half-waveplate element with a photonic crystal that can rotate the polarization direction of the light incident on a waveguide by 90°. Using the dispersion relation of photonic crystals, the polarization rotation length and the optical axis's angle of deviation from the electric field in the eigenmode can be effectively calculated. Polarization rotators designed on the basis of photonic crystal structures can effectively reduce the insertion loss of components and exhibit favorable polarization rotation performance.

Photoaging and Sequential Function Reversal with Cellular-Resolution Optical Coherence Tomography in a Nude Mice Model.

Although nude mice are an ideal photoaging research model, skin biopsies result in inflammation and are rarely performed at baseline. Meanwhile, studies on antiphotoaging antioxidants or rejuvenation techniques often neglect the spontaneous reversal capacity. Full-field optical coherence tomography (FFOCT) can acquire cellular details noninvasively. This study aimed to establish a photoaging and sequential function reversal nude mice model assisted by an in vivo cellular resolution FFOCT system. We investigated whether a picosecond alexandrite laser (PAL) with a diffractive lens array (DLA) accelerated the reversal. In the sequential noninvasive assessment using FFOCT, a spectrophotometer, and DermaLab Combo®, the photodamage percentage recovery plot demonstrated the spontaneous recovery capacity of the affected skin by UVB-induced transepidermal water loss and UVA-induced epidermis thickening. A PAL with DLA not only accelerated skin barrier regeneration with epidermal polarity, but also increased dermal neocollagenesis, whereas the nonlasered group still had >60% collagen intensity loss and 40% erythema from photodamage. Our study demonstrated that FFOCT images accurately resemble the living tissue. The photoaging and sequential function reversal model provides a reference to assess the spontaneous recovery capacity of nude mice from photodamage. This model can be utilized to evaluate the sequential noninvasive photodamage and reversal effects after other interventions.

Near Infrared Spectroscopy Detects Change of Tissue Hemoglobin and Water Levelsin Kawasaki Disease and Coronary Artery Lesions.

Background: Kawasaki disease (KD) is a form of systemic vasculitis that mainly affects children under the age of five years old. Limb swelling and redness are among the primary symptoms of KD. Previous studies have reported that wireless optical monitoring systems can identify limb indurations characteristics in patients with KD. Therefore, we conducted this study to monitor the dynamic changes in different stages of KD and the disease outcome of coronary artery lesions (CAL).Methods: KD patients who were admitted for intravenous immunoglobulin (IVIG) treatment and controls with or without fever were enrolled in this study. Near infrared spectroscopy data were collected for KD patients at different stages, including before (within one day before IVIG treatment, KD1) and shortly after IVIG treatment (within three days, KD2), at least 21 days after IVIG (KD3), 6 months later (KD4), 1 year later (KD5), 2 years later (KD6), and 3 years later (KD7).Results: This study included a total of 350 pieces of data, including data from 20 healthy controls, 64 fever controls, 53 KD1, 67 KD2, 58 KD3, 28 KD4, 25 KD5, 15 KD6, and 20 KD7. The relative HbO2 of the KD1 group were significantly lower than those of the healthy group (0.298 ± 0.01 vs. 0.304 ± 0.05, p = 0.028) but no significant differences were found with the fever group. The HbT concentrations of KD1 group showed significantly lower than health group (0.632 ± 0.019 vs. 0.646 ± 0.021, p = 0.001) but no significant difference with fever control. Relative levels of HbO2, HbT and Hb showed significant difference between KD1 and health control while StO2 and H2O showed difference between KD1 and fever control. The relative H2O concentration was significantly higher in KD patients with CAL formation than without (p < 0.005). Conclusion: This report is the first to use near infrared spectroscopy to detect changes in tissue hemoglobin and water levels at different stages of KD in patients and showed that water content was significantly associated with CAL formation. This non-invasive device may benefit physicians by serving for early identification of KD from fever illness.

Smart Blood Vessel Detection System for Laparoscopic Surgery.

OBJECTIVE: Compared with traditional surgery, laparoscopic surgery offers the advantages of smaller scars and rapid recovery and has gradually become popular. However, laparoscopic surgery has the limitation of low visibility and a lack of touch sense. As such, a physician may unexpectedly damage blood vessels, causing massive bleeding. In clinical settings, Doppler ultrasound is commonly used to detect vascular locations, but this approach is affected by the measuring angle and bone shadow and has poor ability to distinguish arteries from veins. To tackle these problems, a smart blood vessel detection system for laparoscopic surgery is proposed. METHODS: Based on the principle of near-infrared spectroscopy, the proposed instrument can access hemoglobin (HbT) parameters at several depths simultaneously and recognize human tissue type by using a neural network. RESULTS: Using the differences in HbT and StO2 between different tissues, vascular and avascular locations can be recognized. Moreover, a mechanically rotatable stick enables the physician to easily operate in body cavities. Phantom and animal experiments were performed to validate the system's performance. CONCLUSION: The proposed system has high ability to distinguish vascular from avascular locations at various depths.