Joint associations among non-essential heavy metal mixtures and nutritional factors on glucose metabolism indexes in US adults: evidence from the NHANES 2011-2016.

Dietary intake can modify the impact of metals on human health, and is also closely related to glucose metabolism in human bodies. However, research on their interaction is limited. We used data based on 1738 adults aged ≥20 years from the National Health and Nutrition Examination Survey 2011-2016. We combined linear regression and restricted cubic splines with Bayesian kernel machine regression (BKMR) to identify metals associated with each glucose metabolism index (P < 0.05 and the posterior inclusion probabilities of BKMR >0.5) in eight non-essential heavy metals (barium, cadmium, antimony, tungsten, uranium, arsenic, lead, and thallium) and glucose metabolism indexes [fasting plasma glucose (FPG), blood hemoglobin A1c (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR)]. We identified two pairs of metals associated with glucose metabolism indexes: cadmium and tungsten to HbA1c and barium and thallium to HOMA-IR. Then, the cross-validated kernel ensemble (CVEK) approach was applied to identify the specific nutrient group (nutrients) that interacted with the association. By using the CVEK model, we identified significant interactions between the energy-adjusted diet inflammatory index (E-DII) and cadmium, tungsten and barium (all P < 0.05); macro-nutrients and cadmium, tungsten and barium (all P < 0.05); minerals and cadmium, tungsten, barium and thallium (all P < 0.05); and A vitamins and thallium (P = 0.043). Furthermore, a lower E-DII, a lower intake of carbohydrates and phosphorus, and a higher consumption of magnesium seem to attenuate the positive association between metals and glucose metabolism indexes. Our finding identifying the nutrients that interact with non-essential heavy metals could provide a feasible nutritional guideline for the general population to protect against the adverse effects of non-essential heavy metals on glucose metabolism.

Efficacy and safety of raltitrexed-eluting CalliSpheres® bead transarterial chemoembolization in patients with intermediate-stage hepatocellular carcinoma: a single-arm, prospective study.

Background: The most common loadable chemotherapeutic drugs in drug-eluting bead transarterial chemoembolization (DEB-TACE) include doxorubicin, epirubicin, etc. CalliSpheres® beads have exhibited efficient loadability and eluting characteristics for raltitrexed as well as in vitro and animal experiments. However, the efficacy and safety of raltitrexed-loaded DEB-TACE in patients with intermediate-stage hepatocellular carcinoma (HCC) remain unclear. Objectives: To assess the efficacy and safety of raltitrexed-loaded DEB-TACE in patients with intermediate-stage HCC. Design: The study was conducted as a single-arm prospective study. Methods: This study was a prospective, single-arm trial conducted between June 2019 and June 2022. CalliSpheres® beads loaded with raltitrexed were used in the DEB-TACE procedure. The follow-up lasted for at least 1 year or until death. The primary endpoint was overall survival (OS), and the secondary endpoints were time to progression (TTP), progression-free survival (PFS), objective response rate (ORR), and adverse events (AEs). Results: The 6-month ORR and disease control rates were 90.1% and 93.8%, respectively. The median OS was 33.0 months. The 1-, 2-, and 3-year survival rates were 95.1%, 82.1%, and 43.6%, respectively. Child-Pugh class and bilobar disease occurrence were identified as independent OS predictors. The median TTP and PFS were 22.7 and 19.8 months, respectively. Eleven (11.5%) patients experienced at least one grade 3 AE, and serious AEs were reported in five participants (5.2%). No patient experienced grade 4 or 5 AEs. Conclusion: Raltitrexed-loaded DEB-TACE is feasible, safe, and effective in patients with intermediate-stage HCC. Trial registration: This trial was registered at www.chictr.org.cn under the identifier: 1900024097 on 25 June 2019.

Efficacy and safety of raltitrexed-loaded DEB-TACE in patients with intermediate-stage hepatocellular carcinoma The utility of raltitrexed-loaded CalliSphere® beads in drug-eluting bead transarterial chemoembolization (DEB-TACE) has been demonstrated in in vitro and animal experiments. However, its efficacy and safety in patients with intermediate-stage hepatocellular carcinoma (HCC) remain unclear. Hence, this study aimed to assess the efficacy and safety profiles of DEB-TACE for such patients. We discovered that raltitrexed-loaded DEB-TACE led to a 6-month ORR of 90.1%, a median OS of 33.0 months, a median TTP of 22.7 months, and a median PFS of 19.8 months. The 1-, 2-, and 3-year survival rates were 95.1%, 82.1%, and 43.6%, respectively. Factors such as Child-Pugh class and bilobar disease occurrence were identified as independent predictors of OS. The study also showed acceptable safety profiles, with a low incidence of grade 3 adverse events and no grade 4 or 5 adverse events. The results indicated that raltitrexed-eluting CalliSpheres® beads for TACE can be a viable option for treating patients with intermediate-stage HCC.

Fermented Chinese Herbs Improve the Growth and Immunity of Growing Pigs through Regulating Colon Microbiota and Metabolites.

(1) Background: the development of new antibiotic substitutes to promote pig growth and health has become an important way to solve the current dilemma and promote the pig industry. (2) Methods: to assess the effects of a fermented Chinese herbal (FCH) formula on the growth and immunity of growing pigs, 100 Duroc × Landrace × Yorshire three-way crossed growing pigs were randomly divided into control and treatment groups that were fed a basal diet, and a basal diet with 1% (group A), 2% (group B), and 3% (group C) FCH formulas, respectively. A sixty-day formal experiment was conducted, and their growth and serum indices, colonic microbiota, and metabolites were analyzed. (3) Results: the daily gain of growing pigs in groups A, B, and C increased by 7.93%, 17.68%, and 19.61%, respectively, and the feed-to-gain ratios decreased by 8.33%, 15.00%, and 14.58%, respectively. Serum immunity and antioxidant activities were significantly increased in all treatment groups. Particularly, adding a 2% FCH formula significantly changed the colon's microbial structure; the Proteobacteria significantly increased and Firmicutes significantly decreased, and the metabolite composition in the colon's contents significantly changed. (4) Conclusions: these results indicate that the FCH formula is a good feed additive for growing pigs, and the recommended addition ratio was 3%.

A Semantic-Enhancement-Based Social Network User-Alignment Algorithm.

User alignment can associate multiple social network accounts of the same user. It has important research implications. However, the same user has various behaviors and friends across different social networks. This will affect the accuracy of user alignment. In this paper, we aim to improve the accuracy of user alignment by reducing the semantic gap between the same user in different social networks. Therefore, we propose a semantically enhanced social network user alignment algorithm (SENUA). The algorithm performs user alignment based on user attributes, user-generated contents (UGCs), and user check-ins. The interference of local semantic noise can be reduced by mining the user's semantic features for these three factors. In addition, we improve the algorithm's adaptability to noise by multi-view graph-data augmentation. Too much similarity of non-aligned users can have a large negative impact on the user-alignment effect. Therefore, we optimize the embedding vectors based on multi-headed graph attention networks and multi-view contrastive learning. This can enhance the similar semantic features of the aligned users. Experimental results show that SENUA has an average improvement of 6.27% over the baseline method at hit-precision30. This shows that semantic enhancement can effectively improve user alignment.

GenomicKB: a knowledge graph for the human genome.

Genomic Knowledgebase (GenomicKB) is a graph database for researchers to explore and investigate human genome, epigenome, transcriptome, and 4D nucleome with simple and efficient queries. The database uses a knowledge graph to consolidate genomic datasets and annotations from over 30 consortia and portals, including 347 million genomic entities, 1.36 billion relations, and 3.9 billion entity and relation properties. GenomicKB is equipped with a web-based query system (https://gkb.dcmb.med.umich.edu/) which allows users to query the knowledge graph with customized graph patterns and specific constraints on entities and relations. Compared with traditional tabular-structured data stored in separate data portals, GenomicKB emphasizes the relations among genomic entities, intuitively connects isolated data matrices, and supports efficient queries for scientific discoveries. GenomicKB transforms complicated analysis among multiple genomic entities and relations into coding-free queries, and facilitates data-driven genomic discoveries in the future.

Effects of Fermented Bamboo Shoot Processing Waste on Growth Performance, Serum Parameters, and Gut Microbiota of Weaned Piglets.

Gut microbiota (GM) plays a vital role in the nutrition and metabolism of weaned piglets. Some feed additives can be used to adjust the composition of GM to improve the health of weaned piglets. In this study, we investigated the effects of adding fermented bamboo shoot processing waste (FBSPW) to diet on growth performance, serum parameters, and GM of weaned piglets. Seventy-two piglets were divided into four groups and were fed diets containing 0% (control), 4% (group A), 8% (group B), and 12% (group C) FBSPW for 50 days. We found that the addition of FBSPW significantly decreased the average daily feed intake, serum triglyceride content, and urea nitrogen of weaned piglets compared to the control. The cecum and cecal microbiota of weaned piglets fed the basal diet with 12% FBSPW were significantly different compared to the control. A basal diet with 12% FBSPW significantly reduced the taxon feature number, and the relative abundance of Tenericutes in the cecum and cecal microbiota of weaned piglets compared with the control. The addition of 12% FBSPW to weaned piglet feed could improve their nitrogen and lipid metabolisms and have beneficial effects on GM.

NucleoMap: A computational tool for identifying nucleosomes in ultra-high resolution contact maps.

Although poorly positioned nucleosomes are ubiquitous in the eukaryotic genome, they are difficult to identify with existing nucleosome identification methods. Recently available enhanced high-throughput chromatin conformation capture techniques such as Micro-C, DNase Hi-C, and Hi-CO characterize nucleosome-level chromatin proximity, probing the positions of mono-nucleosomes and the spacing between nucleosome pairs at the same time, enabling nucleosome profiling in poorly positioned regions. Here we develop a novel computational approach, NucleoMap, to identify nucleosome positioning from ultra-high resolution chromatin contact maps. By integrating nucleosome read density, contact distances, and binding preferences, NucleoMap precisely locates nucleosomes in both prokaryotic and eukaryotic genomes and outperforms existing nucleosome identification methods in both precision and recall. We rigorously characterize genome-wide association in eukaryotes between the spatial organization of mono-nucleosomes and their corresponding histone modifications, protein binding activities, and higher-order chromatin functions. We also find evidence of two tetra-nucleosome folding structures in human embryonic stem cells and analyze their association with multiple structural and functional regions. Based on the identified nucleosomes, nucleosome contact maps are constructed, reflecting the inter-nucleosome distances and preserving the contact distance profiles in original contact maps.

The Negative Effects of Long Time Physical Activity Calorie Equivalent Labeling on Purchase Intention for Unhealthy Food.

(1) Background: Obesity has become a global epidemic that arouse much attention from governments, companies and scholar. Physical activity calorie equivalent (PACE) labels are introduced as a more effective nudge invention on less-calorie ordering. However, the effects of PACE labels are controversial in previous literature, thus, the research objective is to explore the effects of different PACE labels and furtherly to explore the underlying psychological mechanism; (2) Methods: Across four scenario-based experiments, involving potato chips, chocolate and cookies, this study manipulated the three calorie-information labeling (standard calorie label, long time PACE and short time PACE labels). Meanwhile, the mediating mechanism of the effects involving anticipatory guilt and the moderation effects between consumers' future self-continuity and PACE labels are also measured; (3) Results: Results show that compared with the short time PACE and calorie labels, the longtime PACE labels have more negative influence on consumers' purchase intention for unhealthy food. What's more, the anticipatory guilt has negative effect of PACE labels as consumers are often prone to feeling guilty in the process of unhealthy food consumption. In addition, individuals with high future self-continuity have higher self-control and take more consideration of future outcomes, they are reluctant to choose unhealthy food than others; (4) Conclusions: Unhealthy food with a long time PACE label has more negative effect on consumers' purchase intention rather than a short time PACE label. At the same time, companies that produce healthy foods should actively participate in the movement to label calories through the PACE labels.

p53 inactivation unmasks histone methylation-independent WDR5 functions that drive self-renewal and differentiation of pluripotent stem cells.

p53 alterations occur during culture of pluripotent stem cells (PSCs), but the significance of these events on epigenetic control of PSC fate determination remains poorly understood. Wdr5 deletion in p53-null (DKO) mouse ESCs (mESCs) leads to impaired self-renewal, defective retinal neuroectoderm differentiation, and de-repression of germ cell/meiosis (GCM)-specific genes. Re-introduction of a WDR5 mutant with defective H3K4 methylation activity into DKO ESCs restored self-renewal and suppressed GCM gene expression but failed to induce retinal neuroectoderm differentiation. Mechanistically, mutant WDR5 targets chromatin that is largely devoid of H3K4me3 and regulates gene expression in p53-null mESCs. Furthermore, MAX and WDR5 co-target lineage-specifying chromatin and regulate chromatin accessibility of GCM-related genes. Importantly, MAX and WDR5 are core subunits of a non-canonical polycomb repressor complex 1 responsible for gene silencing. This function, together with canonical, pro-transcriptional WDR5-dependent MLL complex H3K4 methyltransferase activity, highlight how WDR5 mediates crosstalk between transcription and repression during mESC fate choice.

Ray tracing method for removing sidelobe laser interference in AOTF-based hyperspectral imaging.

The sidelobe phenomenon of acousto-optic tunable filter (AOTF)-based hyperspectral imaging is the result of the phase mismatching condition, which will reduce the quality of hyperspectral imaging data. This phenomenon can be observed in two specified scenes, namely, high brightness panchromatic target imaging and high brightness monochromatic target imaging. In this paper, the acousto-optic interaction in these two scenes is discussed using the phase matching condition. As a follow-up work of the previous related research, this paper studies laser interference in AOTF imaging, which is a typical example of the second case. A method to remove laser sidelobes in AOTF-based hyperspectral imaging is proposed, which combines a series of procedures including laser point extraction, reverse imaging before AOTF, ray tracing in AOTF, forward imaging process after AOTF, and laser elimination. Experimental results have verified the effectiveness of the proposed method.

Less Is Better: How Nutrition and Low-Carbon Labels Jointly Backfire on the Evaluation of Food Products.

(1) Background: Labeling is one of the significant strategies to guide sustainable consumption behaviors. Nowadays, multi labels being displayed on the front-of-pack of food products is a common phenomenon. However, labels seldom operate solo, and competition or complement effects may be exerted on different labels. Therefore, the research objective is to explore the interaction effect when nutrition and low-carbon labels appear simultaneously; (2) Methods: Across four scenario-based experiments, including ice cream, yogurt, steak, and toast, this study manipulated the separate and joint occurrences of low-carbon and nutrition labels, the interaction effect of joint labels was tested, and the serial mediation model, which includes resource allocation and anticipated enjoyment of food consumption, was verified; (3) Results: Results show that people have a positive preference for the nutrition label and the carbon label, respectively, while these two labels working simultaneously attenuate the positive effect of the single label. When facing nutrition and carbon labels simultaneously, people would infer partial resources are allocated to healthy and environmental aspects so they have a lower anticipated enjoyment from food consumption. Thus, these two labels working simultaneously attenuate the positive effect of the single label, and consumers have a lower evaluation of food products. In addition, the joint backfire on the effect is only exerted on people with a higher level of zero-sum bias and only when joint labels have a high consistency of labels; (4) Conclusions: This study solved the contradictory problem of the joint effect of positive labels. The findings in this research contribute to promote sustainable food consumption. We suggest that similar labels should be avoided in the same front-of-pack of food, and manufacturers need to use ads to bring down consumers' zero-sum bias.

The Differential Effects of Physical Activity Calorie Equivalent Labeling on Consumer Preferences for Healthy and Unhealthy Food Products: Evidence from a Choice Experiment.

Background: Since numerical calorie labels have limited effects on less-calorie food ordering, an alternative called physical activity calorie equivalent (PACE) labels, which exhibit calories using visible symbols and the minutes of exercise to burn off the calories, may be more effective in reducing calories ordered. Methods: By using a choice experiment (CE) approach, the aims of this study were to estimate the effects of PACE labels on consumer preferences for healthy and unhealth food. Red date walnuts and potato chips were used as the representatives of healthy and unhealthy foods respectively in this study. Moreover, future time perspective (FTP) is an individual trait variable of consumers, which has been recognized as a significant driver of healthy behaviors. We also included FTP into the interaction with PACE labels. Results: Firstly, the results were opposite between the healthy and unhealthy food groups. Respondents showed significantly more positive attitudes toward red date walnuts (i.e., healthy food) with PACE labels, while they showed significantly more negative preferences for chips (i.e., unhealthy food) with PACE labels. Secondly, people with higher FTP are preferred red date walnuts with PACE labels, while PACE labels on chips could undermine the preferences of respondents with higher FTP. Thirdly, we found that women (vs. men) were less inclined to choose healthy food with standard calorie labels and labels showing the minutes of running to burn off the calories, as well as that the elderly (vs. younger) people in the healthy food group preferred the labels showing the minutes of running to burn off the calories. People with a higher body mass index (BMI) were reluctant to purchase walnuts with the information about the minutes of walking. Conclusions: Results from this study showed that PACE labels have significant effects on consumers' preferences for food products.

Spectral content (colour) of noise exposure affects work efficiency.

INTRODUCTION: As part of an effort to enhance the efficiency of workers, experiments relating to three types of noise exposure were conducted. Previous studies have proved that pink noise can cause a brain wave to reach a lower potential. In this study, we utilized physical methods, in cognitive experiments, to understand the impacts that three colour noises have on working efficiency. SUBJECTS AND METHODS: All 22 participants were exposed to a sound environment of quiet, red, pink and white noises respectively. After a laboratory experiment, details of psychomotor speed, continuous performance, executive function and working memory were recorded. RESULTS: Red, pink and white noises were significantly positive in comparison with the quiet environment of the psychomotor speed test. As for the continuous performance test, pink noise gave the only significantly positive result. Red, pink and white noise resulted in a better executive function test. Red and pink noise showed significantly positive improvement, while white noise was significantly positive in comparison with the quiet environment of the working memory test. In addition, the results from the comfort questionnaires showed that red and pink noise increase the possibility of better judgment, implementation, and overall environment. CONCLUSION: At present time, it is considered that noise has negative effects on hearing and health. However, experimental results show that certain noise can enhance environmental comfort. It is feasible, in the future, to use knowledge of colour noises to improve productivity in a workplace with a healthy environment.

Portable Sleep Apnea Syndrome Screening and Event Detection Using Long Short-Term Memory Recurrent Neural Network.

Obstructive sleep apnea/hypopnea syndrome (OSAHS) is characterized by repeated airflow partial reduction or complete cessation due to upper airway collapse during sleep. OSAHS can induce frequent awake and intermittent hypoxia that is associated with hypertension and cardiovascular events. Full-channel Polysomnography (PSG) is the gold standard for diagnosing OSAHS; however, this PSG evaluation process is unsuitable for home screening. To solve this problem, a measuring module integrating abdominal and thoracic triaxial accelerometers, a pulsed oximeter (SpO2) and an electrocardiogram sensor was devised in this study. Moreover, a long short-term memory recurrent neural network model is proposed to classify four types of sleep breathing patterns, namely obstructive sleep apnea (OSA), central sleep apnea (CSA), hypopnea (HYP) events and normal breathing (NOR). The proposed algorithm not only reports the apnea-hypopnea index (AHI) through the acquired overnight signals but also identifies the occurrences of OSA, CSA, HYP and NOR, which assists in OSAHS diagnosis. In the clinical experiment with 115 participants, the performances of the proposed system and algorithm were compared with those of traditional expert interpretation based on PSG signals. The accuracy of AHI severity group classification was 89.3%, and the AHI difference for PSG expert interpretation was 5.0±4.5. The overall accuracy of detecting abnormal OSA, CSA and HYP events was 92.3%.

p53 Integrates Temporal WDR5 Inputs during Neuroectoderm and Mesoderm Differentiation of Mouse Embryonic Stem Cells.

How ubiquitous transcription factors (TFs) coordinate temporal inputs from broadly expressed epigenetic factors to control cell fate remains poorly understood. Here, we uncover a molecular relationship between p53, an abundant embryonic TF, and WDR5, an essential member of the MLL chromatin modifying complex, that regulates mouse embryonic stem cell fate. Wild-type Wdr5 or transient Wdr5 knockout promotes a distinct pattern of global chromatin accessibility and spurs neuroectodermal differentiation through an RbBP5-dependent process in which WDR5 binds to, and activates transcription of, neural genes. Wdr5 rescue after its prolonged inhibition targets WDR5 to mesoderm lineage-specifying genes, stimulating differentiation toward mesoderm fates in a p53-dependent fashion. Finally, we identify a direct interaction between WDR5 and p53 that enables their co-recruitment to, and regulation of, genes known to control cell proliferation and fate. Our results unmask p53-dependent mechanisms that temporally integrate epigenetic WDR5 inputs to drive neuroectoderm and mesoderm differentiation from pluripotent cells.

Jointly Embedding Multiple Single-Cell Omics Measurements.

Many single-cell sequencing technologies are now available, but it is still difficult to apply multiple sequencing technologies to the same single cell. In this paper, we propose an unsupervised manifold alignment algorithm, MMD-MA, for integrating multiple measurements carried out on disjoint aliquots of a given population of cells. Effectively, MMD-MA performs an in silico co-assay by embedding cells measured in different ways into a learned latent space. In the MMD-MA algorithm, single-cell data points from multiple domains are aligned by optimizing an objective function with three components: (1) a maximum mean discrepancy (MMD) term to encourage the differently measured points to have similar distributions in the latent space, (2) a distortion term to preserve the structure of the data between the input space and the latent space, and (3) a penalty term to avoid collapse to a trivial solution. Notably, MMD-MA does not require any correspondence information across data modalities, either between the cells or between the features. Furthermore, MMD-MA's weak distributional requirements for the domains to be aligned allow the algorithm to integrate heterogeneous types of single cell measures, such as gene expression, DNA accessibility, chromatin organization, methylation, and imaging data. We demonstrate the utility of MMD-MA in simulation experiments and using a real data set involving single-cell gene expression and methylation data.

Phenotype-Based and Self-Learning Inter-Individual Sleep Apnea Screening With a Level IV-Like Monitoring System.

Purpose: We propose a phenotype-based artificial intelligence system that can self-learn and is accurate for screening purposes and test it on a Level IV-like monitoring system. Methods: Based on the physiological knowledge, we hypothesize that the phenotype information will allow us to find subjects from a well-annotated database that share similar sleep apnea patterns. Therefore, for a new-arriving subject, we can establish a prediction model from the existing database that is adaptive to the subject. We test the proposed algorithm on a database consisting of 62 subjects with the signals recorded from a Level IV-like wearable device measuring the thoracic and abdominal movements and the SpO2. Results: With the leave-one-subject-out cross validation, the accuracy of the proposed algorithm to screen subjects with an apnea-hypopnea index greater or equal to 15 is 93.6%, the positive likelihood ratio is 6.8, and the negative likelihood ratio is 0.03. Conclusion: The results confirm the hypothesis and show that the proposed algorithm has potential to screen patients with SAS.

A Two-Stage Reconstruction Processor for Human Detection in Compressive Sensing CMOS Radar.

Complementary metal-oxide-semiconductor (CMOS) radar has recently gained much research attraction because small and low-power CMOS devices are very suitable for deploying sensing nodes in a low-power wireless sensing system. This study focuses on the signal processing of a wireless CMOS impulse radar system that can detect humans and objects in the home-care internet-of-things sensing system. The challenges of low-power CMOS radar systems are the weakness of human signals and the high computational complexity of the target detection algorithm. The compressive sensing-based detection algorithm can relax the computational costs by avoiding the utilization of matched filters and reducing the analog-to-digital converter bandwidth requirement. The orthogonal matching pursuit (OMP) is one of the popular signal reconstruction algorithms for compressive sensing radar; however, the complexity is still very high because the high resolution of human respiration leads to high-dimension signal reconstruction. Thus, this paper proposes a two-stage reconstruction algorithm for compressive sensing radar. The proposed algorithm not only has lower complexity than the OMP algorithm by 75% but also achieves better positioning performance than the OMP algorithm especially in noisy environments. This study also designed and implemented the algorithm by using Vertex-7 FPGA chip (Xilinx, San Jose, CA, USA). The proposed reconstruction processor can support the 256 × 13 real-time radar image display with a throughput of 28.2 frames per second.

Sleep Apnea Detection Based on Thoracic and Abdominal Movement Signals of Wearable Piezo-Electric Bands.

Physiologically, the thoracic (THO) and abdominal (ABD) movement signals, captured using wearable piezo-electric bands, provide information about various types of apnea, including central sleep apnea (CSA) and obstructive sleep apnea (OSA). However, the use of piezo-electric wearables in detecting sleep apnea events has been seldom explored in the literature. This study explored the possibility of identifying sleep apnea events, including OSA and CSA, by solely analyzing one or both the THO and ABD signals. An adaptive non-harmonic model was introduced to model the THO and ABD signals, which allows us to design features for sleep apnea events. To confirm the suitability of the extracted features, a support vector machine was applied to classify three categories - normal and hypopnea, OSA, and CSA. According to a database of 34 subjects, the overall classification accuracies were on average 75.9%±11.7% and 73.8%±4.4%, respectively, based on the cross validation. When the features determined from the THO and ABD signals were combined, the overall classification accuracy became 81.8%±9.4%. These features were applied for designing a state machine for online apnea event detection. Two event-byevent accuracy indices, S and I, were proposed for evaluating the performance of the state machine. For the same database, the S index was 84.01%±9.06%, and the I index was 77.21%±19.01%. The results indicate the considerable potential of applying the proposed algorithm to clinical examinations for both screening and homecare purposes.

A UWB Radar Signal Processing Platform for Real-Time Human Respiratory Feature Extraction Based on Four-Segment Linear Waveform Model.

This paper presents an ultra-wideband (UWB) impulse-radio radar signal processing platform used to analyze human respiratory features. Conventional radar systems used in human detection only analyze human respiration rates or the response of a target. However, additional respiratory signal information is available that has not been explored using radar detection. The authors previously proposed a modified raised cosine waveform (MRCW) respiration model and an iterative correlation search algorithm that could acquire additional respiratory features such as the inspiration and expiration speeds, respiration intensity, and respiration holding ratio. To realize real-time respiratory feature extraction by using the proposed UWB signal processing platform, this paper proposes a new four-segment linear waveform (FSLW) respiration model. This model offers a superior fit to the measured respiration signal compared with the MRCW model and decreases the computational complexity of feature extraction. In addition, an early-terminated iterative correlation search algorithm is presented, substantially decreasing the computational complexity and yielding negligible performance degradation. These extracted features can be considered the compressed signals used to decrease the amount of data storage required for use in long-term medical monitoring systems and can also be used in clinical diagnosis. The proposed respiratory feature extraction algorithm was designed and implemented using the proposed UWB radar signal processing platform including a radar front-end chip and an FPGA chip. The proposed radar system can detect human respiration rates at 0.1 to 1 Hz and facilitates the real-time analysis of the respiratory features of each respiration period.