Developing a deep learning model for sleep stage prediction in obstructive sleep apnea cohort using 60 GHz frequency-modulated continuous-wave radar.

Given the significant impact of sleep on overall health, radar technology offers a promising, non-invasive, and cost-effective avenue for the early detection of sleep disorders, even prior to relying on polysomnography (PSG)-based classification. In this study, we employed an attention-based bidirectional long short-term memory (Attention Bi-LSTM) model to accurately predict sleep stages using 60 GHz frequency-modulated continuous-wave (FMCW) radar. Our dataset comprised 78 participants from an ongoing obstructive sleep apnea (OSA) cohort, recruited between July 2021 and November 2022, who underwent overnight polysomnography alongside radar sensor monitoring. The dataset encompasses comprehensive polysomnography recordings, spanning both sleep and wakefulness states. The predictions achieved a Cohen's kappa coefficient of 0.746 and an overall accuracy of 85.2% in classifying wakefulness, rapid-eye-movement (REM) sleep, and non-REM (NREM) sleep (N1 + N2 + N3). The results demonstrated that the models incorporating both Radar 1 and Radar 2 data consistently outperformed those using only Radar 1 data, indicating the potential benefits of utilising multiple radars for sleep stage classification. Although the performance of the models tended to decline with increasing OSA severity, the addition of Radar 2 data notably improved the classification accuracy. These findings demonstrate the potential of radar technology as a valuable screening tool for sleep stage classification.

Non-Contact VITAL Signs Monitoring of a Patient Lying on Surgical Bed Using Beamforming FMCW Radar.

Respiration and heartrates are important information for surgery. When the vital signs of the patient lying prone are monitored using radar installed on the back of the surgical bed, the surgeon's movements reduce the accuracy of these monitored vital signs. This study proposes a method for enhancing the monitored vital sign accuracies of a patient lying on a surgical bed using a 60 GHz frequency modulated continuous wave (FMCW) radar system with beamforming. The vital sign accuracies were enhanced by applying a fast Fourier transform (FFT) for range and beamforming which suppress the noise generated at different ranges and angles from the patient's position. The experiment was performed for a patient lying on a surgical bed with or without surgeon. Comparing a continuous-wave (CW) Doppler radar, the FMCW radar with beamforming improved almost 22 dB of signal-to-interference and noise ratio (SINR) for vital signals. More than 90% accuracy of monitoring respiration and heartrates was achieved even though the surgeon was located next to the patient as an interferer. It was analyzed using a proposed vital signal model included in the radar IF equation.

Automated Detection of Sleep Apnea-Hypopnea Events Based on 60 GHz Frequency-Modulated Continuous-Wave Radar Using Convolutional Recurrent Neural Networks: A Preliminary Report of a Prospective Cohort Study.

Radar is a promising non-contact sensor for overnight polysomnography (PSG), the gold standard for diagnosing obstructive sleep apnea (OSA). This preliminary study aimed to demonstrate the feasibility of the automated detection of apnea-hypopnea events for OSA diagnosis based on 60 GHz frequency-modulated continuous-wave radar using convolutional recurrent neural networks. The dataset comprised 44 participants from an ongoing OSA cohort, recruited from July 2021 to April 2022, who underwent overnight PSG with a radar sensor. All PSG recordings, including sleep and wakefulness, were included in the dataset. Model development and evaluation were based on a five-fold cross-validation. The area under the receiver operating characteristic curve for the classification of 1-min segments ranged from 0.796 to 0.859. Depending on OSA severity, the sensitivities for apnea-hypopnea events were 49.0-67.6%, and the number of false-positive detections per participant was 23.4-52.8. The estimated apnea-hypopnea index showed strong correlations (Pearson correlation coefficient = 0.805-0.949) and good to excellent agreement (intraclass correlation coefficient = 0.776-0.929) with the ground truth. There was substantial agreement between the estimated and ground truth OSA severity (kappa statistics = 0.648-0.736). The results demonstrate the potential of radar as a standalone screening tool for OSA.

Systemic PEGylated TRAIL treatment ameliorates liver cirrhosis in rats by eliminating activated hepatic stellate cells.

UNLABELLED: Liver fibrosis is a common outcome of chronic liver disease that leads to liver cirrhosis and hepatocellular carcinoma. No US Food and Drug Administration-approved targeted antifibrotic therapy exists. Activated hepatic stellate cells (aHSCs) are the major cell types responsible for liver fibrosis; therefore, eradication of aHSCs, while preserving quiescent HSCs and other normal cells, is a logical strategy to stop and/or reverse liver fibrogenesis/fibrosis. However, there are no effective approaches to specifically deplete aHSCs during fibrosis without systemic toxicity. aHSCs are associated with elevated expression of death receptors and become sensitive to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-induced cell death. Treatment with recombinant TRAIL could be a potential strategy to ameliorate liver fibrosis; however, the therapeutic application of recombinant TRAIL is halted due to its very short half-life. To overcome this problem, we previously generated PEGylated TRAIL (TRAILPEG ) that has a much longer half-life in rodents than native-type TRAIL. In this study, we demonstrate that intravenous TRAILPEG has a markedly extended half-life over native-type TRAIL in nonhuman primates and has no toxicity in primary human hepatocytes. Intravenous injection of TRAILPEG directly induces apoptosis of aHSCs in vivo and ameliorates carbon tetrachloride-induced fibrosis/cirrhosis in rats by simultaneously down-regulating multiple key fibrotic markers that are associated with aHSCs. CONCLUSION: TRAIL-based therapies could serve as new therapeutics for liver fibrosis/cirrhosis and possibly other fibrotic diseases. (Hepatology 2016;64:209-223).

Epoxy-based multifunctional solid polymer electrolytes for structural batteries and supercapacitors. a short review.

The potential applications of epoxy-based solid polymer electrolytes are continually expanding because of their versatile characteristics. These characteristics include mechanical rigidity, nonvolatility, nonflammability, and electrochemical stability. However, it is worth noting that pure epoxy-based solid polymer electrolytes inherently exhibit lower ion transport capabilities when compared to traditional liquid electrolytes. Striking a balance between high mechanical integrity and superior ionic conductivity at room temperature poses a significant challenge. In light of this challenge, this review is dedicated to elucidating the fundamental concepts of epoxy-based solid polymer electrolytes. It will explore various preparation techniques, the incorporation of different nanomaterials into epoxy-based solid polymer electrolytes, and an evaluation of their multifunctional properties. This comprehensive evaluation will cover both mechanical and electrical properties with a specific focus on their potential applications in batteries and structural supercapacitors.