Radar-based non-contact health monitoring technology (RBNHMT) has emerged as a transformative paradigm in continuous health sensing, enabling non-invasive and continuous monitoring of physiological parameters and behavioral patterns by transmitting electromagnetic waves, analyzing the reflected signals, and detecting subtle bodily movements—ranging from millimeter-scale chest wall displacements due to respiration to micro-scale vibrations associated with cardiac activity—ultimately transforming them into quantifiable health data. Distinguished by its non-contact operation, inherent privacy preservation, and adaptability to diverse scenarios, RBNHMT exhibits stronger resistance to environmental interference than conventional contact-based monitoring, and has solidified its position as a prominent and dynamic research focus in the field of non-contact health monitoring. Currently, significant and multifaceted progress has been made across several key areas. In human activity recognition (HAR), systems leveraging micro-Doppler signatures or point cloud sequences achieve high-precision detection of gait, gestures, and fall events, with state-of-the-art deep learning-based models achieving accuracy rates exceeding 99% in controlled experimental settings. For vital sign and sleep monitoring, it not only tracks respiratory and heart rates continuously but also extracts clinically relevant metrics such as heart rate variability (HRV) for autonomic nervous system assessment and estimates blood pressure through indirect methods like pulse transit time analysis, while maintaining robustness in dynamic settings through advanced motion compensation algorithms. In sleep monitoring, it further enables sleep posture classification and apnea event detection. In emotion and stress recognition, it provides a non-intrusive approach for psychological assessment by analyzing autonomic-response physiological signal patterns or behavioral features. Furthermore, its applications in auxiliary medical diagnosis have expanded to promising interdisciplinary areas such as non-contact heart sound auscultation, radar-based screening for obstructive sleep apnea (OSA), and emerging research into breast cancer detection using microwave and millimeter-wave imaging techniques. However, several challenges impede its practical deployment. Signal quality is significantly compromised by multipath interference in complex indoor environments and clutter from static objects, and by motion artifacts in dynamic scenarios where gross body movements obscure the subtle physiological signals. Algorithmically, separating signals from multiple targets in close proximity and calibrating for substantial individual physiological differences, such as body habitus, baseline vital signs, remain difficult and limit generalizability. Hardware design also faces the challenge of balancing power consumption, cost, integration, and performance, often requiring trade-offs that constrain miniaturization, battery life, or measurement sensitivity. Future advancement, therefore, requires collaborative and targeted innovation across multiple dimensions. Algorithmically, developing adaptive signal processing models based on emerging paradigms such as few-shot learning (for user-specific calibration with minimal data) and reinforcement learning (for dynamic noise suppression) is essential. At the hardware level, highly integrated radar SoCs with embedded processing capabilities and advanced packaging technologies are crucial for achieving the dual goals of device miniaturization and cost reduction without sacrificing performance. At the system level, fusing radar data with complementary modalities such as infrared and acoustic sensing can create a synergistic, multi-modal framework that significantly enhances perceptual robustness and reliability in complex, real-world environments. This review provides a comprehensive synthesis that systematically summarizes the relevant theoretical foundations and application progress, and offers an in-depth analysis of the current technical bottlenecks. It aims to provide a clear development path and a foundational academic reference for the in-depth integration and practical application of RBNHMT in critical scenarios including rehabilitation engineering, smart elderly care, in-vehicle health monitoring, and beyond, thereby offering innovative technical support for the vision of universal, proactive, and personalized health management.

OBJECTIVE To optimize the extraction process of flavonoids from Potentilla discolor .METHODS Deep eutectic solvents （DESs） were used as the extraction solvent to prepare test sample solutions. The contents of rutin， quercitrin， and kaempferol were determined by ultra-performance liquid chromatography. The analytic hierarchy process combined with the criteria importance through intercriteria correlation weighting method was employed to assign comprehensive weights to the contents of the three flavonoids， and calculate the comprehensive score. The optimal DESs were screened based on the comprehensive score.Mean while， using the comprehensive score as the response variable and the liquid-to-solid ratio， ultrasonic time， and urltrasonic temperature as the influencing factors， the extraction technology of flavonoids from P.discolor was optimized by Box-Behnken response surface methodology and subsequently validated.RESULTS The comprehensive weight coefficients of rutin， quercitrin， and kaempferol were 0.646 7， 0.207 5， and 0.145 8， respectively. The optimal DESs were choline chloride-lactic acid （molar ratio 1∶4） with a water content of 40%. The optimal extraction conditions were determined as follows： liquid-to-solid ratio of 25∶1， ultrasonic time of 40 min， and ultrasonic temperature of 50 ℃. The validation results showed that the average comprehensive score of three batches of samples was 99.28， with an RSD of 0.54% （ n ＝3）.CONCLUSIONS The optimal extraction technology of flavonoids from P. discolor based on DESs obtained in this study was stable and feasible.

To evaluate long-term survival and clinical outcomes of patients with knee osteo-arthritis undergoing total knee arthroplasty (TKA) through long-term follow-up.

Objective To investigate the factors influencing the prognosis of patients with cere-bral infarction(CI)and nursing risk management measures.Methods A retrospective analysis was conducted in 80 CI patients as study subjects.All patients underwent risk management,and their prognosis was assessed,with 58 patients in good prognosis group and 22 patients in poor prognosis group.General patient data and disease-related characteristics were collected,and differences were ana-lyzed using the Logistic regression equation to identify factors influencing patient prognosis.A receiver operating characteristic(ROC)curve was plotted to analyze the predictive value of these factors for poor prognosis.Results There were statistically significant differences between the poor prognosis group and the good prognosis group in terms of age,baseline National Institutes of Health Stroke Scale(NIHSS)score,and the presence of comorbid hypertension(P＜0.05).Logistic regression analysis revealed that these indicators were all influencing factors for poor prognosis in patients,with area under the curve val-ues ranging from 0.676 to 0.723,indicating high sensitivity and specificity.Conclusion Multiple factors,such as age,baseline NIHSS score,and comorbid hypertension,influence poor prognosis in CI patients and have certain predictive value for poor prognosis.

OBJECTIVE: The study aim was to investigate the effects of exposure to multiple environmental organic pollutants on cardiopulmonary health with a focus on the potential mediating role of oxidative stress. METHODS: A repeated-measures randomized crossover study involving healthy college students in Beijing was conducted. Biological samples, including morning urine and venous blood, were collected to measure concentrations of 29 typical organic pollutants, including hydroxy polycyclic aromatic hydrocarbons (OH-PAHs), bisphenol A and its substitutes, phthalates and their metabolites, parabens, and five biomarkers of oxidative stress. Health assessments included blood pressure measurements and lung function indicators. RESULTS: Urinary concentrations of 2-hydroxyphenanthrene (2-OH-PHE) ( β = 4.35% [95% confidence interval ( CI): 0.85%, 7.97%]), 3-hydroxyphenanthrene ( β = 3.44% [95% CI: 0.19%, 6.79%]), and 4-hydroxyphenanthrene (4-OH-PHE) ( β = 5.78% [95% CI: 1.27%, 10.5%]) were significantly and positively associated with systolic blood pressure. Exposures to 1-hydroxypyrene (1-OH-PYR) ( β = 3.05% [95% CI: -4.66%, -1.41%]), 2-OH-PHE ( β = 2.68% [95% CI: -4%, -1.34%]), and 4-OH-PHE ( β = 3% [95% CI: -4.68%, -1.29%]) were negatively associated with the ratio of forced expiratory volume in the first second to forced vital capacity. These findings highlight the adverse effects of exposure to multiple pollutants on cardiopulmonary health. Biomarkers of oxidative stress, including 8-hydroxy-2'-deoxyguanosine and extracellular superoxide dismutase, mediated the effects of multiple OH-PAHs on blood pressure and lung function. CONCLUSION Exposure to multiple organic pollutants can adversely affect cardiopulmonary health. Oxidative stress is a key mediator of the effects of OH-PAHs on blood pressure and lung function.
Humans ; Oxidative Stress/drug effects* ; Male ; Cross-Over Studies ; Female ; Young Adult ; Environmental Pollutants/toxicity* ; Environmental Exposure/adverse effects* ; Biomarkers/blood* ; Adult ; Blood Pressure/drug effects* ; Polycyclic Aromatic Hydrocarbons/urine* ; Beijing

Objective A scoping review of studies on pulmonary prehabilitation in cardiac surgery patients was conducted to provide evidence support for the construction of a preoperative pulmonary rehabilitation program for cardiac surgery patients that suitable for China's national conditions.Methods In accordance with the scope review's research methodologies,databases including PubMed,Embase,Web of Science,CINAHL,CNKI and Wanfang were searched by the computer for relevant studies.The deadline for retrieval is from the establishment of databases to June,2024.The included literature was systematically analyzed.Results 26 articles were finally included.Among them,4 were quasi-experiment studies,while the other 22 were randomized controlled trials.Forms of the intervention included comprehensive breathing exercises,inspiratory muscle training,positive expiratory pressure,incentive spirometer training and balloon blowing training.The intervention initiation ranged from 10 weeks to 1 day preoperatively;the outcome measures included postoperative pulmonary complications,lung function metrics,the 6-Minute Walk Test,duration of mechanical ventilation,length of hospital stay,patient-reported outcomes and so on.Conclusion There remains a deficiency in standardized protocols for preoperative pulmonary rehabilitation training among patients undergoing cardiac surgery.High-quality studies should be conducted,and intervention strategies for pulmonary prehabilitation in cardiac surgery patients should be optimized and a unified evaluation standard system should be established.

AIM To establish a UPLC-MS/MS method for the simultaneous content determination of liquiritin,liquiritin apioside,verbascoside,narirutin,isoacteoside,apigetrin,hesperidin,isoliquiritin,ononin,liquiritigenin,glycyrrhizic acid,isoliquiritigenin,honokiol,obovatol,pogostone and magnolol in Jiawei Huoxiang Zhengqi Soft Capsules.METHODS The analysis was performed on a 40 ℃ thermostatic ZORBAX Eclipse Plus C18 column(2.1 mm×100 mm,1.8 μm),with the mobile phase comprising of 0.1％formic acid-acetonitrile flowing at 0.4 mL/min in a gradient elution manner,and electron spray ionization source was adopted in positive and negative ion scanning with multiple reaction monitoring mode.RESULTS Sixteen constituents showed good linear relationships within their own ranges(r＞0.990 0),whose average recoveries were 83.74％-105.12％with the RSDs of 1.10％-4.8％.CONCLUSION This accurate,sensitive,stable and reproducible method can provide a reference for the overall quality control of Jiawei Huoxiang Zhengqi Soft Capsules.