Electronic Skin for Health Monitoring Systems: Properties, Functions, and Applications.

Electronic skin (e-skin), a skin-like wearable electronic device, holds great promise in the fields of telemedicine and personalized healthcare because of its good flexibility, biocompatibility, skin conformability, and sensing performance. E-skin can monitor various health indicators of the human body in real time and over the long term, including physical indicators (exercise, respiration, blood pressure, etc.) and chemical indicators (saliva, sweat, urine, etc.). In recent years, the development of various materials, analysis, and manufacturing technologies has promoted significant development of e-skin, laying the foundation for the application of next-generation wearable medical technologies and devices. Herein, the properties required for e-skin health monitoring devices to achieve long-term and precise monitoring and summarize several detectable indicators in the health monitoring field are discussed. Subsequently, the applications of integrated e-skin health monitoring systems are reviewed. Finally, current challenges and future development directions in this field are discussed. This review is expected to generate great interest and inspiration for the development and improvement of e-skin and health monitoring systems.

Dynamic cerebral blood flow assessment based on electromagnetic coupling sensing and image feature analysis.

Dynamic assessment of cerebral blood flow (CBF) is crucial for guiding personalized management and treatment strategies, and improving the prognosis of stroke. However, a safe, reliable, and effective method for dynamic CBF evaluation is currently lacking in clinical practice. In this study, we developed a CBF monitoring system utilizing electromagnetic coupling sensing (ECS). This system detects variations in brain conductivity and dielectric constant by identifying the resonant frequency (RF) in an equivalent circuit containing both magnetic induction and electrical coupling. We evaluated the performance of the system using a self-made physical model of blood vessel pulsation to test pulsatile CBF. Additionally, we recruited 29 healthy volunteers to monitor cerebral oxygen (CO), cerebral blood flow velocity (CBFV) data and RF data before and after caffeine consumption. We analyzed RF and CBFV trends during immediate responses to abnormal intracranial blood supply, induced by changes in vascular stiffness, and compared them with CO data. Furthermore, we explored a method of dynamically assessing the overall level of CBF by leveraging image feature analysis. Experimental testing substantiates that this system provides a detection range and depth enhanced by three to four times compared to conventional electromagnetic detection techniques, thereby comprehensively covering the principal intracranial blood supply areas. And the system effectively captures CBF responses under different intravascular pressure stimulations. In healthy volunteers, as cerebral vascular stiffness increases and CO decreases due to caffeine intake, the RF pulsation amplitude diminishes progressively. Upon extraction and selection of image features, widely used machine learning algorithms exhibit commendable performance in classifying overall CBF levels. These results highlight that our proposed methodology, predicated on ECS and image feature analysis, enables the capture of immediate responses of abnormal intracranial blood supply triggered by alterations in vascular stiffness. Moreover, it provides an accurate diagnosis of the overall CBF level under varying physiological conditions.

Health economic analysis and medical cost analysis of children with severe hepatitis B in China: A retrospective study from 2016 to 2022.

BACKGROUND: Hepatitis B poses a heavy burden for children in China, however, the national studies on the distributional characteristics and health care costs of children with severe hepatitis B is still lacking. This study aimed to analyze the disease characteristics, health economic effects, and medical cost for children with severe hepatitis B in China. METHODS: Based on patient information in the Hospital Quality Monitoring System, cases with severe hepatitis B were divided into four groups according to age, and the etiology and symptoms of each group were quantified. The cost of hospitalization was calculated for cases with different disease processes, and severity of disease. The spatial aggregation of cases and the relationship with health economic factors were analyzed by Moran's I  analysis. RESULTS: The total number of children discharged with hepatitis B from January 2016 to April 2022 was 1603, with an average age of 10.5 years. Liver failure cases accounted for 43.48% (697/1603,) of total cases and cirrhosis cases accounted for 11.23% (180/1603,). According to the grouping of disease progression, there were 1292 cases without associated complications, and the median hospitalization cost was $818.12. According to the spatial analysis, the aggregation of cases was statistically significant at the prefectural and provincial levels in 2019, 2020, and 2021 (all P <0.05). The number of severe cases was negatively correlated with gross domestic product (GDP, Moran's I <0) and percentage of urban population (Moran's I <0), and positively correlated with the number of pediatric beds per million population (Moran's I >0). CONCLUSION: The number of severe hepatitis B cases is low in areas with high GDP levels and high urban population ratios, and health care costs have been declining over the years.

Technical, economic, and environmental assessment of a stand-alone power system based on diesel engine with/without energy storage using an optimization algorithm: A case study in China.

In stand-alone power systems, technical, economic, and environmental (TEE) assessment of hybrid energy systems under uncertainty is an important issue. This paper focuses on the TEE assessment of a stand-alone hybrid energy system composed of photovoltaic (PV) and diesel generator (DG) with/without battery energy storage (BS) in remote islands in China. So, determining the optimal sizes of PV and DG with/without BS for economic, reliable, and efficient operation of a hybrid power system in a microgrid is important. For this goal, a modified swarm intelligence algorithm is used to optimize, techno-economic feasibility and avoid potential CO2 emission. To demonstrate the effectiveness of the modified swarm intelligence algorithm, it is compared with the standard swarm intelligence method and simple simulated annealing method in terms of operational cost reduction and power loss reduction. The aim of the optimization is to minimize the cost of a stand-alone solar power system based on diesel engine with/without battery energy storage system by optimal determination of the load uncertainty and CO2 emission. The optimal results are developed further by performing sensitivity analysis, such as the effect of the fuel cost and the penalty cost of CO2 emission. Over the case study, simulation results show that the proposed algorithm obtains more promising results in terms of TEE aspects. The reliability, low carbon, and cost-effectiveness of stand-alone solar power systems based on diesel engine with battery energy storage system can be easily calculated using the correlations derived in this analysis. The resulting cost of energy is in the range of 0.2845 to 0.6492 $/kWh.

Early assessment of acute ischemic stroke in rabbits based on multi-parameter near-field coupling sensing.

BACKGROUND: Early diagnosis and continuous monitoring are the key to emergency treatment and intensive care of patients with acute ischemic stroke (AIS). Nevertheless, there has not been a fully accepted method targeting continuous assessment of AIS in clinical. METHODS: Near-field coupling (NFC) sensing can obtain the conductivity related to the volume of intracranial components with advantages of non-invasiveness, strong penetrability and real-time monitoring. In this work, we built a multi-parameter monitoring system that is able to measure changes of phase and amplitude in the process of electromagnetic wave (EW) reflection and transmission. For investigating its feasibility in AIS detection, 16 rabbits were chosen to establish AIS models by bilateral common carotid artery ligation and then were enrolled for monitoring experiments. RESULTS: During the 6 h after AIS, the reflection amplitude (RA) shows a decline trend with a range of 0.69 dB and reflection phase (RP) has an increased variation of 6.48° . Meanwhile, transmission amplitude (TA) and transmission phase (TP) decrease 2.14 dB and 24.29° , respectively. The statistical analysis illustrates that before ligation, 3 h after ligation and 6 h after ligation can be effectively distinguished by the four parameters individually. When all those parameters are regarded as recognition features in back propagation (BP) network, the classification accuracy of the three different periods reaches almost 100%. CONCLUSION: These results prove the feasibility of multi-parameter NFC sensing to assess AIS, which is promised to become an outstanding point-of-care testing method in the future.

Noninvasive real-time assessment of intracranial pressure after traumatic brain injury based on electromagnetic coupling phase sensing technology.

BACKGROUND: To investigate the feasibility of intracranial pressure (ICP) monitoring after traumatic brain injury (TBI) by electromagnetic coupling phase sensing, we established a portable electromagnetic coupling phase shift (ECPS) test system and conducted a comparison with invasive ICP. METHODS: TBI rabbits' model were all synchronously monitored for 24 h by ECPS testing and invasive ICP. We investigated the abilities of the ECPS to detect targeted ICP by feature extraction and traditional classification decision algorithms. RESULTS: The ECPS showed an overall downward trend with a variation range of - 13.370 ± 2.245° as ICP rose from 11.450 ± 0.510 mmHg to 38.750 ± 4.064 mmHg, but its change rate gradually declined. It was greater than 1.5°/h during the first 6 h, then decreased to 0.5°/h and finally reached the minimum of 0.14°/h. Nonlinear regression analysis results illustrated that both the ECPS and its change rate decrease with increasing ICP post-TBI. When used as a recognition feature, the ability (area under the receiver operating characteristic curve, AUCs) of the ECPS to detect ICP ≥ 20 mmHg was 0.88 ± 0.01 based on the optimized adaptive boosting model, reaching the advanced level of current noninvasive ICP assessment methods. CONCLUSIONS: The ECPS has the potential to be used for noninvasive continuous monitoring of elevated ICP post-TBI.

Is SABR Cost-Effective in Oligometastatic Cancer? An Economic Analysis of the SABR-COMET Randomized Trial.

PURPOSE: The phase 2 randomized study SABR-COMET demonstrated that in patients with controlled primary tumors and 1 to 5 oligometastatic lesions, SABR was associated with improved progression-free survival (PFS) compared with standard of care (SoC), but with higher costs and treatment-related toxicities. The aim of this study was to assess the cost-effectiveness of SABR versus SoC in this setting. METHODS AND MATERIALS: A Markov model was constructed to perform a cost-utility analysis from the Canadian health care system perspective. Utility values and transition probabilities were derived from individual-level data from the SABR-COMET trial. One-way, 2-way, and probabilistic sensitivity analyses were performed. Costs were expressed in 2018 CAD. A separate analysis based on US payer's perspective was performed. An incremental cost-effectiveness ratio (ICER) at a willingness-to-pay threshold of $100,000 per quality-adjusted life year (QALY) was used. RESULTS: In the base case scenario, SABR was cost-effective at an ICER of $37,157 per QALY gained. This finding was most sensitive to the number of metastatic lesions treated with SABR (ICER: $28,066 per QALY for 2, increasing to $64,429 per QALY for 5), difference in chemotherapy use (ICER: $27,173-$53,738 per QALY), and PFS hazard ratio (HR) between strategies (ICER: $31,548-$53,273 per QALY). Probabilistic sensitivity analysis revealed that SABR was cost-effective in 97% of all iterations. Two-way sensitivity analysis demonstrated a nonlinear relationship between the number of lesions and the PFS HR. To maintain cost-effectiveness for each additional metastasis, the HR must decrease by approximately 0.047. The US cost analysis yielded similar results, with an ICER of $54,564 (2018 USD per QALY) for SABR. CONCLUSIONS: SABR is cost-effective for patients with 1 to 5 oligometastatic lesions compared with SoC.

Slow unfolded-state structuring in Acyl-CoA binding protein folding revealed by simulation and experiment.

Protein folding is a fundamental process in biology, key to understanding many human diseases. Experimentally, proteins often appear to fold via simple two- or three-state mechanisms involving mainly native-state interactions, yet recent network models built from atomistic simulations of small proteins suggest the existence of many possible metastable states and folding pathways. We reconcile these two pictures in a combined experimental and simulation study of acyl-coenzyme A binding protein (ACBP), a two-state folder (folding time ~10 ms) exhibiting residual unfolded-state structure, and a putative early folding intermediate. Using single-molecule FRET in conjunction with side-chain mutagenesis, we first demonstrate that the denatured state of ACBP at near-zero denaturant is unusually compact and enriched in long-range structure that can be perturbed by discrete hydrophobic core mutations. We then employ ultrafast laminar-flow mixing experiments to study the folding kinetics of ACBP on the microsecond time scale. These studies, along with Trp-Cys quenching measurements of unfolded-state dynamics, suggest that unfolded-state structure forms on a surprisingly slow (~100 µs) time scale, and that sequence mutations strikingly perturb both time-resolved and equilibrium smFRET measurements in a similar way. A Markov state model (MSM) of the ACBP folding reaction, constructed from over 30 ms of molecular dynamics trajectory data, predicts a complex network of metastable stables, residual unfolded-state structure, and kinetics consistent with experiment but no well-defined intermediate preceding the main folding barrier. Taken together, these experimental and simulation results suggest that the previously characterized fast kinetic phase is not due to formation of a barrier-limited intermediate but rather to a more heterogeneous and slow acquisition of unfolded-state structure.