Hydrogel, with excellent hydrophilicity biocompatibility and stimuli responsive, has been widely used in biomedical and artificial organs fields. However, synthetic hydrogel usually displays poor gel strength, poor toughness and slow speed of absorbing water. Therefore, extensive exploratory research is still required to develop new composite materials for the application of bionic viscera. In this work, we constructed a new kind of composite hydrogel by a facile wet chemistry method to cross-link three kinds of polymer resin, polyvinyl alcohol, carboxymethyl cellulose, and carboxymethyl starch. The conductivity, moisture content and elastic modulus of hydrogel can be controlled by the dosage of potassium salt, sodium salt, water and glycerol. After molding and testing, the electrical conductivity, elastic modulus, and moisture content of the artificial liver and kidney organs were similar to those of the corresponding pig viscera, which is superior to most of the current research on hydrogels. This work provides a facile approach to synthesize highly efficient hydrogel, which accelerates the application of hydrogel in bionic organs.

Sedation is an essential component of the anesthesia process. Inadequate sedation during anesthesia increases the risk of patient discomfort, intraoperative awareness, and psychological trauma. Conventional electroencephalography (EEG) based depth of anesthesia monitoring is often impractical in out-of-hospital settings due to equipment limitations and signal artifacts. Alternative non-EEG-based approaches are therefore required. In this study, we developed a machine learning model to detect inadequate sedation using 27 feature parameters, including demographics, vital signs, and heart rate variability metrics, from the open-access VitalDB database. Patient states were defined as inadequate sedation when the bispectral index (BIS) > 60. We systematically evaluated four temporal windows and four algorithms, and assessed model interpretability using Shapley Additive Explanations (SHAP). The Light Gradient Boosting Machine (LGBM) achieved the best performance, with an area under the receiver operating characteristic curve (AUC) of 0.825 and an accuracy (ACC) of 0.741 using a 2 s time window. Extending the time window to 20 s improved both metrics by approximately 0.012. Feature selection identified 12 key parameters that maintained comparable accuracy, confirming robustness with reduced complexity. These findings demonstrate the feasibility of using non-EEG-based physiological data for real-time detection of inadequate sedation. The developed model is interpretable, resource-efficient, scalable, and shows strong potential for integration into portable monitoring systems in prehospital, emergency, and low-resource surgical settings.

Transthoracic impedance is one of the key factors affecting the success of defibrillation. Impedance compensation technique is used to adjust defibrillation parameters according to the transthoracic impedance of the defibrillator. In this paper, a combined impedance compensation strategy is proposed to address the shortcomings of existing compensation strategies. In order to evaluate the performance of the combined compensation strategy, this paper uses the prototype as the experimental machine, and uses two AED with representative impedance compensation strategies as the control machine, and the simulated defibrillation method is used for comparative testing. The results show that the combined impedance compensation has a more steadier distribution over the defibrillation energy and current: compared with the energy-based impedance compensation strategy, this strategy can significantly reduce the peak current (25 Ω: 27.8 vs. 54.7 A; 50 Ω: 20.7 vs. 32.3 A) and average current (25 Ω: 24.8 vs. 37.5 A) of defibrillation at low impedance, and compared with the current impedance compensation strategy, it can significantly reduce the defibrillation energy (150 Ω: 8.6 vs. 1.7 %, 175 Ω: 15.6 vs. 4.9 %, 200 Ω: 21.9 vs. 8.5 %) at high impedance. Impedance compensation is more precise and the current passing during defibrillation is steadier.