A wearable microfluidic system for efficient sweat collection and real-time detection.

Sweat is an important biofluid with rich physiological information that can evaluate human health condition. Wearable sweat sensors have received widespread attention in recent years due to the benefits of non-invasive, continuous, and real-time monitoring. Currently, an efficient device integrating sweat collection and detection is still needed. Here, a wearable sweat microfluidic system was fabricated for real-time collection and analysis of sweat. The fabricated microfluidic system consisted of four layers, including a skin adhesive layer, a microfluidic layer, an electrode layer, and a capping layer. The sweat collection rate was around 0.79 µL/min, which demonstrated efficient sweat sampling, storage, and refreshing capabilities. Simultaneous detection of multiple sweat biomarkers was achieved with a screen-printed sweat sensing array, which could realize high-precision detection of Na+, K+, and glucose. Moreover, the sensing array also showed good repeatability and stability, with a relative standard deviation of sensitivity of less than 5%. Additionally, human testing was conducted to demonstrate that this microfluidic system can continuously monitor Na+, K+, and glucose in subjects' sweat during exercise, which showed high potential for non-invasive human health monitoring.

Effect of interstitial fluid pH on transdermal glucose extraction by reverse iontophoresis.

Reverse iontophoresis (RI) is a promising technology in the field of continuous glucose monitoring (CGM), offering significant advantages such as finger-stick-free operation, wearability, and non-invasiveness. In the glucose extraction process based on RI, the pH of the interstitial fluid (ISF) is a critical factor that needs further investigation, as it directly influences the accuracy of transdermal glucose monitoring. In this study, a theoretical analysis was conducted to investigate the mechanism by which pH affects the glucose extraction flux. Modeling and numerical simulations performed at different pH conditions indicated that the zeta potential was significantly impacted by the pH, thereby altering the direction and flux of the glucose iontophoretic extraction. A screen-printed glucose biosensor integrated with RI extraction electrodes was developed for ISF extraction and glucose monitoring. The accuracy and stability of the ISF extraction and glucose detection device were demonstrated with extraction experiments using different subdermal glucose concentrations ranging from 0 to 20 mM. The extraction results for different ISF pH values exhibited that at 5 mM and 10 mM subcutaneous glucose, the extracted glucose concentration was increased by 0.08212 mM and 0.14639 mM for every 1 pH unit increase, respectively. Furthermore, the normalized results for 5 mM and 10 mM glucose demonstrated a linear correlation, indicating considerable potential for incorporating a pH correction factor in the blood glucose prediction model used to calibrate glucose monitoring.

Electrically Inspired Flexible Electrochemical Film Power Supply for Long-Term Epidermal Sensors.

This paper, for the first time, reports an electrically inspired flexible electrochemical film power supply for long-term epidermal sensors. This device can periodically provide electrical power for several hours after a short-time electrical activation. The electrical activation makes acetylcholine, which is infused into the subcutaneous tissue by iontophoresis. The interstitial fluid (ISF) with glucose molecules is then permeated autonomously for several hours. At this period, the device can provide electrical power. The electrical power is generated from the catalyzing reaction between the glucose oxidase immobilized on the anode and the permeated glucose molecules. After the ISF permeation stops, we give a short-time electrical activation to provide electrical power for several hours again. The power supply is flexible, which makes it adaptively conform to skin. The episodic short-time electrical activation can be enabled by an integrated small film lithium-ion battery. This method extends the service life of a lithium-ion battery 10-fold and suggests the application of small lithium-ion batteries for long-term epidermal sensors.

Using dynamic data reconciliation to improve the performance of PID feedback control systems with Gaussian/non-Gaussian distributed disturbance and measurement noise.

For a stochastic PID feedback control system, the uncertainty of the working environment often leads to the unsatisfied performance of the system, which does not meet the profit requirements. The working environment generally includes external disturbance and measurement noise, etc. Gaussian distributed measurement noise and disturbances are widely considered while non-Gaussian distributed measurement noise and disturbances are rarely considered. In this paper, the performance degradation of Gaussian/non-Gaussian disturbances and measurement noise on a stochastic PID feedback system is considered and analyzed. An efficient method, dynamic data reconciliation (DDR) is developed to filter measurement noise and disturbances and improve the performance of the stochastic PID feedback control system. By utilizing model-based and measured information, DDR avoids time delays in output estimation. With the detailed theoretical analysis and simulation verification, the effectiveness of the proposed DDR technology on the stochastic PID feedback control system is verified. Compared with conventional exponential filters, DDR can achieve better control performance. The proposed DDR is also used for the control system of the DC-AC​ converter. The improved effect of DDR on the output quality is demonstrated by the results.

Dynamic data reconciliation to improve the result of controller performance assessment based on GMVC.

Due to the complexity of the industrial working environment, controllers are susceptible to various disturbance signals, resulting in unsatisfactory control performance. Therefore, it is especially important to assess the controller performance. Considering the harmful effect of measurement noise on controller performance assessment (CPA) based on generalized minimum variance control (GMVC), this paper proposes dynamic data reconciliation (DDR) to improve the accuracy of CPA based on GMVC. The paper first introduces CPA based on GMVC, and then analyzes the influence of measurement noise on GMVC based CPA index. DDR combined with GMVC based CPA is then proposed and analyzed in both SISO and MIMO systems to weaken the impact of measurement noise on CPA index. For both Gaussian distributed noise and non-Gaussian distributed noise, the formulation of DDR is derived from the Bayesian formula and maximum likelihood estimate. The effectiveness of the proposed method is verified in different case studies (involving both SISO and MIMO systems), and further verified by the control process of DC-AC converter. The simulation and experiment results demonstrate that the results of CPA based on GMVC can be obviously improved by using DDR.