Low limit of detection of the AlGaN/GaN-based sensor by the Kelvin connection detection technique

The AlGaN/GaN-based sensor is a promising POCT(point-of-care-testing)device featuring miniaturization,low cost,and high sensitivity.BNP is an effective protein biomarker for the early diagnosis of HF(heart failure).In this work,a novel AlGaN/GaN device with the Kelvin connection structure and the corresponding detection technique was proposed.This technique can effectively suppress the background noise and improve the SNR(signal-to-noise ratio).A BNP detection experiment was carried out to verify the effectiveness of this technique.It is shown that compared with that of the traditional detection method,the LOD(limit of detection)was improved from 0.47 ng/mL to 1.29 pg/mL.The BNP detection experiment was also carried out with a traditional electrochemical Au-electrode sensor with the same surface functionalization steps.The AlGaN/GaN sensor showed a better LOD than the Au-electrode sensor.Moreover,the influence of AlGaN/GaN sensor package on background noise was investigated with the mechanism of the noise source revealed.Finally,based on the optimized package,the optimal SNR quiescent operating point of the AlGaN/GaN sensor was determined.By biasing the sensor at the optimal quiescent operating point and immobilizing the magnetic beads with anti-BNP on the gate of the AlGaN/GaN sensor,the LOD for BNP detection was further improved to 0.097 pg/mL.

Design and Evaluation of an Exergame System of Knee with the Azure Kinect

Timely and effective knee function evaluation and knee exercises promote the prevention and self-management of knee diseases.In this paper,aKinectbased exergame system is proposed to assess and train the knee function.Azure Kinect was used to capture and generate 3D models of the user and immerse them in an interactive virtual environment.The software included three functional modules:knee function evaluation,Knee exercises game,and Comprehensive evaluation.The stand,step,leg lift,and squat were selected for knee function evaluation and exercises.Twenty volunteers participated in the experiment.Intraclass correlation coefficients(ICCs)were calculated to assess the reliability of kinematic measurements of knee angles during the movements.The ICC of these movements were stand(ICC=0.987),step(ICC=0.997),left leg lift(ICC=0.981),right leg lift(ICC=0.990),stand(ICC=0.998).The results show that the test-retest reliability is high.It means that the motion capture data is effective and the data obtained by Kinect is stable.