Metal-enhanced fluorescence biosensor integrated in capillary flow-driven microfluidic cartridge for highly sensitive immunoassays.

Point-of-care testing (POCT) for low-concentration protein biomarkers remains challenging due to limitations in biosensor sensitivity and platform integration. This study addresses this gap by presenting a novel approach that integrates a metal-enhanced fluorescence (MEF) biosensor within a capillary flow-driven microfluidic cartridge (CFMC) for the ultrasensitive detection of the Parkinson's disease biomarker, aminoacyl-tRNA synthetase complex interacting multi-functional protein 2 (AIMP-2). Crucial point to this approach is the orientation-controlled immobilization of capture antibody on a nanodimple-structured MEF substrate within the CFMC.

Techniques for Improving the Reliability of Prosthesis Wearer Muscle Signals Using Pressure and EMG Sensors.

In this study, we propose a technique to increase the reliability of muscle signals in case of weak muscle signal measurements using pressure sensors in a prosthesis wearer for measuring the degree of contraction of the muscle. This technique is applied when determining the intention of the wearer of an intelligent prosthesis. Through this technique, it is possible to determine the intention of a prosthesis wearer, which was previously not possible.

Fully Stretchable Capillary Microfluidics-Integrated Nanoporous Gold Electrochemical Sensor for Wearable Continuous Glucose Monitoring.

Biosensor systems for wearable continuous monitoring are desired to be developed into conformal patch platforms. However, developing such patches is very challenging owing to the difficulty of imparting materials and components with both high stretchability and high performance. Herein, we report a fully stretchable microfluidics-integrated glucose sensor patch comprised of an omnidirectionally stretchable nanoporous gold (NPG) electrochemical biosensor and a stretchable passive microfluidic device.

A study on the operation of rehabilitation interfaces in active rehabilitation exercises for upper limb hemiplegic patients: Interfaces for lateral and bilateral exercises.

Background: For implementing autonomous rehabilitation exercises for upper limb hemiplegic patients, interfaces and a rehabilitation scenario that allow lateral and bilateral motions in a rehabilitation exercise robot are proposed.

Objective: The proposed method measures the motion information generated from the unaffected part and projects it to an affected part in which the affected part expresses motions of the unaffected part.

Methods: Both the accelerometer and gyro data were merged for estimating the motion information of the unaffected part.

Hand region extraction and gesture recognition from video stream with complex background through entropy analysis.

Hand gesture recognition utilizing image processing relies upon recognition through markers or hand extraction by colors, and therefore is heavily restricted by the colors of clothes or skin. We propose a method to recognize band gestures extracted from images with a complex background for a more natural interface in HCI (human computer interaction). The proposed method obtains the image by subtracting one image from another sequential image, measures the entropy, separates hand region from images, tracks the hand region and recognizes hand gestures.