Quantifying instability in neurological disorders EEG based on phase space DTM function.

Classifying individuals with neurological disorders and healthy subjects using EEG is a crucial area of research. The current feature extraction approach focuses on the frequency domain features in each of the EEG frequency bands and functional brain networks. In recent years, researchers have discovered and extensively studied stability differences in the electroencephalograms (EEG) of patients with neurological disorders.

Screen-Printable Iontronic Pressure Sensor with Thermal Expansion Microspheres for Pulse Monitoring.

Constructing microstructures to improve the sensitivity of flexible pressure sensors is an effective approach. However, the preparation of microstructures usually involves inverted molds or subtractive manufacturing methods, which are difficult in large-scale (e.g.

A pooling convolution model for multi-classification of ECG and PCG signals.

Electrocardiogram (ECG) and phonocardiogram (PCG) signals are physiological signals generated throughout the cardiac cycle. The application of deep learning techniques to recognize ECG and PCG signals can greatly enhance the efficiency of cardiovascular disease detection. Therefore, we propose a series of straightforward and effective pooling convolutional models for the multi-classification of ECG and PCG signals.

Boron nitride-enabled printing of a highly sensitive and flexible iontronic pressure sensing system for spatial mapping.

Recently, flexible iontronic pressure sensors (FIPSs) with higher sensitivities and wider sensing ranges than conventional capacitive sensors have been widely investigated. Due to the difficulty of fabricating the nanostructures that are commonly used on electrodes and ionic layers by screen printing techniques, strategies for fabricating such devices using these techniques to drive their mass production have rarely been reported. Herein, for the first time, we employed a 2-dimensional (2D) hexagonal boron nitride (-BN) as both an additive and an ionic liquid reservoir in an ionic film, making the sensor printable and significantly improving its sensitivity and sensing range through screen printing.

A Pressure and Temperature Dual-Parameter Sensor Based on a Composite Material for Electronic Wearable Devices.

Wearable sensors integrating multiple functionalities are highly desirable in artificial wearable devices, which are of great significance in the field of biomedical research and for human-computer interactions. However, it is still a great challenge to simultaneously perceive multiple external stimuli such as pressure and temperature with one single sensor. Combining the piezoresistive effect with the negative temperature coefficient of resistance, in this paper, we report on a pressure-temperature dual-parameter sensor composed of a polydimethylsiloxane film, carbon nanotube sponge, and poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate).

Refractive Index Sensor Based on the Fano Resonance in Metal-Insulator-Metal Waveguides Coupled with a Whistle-Shaped Cavity.

A plasmonic refractive index sensor based on surface plasmon polaritons (SPPs) that consist of metal-insulator-metal (MIM) waveguides and a whistle-shaped cavity is proposed. The transmission properties were simulated numerically by using the finite element method. The Fano resonance phenomenon can be observed in their transmission spectra, which is due to the coupling of SPPs between the transmission along the clockwise and anticlockwise directions.

Double Fano Resonance and Independent Regulation Characteristics in a Rectangular-like Nanotetramer Metasurface Structure.

Fano resonance, which is based on a plasmonic metasurface, has many potential applications in various fields, such as biochemical sensors, slow light effect, and integrated optical circuits. In this study, a rectangular-like nanotetramer metasurface structure composed of four round-head nanorods was designed. The transmission spectrum, surface charge, and electrical field distributions of the proposed structure were simulated using the finite element method.

Design and Fabrication of High-Frequency Piezoelectric Micromachined Ultrasonic Transducer Based on an AlN Thin Film.

A piezoelectric micromachined ultrasonic transducer (PMUT) is a microelectromechanical system (MEMS) device that can transmit and receive ultrasonic waves. Given its advantages of high-frequency ultrasound with good directionality and high resolution, PMUT can be used in application scenarios with low power supply, such as fingerprint recognition, nondestructive testing, and medical diagnosis. Here, a PMUT based on an aluminum nitride thin-film material is designed and fabricated.

Enhancement of the Transmission Performance of Piezoelectric Micromachined Ultrasound Transducers by Vibration Mode Optimization.

Ultrasound is widely used in industry and the agricultural, biomedical, military, and other fields. As key components in ultrasonic applications, the characteristic parameters of ultrasonic transducers fundamentally determine the performance of ultrasonic systems. High-frequency ultrasonic transducers are small in size and require high precision, which puts forward higher requirements for sensor design, material selection, and processing methods.

Automatic Classification Framework of Tongue Feature Based on Convolutional Neural Networks.

Tongue diagnosis is an important part of the diagnostic process in traditional Chinese medicine (TCM). It primarily relies on the expertise and experience of TCM practitioners in identifying tongue features, which are subjective and unstable. We proposed a tongue feature classification framework based on convolutional neural networks to reduce the differences in diagnoses among TCM practitioners.

Design of a Novel Medical Acoustic Sensor Based on MEMS Bionic Fish Ear Structure.

High-performance medical acoustic sensors are essential in medical equipment and diagnosis. Commercially available medical acoustic sensors are capacitive and piezoelectric types. When they are used to detect heart sound signals, there is attenuation and distortion due to the sound transmission between different media.

An Optimal Design Method for Improving the Efficiency of Ultrasonic Wireless Power Transmission during Communication.

Due to the excellent directivity, strong penetrability, and no electromagnetic shielding effect, ultrasonic waves have good potential for wireless energy transmission and information transfer inside and outside of sealed metal devices. However, traditional ultrasonic based energy transmission methods usually result in considerable energy consumption because of the impedance mismatch during the impedance modulation of the communication. This paper presents an optimal design method for efficient energy transfer during ultrasonic communication.