Thailand Electrical Engineering Journal (TEEJ)

Major Depression Disorder detection on EEG-Based with the Convolution Neural Networks approach improved with the Inter-trial phase clustering

Rathanon Suwanteerangkul — 2025-12-08

Nowadays, Major Depression Disorder is still a concern about human mental health, and there are significant challenges in the diagnosis. There are still limitations in the traditional method used to classify patients from healthy groups and required specialized personnel such as a psychiatrist or psychologist. The aim of this study is to introduce the ability of a deep learning approach to detect abnormalities in EEG (Electroencephalogram) signals of patients with depression. The EEG features are based on the Time-Frequency Analysis of EEG signals from the Morlet wavelet transformation, also known as ERPs (Event-Related Potentials) and ITPC (Inter-trial phase clustering), which is complex and challenging to assess by humans. We proposed a deep learning model that are integrating the two Convolution Neural Networks (CNNs) models to learn both EEG features at the same time to increase efficiency in classification. The result shows that the concatenation CNNs between two input's EEG features received accuracy in classification at 91.60% compared with general CNNs that use single input ERPs with accuracy only 83.33%. Also, we are comparing with a machine learning approach, such as KNN (K-nearest neighbor), that received an accuracy of 67.00%.

Jerk Model Current-mode Chaotic Oscillator based on OTA

Khunanon Karawanich — 2025-12-08

This paper describes a chaotic oscillator circuit based on Jerk model and nonlinear function. The signum function is

deployed to realize the chaotic oscillator which controlled by using a single parameter. The OTA and grounded capacitors are used without the resistors for achieving the chaotic oscillator. The circuit consists of main three parts, lossless integrator, biquadratic low-pass filter, and nonlinear function circuits. The condition of chaos signal can be electronically tuned through the quality factor of biquadratic low-pass filter. The simulation results are incorporated by PSpice and MATLAB which found that the chaos signal can be generated agree well to the theory. The chaos behavior can also be proved by bifurcation diagram. The signal output has doubling periods according to the circuit

results.

Designed and Implementation of Grid Connected Converter System for Exercise Bike

Jirawut Benjanarasut. — 2025-12-08

This paper proposed an experimental design and implementations of 250 VA grid connected converter system for an exercise bike that consist of an exercise bike, coupling with a generator and a grid connected converter system. The converter system has two main parts. The first part is a synchronous boost converter that adjusts viscosity of an exercise bike generator via control synchronous boost converter current. It was applied to an analog comparator module of STM32F334R8 microcontroller. The second part is a grid tie inverter that transfers energy from synchronous boost converter to grid. The experimental results verify the system can adjust the viscosity of an exercise bike equal to the conventional exercise bike and can deliver.

module