Brain-computer interfaces (BCIs) enable people to communicate with others or devices, and improving BCI performance is essential for developing real-life applications. In this study, a steady-state visual evoked potential-based (SSVEP-based BCI) multi-domain features multi-task learning developed. To accurately represent the characteristics of an SSVEP signal, signals in time frequency domains are selected as features. Convolutional neural networks separately used domain effectively extract...

Brain–computer interfaces (BCIs) enable people to communicate with others or devices, and improving BCI performance is essential for developing real-life applications. In this study, a steady-state visual evoked potential-based (SSVEP-based BCI) multi-domain features multi-task learning developed. To accurately represent the characteristics of an SSVEP signal, signals in time frequency domains are selected as features. Convolutional neural networks separately used domain extract embedding...

Solar cells may possess defects during the manufacturing process in photovoltaic (PV) industries. To precisely evaluate effectiveness of solar PV modules, are required to be identified. Conventional defect inspection industries mainly depends on manual by highly skilled inspectors, which still give inconsistent, subjective identification results. In order automatize visual process, an automatic cell segmentation technique and a convolutional neural network (CNN)-based detection system with...

Various physiological parameters have been widely used in the prevention and detection of diseases. In particular, occurrence cardiovascular diseases can be observed through daily measurement blood pressure. Currently, most common pressure method records on upper arm. This lead to subject feeling uncomfortable tension arm from stress may errors. An electrocardiogram represents electrical activity during heart function, but also contains pressure–related information. study is an attempt...

Subjects with amyotrophic lateral sclerosis (ALS) consistently experience decreasing quality of life because this distinctive disease. Thus, a practical brain-computer interface (BCI) application can effectively help subjects ALS to participate in communication or entertainment. In study, fuzzy tracking and control algorithm is proposed for developing BCI remote system. To represent the characteristics measured electroencephalography (EEG) signals after visual stimulation, fast Fourier...

In order to promote the quality of life for subjects with motor neuron disease, an interesting maze game operated by steady state visual evoked potential (SSVEP) based brain-computer Interface (BCI) was developed. The SSVEP BCI provides 4 options including: "counterclockwise", "clockwise" "forward" and "backward". A liquid crystal display (LCD) monitor is used as stimulation device showing option icons flickering at different frequencies respectively induce subject's brain waves. Then...

This study proposes the development of a contactless emergency assistance system designed for individuals with severe physical disabilities (tetraplegia and no voice but normal mouth movements) to address limitations traditional bells in sudden emergencies. The core technology includes artificial intelligence facial recognition fuzzy motion algorithms identify movements. After auxiliary signal is triggered, uses Message Queuing Telemetry Transport (MQTT) activate warning lights speakers....

The issue of smart home control is one popular applications Internet Things (IoT). However, most the designs are for normal people, just few appliance automation designed disabled. This study shows novel implementation based on a Morse code text input (McTin) controller by research team people with severe disabilities and analyzes living behavior subject according to operation frequencies different appliances.

Objective: This study explored tone production, perception and intelligibility of produced speech in Mandarin-speaking prelingually deaf children with at least 5 years cochlear implant (CI) experience. Another focus was on the predictive value production as they relate to intelligibility. Design: Cross-sectional research. Study sample: Thirty-three deafened aged over eight five experience CI underwent tests for perception, Speech Intelligibility Rating (SIR). A Pearson correlation a stepwise...

Articulation errors seriously reduce speech intelligibility and the ease of spoken communication. Speech-language pathologists manually identify articulation error patterns based on their clinical experience, which is a time-consuming expensive process. This study proposes an automatic pronunciation identification system that uses novel dependence network (DN) approach. In order to derive subject's articulatory information, photo naming task performed obtain patterns. Based knowledge about...

People suffering from paralysis caused by serious neural disorder or spinal cord injury also need to be given a means of recreation other than general living aids. Although there have been proliferation brain computer interface (BCI) applications, developments for recreational activities are scarcely seen. The objective this study is develop BCI-based remote control integrated with commercial devices such as the controlled Air Swimmer. visually stimulated using boxes flickering at...

While deep convolutional neural networks (CNNs) have recently made large advances in AI, the need of datasets for CNN learning is still a barrier to many industrial applications where only limited data samples can be offered system developments due confidential issues. We thus propose an approach multi-scale image augmentation and classification training CNNs from small dataset surface defect detection on cylindrical lithium-ion batteries. In proposed Lithium-ion battery Surface Defect...

Monitoring people’s blood pressure can effectively prevent pressure-related diseases. Therefore, providing a convenient and comfortable approach help patients in monitoring pressure. In this study, an attention mechanism-based convolutional long short-term memory (LSTM) neural network is proposed to easily estimate To comfortably pressure, electrocardiogram (ECG) photoplethysmography (PPG) signals are acquired. precisely represent the characteristics of ECG PPG signals, time frequency domain...

The power cepstrum‐based parameters for steady‐state visually evoked potential (SSVEP) is proposed. To precisely represent the characteristics of frequency responses a stimulated electroencephalography (EEG) signal, cepstrum analysis adopted to estimate in low‐dimensional space. SSVEP, log‐magnitude spectrum an EEG signal estimated by fast Fourier transform. Subsequently, discrete cosine transform applied linearly into domain, and then generate set coefficients. Finally, Bayesian decision...

A lot of people with severe disabilities such as amyotrophic lateral sclerosis, motor neuron diseases, cerebral palsy, stroke, and spinal cord injury intubation always have different degrees communication problems. Therefore, it is very important to develop an effective easy use assistive system for the severely disabled. In this study, a wireless home (WHAS) types input accessories sensors, Morse code translator, human machine interface developed tested help disabled communicate machines....

The so-called amyotrophic lateral sclerosis (ALS) or motor neuron disease (MND) is a neurodegenerative with various causes. It characterized by muscle spasticity, rapidly progressive weakness due to atrophy, and difficulty in speaking, swallowing, breathing. severe disabled always have common problem that about communication except physical malfunctions. steady-state visually evoked potential based brain computer interfaces (BCI), which apply visual stimulus, are very suitable play the role...

Subjects with amyotrophic lateral sclerosis (ALS) consistently experience decreasing quality of life because this distinctive disease. Thus, a practical brain-computer interface (BCI) application can effectively help subjects ALS to participate in communication. In practices, the noise would greatly reduce performance BCIs. study, minima controlled recursive averaging is applied suppress and improve BCI applications. Minima used correctively track noise. To these noises, log-spectral...

Purpose Articulation errors substantially reduce speech intelligibility and the ease of spoken communication. Moreover, articulation learning process that speech-language pathologists must provide is time consuming expensive. The purpose this paper, to facilitate process, develop a computer-aided system help subjects with disorders. Design/methodology/approach Facial animations, including lip tongue are used convey manner place subject. This improves effectiveness learning. An interactive...

Cardiovascular disease (CVD) has been the most common factor of death for decades, and one method to detect CVD is through heart sound auscultation.Numerous studies have investigated improvements in precision accuracy classification using machine learning.Nonetheless, methods utilize many features their learning increase predictive model address challenges associated with signals acquired sensors placed at different locations.In this paper, we propose use sounds segmented into three...