A prominence model is proposed for enhancing prosodic features in automatic lexical stress and pitch accent detection. We make use of a loudness model and incorporate differential pitch values to improve conventional features. Experiments show that these new prosodic features can improve the detection of lexical stress and pitch accent by about 6%. We further employ a prominence model to take i...

Although English pitch accent detection has been studied extensively, there relatively a few works explore Mandarin stress etection. Moreover, the comparison and analysis between Mandarin stress detection and English pitch accent detection have not een touched for such counterpart tasks. In this paper, we discuss Mandarin stress detection and compare it with English pitch accent etection. The c...

Stress remains a significant social problem for individuals in modern societies. This paper presents a machine learning approach for the automatic detection of stress of people in a social situation by combining two sensor systems that capture physiological and social responses. We compare the performance using different classifiers including support vector machine, AdaBoost, and [Formula: see ...

For human body, oxidative stress is considered pathophysiological mechanism in different pathologies therefore oxidative damage biomarkers detection is real help for clinical purposes. Easy to use devices that can help in the early diagnosis and innovative therapeutic approaches are needed. This paper presents an extensive review of sensitive and specific devices such as biosensors used for rea...

This work presents a new additive manufacturing electrochemical device with conductive graphene and polylactic acid (PLA) filament its application for epinephrine sensing. A three-electrode configuration based on screen-printed electrode architecture an easy-to-connect connector was designed. The sensor surface chemically treated dimethylformamide (DMF) to remove the insulating thermoplastic ex...

Stress has a significant negative impact on people, which made it primary social concern. Early stress detection is essential for effective management. This study proposes Deep Learning (DL) method using multimodal physiological signals - Electrocardiogram (ECG) and Electrodermal activity (EDA). The extensive latent feature representation of DL models yet to be fully explored. Hence, this paper...

Objectives Stress management is related to public healthcare and quality of life; an accurate stress classification method is necessary for the design of stress monitoring systems. Therefore, the goal of this study was to design a novel stress classification model using a deep learning method. Methods In this paper, we present a stress classification model using the dataset from the sixth Kor...