Chi-Jane Wang

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Emotions evoked by were analyzed. An estimation of the correlation coefficient was applied to determine features of music that evoke an emotion. These features were then used to train two support vector machines (SVMs) for an individual subject to classify music that evokes happiness, anger, sadness, and peacefulness. The proposed approach can be used to(More)
BACKGROUND While mortality from coronary heart disease (CHD) has declined substantially in most developed countries in recent decades, discordant rising trends have been observed in many developing and newly developed countries. In this study, we examined the trends of CHD mortality and its hospitalization rate, and correlated the trends with changes in(More)
The habit of drinking tea is highly prevalent in Asian countries. The aim of this study was to investigate the prevalence of tea drinking and to explore the correlated factors on tea drinking among young new students in the university, using a validated self-reported questionnaire. This study was carried out with 5936 new students in a university in Taiwan.(More)
The main objective of this work is to develop a music emotion recognition technique using Mel frequency cepstral coefficient (MFCC), Auto associative neural network (AANN) and support vector machine (SVM). The emotions taken are anger, happy, sad, fear, and neutral. Music database is collected at 44. 1 KHz with 16 bits per sample from various movies and(More)
Facial expression are widely used for emotion recognition. Facial expressions may be expressed differently by different people subjectively, inaccurate results are unavoidable. Nevertheless, physiological reactions are non-autonomic nerves in physiology. The physiological reactions and the corresponding signals are hardly to control while emotions are(More)
An emotion recognition system with consideration of facial expression and physiological signals is proposed in this paper. A specific designed mood induction experiment is performed to collect facial expressing images and physiological signals of subjects. We detected 14 feature points and extracted 12 facial features from facial expression images.(More)
PURPOSE Impairments in word finding, language skills and memory in dementia patients increase the obstacles for health professionals to provide effective care. Although some research on communication with dementia patients has been done, no research that pre-assessed nurses' difficulties in communicating with dementia patients has been identified. This(More)
BACKGROUND Self-monitoring is part of many weight-loss programs and is widely accepted as effective. However, there is a lack of research related to the efficacy of various self-monitoring instruments in meeting the needs of individuals with limited mobility or access to healthcare providers, especially those with limited education living in rural settings.(More)
Cases of physical and mental diseases caused by stress and negative emotions have increased annually. Many emotion recognition methods have been proposed. Facial expression is widely used for emotion recognition. However, since facial expressions may be expressed differently by different people, inaccurate results are unavoidable. Nerve and Physiological(More)
Patients with dementia, especially those with advanced dementia, may not be able to express their bowel movement and urination needs using lucid language, and instead do so through behaviors. The aim of the current study was to understand and compare the behavioral characteristics of bowel movement and urination needs in patients with dementia. Observations(More)