Emotion recognition based on affective physiological changes is a pattern problem, and selecting specific signals necessary helpful to recognize the emotions. Fingertip blood oxygen saturation (OXY), galvanic skin response (GSR) heart rate (HR) are acquired while amusement, anger, grief fear of 101 subjects individually elicited by films. The in multi-subject GSR, first derivative GSR (FD_GSR) HR detected multi-variant correlation method. analysis reveals that HR, FD_GSR fluctuations...

Social anxiety is a negative emotion which may impair the health of heart and social functioning an individual. This work analyzes influence on autonomic nerve control in two exposure events: public speaking thesis defending. In experiment speaking, 59 human subjects were tested, 11 conventional heartbeat measures measure named range local Hurst exponents (RLHE) evaluated for their capabilities to reveal onset anxiety. Two-sample t-test between baseline data high shows that significantly...

The matching of cognitive load and working memory is the key for effective learning, effort in learning process has nervous responses which can be quantified various physiological parameters. Therefore, it meaningful to explore automatic pattern recognition by using measures. Firstly, this work extracted 33 commonly used features quantify autonomic central activities. Secondly, we selected a critical feature subset sequential backward selection particle swarm optimization algorithms....

Non-restorative sleep is prevalent among individuals with depression and strongly associated the severity of condition. Therefore, identifying non-restorative can aid in early screening depression. Investigating necessitates long-term monitoring under naturalistic conditions. In this study, we recruited 149 participants collected electrocardiogram triaxial acceleration from them, resulting a total 761 nights data. The period midnight to 6:30 AM was segmented into 78 five-minute intervals,...

Previous studies have attempted to find autonomic differences of the cardiac system between congestive heart failure (CHF) disease and healthy groups using a variety algorithms pattern recognition. By comparing previous literature, we found that there are two shortcomings: (1) focused on improving accuracy models, but number features used has mostly exceeded 10, leading poor generalization performance; (2) works rarely distinguish severity levels CHF disease. In order make up for these...

Electrocardiography (ECG) data acquisition, preprocessing, feature extraction and emotion recognition based on ECG classification were effectively implemented. Joy sad movies selected presented to 154 subjects whose recorded at the movie presentation time. The automatic location of QRS complex, which is critical importance for by computer, was performed non-linear transformation first derivative ECG. By means tabu search, best combination features classification. classified into certain...

This work analyzed the autonomic reactivity of real-scene stress. Electrocardiogram (ECG) data were acquired from 16 subjects during final examinations a semester and after long winter holiday. Weak stress strong datasets constructed ECG subjects. Statistical analysis showed that there was significant difference between weak The classified by using support vector machine (SVM), obtained accuracy 93.75% 87.5% for binary classification stress, respectively. By sequential backward selection...

Anxiety is a kind of extremely negative emotion, and long-term anxiety the cause many serious physical mental diseases. In daily life, real-time accurate detection state conducive to block hazards timely. based on autonomic nervous patterns has achieved high-detection precision in certain scenes. However, motion interferes with arbitrary scenes leading false report anxiety. This paper designed four different intensities motions analyze activity typical states, found out states similar...

The aim of this article is to recognize public speaking anxiety based on galvanic skin response through recurrence plot and quantification analysis. Twenty-two female subjects have participated in study, the state induced by anticipated real speaking. Two nonlinear features, rate entropy diagonal length, are extracted from plots as feature set. Furthermore, paper applies back-propagation neural network algorithm achieve goal binary-classifications between calmness high state, well low state....

This paper explored the difference between weak stress (WS) and strong (SS) on relative ejection period (REP) of blood volume pulse (BVP). Features were extracted from REP series to recognize WS SS. The data acquired during defense 31 graduate students for their master's degree under real environment. result shows that, in situation, features have obtained a correct rate 91.93% distinguishing state state.

Stress plays an important role in our daily life. Long-term's psychological stress will lead to serious health as well social problems, it is detect and monitor the its early stage. Most existing detection equipment are contact-type, such wrist strap. However, a real application, working environment, contact-free system bring greater convenience. In this paper, we proposed novel framework for detecting classifying human based on respiratory signals measured remotely by using Kinect sensor...

This paper explored the influence of music on dental anxiety during ultrasonic scaling. Twenty-six patients having scaling treatment were randomly allocated to either an experimental group (with background scaling) or a control (without scaling), and their Electrocardiogram (ECG) data obtained. Statistic test showed that six ECG features had significant difference between controlled group. These further applied distinguish from those A SVM classifier achieved 92.3% accuracy for...

A multi-subject affective physiological database containing 380 records of 250 subjects is presented in this paper. While the individually watch amusement, anger, fear, or sadness elicitation film clip, their oxygen saturation (OXY), galvanic skin response (GSR), electrocardiogram (ECG), and front face videos are synchronously recorded. The have reported duration category emotion experience by means pressing a button during experiment filling out revised PANAS-X after experiment,...

Social anxiety (SA) would cause substantial distress and functional impairment. People who falls into SA produce excessive catecholamine, leading to the elevation of arterial blood pressure (ABP). Moreover, pulse transit time (PTT) has a high correlation with ABP. This paper puts forward use PTT series evaluate SA. The subjects' state low are respectively induced by impromptu speaking 21 audience without audience. mean is extracted as effective feature. Two sample t-test between shows that...

Depression is a major psychiatric concern and severely impacts the quality of life. Currently, questionnaires physiological signals are main methods to assess depression. This paper proposed achieve depression detection based on electrocardiogram (ECG) from realistic scenes. Forty-one college students took part in entire experiment. Thirty-nine indicators autonomic nervous system were calculated, including time domain, frequency non-linear features. Then, five machine learning classifiers...

Abstract Physiological studies have found that the autonomic nervous system plays an important role in controlling blood pressure values. This paper, based on machine learning approaches, analysed short-term heart rate variability to determine differences function between hypertensive patients and normal population. The electrocardiogram (ECG) of are 137 ECG recordings provided by Smart Health for Assessing Risk Events via (SHAREE database). RR intervals healthy subjects include data 18 from...

Public Speaking Anxiety (PSA) is one of the most universal subtypes social anxiety, and facial expression recognition PSA an immediate area research focus. The experiment obtained data 18 postgraduates in their thesis defense for master's degree. Then, valid were selected by using self-evaluation subject average evaluation 5 audience. Next, paper used Active Shape Model (ASM) algorithm feature extraction 68 points zones. Moreover, applied support vector machine to recognize anxiety state...

The current work applied machine learning methods to analyze students' group and individual states in the real classroom environment. purpose is provide insights into process for teachers students, so that they can manage effectively. We extracted three couples of learning, i.e., information input/processing retrieval/processing states, cognitive load matching mismatching mental fatigue nonfatigue states. recognition above was regarded as five binary classification problems. collected...