Remarks on Emotion Recognition from Bio-Potential Signals

نویسنده

  • Kazuhiko Takahashi
چکیده

This paper proposes an emotion recognition system from multi-modal bio-potential signals. For emotion recognition, support vector machines (SVM) are applied to design the emotion classifier and its characteristics are investigated. Using gathered data under psychological emotion stimulation experiments, the classifier is trained and tested. In experiments of recognizing five emotion: joy, anger, sadness, fear, and relax, recognition rate of 41.7% is achieved. The experimental result shows that using multi-modal bio-potential signals is feasible and that SVM is well suited for emotion recognition tasks.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Quantative Evaluation of the Efficiency of Facial Bio-potential Signals Based on Forehead Three-Channel Electrode Placement For Facial Gesture Recognition Applicable in a Human-Machine Interface

Introduction: Today, facial bio-potential signals are employed in many human-machine interface applications for enhancing and empowering the rehabilitation process. The main point to achieve that goal is to record appropriate bioelectric signals from the human face by placing and configuring electrodes over it in the right way. In this paper, heuristic geometrical position and configuration of ...

متن کامل

An Emotion Recognition Approach based on Wavelet Transform and Second-Order Difference Plot of ECG

Emotion, as a psychophysiological state, plays an important role in human communications and daily life. Emotion studies related to the physiological signals are recently the subject of many researches. In This study a hybrid feature based approach was proposed to examine affective states. To this effect, Electrocardiogram (ECG) signals of 47 students were recorded using pictorial emotion elici...

متن کامل

Speech Emotion Recognition Using Scalogram Based Deep Structure

Speech Emotion Recognition (SER) is an important part of speech-based Human-Computer Interface (HCI) applications. Previous SER methods rely on the extraction of features and training an appropriate classifier. However, most of those features can be affected by emotionally irrelevant factors such as gender, speaking styles and environment. Here, an SER method has been proposed based on a concat...

متن کامل

Real-time Analysis of Heart Rate Variability for a Mobile Human Emotion Recognition System

In this paper, we are focused on a mobile human emotion recognition system which is based on biosignal. Cardio signal is a proper bio-signal for emotion recognition and we use photoplethysmography (PPG) sensors to gather cardio signals. We mainly consider real-time heart rate variability (HRV) analysis which is essential to mobile emotion recognition. A mobile sensor module embedding a digital ...

متن کامل

Bio-sensing for Emotional Characterization without Word Labels

In this article, we address some of the issues concerning emotion recognition from processing physiological signals captured by bio-sensors. We discuss some of our preliminary results, and propose future directions for emotion recognition based on our lessons learned.

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004