| 講演名 | 2018-12-25 Emotions detection scheme using facial skin temperature and heart rate Kahil Mustafa Jamal S(SIT), Eiji Kamioka(SIT), |
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| 抄録(和) | The main aim of this study is to detect emotions based on facial skin temperature and Heart Rate (HR) Using thermals camera, HR monitor and machine learning techniques. The emotions targeted in this paper are Relax, Fear, Sadness, and Joy. An experiment was conducted with 20 healthy subjects (10 females and 10 males, 20 to 31 years old). Both visual and auditory media were used to induce these emotions in the experiment. Five points on the face were focused on, which are: nose, glabellar line (between the eyes and eyebrows), right/left cheeks, and the chin as well as the HR of the subjects. To determine the emotion, Artificial Neural Network (ANN) was used as a classifier and it achieved the accuracy of 85% with Multilayer Perceptron (MLP) as a classifier. This mechanism proves that facial skin temperature and HR can be a good indicator of the changes in humans? emotions state. |
| 抄録(英) | The main aim of this study is to detect emotions based on facial skin temperature and Heart Rate (HR) Using thermals camera, HR monitor and machine learning techniques. The emotions targeted in this paper are Relax, Fear, Sadness, and Joy. An experiment was conducted with 20 healthy subjects (10 females and 10 males, 20 to 31 years old). Both visual and auditory media were used to induce these emotions in the experiment. Five points on the face were focused on, which are: nose, glabellar line (between the eyes and eyebrows), right/left cheeks, and the chin as well as the HR of the subjects. To determine the emotion, Artificial Neural Network (ANN) was used as a classifier and it achieved the accuracy of 85% with Multilayer Perceptron (MLP) as a classifier. This mechanism proves that facial skin temperature and HR can be a good indicator of the changes in humans? emotions state. |
| キーワード(和) | Emotions detection / Facial skin temperature / Artificial neural network(ANN) / Thermals camera / Machine learning / Heart rate (HR) |
| キーワード(英) | Emotions detection / Facial skin temperature / Artificial neural network(ANN) / Thermals camera / Machine learning / Heart rate (HR) |
| 資料番号 | MoNA2018-47 |
| 発行日 | 2018-12-18 (MoNA) |
| 研究会情報 | |
| 研究会 | MoNA |
|---|---|
| 開催期間 | 2018/12/25(から1日開催) |
| 開催地（和） | 芝浦工大豊洲キャンパス |
| 開催地（英） | |
| テーマ（和） | 一般 |
| テーマ（英） | General |
| 委員長氏名（和） | 新熊 亮一(京大) |
| 委員長氏名（英） | Ryoichi Shinkuma(Kyoto Univ.) |
| 副委員長氏名（和） | 田頭 茂明(関大) / 北形 元(東北大) |
| 副委員長氏名（英） | Shigeaki Tagashira(Kansai Univ.) / Gen Kitagata(Tohoku Univ.) |
| 幹事氏名（和） | 石田 繁巳(九大) / 二瓶 浩一(NEC) / 西尾 理志(京大) / 齊藤 隆仁(NTTドコモ) |
| 幹事氏名（英） | Shigemi Ishida(Kyushu Univ.) / Koichi Nihei(NEC) / Takayuki Nishio(Kyoto Univ.) / Takato Saito(NTT DOCOMO) |
| 幹事補佐氏名（和） | 臼井 健(KDDI総合研究所) / 金井 謙治(早大) |
| 幹事補佐氏名（英） | Ken Usui(KDDI Research) / Kenji Kanai(Waseda Univ.) |
| 講演論文情報詳細 | |
| 申込み研究会 | Technical Committee on Mobile Network and Applications |
|---|---|
| 本文の言語 | ENG |
| タイトル（和） | |
| サブタイトル（和） | |
| タイトル（英） | Emotions detection scheme using facial skin temperature and heart rate |
| サブタイトル（和） | |
| キーワード(1)（和/英） | Emotions detection / Emotions detection |
| キーワード(2)（和/英） | Facial skin temperature / Facial skin temperature |
| キーワード(3)（和/英） | Artificial neural network(ANN) / Artificial neural network(ANN) |
| キーワード(4)（和/英） | Thermals camera / Thermals camera |
| キーワード(5)（和/英） | Machine learning / Machine learning |
| キーワード(6)（和/英） | Heart rate (HR) / Heart rate (HR) |
| 第 1 著者 氏名（和/英） | Kahil Mustafa Jamal S / Kahil Mustafa Jamal S |
| 第 1 著者 所属（和/英） | Shibaura institute of technology(略称：SIT) Shibaura institute of technology(略称：SIT) |
| 第 2 著者 氏名（和/英） | Eiji Kamioka / Eiji Kamioka |
| 第 2 著者 所属（和/英） | Shibaura institute of technology(略称：SIT) Shibaura institute of technology(略称：SIT) |
| 発表年月日 | 2018-12-25 |
| 資料番号 | MoNA2018-47 |
| 巻番号（vol） | vol.118 |
| 号番号（no） | MoNA-378 |
| ページ範囲 | pp.49-54(MoNA), |
| ページ数 | 6 |
| 発行日 | 2018-12-18 (MoNA) |