A4 Vertaisarvioitu artikkeli konferenssijulkaisussa
Facial expression recognition with sEMG method
Tekijät: Mingzhe Jiang, Amir-Mohammad Rahmani, Tomi Westerlund, Pasi Liljeberg, Hannu Tenhunen
Toimittaja: Yulei Wu, Geyong Min, Nektarios Georgalas, Jia Hu, Luigi Atzori, Xiaolong Jin, Stephen Jarvis, Lei Liu, Ramón Agüero Calvo
Konferenssin vakiintunut nimi: IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing
Julkaisuvuosi: 2015
Kokoomateoksen nimi: 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM)
Aloitussivu: 981
Lopetussivu: 988
Sivujen määrä: 8
ISBN: 978-1-5090-0153-8
DOI: https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.148
Facial expression recognition has broad application prospects in the fields of psychological study, nursing care, Human Computer Interaction as well as affective computing. The method with surface Electromyogram (sEMG), which is one of vital bio-signals, has its superiority in several aspects such as high temporal resolution and data processing efficiency over other methods. Researches regarding EMG signal to study emotional expression have started since the second half of last century. Meanwhile, studies on myoelectrical control systems focusing on the computation of bio-signal processing and data analysis have been blooming in the recent twenty years. To have a comprehensive view of utilizing facial sEMG method, a systematic review is presented in this paper for facial expression recognition from experiment design to measurement systems, and data analysis steps.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
