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نمایش تعداد 1-6 از 6

Emotion classification based on forehead biosignals using support vector machines in music listening

نوع: Journal Paper

نویسنده : Mohsen Naji; Mohammad Firoozabadi; Parviz Azadfallah

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Evaluating nonlinear variability of mental fatigue behavioral indices during long-term attentive task

نوع: Journal Paper

نویسنده : Mahdi Azarnoosh; Ali Motie Nasrabadi; Mohammad Reza Mohammadi; Mohammad Firoozabadi

سال: 2012

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Investigation of mental fatigue through EEG signal processing based on nonlinear analysis: Symbolic dynamics

نوع: Journal Paper

نویسنده : Mahdi Azarnoosh; Ali Motie Nasrabadi; Mohammad Reza Mohammadi; Mohammad Firoozabadi

سال: 2011

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A novel human–machine interface based on recognition of multi-channel facial bioelectric signals

نوع: Journal Paper

نویسنده : Iman Mohammad Rezazadeh; S. Mohammad Firoozabadi; Huosheng Hu; S. Mohammad Reza Hashemi Golpayegani

سال: 2011

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Using affective human–machine interface to increase the operation performance in virtual construction crane training system: A novel approach

نوع: Journal Paper

نویسنده : Iman Mohammad Rezazadeh; Xiangyu Wang; Mohammad Firoozabadi; Mohammad Reza Hashemi Golpayegani

سال: 2011

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Co-Adaptive and Affective Human-Machine Interface for Improving Training Performances of Virtual Myoelectric Forearm Prosthesis

نوع: Journal Paper

نویسنده : Iman Mohammad Rezazadeh; Mohammad Firoozabadi; Huosheng Hu; S. Mohammad Reza Hashemi Golpayegani

سال: 2012

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Emotion classification based on forehead biosignals using support vector machines in music listening

Evaluating nonlinear variability of mental fatigue behavioral indices during long-term attentive task

Investigation of mental fatigue through EEG signal processing based on nonlinear analysis: Symbolic dynamics

A novel human–machine interface based on recognition of multi-channel facial bioelectric signals

Using affective human–machine interface to increase the operation performance in virtual construction crane training system: A novel approach

Co-Adaptive and Affective Human-Machine Interface for Improving Training Performances of Virtual Myoelectric Forearm Prosthesis

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Emotion classification based on forehead biosignals using support vector machines in music listening

Evaluating nonlinear variability of mental fatigue behavioral indices during long-term attentive task

Investigation of mental fatigue through EEG signal processing based on nonlinear analysis: Symbolic dynamics

A novel human–machine interface based on recognition of multi-channel facial bioelectric signals

Using affective human–machine interface to increase the operation performance in virtual construction crane training system: A novel approach

Co-Adaptive and Affective Human-Machine Interface for Improving Training Performances of Virtual Myoelectric Forearm Prosthesis