Improving Eye Motion Sequence Recognition Using Electrooculography Based on Context-Dependent HMM
المؤلفون المشاركون
Fang, Fuming
Shinozaki, Takahiro
Horiuchi, Yasuo
Kuroiwa, Shingo
Furui, Sadaoki
Musha, Toshimitsu
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-09-27
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Eye motion-based human-machine interfaces are used to provide a means of communication for those who can move nothing but their eyes because of injury or disease.
To detect eye motions, electrooculography (EOG) is used.
For efficient communication, the input speed is critical.
However, it is difficult for conventional EOG recognition methods to accurately recognize fast, sequentially input eye motions because adjacent eye motions influence each other.
In this paper, we propose a context-dependent hidden Markov model- (HMM-) based EOG modeling approach that uses separate models for identical eye motions with different contexts.
Because the influence of adjacent eye motions is explicitly modeled, higher recognition accuracy is achieved.
Additionally, we propose a method of user adaptation based on a user-independent EOG model to investigate the trade-off between recognition accuracy and the amount of user-dependent data required for HMM training.
Experimental results show that when the proposed context-dependent HMMs are used, the character error rate (CER) is significantly reduced compared with the conventional baseline under user-dependent conditions, from 36.0 to 1.3%.
Although the CER increases again to 17.3% when the context-dependent but user-independent HMMs are used, it can be reduced to 7.3% by applying the proposed user adaptation method.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Fang, Fuming& Shinozaki, Takahiro& Horiuchi, Yasuo& Kuroiwa, Shingo& Furui, Sadaoki& Musha, Toshimitsu. 2016. Improving Eye Motion Sequence Recognition Using Electrooculography Based on Context-Dependent HMM. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1099741
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Fang, Fuming…[et al.]. Improving Eye Motion Sequence Recognition Using Electrooculography Based on Context-Dependent HMM. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1099741
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Fang, Fuming& Shinozaki, Takahiro& Horiuchi, Yasuo& Kuroiwa, Shingo& Furui, Sadaoki& Musha, Toshimitsu. Improving Eye Motion Sequence Recognition Using Electrooculography Based on Context-Dependent HMM. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1099741
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1099741
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر