The SSVEP-Based BCI Text Input System Using Entropy Encoding Algorithm
المؤلفون المشاركون
Chen, Pei-Jarn
Zaeni, Ilham A. E.
Wu, Chung-Min
Tickle, Andrew Jason
Chen, Yeou-Jiunn
Chen, Shih-Chung
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-08-27
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
The so-called amyotrophic lateral sclerosis (ALS) or motor neuron disease (MND) is a neurodegenerative disease with various causes.
It is characterized by muscle spasticity, rapidly progressive weakness due to muscle atrophy, and difficulty in speaking, swallowing, and breathing.
The severe disabled always have a common problem that is about communication except physical malfunctions.
The steady-state visually evoked potential based brain computer interfaces (BCI), which apply visual stimulus, are very suitable to play the role of communication interface for patients with neuromuscular impairments.
In this study, the entropy encoding algorithm is proposed to encode the letters of multilevel selection interface for BCI text input systems.
According to the appearance frequency of each letter, the entropy encoding algorithm is proposed to construct a variable-length tree for the letter arrangement of multilevel selection interface.
Then, the Gaussian mixture models are applied to recognize electrical activity of the brain.
According to the recognition results, the multilevel selection interface guides the subject to spell and type the words.
The experimental results showed that the proposed approach outperforms the baseline system, which does not consider the appearance frequency of each letter.
Hence, the proposed approach is able to ease text input interface for patients with neuromuscular impairments.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Chen, Yeou-Jiunn& Chen, Shih-Chung& Zaeni, Ilham A. E.& Wu, Chung-Min& Tickle, Andrew Jason& Chen, Pei-Jarn. 2015. The SSVEP-Based BCI Text Input System Using Entropy Encoding Algorithm. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1073274
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Chen, Yeou-Jiunn…[et al.]. The SSVEP-Based BCI Text Input System Using Entropy Encoding Algorithm. Mathematical Problems in Engineering No. 2015 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1073274
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Chen, Yeou-Jiunn& Chen, Shih-Chung& Zaeni, Ilham A. E.& Wu, Chung-Min& Tickle, Andrew Jason& Chen, Pei-Jarn. The SSVEP-Based BCI Text Input System Using Entropy Encoding Algorithm. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1073274
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1073274
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