Pilot Study on Gait Classification Using fNIRS Signals
المؤلفون المشاركون
Jin, Hedian
Li, Chunguang
Xu, Jiacheng
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-10-17
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Rehabilitation training is essential for motor dysfunction patients, and the training through their subjective motion intention, comparing to passive training, is more conducive to rehabilitation.
This study proposes a method to identify motion intention of different walking states under the normal environment, by using the functional near-infrared spectroscopy (fNIRS) technology.
Twenty-two healthy subjects were recruited to walk with three different gaits (including small-step with low-speed, small-step with midspeed, midstep with low-speed).
The wavelet packet decomposition was used to find out the main characteristic channels in different motion states, and these channels with links in frequency and space were combined to define as feature vectors.
According to different permutations and combinations of all feature vectors, a library for support vector machines (libSVM) was used to achieve the best recognition model.
Finally, the accuracy rate of these three walking states was 78.79%.
This study implemented the classification of different states’ motion intention by using the fNIRS technology.
It laid a foundation to apply the classified motion intention of different states timely, to help severe motor dysfunction patients control a walking-assistive device for rehabilitation training, so as to help them restore independent walking abilities and reduce the economic burdens on society.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Jin, Hedian& Li, Chunguang& Xu, Jiacheng. 2018. Pilot Study on Gait Classification Using fNIRS Signals. Computational Intelligence and Neuroscience،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1130832
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Jin, Hedian…[et al.]. Pilot Study on Gait Classification Using fNIRS Signals. Computational Intelligence and Neuroscience No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1130832
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Jin, Hedian& Li, Chunguang& Xu, Jiacheng. Pilot Study on Gait Classification Using fNIRS Signals. Computational Intelligence and Neuroscience. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1130832
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1130832
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