Browsing Wan Khairunizam Wan Ahmad, Assoc. Prof. Ir. Ts. Dr. by Author "liana@uum.edu.my"

Now showing items 1-5 of 5

    • Accurate and effective method to smoothen grasping force signal of glovemap using gaussian filter 

      Nazrul Hamizi, Adnan; Wan Khairunizam, Wan Ahmad, Dr.; Zuradzman, Mohamad Razlan, Dr.; Juliana Aida, Abu Bakar, Dr.; Mohd Azri, Abd Aziz; M. Hazwan, Ali (IJENS Publishers, 2013-06)
      This paper presents the use of Gaussian filtering method to smoothen the grasping force signals by using computational Gaussian Algorithm. The finger grasping force signals are measured using a low cost DataGlove called ...

    • Analysis of finger movement by using motion information from glovemap and motion capture system 

      Moustafa Hazwan, Ali; Wan Khairunizam, Wan Ahmad, Dr.; Nazrul Hamizi, Adnan; Y. C, Seah; Juliana Aida, Abu Bakar, Dr.; Zuradzman, Mohamad Razlan, Dr. (IJENS Publishers, 2013)
      Nowadays, through the advancement of science and technology, possibility of human finger provide information into computer is no longer question. Fingers movement and hand motion continuously being center of research in ...

    • Classification of finger grasping by using PCA based on best matching unit (BMU) approach 

      Nazrul Hamizi, Adnan; Wan Khairunizam, Wan Ahmad, Dr.; Shahriman, Abu Bakar, Dr.; Juliana Aida, Abu Bakar (International Association for Engineering and Management Education (IAEME), 2013)
      In this paper we proposed to analyze in depth the thumb, index and middle fingers on the fingertips bending or grasping movement against an objects. The finger movement data are measured using a low cost DataGlove “GloveMAP” ...

    • Extracting features of fingertips bending by using self-organizing map 

      Nazrul Hamizi, Adnan; Wan Khairunizam, Wan Ahmad, Dr.; Shahriman, Abu Bakar, Dr.; Juliana Aida, Abu Bakar (American-Eurasian Network for Scientific Information (AENSI), 2014)
      In this paper the method of Self-Organizing Maps (SOM) is introduced to analyze the human grasping activities of human fingertips bending using the low cost DataGlove called as GloveMAP. The research shows that the ...

    • Principle component analysis for the classification of fingers movement data using dataglove "glovemap" 

      Nazrul H., Adnan; Wan Khairunizam, Wan Ahmad, Dr.; Shahriman, Abu Bakar, Dr.; Juliana Aida, Abu Bakar (International Association for Engineeering and Management Education, 2013-03)
      Nowadays, many classifier methods have been used to classify or categorizehuman body motions of human posture including the classification of fingers movement. Principal Component Analysis (PCA) is one of classical method ...