Browsing Shahriman Abu Bakar, Assoc. Prof. Ir. Ts. Dr. by Author "Juliana Aida, Abu Bakar"

Now showing items 1-5 of 5

    • 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” ...

    • Clustering analysis of human finger grasping based on SOM neural network model 

      Nazrul H., Adnan; Wan Khairunizam, Wan Ahmad, Dr.; Shahriman, Abu Bakar, Dr.; Juliana Aida, Abu Bakar (IJENS Publishers, 2014)
      SOM (Self-organizing Maps) model was introduced to cluster and analyse on the human grasping activities of GloveMAP based on data reduction of the initial grasping data.By acquiring the data reduction of the initial hand ...

    • Experimental and analysis study on glovemap grasping force signal using Gaussian filtering method and principal component analysis (PCA) 

      Nazrul Hamizi, Adnan; Wan Khairunizam, Wan Ahmad, Dr.; Shahriman, Abu Bakar, Dr.; Hazry, Desa, Assoc. Prof. Dr.; Zuradzman, Mohamad Razlan, Dr.; Juliana Aida, Abu Bakar (ICIC International, 2014-06)
      This research paper presents the analysis study of human grasping forces for several objects by using a DataGlove called GloveMAP. The grasping force is generated from the bending of proximal and intermediate phalanges of ...

    • 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 ...