Wan Zuki Azman Wan Muhamad
Thumbnail Image
Preferred name
Wan Zuki Azman Wan Muhamad
Official Name
Wan Zuki Azman, Wan Muhamad
Alternative Name
Azman, Wan Zuki
Wan Ahmad, Wan Zuki Azman
Muhamad, Wan Zuki Azmanwan
Main Affiliation
Scopus Author ID
55860800560
Researcher ID
R-4128-2019

Research Output

Filters

2
2
2
2
Reset filters

Settings
Now showing 1 - 2 of 2
  • Publication
    Effect of Arm Swing Direction on Forward and Backward Jump Performance Based on Biomechanical Analysis
    ( 2021-11-25)
    Teoh L.M.
    ;
    Hamzah Sakeran
    ;
    Ahmad Faizal Salleh
    ;
    Mohammad Shahril Salim
    ;
    Wan Zuki Azman Wan Muhamad
    ;
    Shapie M.A.M.
    Previous studies have examined the role of arm swing for various types of jumping technique, but none have been found to study about the gender differences in term of the role of arm swing on forward and backward jump. This study aimed to compare the jumping performance between male and female for forward and backward jump. Seven male and seven female subjects performed four trials of forward and backward jump with (FJA, BJA) and without arm swing (FJ, BJ) respectively. Qualisys Track Manager System, EEGO Sports, Visual3D and MATLAB software was used to record and analyze the performance. According to the result, the triceps brachii muscle is the most active muscle compared to other muscles during jumping. The normalized vGRF showed significant correlation with jump height when jumping forward and backward (p<0.01). The arm swing enhanced the jumping performance by increasing the jump height. Males demonstrated greater vGRF and jump height than females. When jump with arm swing, the left knee flexion angle of males increased whereas females decreased. These findings concluded there is different between males and females during jumping.
  • Publication
    Statistical analysis in clinical gait analysis using Kinovea between normal and simulated abnormal gaits
    ( 2023-02-21)
    Rahim S.A.
    ;
    Hamzah Sakeran
    ;
    Ahmad Faizal Salleh
    ;
    Mohammad Shahril Salim
    ;
    Wan Zuki Azman Wan Muhamad
    ;
    Shapie M.A.M.
    Kinematic analysis of human gait is an effective strategy to detect and assess an individual's gait to diagnose and develop and guide follow-on rehabilitation protocols. So, an accurate, objective gait analysis system has potential to facilitate rehabilitation process. System using smartphone-Kinovea represent an emerging technology for physical activity assessment and that may be relevant for gait analysis. The objective of this study was to determine gait displacement, speed and joint angle by using smartphone-Kinovea software system - to compare the normal gait with four distinct simulated gait abnormalities. Also, to assess validity of the proposed system by compared with QTM as gold standard. 30 participants completed an experiment in which they completed several gait trails on single day. Gait types were analyzed using statistical analysis (two-way MANOVA). As for validation assessment was analyzed using paired t-test by comparing proposed system with QTM. Results shows that joint angles for abnormal gaits are higher mean (Standard Deviation) compared to normal gait during HS and TO. While, normal gait exhibits higher mean (Standard Deviation) for d and s during both IDS and TDS phases compared to other four abnormal gaits in both genders. Also, there are significant different (p<0.05) of gait for all gait comparisons for all parameters, except hip angle of normal-HP with p=0.495. Moreover, there is some gait was similar with other gait due to they shared underlying kinematic aspects such as BA and DP. The validation of the system gives moderate result. These support that the smartphone-Kinovea system have potential in detecting and identifying abnormal gaits, and for future implementation in diagnosis and rehabilitation.