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All Journal Perfecting a Video Game with Game Metrics Indonesian Journal of Electrical Engineering and Computer Science
Mohd Azizi Abdul Rahman
Universiti Teknologi Malaysia
Computer Science & IT

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The Fusion of HRV and EMG Signals for Automatic Gender Recognition during Stepping Exercise Nor Aziyatul Izni Mohd Rosli; Mohd Azizi Abdul Rahman; Malarvili Balakrishnan; Saiful Amri Mazlan; Hairi Zamzuri
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 2: June 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i2.6113

Abstract

In this paper, a new gender recognition approach in accordance with the fusion of features extracted from electromyogram (EMG) and heart rate variability (HRV) during stepping activity using a stair stepper device is proposed. The fusion of EMG and HRV is investigated based on feature fusion approach. The feature fusion is carried out by chaining the feature vector extracted from the EMG and HRV signals. A proposed approach comprises of a sequence of processing steps which are preprocessing, feature extraction, feature selection and the feature fusion. The results demonstrated that the fusion approach had enhanced the performance of gender recognition compared to solely on EMG or HRV for the gender recognition.
Potential Field Based Motion Planning with Steering Control and DYC for ADAS Nurbaiti Wahid; Hairi Zamzuri; Nurhaffizah Hassan; Mohd Azizi Abdul Rahman
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 2: June 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i2.6132

Abstract

In this study, the development of motion planning and control for collision avoidance driver assistance systems is presented. A potential field approach has been used in formulating the collision avoidance algorithm based on predicted vehicle motion. Then, to realize the advanced driver assistance systems (ADAS) for collision avoidance, steering control system and direct yaw moment control (DYC) is designed to follow the desired vehicle motion. Performance evaluation is conducted in simulation environment in term of its performance in avoiding the obstacles. Simulation results show that the vehicle collision avoidance assistance systems can successfully complete the avoidance behavior without colliding.
Radial basis function neural network for head roll prediction modelling in a motion sickness study Sarah ‘Atifah Saruchi; Mohd Hatta Mohammed Ariff; Mohd Ibrahim Shapiai; Nurhaffizah Hassan; Nurbaiti Wahid; Noor Jannah Zakaria; Mohd Azizi Abdul Rahman; Hairi Zamzuri
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1637-1644

Abstract

Motion Sickness (MS) is the result of uneasy feelings that occurs when travelling. In MS mitigation studies, it is necessary to investigate and measure the occupant’s Motion Sickness Incidence (MSI) for analysis purposes. One way to mathematically calculate the MSI is by using a 6-DOF Subjective Vertical Conflict (SVC) model. This model utilises the information of the vehicle lateral acceleration and the occupant’s head roll angle to determine the MSI. The data of the lateral acceleration can be obtained by using a sensor. However, it is impractical to use a sensor to acquire the occupant’s head roll response. Therefore, this study presents the occupant’s head roll prediction model by using the Radial Basis Function Neural Network (RBFNN) method to estimate the actual head roll responses. The prediction model is modelled based on the correlation between lateral acceleration and head roll angle during curve driving. Experiments have been conducted to collect real naturalistic data for modelling purposes. The results show that the predicted responses from the model are similar with the real responses from the experiment. In future, it is expected that the prediction model will be useful in measuring the occupant’s MSI level by providing the estimated head roll responses.
The Gender Effects of Heart Rate Variability Response during Short-Term Exercise using Stair Stepper from Statistical Analysis Nor Aziyatul Izni Mohd Rosli; Mohd Azizi Abdul Rahman; Malarvili Balakrishnan; Takashi Komeda; Saiful Amri Mazlan; Hairi Zamzuri
Indonesian Journal of Electrical Engineering and Computer Science Vol 2, No 2: May 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v2.i2.pp359-366

Abstract

This study is aimed to explore the Heart Rate Variability (HRV) response during short-term exercise by stair stepper and to compare the finding between young healthy male and female subjects. The responses were statistically analyzed by applying independent-samples t-test statistical method. The calculation of Coefficient of Variation (CoV (%)) and the slope of the linear regression is used to assess the steadiness of the HRV. Furthermore, the results also demonstrated that female subjects had greater significant p-value of RMSSD feature and significance p-value in a LF feature is greater in male. Thus, the ongoing results demonstrated that males have the sympathetic drive and females have predominant parasympathetic drive using short-term exercise by stepper. Thus, the experiment results indicate the suitability of developing rehabilitation devices in the field of Autonomic Nervous System (ANS), research, control system and rehabilitation enginering, which may help to isolate males and females.
Co-Authors Hairi Zamzuri Malarvili Balakrishnan Mohd Hatta Mohammed Ariff Mohd Ibrahim Shapiai Noor Jannah Zakaria Nor Aziyatul Izni Mohd Rosli Nurbaiti Wahid Nurbaiti Wahid Nurhaffizah Hassan Nurhaffizah Hassan Saiful Amri Mazlan Sarah ‘Atifah Saruchi Takashi Komeda