Shahriman Abu Bakar
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Preferred name
Shahriman Abu Bakar
Official Name
Shahriman, Abu Bakar
Alternative Name
Bakar, Shahriman A.B.
Shariman, A. B.
Ab, Shahriman
Abu Bakar, S.
Bakar, A. S.
Bakar, S. A.
Bakar, Shahriman Abu
Bakar, Sharifah Adzila Syed Abu
Bakar, S. Abu
Main Affiliation
Scopus Author ID
57196198202
Researcher ID
ELT-0087-2022

Research Output

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  • Publication
    Quantifying the Impact of Drilling Parameters on Temperature Elevation within Bone during the Process of Implant Site Preparation
    ( 2024-04-01)
    Islam M.A.
    ;
    Kamarrudin N.S.
    ;
    Ruslizam Daud
    ;
    Ishak Ibrahim
    ;
    Shahriman Abu Bakar
    ;
    Noor S.N.F.M.
    This study aimed to elucidate the influences of several drilling parameters on bone temperature during drilling, as excessive heat generation can cause thermal bone damage and affect post-surgery recovery. In vitro drilling tests were conducted on bovine femoral shaft cortical bone specimens. The parameters considered included tool rotational speed (s), feed rate (f), tool diameter (d), and drill tip angles of 118° and 135°. Drilling temperatures were studied across a range of 800–2000 rpm rotational speeds, 20–40 mm/min feed rates, and 2–4 mm drill diameters. A predictive statistical model was constructed using the response surface methodology (RSM). Analysis of variance (ANOVA) at a 95% confidence level (α = 0.05) revealed that rotational speed significantly impacted temperature increase, contributing to 59.74% of observed temperature rises. Drill diameter accounted for 16.21% of temperature variations, while feed rate contributed to 10.04% of the temperature rises. The study provides valuable insights into the predominant factors affecting bone temperature during drilling. Understanding these parameters and their interplay is pivotal for optimizing drilling conditions and minimizing potential thermal damage to bones.
  • Publication
    Lower extremity joint reaction forces and plantar fascia strain responses due to incline and decline walking
    ( 2021-01-01)
    Noor Arifah Azwani Abdul Yamin
    ;
    Khairul Salleh Basaruddin
    ;
    Shahriman Abu Bakar
    ;
    Ahmad Faizal Salleh
    ;
    Mohd Hanafi Mat Som
    ;
    Asyraf Hakimi Abu Bakar
    Purpose: The present study aims to investigate the effect of incline and decline walking on ground and joint reaction forces (JRF) of lower extremity and plantar fascia strain (PFS) under certain surface inclination angles. Methods: Twenty-three male subjects walked on a customized platform with four different surface inclinations (i.e., 0°, 5°,7.5° and 10°) with inclined and declined directions. The motion of the ten reflective markers was captured using Qualysis motion capture system (Qualysis, Gothenburg, Sweden) and exported to a visual three-dimensional (3D) software (C-motion, Germantown, USA) in order to analyze the GRF, JRF and PFS. Results: The results found that the peak vertical GRF is almost consistent for 0° and 5° inclination slope but started to decrease at 7.5° onwards during decline walking. The most affected JRF was found on knee at medial-lateral direction even as low as 5°, to 10° inclination for both walking conditions. Furthermore, the findings also show that the JRF of lower extremity was more affected during declined walking compared to inclined walking based on the number of significant differences observed in each inclination angle. The PFS was found increased with the increase of surface inclination. Conclusions: The findings could provide a new insight on the relationship of joint reaction forces and strain parameter in response to the incline and decline walking. It would benefit in providing a better precaution that should be considered during hiking activity, especially in medial-lateral direction in order to prevent injury or fall risk.
      4
  • Publication
    An Experimental Framework for Assessing Emotions of Stroke Patients using Electroencephalogram (EEG)
    ( 2020-06-17)
    Wan Khairunizam Wan Ahmad
    ;
    Yean C.W.
    ;
    Murugappan M.
    ;
    Ahmad Kadri Junoh
    ;
    Zuradzman Mohamad Razlan
    ;
    Wan Azani Wan Mustafa
    ;
    Shahriman Abu Bakar
    ;
    Ibrahim Z.
    ;
    Nurhafizah S.
    This research aims to assess the emotional experiences of stroke patients using Electroencephalogram (EEG) signals. Since emotion and health are interrelated, thus it is important to analyse the emotional states of stroke patients for neurofeedback treatment. Moreover, the conventional methods for emotional assessment in stroke patients are based on observational approaches where the results can be fraud easily. The observational-based approaches are conducted by filling up the international standard questionnaires or face to face interview for symptom recognition from psychological reactions of patients and do not involve experimental study. This paper introduces an experimental framework for assessing emotions of the stroke patient. The experimental protocol is designed to induce six emotional states of the stroke patient in the form of video-audio clips. In the experiments, EEG data are collected from 3 groups of subjects, namely the stroke patients with left brain damage (LBD), the stroke patients with right brain damage (RBD), and the normal control (NC). The EEG signals exhibit nonlinear properties, hence the non-linear methods such as the Higher Order Spectra (HOS) could give more information on EEG in the signal's analysis. Furthermore, the EEG classification works with a large amount of complex data, a simple mathematical concept is almost impossible to classify the EEG signal. From the investigation, the proposed experimental framework able to induce the emotions of stroke patient and could be acquired through EEG.
      1  11
  • Publication
    Investigating the Effect of Individuality Factors in Measuring Aggression induced by Human Brain
    ( 2022-01-01)
    Wan Khairunizam Wan Ahmad
    ;
    Xutung K.
    ;
    Lugieswaran M.
    ;
    Mustafa W.A.
    ;
    Ali H.
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    ;
    Mokhtar N.
    Aggression is a behaviour of human that may cause physical or emotional harm to others. Several factors that cause aggressive behaviour such as physical health, mental health and socioeconomic. Many previous researchers reported that aggression could be measured through either questionnaire or the brain signals. This paper proposes the experimental studies to collect the brain signal of the human subject for investigating the effect of individuality in aggression. Ten subjects are selected to perform the aggression activities. The experimental protocol for inducing aggression is proposed. In general, there are four tasks which is collecting brain data in relaxing state before and after the experiments, and data collection while playing game in muted and maximum volume levels. In the experiments, the subject are required to play a popular non-violence smart phone game named “Subway Surfers” and at the same time the EEG signals are recorded from the subject’s brain. In the signal pre-processing stage, a Butterworth filter is used to remove the noises contain in the signals. A windowing technique is employed for extracting significant features. A Pearson correlation technique is used to reduce and remain the less and most significant features. In the methodologies, the aggressiveness level A, is defined to investigate the effect of individuality in inducing the aggression signals. The proposed experimental protocol and signal processing techniques are seen able to generate level of aggression.
      1  25
  • Publication
    A study on the significance of exhaust manifold’s bending angle to the brake torque of 115cc SI engine
    ( 2023-01-01)
    Murali R.
    ;
    Shahriman Abu Bakar
    ;
    Mohd Afendi Rojan
    ;
    Zuradzman Mohamad Razlan
    ;
    Azizul A.I.
    ;
    Rani M.F.H.
    ;
    Mohd Ridzuan Mohd Jamir
    ;
    Sunan S.
    ;
    Ali M.H.A.
    ;
    Ramasamy G.
    ;
    Hisham M.H.N.
    The exhaust manifold is a crucial component of the exhaust system in any SI engine, responsible for efficiently expelling combustion products. However, when the exhaust manifold's design is suboptimal, it leads to negative consequences for the engine's performance due to the presence of backpressure. Backpressure refers to the difference between maximum exhaust pressure and atmospheric pressure. An increase in backpressure decreases the overall performance and fuel efficiency of an SI engine. This study aimed to investigate the bending angle characteristics of the exhaust manifold and the brake torque of the 115cc SI engine using 1D engine analysis. The relationship between the exhaust manifold's bending angle characteristics and the brake torque was analysed using Analysis of Variance (ANOVA) with a p-value of less than 0.05, while the validation with experimental data showed a maximum error of 6.62. In the previous research, it was noted that a lower bending angle leads to better performance. However, the current results indicate that out of the three bending angles considered, having one of them yields the most substantial enhancement in brake torque. The optimized bending angle configuration obtained from the analysis increased the mean brake torque by 0.011 Nm (0.14%). Consequently, this study enhances the average brake torque through the optimal bending angle characteristics of the exhaust manifold. The study's objective aligns with Sustainable Development Goal (SDG) 9: Industry, Innovation, and Infrastructure, as the improved performance achieved through an optimal exhaust manifold design configuration is expected to promote domestic technology development.
      1  17
  • Publication
    Development of Driving Simulation Experiment Protocol for the Study of Drivers’ Emotions by using EEG Signal
    ( 2024-06-01)
    Abdul Hafiz Abd Halin
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Wan Azani Wan Mustafa
    ;
    Muhajir Ab. Rahim
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    ;
    Saidatul Ardeenawatie Awang
    The Brain-Computer Interface (BCI) is a field of research that studies the EEG signal in order to elevate our understanding of the human brain. The applications of BCI are not limited to the study of the brain wave but also include its applications. The studies of human emotions specific to the vehicle driver are limited and not vastly explored. The EEG signal is used in this study to classify the emotions of drivers. This research aims to study the emotion classifications (surprise, relax/neutral, focus, fear, and nervousness) while driving the simulated vehicle by analyse the EEG signals. The experiments were conducted in 2 conditions, autonomous and manual drive in the simulated environment. In autonomous driving, vehicle control is disabled. While in manual drive, the subjects are able to control the steering angle, acceleration, and brake pedal. During the experiments, the EEG data of the subjects is recorded and then analyzed.
      1  28
  • Publication
    Classification of Human Emotions Using EEG Signals in a Simulated Environment
    ( 2022-01-01)
    Hafiz Halin
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Wan Azani Wan Mustafa
    ;
    Muhajir Ab. Rahim
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    The Brain-Computer Interface (BCI) is a computer-based system that acquires and analyses brain signals. The analysis of brain signals shows the physiological change that happens to the drivers. The physiological changes detected by the BCI system may not be visible to the naked eye. By using the BCI, it increases the diagnostic capability to detect the drivers' emotions. The negative drivers' emotions may cause bad decision making during driving the vehicle. The proposed method was developed to study the related emotions that occur during driving in the simulation environment. The experiments were designed in two situations, which are manual and autonomous drive. In the manual mode, the subjects will control the steering wheel and acceleration of the simulated vehicle. While in autonomous mode, all controls are disable and the subjects will experience the automatic simulation drive. The EEG data was recorded during the simulated drive (manual and autonomous). The EEG data from the subjects were then categorised into five emotions classifications.
      2  21
  • Publication
    Comparative study of surface temperature of lithium-ion polymer cells at different discharging rates by infrared thermography and thermocouple
    ( 2020-06-01)
    Rani M.F.H.
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    ;
    Ibrahim Z.
    ;
    Wan W.K.
    The objective of this study was to compare the surface temperature of lithium-ion polymer cells at different discharging rates by infrared thermography and thermocouple measurement. The cells were discharged by using a battery workstation at discharging rates of 2.0 A, 4.0 A, 6.0 A, 8.0 A, and 10.0 A in a controlled testing condition. This study focused on surface temperature distribution, maximum surface temperature, and temperature rise evolution. Higher discharging rate generates more heat in LiPo cells, which causes larger temperature gradient, higher maximum surface temperature, and higher temperature rise. During the discharging process, non-uniformity spatial distribution of LiPo cells was observed. No critical surface temperature was observed when reaching towards the end of discharging process as the surface temperature distribution managed to become spatially uniform. Most of the maximum surface temperatures were spotted at the lower part of the LiPo cells. In addition, the captured infrared (IR) images found that the temperature rises rapidly at higher discharging rates. In comparison, surface temperature measurement by infrared thermography provided higher accuracy than thermocouple. The findings of this study provide evidences in better development of battery thermal management systems with consideration of surface temperature distribution and temperature rise.
      2
  • Publication
    Structure dynamic analysis on mobility robot footrest for adult male
    ( 2022-01-01)
    Tan Wei Hong
    ;
    Shahriman Abu Bakar
    ;
    Teoh C.Y.
    ;
    Lee C.H.
    Mobility robot is mostly used by blind and partially sighted people as a mode of transport, leading to more people becoming vulnerable to invisible harm caused by vibration propagated along with the mobility robot structure. Random vibration from different sources propagated along with mobility robot to members of rider body, commonly known as Whole-body Vibration (WBV). Riders commonly experience WBV due to the propagation of vigorous vibration along with the mobility robot footrest. Therefore, vibration analysis is conducted onto the footrest of mobility robot to study its dynamic characteristics corresponding to the excitation frequency induced from the power train of mobility robot. Simulation analysis approach is selected as the method to conduct Finite Element Analysis (FEA). Computer-Aided Drawing (CAD) drafts of the footrest are prepared using CATIA and import the CAD footrest models to ANSYS Workbench to conduct FEA. Two set CAD drafts of footrests are prepared consist of the original and proposed footrest. As a result, it is found that increasing the mass of footrest can reduce the vibration level by more than 93% for X-axis, 70% for Y-axis and 90% for Z-axis. Furthermore, increasing the stiffness of footrest also increased the natural frequencies with the highest increment percentage in the second natural frequency of the proposed footrest, up to 70.12%. In a nutshell, with the increase of mass and designing an appropriate geometry of footrest able to reduce the vibration level significantly.
      8  2
  • Publication
    Classification of human emotions using EEG Signals in a simulated environment
    ( 2022-01-01)
    Hafiz Halin
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Wan Azani Wan Mustafa
    ;
    Muhajir Ab. Rahim
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    The Brain-Computer Interface (BCI) is a computer-based system that acquires and analyses brain signals. The analysis of brain signals shows the physiological change that happens to the drivers. The physiological changes detected by the BCI system may not be visible to the naked eye. By using the BCI, it increases the diagnostic capability to detect the drivers' emotions. The negative drivers' emotions may cause bad decision making during driving the vehicle. The proposed method was developed to study the related emotions that occur during driving in the simulation environment. The experiments were designed in two situations, which are manual and autonomous drive. In the manual mode, the subjects will control the steering wheel and acceleration of the simulated vehicle. While in autonomous mode, all controls are disable and the subjects will experience the automatic simulation drive. The EEG data was recorded during the simulated drive (manual and autonomous). The EEG data from the subjects were then categorised into five emotions classifications.
      4  3