Mohd Hanafi Mat Som
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Mohd Hanafi Mat Som
Official Name
Mohd Hanafi , Mat Som
Alternative Name
Mat Som, M. H
Mat Som, Mohd Hanafi
Som, M. H.M.
Som, M. H.Mat
Som, Mohd Hanafi Mat
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Scopus Author ID
57215715847
Researcher ID
R-4326-2019

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Correlation between postural stability and lower extremity joint reaction forces in young adults during incline and decline walking

2023 , Noor Arifah Azwani Abdul Yamin , Khairul Salleh Basaruddin , Muhammad Farzik Ijaz , Hiroshi Takemura , Mohd Hanafi Mat Som , Muhammad Nazrin Shah Shahrol Aman

Postural stability may be affected during slope walking, as there are different body kinetics and kinematic responses compared with level walking. Understanding body adaptations toward different inclinations is essential to prevent the risk of injury from falls or slips. This study was conducted to determine the correlations between stability parameters and loading response in terms of joint reaction force at the lower-extremity joints during inclined and declined walking. Twenty male subjects walked in the level, incline, and decline directions on a custom-built platform at three different slope angles (i.e., 5°, 7.5°, and 10°). To determine the ground reaction force (GRF), joint reaction force (JRF), center of pressure (COP), and center of mass (COM), a motion capture system was used to read the data of the ten reflective markers and transfer them to visual three-dimensional (3D) software. Pearson’s correlation test was performed with statistical significance set at p < 0.05 to evaluate the correlation of the required coefficient of friction (RCOF), postural stability index (PSI), and COP-COM distance with the JRF. This study has identified that the JRF changes in opposition to the changes in the RCOF during the initial strike during incline and decline walking, as JRF increases, the RCOF decreases with different strengths of correlation. There is also a strong positive correlation between the PSI and JRF in the proximal–distal direction, where the JRFs change in accordance with the change in the PSI, and the JRF increases with the increment of PSI. In addition, the JRF of the lower extremity also changed in a manner similar to the COP-COM distance in the medial–lateral direction. Overall, each stability parameter was correlated with the JRF of the lower-extremity joints in different directions and strengths. This study demonstrated that slope walking is particularly affected by surface inclination in terms of stability and loading. Therefore, this research can serve as a basis for future studies on slopes, as there is no specific basis for a maximum degree of inclination that is safe and suitable for all applications.

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Performance analysis of diabetic retinopathy detection using fuzzy entropy multi-level thresholding

2023-07-01 , Qaid M.S.A. , Shafriza Nisha Basah , Yazid H. , Mohd Hanafi Mat Som , Khairul Salleh Basaruddin , Ali Hassan M.K.

Diabetic Retinopathy (DR) is one of the major causes of blindness. Many DR detection systems were developed to segment and determine the type and number of lesions that appeared on retinal images and used to classify DR and its severity level. Even though several researchers have already proposed many automated diagnosis systems with different image segmentation algorithms, their accuracy and reliability are generally unexplored. The accuracy of an automated diagnosis system usually depends on the segmentation techniques. The accuracy of this system is heavily dependent upon the retinal and image parameters, which have intensity level difference between background (BG)-blood vessels (BV), BV-bright lesions, BV-dark lesions, and noise levels. In this work, the automated diagnosis system accuracy has been analysed to successfully detect DR and its severity levels. The focus is on fundus image modalities segmentation based on fuzzy entropy multi-level thresholding. The analysis aimed to develop conditions to guarantee accurate DR detection and its severity level. Firstly, a retinal image model was developed that represents the retina under the variation of all retinal and image parameters. Overall, 45,000 images were developed using the retinal model. Secondly, feasibility and consistency analysis were performed based on a specific design Monte Carlo statistical method to quantify the successful detection of DR and its severity levels. The conditions to guarantee accurate DR detections are: BG to BV > 30% and BV to the dark lesions (MAs) >15% for mild DR, BG to BV > 40% and BV to the dark lesions (MAs and HEM) > 20% for moderate DR, and BG to BV > 30% and BV to the dark lesions (MAs and HEM) > 15%, and BV to the bright lesions (EX) > 55% for severe DR. Finally, the validity of these conditions was verified by comparing their accuracy against real retinal images from publicly available datasets. The verification results demonstrated that the condition for the analysis could be used to predict the success of DR detection.

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Pre- and Post-operative Assessment of Bone with Osteogenesis Imperfecta using Finite Element Analysis: A Review

2024-02-01 , Wanna Soh Bua Chai , Khairul Salleh Basaruddin , Mohd Hanafi Mat Som , Fauziah Che Mat , Muhamad Khairul Ali Hassan

Applications of finite element analysis (FEA) to demonstrate the pre-and post-operative conditions of the brittle bone-related disease known as osteogenesis imperfecta (OI) has been widely used in the past and at present. The method used to reconstruct the bone model that resemble the OI bone geometry plays an important aspect to accurately represent the bone condition to provide more alternative ways to evaluate surgical intervention options. Other factors such as material properties and boundary conditions also reflect the results of the analysis. Therefore, the aim of this review paper is to analyse the approaches of previous studies in terms of model geometry construction, selection of materials properties and boundary conditions to enable a deeper understanding and evaluation of bone fractures in OI patients. The biomechanical design of the intramedullary (IM) rods used in post-operative surgery and the interface between IM rods and bone fragments are also discussed in this review paper.

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Finite Element Analysis on Tibia with Osteogenesis Imperfecta: The Influence of Incomplete Bone in Model Reconstruction

2020-07-01 , Tan S.L. , Mohd Hanafi Mat Som , Khairul Salleh Basaruddin , Sulaiman A.R. , Aziz Safar M.J. , Amin Megat Ali M.S.

Osteogenesis Imperfecta (OI) patients continuously experience bone fractures throughout their lifetime. To date, physicians still have difficulties to determine a suitable method to predict fractures. The paper aims to develop finite element (FE) model based on patient-specific computed tomography (CT) images for the purpose of determination of fracture risk. Three types of FE models have been developed using VOXELCON. The first tibia model was a complete tibia composed of epiphysis and diaphysis part of the bone. The second tibia model only include the diaphysis part of the bone which is the shaft. The final tibia model, composed of diaphysis, and a part of epiphysis of the bone which is the extension shaft. Each model uses the same Young's Modulus (19 GPa) and Poisson's ratio (0.3). The developed models were used for FE analysis using VOXELCON under various loadings, and then the results of the different models were compared. Geometry and volume of the models, and surface area of load applied on the models affect distribution of von Mises stress. All the stress values were judged by the fracture criteria, assumed at 115 MPa. It was found out patient is safe in the standing position. Conversely, jumping will cause fracture in the three types of FE models.

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Performance analysis of diabetic retinopathy detection using fuzzy entropy multi-level thresholding

2023 , Mohammed Saleh Ahmed Qaid , Shafriza Nisha Basah , Khairul Salleh Basaruddin , Haniza Yazid , Muhamad Khairul Ali Hassan , Mohd Hanafi Mat Som

Diabetic Retinopathy (DR) is one of the major causes of blindness. Many DR detection systems were developed to segment and determine the type and number of lesions that appeared on retinal images and used to classify DR and its severity level. Even though several researchers have already proposed many automated diagnosis systems with different image segmentation algorithms, their accuracy and reliability are generally unexplored. The accuracy of an automated diagnosis system usually depends on the segmentation techniques. The accuracy of this system is heavily dependent upon the retinal and image parameters, which have intensity level difference between background (BG)-blood vessels (BV), BV-bright lesions, BV-dark lesions, and noise levels. In this work, the automated diagnosis system accuracy has been analysed to successfully detect DR and its severity levels. The focus is on fundus image modalities segmentation based on fuzzy entropy multi-level thresholding. The analysis aimed to develop conditions to guarantee accurate DR detection and its severity level. Firstly, a retinal image model was developed that represents the retina under the variation of all retinal and image parameters. Overall, 45,000 images were developed using the retinal model. Secondly, feasibility and consistency analysis were performed based on a specific design Monte Carlo statistical method to quantify the successful detection of DR and its severity levels. The conditions to guarantee accurate DR detections are: BG to BV > 30% and BV to the dark lesions (MAs) >15% for mild DR, BG to BV > 40% and BV to the dark lesions (MAs and HEM) > 20% for moderate DR, and BG to BV > 30% and BV to the dark lesions (MAs and HEM) > 15%, and BV to the bright lesions (EX) > 55% for severe DR. Finally, the validity of these conditions was verified by comparing their accuracy against real retinal images from publicly available datasets. The verification results demonstrated that the condition for the analysis could be used to predict the success of DR detection.

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Effect of sloped walking on ground and joint reaction forces

2023-04-24 , Noor Arifah Azwani Abdul Yamin , Khairul Salleh Basaruddin , Zahar N.Z.A.C. , Mohd Hanafi Mat Som , Salleh A.F. , Khudzari A.Z.M.

Sloped walking is commonly known to be benefited to health. However, the increase of GRF that contribute to increment to JRF during inclined walking compared to level-ground walking also has been a concern in preventing injury. Therefore, the aim of this study was to assess the effect of sloped walking in comparison with level-ground walking to GRF and JRF at hip, knee and ankle joints. Ten healthy male participants (age: 24 ± 1.2 years old with normal body mass index (BMI)) were asked to walk at preferred speed on customized ramp at the slopes of -5°, 0° and 5°. Kinematic data were captured with five-camera motion capture system (Qualysis Track Motion). Kinetic data were measured with two force plate (Bertex) which embedded into the ramp. A musculoskeletal model (Visual 3D C-motion) was used to assess joint reaction force (JRF) of lower limb. Result show that peak value of mean GRF as well as maximum JRF at all joints of lower limb were higher during sloped walking compared to level-ground walking. In addition, the maximum JRF at hip is the highest, followed by knee and ankle for all walking conditions. GRF had a significant influence to the JRF at lower limb during inclined and declined walking where sloped walking have a higher force at all joints of lower limb than level- ground walking. Therefore, a suitable walking strategy in adapting the forces demand is required in preventing any slope slippage and/or vertical body instability that might lead to musculoskeletal injury.

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Analysis of Optical Character Recognition using EasyOCR under Image Degradation

2023 , Muhamad Aqil Mirza Salehudin , Shafriza Nisha Basah , Haniza Yazid , Khairul Salleh Basaruddin , Muhammad Juhairi Aziz Safar , Mohd Hanafi Mat Som , Khairul Azami Sidek

This project explores EasyOCR's performance with Latin characters under image degradation. Variables like character-background intensity difference, Gaussian blur, and relative character size were tested. EasyOCR excels in distinguishing unique lowercase and uppercase characters but tends to favor uppercase for similar shapes like C, S, U, or Z. Results showed that high character-background intensity differences affected OCR output, with confidence scores ranging from 3 % to 80%. Higher differences caused confusion between characters like o and 0, or i and 1. Increased Gaussian blur hindered recognition but improved it for certain letters like v. Image size had a significant impact, with character detection failing as sizes decreased to 40% to 30% of the original. These findings provide insights into EasyOCR's capabilities and limitations with Latin characters under image degradation.

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Effect of sloped walking on ground and joint reaction forces

2023 , Noor Arifah Azwani Abdul Yamin , Khairul Salleh Basaruddin , N. Z. A. C. Zahar , Mohd Hanafi Mat Som , Ahmad Faizal Salleh , Zahran Khudzari

Sloped walking is commonly known to be benefited to health. However, the increase of GRF that contribute to increment to JRF during inclined walking compared to level-ground walking also has been a concern in preventing injury. Therefore, the aim of this study was to assess the effect of sloped walking in comparison with level-ground walking to GRF and JRF at hip, knee and ankle joints. Ten healthy male participants (age: 24 ± 1.2 years old with normal body mass index (BMI)) were asked to walk at preferred speed on customized ramp at the slopes of -5°, 0° and 5°. Kinematic data were captured with five-camera motion capture system (Qualysis Track Motion). Kinetic data were measured with two force plate (Bertex) which embedded into the ramp. A musculoskeletal model (Visual 3D C-motion) was used to assess joint reaction force (JRF) of lower limb. Result show that peak value of mean GRF as well as maximum JRF at all joints of lower limb were higher during sloped walking compared to level-ground walking. In addition, the maximum JRF at hip is the highest, followed by knee and ankle for all walking conditions. GRF had a significant influence to the JRF at lower limb during inclined and declined walking where sloped walking have a higher force at all joints of lower limb than level- ground walking. Therefore, a suitable walking strategy in adapting the forces demand is required in preventing any slope slippage and/or vertical body instability that might lead to musculoskeletal injury.

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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.

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A Review on Deep Convolutional Neural Network Architectures for Medical Image Segmentation

2022-01-01 , Nik Hasnida Awang Mustapa , Mohd Hanafi Mat Som , Khairul Salleh Basaruddin , Megat Syahirul Amin Megat Ali

Osteogenesis Imperfecta (OI) image segmentation by using Deep Convolutional Neural Network (DCNN) is yet to be evaluated. The segmentation of OI is very important as a useful tool for medical experts to further analyze the fracture risk and avoid bone fractures. In this paper, we present the review of DCNN architecture used in image segmentation. The images were obtained from different types of modalities such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), or Ultrasound. Several architectures have been used by previous studies include U-Net, faster R-CNN, ResNet, and MS-Net architecture to automatically segment the images. Overall, all researchers from the reviewed papers concluded that the proposed DCNN architecture gave good performance results.

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