Pub Date : 2019-11-01DOI: 10.1109/BMEiCON47515.2019.8990257
Jamie A. O’Reilly, Sakuntala Tanpradit, T. Puttasakul, M. Sangworasil, T. Matsuura, P. Wibulpolprasert, Khaisang Chousangsuntorn
Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressive bilateral renal cyst formation, leading to severe increases in kidney volume and loss of function. Total kidney volume (TKV) is the only established biomarker for tracking ADPKD. This is measured multiple times per year from each patient to examine the extent of renal enlargement and overall cyst load. Currently this is conducted by planimetry tracing, which involves manually delineating kidneys from surrounding tissues in the abdominal cavity using a digital drawing tool. By performing this on every image in a magnetic resonance scan, TKV is estimated. This is a time-consuming and laborious process for radiologists. Our aim is to develop an automated method for ADPKD patient kidney segmentation and quantifying TKV. Thirteen MRI scans of kidneys ranging across the spectrum from normal to severe cyst load were analyzed. Images were separated into two halves, each made up of 200 square regions. Features were extracted from grayscale values of each region, and these data were combined in a supervised decision tree algorithm to classify between kidney and non-kidney regions. Filtering and dilation were applied to the classified 400x400 matrix in order to roughly segment the kidneys. Contrast enhancement and k-means clustering was performed before applying an active contour function to determine kidney edges. Eccentricity analysis confirmed appropriate relative sphericity for segmented kidney shapes, before combining their areas with linear extrapolation to estimate TKV. This protocol is evaluated against clinical reference standard TKV measurements.
{"title":"Automatic segmentation of polycystic kidneys from magnetic resonance images using decision tree classification and snake algorithm","authors":"Jamie A. O’Reilly, Sakuntala Tanpradit, T. Puttasakul, M. Sangworasil, T. Matsuura, P. Wibulpolprasert, Khaisang Chousangsuntorn","doi":"10.1109/BMEiCON47515.2019.8990257","DOIUrl":"https://doi.org/10.1109/BMEiCON47515.2019.8990257","url":null,"abstract":"Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressive bilateral renal cyst formation, leading to severe increases in kidney volume and loss of function. Total kidney volume (TKV) is the only established biomarker for tracking ADPKD. This is measured multiple times per year from each patient to examine the extent of renal enlargement and overall cyst load. Currently this is conducted by planimetry tracing, which involves manually delineating kidneys from surrounding tissues in the abdominal cavity using a digital drawing tool. By performing this on every image in a magnetic resonance scan, TKV is estimated. This is a time-consuming and laborious process for radiologists. Our aim is to develop an automated method for ADPKD patient kidney segmentation and quantifying TKV. Thirteen MRI scans of kidneys ranging across the spectrum from normal to severe cyst load were analyzed. Images were separated into two halves, each made up of 200 square regions. Features were extracted from grayscale values of each region, and these data were combined in a supervised decision tree algorithm to classify between kidney and non-kidney regions. Filtering and dilation were applied to the classified 400x400 matrix in order to roughly segment the kidneys. Contrast enhancement and k-means clustering was performed before applying an active contour function to determine kidney edges. Eccentricity analysis confirmed appropriate relative sphericity for segmented kidney shapes, before combining their areas with linear extrapolation to estimate TKV. This protocol is evaluated against clinical reference standard TKV measurements.","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133355869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/BMEiCON47515.2019.8990274
K. Charoensuk, T. Sethaput, I. Nilkhamhang
In case study, the dynamical behavior of various systems including intracranial pressure (ICP), cerebral perfusion pressure (CPP), intraocular pressure (IOP), arterial blood pressure (ABP), and blood flow (BF) are studied based on the equivalent electrical model. The healthy people from clinical data are used for study those behaviors. Resistor-Capacitance network is constructed to simulate ICP inside the skull, IOP of the retinal vessel, CPP in the skull. Moreover, ABP from the heart (85 - 120 mmHg) and Intraspinal Pressure (ISP) (50 - 60 mmHg) are applied as inputs to this model. The results show the value of ICP of normal state, IOP, and CPP in the skull are 5-15 mmHg, 20-35 mmHg, and 65-90 mmHg respectively. For the phase relationship among ABP, CPP, IOP, and ICP are synchronized. The differential phase between ABP and BF is 0.25 to 0.5 second where ABP waveform was leaded BF waveform. Our model is verified by clinical data from noninvasive measuring method. This model provides a clear explanation of the interaction behavior between ICP, CCP, IOP, ABP and BF of healthy individuals.
{"title":"Electrical Modeling of Dynamical Interaction among Intracranial Pressure, Intraocular Pressure, Cerebral Perfusion Pressure, and Arterial Blood Pressure","authors":"K. Charoensuk, T. Sethaput, I. Nilkhamhang","doi":"10.1109/BMEiCON47515.2019.8990274","DOIUrl":"https://doi.org/10.1109/BMEiCON47515.2019.8990274","url":null,"abstract":"In case study, the dynamical behavior of various systems including intracranial pressure (ICP), cerebral perfusion pressure (CPP), intraocular pressure (IOP), arterial blood pressure (ABP), and blood flow (BF) are studied based on the equivalent electrical model. The healthy people from clinical data are used for study those behaviors. Resistor-Capacitance network is constructed to simulate ICP inside the skull, IOP of the retinal vessel, CPP in the skull. Moreover, ABP from the heart (85 - 120 mmHg) and Intraspinal Pressure (ISP) (50 - 60 mmHg) are applied as inputs to this model. The results show the value of ICP of normal state, IOP, and CPP in the skull are 5-15 mmHg, 20-35 mmHg, and 65-90 mmHg respectively. For the phase relationship among ABP, CPP, IOP, and ICP are synchronized. The differential phase between ABP and BF is 0.25 to 0.5 second where ABP waveform was leaded BF waveform. Our model is verified by clinical data from noninvasive measuring method. This model provides a clear explanation of the interaction behavior between ICP, CCP, IOP, ABP and BF of healthy individuals.","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132928565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/BMEiCON47515.2019.8990317
Tustanah Phukhachee, S. Maneewongvatana, B. Kaewkamnerdpong
Intrinsic motivation is an internal brain state that leads us to increase the efforts and attention in pursuing the goal. This intrinsic motivation can emerge for self-satisfaction without any external reward. In the education system, knowing the factors that lead students to have intrinsic motivation is, therefore, crucial information in improving the efficiency of the learning process. There were some studies on emotional scenes that could influence the intrinsic motivation of participants. However, it could be hard to apply the complete scene to the teaching material. It would be better if we know the components which lead students to have intrinsic motivation and apply them to the teaching material. In this study, we analyzed the motivation components of visual cognitive stimuli from motivation-based cognitive data. The components were analyzed in terms of scene types (indoor/outdoor) and motivational objects that cause participants to have intrinsic motivation. It was found that participants were motivated to memorize the outdoor scenes than the indoor scenes (p < 0.01). Using decision tree, the relationship of the motivational object that lead participants to have intrinsic motivation are reported as the suggestion for applying to the visual teaching material in the future.
{"title":"Analyzing Motivational Components of Visual Cognitive Stimulus","authors":"Tustanah Phukhachee, S. Maneewongvatana, B. Kaewkamnerdpong","doi":"10.1109/BMEiCON47515.2019.8990317","DOIUrl":"https://doi.org/10.1109/BMEiCON47515.2019.8990317","url":null,"abstract":"Intrinsic motivation is an internal brain state that leads us to increase the efforts and attention in pursuing the goal. This intrinsic motivation can emerge for self-satisfaction without any external reward. In the education system, knowing the factors that lead students to have intrinsic motivation is, therefore, crucial information in improving the efficiency of the learning process. There were some studies on emotional scenes that could influence the intrinsic motivation of participants. However, it could be hard to apply the complete scene to the teaching material. It would be better if we know the components which lead students to have intrinsic motivation and apply them to the teaching material. In this study, we analyzed the motivation components of visual cognitive stimuli from motivation-based cognitive data. The components were analyzed in terms of scene types (indoor/outdoor) and motivational objects that cause participants to have intrinsic motivation. It was found that participants were motivated to memorize the outdoor scenes than the indoor scenes (p < 0.01). Using decision tree, the relationship of the motivational object that lead participants to have intrinsic motivation are reported as the suggestion for applying to the visual teaching material in the future.","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133699337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/BMEiCON47515.2019.8990191
K. Teeravajanadet, N. Siwilai, K. Thanaselanggul, N. Ponsiricharoenphan, S. Tungjitkusolmun, P. Phasukkit
In this paper, an investigation of crying signal spectra is used to classify categories of infant cries. Three different types of crying considered in this work are hungry, sleepy and burping need. These cries are preprocessed and converted for calculation of Mel-Frequency Cepstral Coefficients (MFCC) before being classified by Convolutional Neural Network (CNN). Experimental results show that CNN based deep learning achieves high performance of 84%.
{"title":"An Infant Cry Recognition based on Convolutional Neural Network Method","authors":"K. Teeravajanadet, N. Siwilai, K. Thanaselanggul, N. Ponsiricharoenphan, S. Tungjitkusolmun, P. Phasukkit","doi":"10.1109/BMEiCON47515.2019.8990191","DOIUrl":"https://doi.org/10.1109/BMEiCON47515.2019.8990191","url":null,"abstract":"In this paper, an investigation of crying signal spectra is used to classify categories of infant cries. Three different types of crying considered in this work are hungry, sleepy and burping need. These cries are preprocessed and converted for calculation of Mel-Frequency Cepstral Coefficients (MFCC) before being classified by Convolutional Neural Network (CNN). Experimental results show that CNN based deep learning achieves high performance of 84%.","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131041869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/BMEiCON47515.2019.8990254
P. Wayalun, Kanuengnij Kubola
The light microscopic image of the chromosome is one of the sources to diagnose genetic disorders. Chromosome counting is the first step for diagnosing genetic abnormalities. However, in the case of complicated chromosome pattern in images, it still needs improvement due to its complication and poor image quality. Moreover, every chromosome images are different in contrast and brightness. Therefore, in order to achieve a better performance in chromosome counting, the complicated chromosome images need to be specially enhanced. This paper proposes a technique called Adaptive Complicated Chromosome Image Enhancement (ACCIE) using the determining threshold value method, and the dynamically determining intensity adjustment method. The proposed method helps to generate a proper chromosome skeletonization and yields 86.81% for complicated chromosome number determination.
{"title":"Adaptive Image Enhancement for Automatic Complicated G-band Chromosome Number Determination","authors":"P. Wayalun, Kanuengnij Kubola","doi":"10.1109/BMEiCON47515.2019.8990254","DOIUrl":"https://doi.org/10.1109/BMEiCON47515.2019.8990254","url":null,"abstract":"The light microscopic image of the chromosome is one of the sources to diagnose genetic disorders. Chromosome counting is the first step for diagnosing genetic abnormalities. However, in the case of complicated chromosome pattern in images, it still needs improvement due to its complication and poor image quality. Moreover, every chromosome images are different in contrast and brightness. Therefore, in order to achieve a better performance in chromosome counting, the complicated chromosome images need to be specially enhanced. This paper proposes a technique called Adaptive Complicated Chromosome Image Enhancement (ACCIE) using the determining threshold value method, and the dynamically determining intensity adjustment method. The proposed method helps to generate a proper chromosome skeletonization and yields 86.81% for complicated chromosome number determination.","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129760563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cartilage has limited intrinsic capacity for self-repair after injury due to a lack of blood supply and low cell density. Tissue engineering holds promise for building cartilage grafts that withstand the stresses in joint. Major challenges of functional cartilage tissue development are scaffolding materials and structure of scaffold to support cartilage tissue formation. Scaffolds for engineered cartilage have been involved with the use of synthetic and natural polymers. Synthetic polymers provide well-control mechanical properties, while they are relatively inert to cell adhesion and tissue formation. Instead, natural polymers allow inherent cellular interaction and are present in abundance. In this study, polyvinyl alcohol (PVA) and carboxymethyl cellulose (CMC) were combined to form copolymer solution used in porous scaffold fabrication. Our goal was to investigate effects of PVA/CMC complex network on pore formation in scaffold and on cartilage tissue development. We found that addition of CMC into polymer solution could modulate scaffold architecture and swelling abilities. Fourier transform Infrared Spectroscopy (FTIR) of PVA/CMC scaffold showed the peak at 1599 cm−1 of C=O group, indicating the incorporation of CMC into the scaffold. Chondrocyte viability was observed up to 14 days post-cell seeding. These data suggested that PVA/CMC porous scaffold could be used in cartilage tissue repair.
{"title":"Polyvinyl alcohol-carboxymethyl cellulose scaffolds for cartilage tissue formation","authors":"Jirapat Namkaew, Nuttapong Sawaddee, Supansa Yodmuang","doi":"10.1109/BMEiCON47515.2019.8990252","DOIUrl":"https://doi.org/10.1109/BMEiCON47515.2019.8990252","url":null,"abstract":"Cartilage has limited intrinsic capacity for self-repair after injury due to a lack of blood supply and low cell density. Tissue engineering holds promise for building cartilage grafts that withstand the stresses in joint. Major challenges of functional cartilage tissue development are scaffolding materials and structure of scaffold to support cartilage tissue formation. Scaffolds for engineered cartilage have been involved with the use of synthetic and natural polymers. Synthetic polymers provide well-control mechanical properties, while they are relatively inert to cell adhesion and tissue formation. Instead, natural polymers allow inherent cellular interaction and are present in abundance. In this study, polyvinyl alcohol (PVA) and carboxymethyl cellulose (CMC) were combined to form copolymer solution used in porous scaffold fabrication. Our goal was to investigate effects of PVA/CMC complex network on pore formation in scaffold and on cartilage tissue development. We found that addition of CMC into polymer solution could modulate scaffold architecture and swelling abilities. Fourier transform Infrared Spectroscopy (FTIR) of PVA/CMC scaffold showed the peak at 1599 cm−1 of C=O group, indicating the incorporation of CMC into the scaffold. Chondrocyte viability was observed up to 14 days post-cell seeding. These data suggested that PVA/CMC porous scaffold could be used in cartilage tissue repair.","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125305771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/BMEiCON47515.2019.8990268
A. Noymai, Krit Janard, Sangvorn Seesutas, Tharapong Soonrach, P. Israsena
In this work, we experimented with the use of EEG signal to control a beamforming function of a hearing aid. An external EEG sensing system was designed and paired with a hearing aid. EEG signal was continuously read, with artifacts resulted from intentional eye blinks interpreted based on our average and variance model to identify the wearer’s intention to change the mode of the hearing aid. Based on the received command, the hearing aid would function either in an Omni-directional fashion, or directionally based on the designed beam forming structure. Experiments on experienced EEG users and volunteers were carried out to collect data to develop our decision model. The volunteers group was then retested to confirm the accuracy of the developed model. It was found that, in the controlled situation 100% accuracy was achieved, indicating the potential use of EEG as an enabler for smart control of hearing aid.
{"title":"Smart Control of Hearing Aid Using EEG","authors":"A. Noymai, Krit Janard, Sangvorn Seesutas, Tharapong Soonrach, P. Israsena","doi":"10.1109/BMEiCON47515.2019.8990268","DOIUrl":"https://doi.org/10.1109/BMEiCON47515.2019.8990268","url":null,"abstract":"In this work, we experimented with the use of EEG signal to control a beamforming function of a hearing aid. An external EEG sensing system was designed and paired with a hearing aid. EEG signal was continuously read, with artifacts resulted from intentional eye blinks interpreted based on our average and variance model to identify the wearer’s intention to change the mode of the hearing aid. Based on the received command, the hearing aid would function either in an Omni-directional fashion, or directionally based on the designed beam forming structure. Experiments on experienced EEG users and volunteers were carried out to collect data to develop our decision model. The volunteers group was then retested to confirm the accuracy of the developed model. It was found that, in the controlled situation 100% accuracy was achieved, indicating the potential use of EEG as an enabler for smart control of hearing aid.","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121917900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/BMEiCON47515.2019.8990334
Hannah Riedle, Peter Wittmann, J. Franke, K. Rössler
Haptic surgical simulators can improve skills and knowledge through experience. One possible application is the training of the high-risk procedure of an endoscopic third ventriculostomy (ETV) to treat an occlusive hydrocephalus. This study presents the development of a neurosurgical simulator optimized for automated manufacturing, while maintaining anatomical details and a variety of material properties. The core of the simulator is a 3D printed silicone model of the ventricular system, embedded in soft silicone gel, simulating the brain matter. Hard anatomical elements and a dynamic body fluid system complete the setup. The evaluation of the simulator by a medical expert shows that the anatomical geometries are realistic; the material properties however still need improvement.
{"title":"Design and Fabrication of a Multi-Material Neurosurgical Simulator for an Endoscopic Third Ventriculostomy","authors":"Hannah Riedle, Peter Wittmann, J. Franke, K. Rössler","doi":"10.1109/BMEiCON47515.2019.8990334","DOIUrl":"https://doi.org/10.1109/BMEiCON47515.2019.8990334","url":null,"abstract":"Haptic surgical simulators can improve skills and knowledge through experience. One possible application is the training of the high-risk procedure of an endoscopic third ventriculostomy (ETV) to treat an occlusive hydrocephalus. This study presents the development of a neurosurgical simulator optimized for automated manufacturing, while maintaining anatomical details and a variety of material properties. The core of the simulator is a 3D printed silicone model of the ventricular system, embedded in soft silicone gel, simulating the brain matter. Hard anatomical elements and a dynamic body fluid system complete the setup. The evaluation of the simulator by a medical expert shows that the anatomical geometries are realistic; the material properties however still need improvement.","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131184613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A foot is the importance organs that bear the weight of the entire body. Nowadays, the improper weight distribution of the sole causes damage to the body such as plantar fasciitis and the incidence of pressure injury in the sole, which lead to long-term effect. Shoes that are suitable to the person’s feet condition including using shoe accessories in each person can help to relieve initial symptoms. However, the weight that presses to each part of the sole is different. Therefore, measured the pressed weight of each part of sole can be used to create the proper shoes accessories, which help balancing the force for individual foot condition. This research aims to improve the shoe accessory product by using the Fore sensor with the display report of graphical user interface color map for measuring the real-time pressure on moving plantar. The data from sensor was wirelessly sent to the computer, which then displayed the image results. From the result of measured pressured on planar indicated that our Force sensor padder can help patient correctly control the weight distribution of the body to make the muscles of legs and feet to function effectively.
{"title":"Force Sensor for Measuring Plantar Pressure","authors":"Ms. Thitirat Teechot, Ms. Areerat Maneerat, Ms. Inarm Sansutnanont, Ms. Ornnattida Ornketphon, Ms. Treesukon Treebupachatsakul, C. Pintavirooj","doi":"10.1109/BMEiCON47515.2019.8990304","DOIUrl":"https://doi.org/10.1109/BMEiCON47515.2019.8990304","url":null,"abstract":"A foot is the importance organs that bear the weight of the entire body. Nowadays, the improper weight distribution of the sole causes damage to the body such as plantar fasciitis and the incidence of pressure injury in the sole, which lead to long-term effect. Shoes that are suitable to the person’s feet condition including using shoe accessories in each person can help to relieve initial symptoms. However, the weight that presses to each part of the sole is different. Therefore, measured the pressed weight of each part of sole can be used to create the proper shoes accessories, which help balancing the force for individual foot condition. This research aims to improve the shoe accessory product by using the Fore sensor with the display report of graphical user interface color map for measuring the real-time pressure on moving plantar. The data from sensor was wirelessly sent to the computer, which then displayed the image results. From the result of measured pressured on planar indicated that our Force sensor padder can help patient correctly control the weight distribution of the body to make the muscles of legs and feet to function effectively.","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130475638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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