Pub Date : 2020-08-13DOI: 10.4236/jbise.2020.138018
A. Byrns, H. Abdessalem, M. Cuesta, M. Bruneau, S. Belleville, C. Frasson
Alzheimer’s disease is the most common form of dementia, affecting nearly 9.9 million new people every year. The disease provokes important memory and cognitive impairment, eventually causing individuals to forget their loved ones and rendering them completely dependent on their caretakers. Alzheimer’s patients typically experience more negative emotions, such as frustration and apathy, than healthy older adults. There is currently no cure for the disease. Our research group explores how the integration of virtual reality (VR) and an EEG-based intelligent agent in music therapy can alleviate psychological and cognitive symptoms of the disease. We propose a theory explaining how, through activation of the brain reward system, music can reduce negative emotions, increase positive emotions and as a result increase performance on cognitive tasks. The results of our experimental study concord with our theory: emotional states of participants are improved, as per recorded through EEG, and performances on memory tasks show improvement following the intervention. We believe that the combination of EEG brain assessment, VR and music therapy is a promising method for emotional states and cognitive symptoms of Alzheimer’s disease.
{"title":"EEG Analysis of the Contribution of Music Therapy and Virtual Reality to the Improvement of Cognition in Alzheimer’s Disease","authors":"A. Byrns, H. Abdessalem, M. Cuesta, M. Bruneau, S. Belleville, C. Frasson","doi":"10.4236/jbise.2020.138018","DOIUrl":"https://doi.org/10.4236/jbise.2020.138018","url":null,"abstract":"Alzheimer’s disease is the most common form of dementia, affecting nearly 9.9 million new people every year. The disease provokes important memory and cognitive impairment, eventually causing individuals to forget their loved ones and rendering them completely dependent on their caretakers. Alzheimer’s patients typically experience more negative emotions, such as frustration and apathy, than healthy older adults. There is currently no cure for the disease. Our research group explores how the integration of virtual reality (VR) and an EEG-based intelligent agent in music therapy can alleviate psychological and cognitive symptoms of the disease. We propose a theory explaining how, through activation of the brain reward system, music can reduce negative emotions, increase positive emotions and as a result increase performance on cognitive tasks. The results of our experimental study concord with our theory: emotional states of participants are improved, as per recorded through EEG, and performances on memory tasks show improvement following the intervention. We believe that the combination of EEG brain assessment, VR and music therapy is a promising method for emotional states and cognitive symptoms of Alzheimer’s disease.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"13 1","pages":"187-201"},"PeriodicalIF":0.0,"publicationDate":"2020-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44606355","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 : 2020-06-11DOI: 10.4236/jbise.2020.136010
A. Sarhan
A brain tumor is a mass of abnormal cells in the brain. Brain tumors can be benign (noncancerous) or malignant (cancerous). Conventional diagnosis of a brain tumor by the radiologist is done by examining a set of images produced by magnetic resonance imaging (MRI). Many computer-aided detection (CAD) systems have been developed in order to help the radiologists reach their goal of correctly classifying the MRI image. Convolutional neural networks (CNNs) have been widely used in the classification of medical images. This paper presents a novel CAD technique for the classification of brain tumors in MRI images. The proposed system extracts features from the brain MRI images by utilizing the strong energy compactness property exhibited by the Discrete Wavelet Transform (DWT). The Wavelet features are then applied to a CNN to classify the input MRI image. Experimental results indicate that the proposed approach outperforms other commonly used methods and gives an overall accuracy of 99.3%.
{"title":"Brain Tumor Classification in Magnetic Resonance Images Using Deep Learning and Wavelet Transform","authors":"A. Sarhan","doi":"10.4236/jbise.2020.136010","DOIUrl":"https://doi.org/10.4236/jbise.2020.136010","url":null,"abstract":"A brain tumor is a mass of abnormal cells in the brain. Brain tumors can be benign (noncancerous) or malignant (cancerous). Conventional diagnosis of a brain tumor by the radiologist is done by examining a set of images produced by magnetic resonance imaging (MRI). Many computer-aided detection (CAD) systems have been developed in order to help the radiologists reach their goal of correctly classifying the MRI image. Convolutional neural networks (CNNs) have been widely used in the classification of medical images. This paper presents a novel CAD technique for the classification of brain tumors in MRI images. The proposed system extracts features from the brain MRI images by utilizing the strong energy compactness property exhibited by the Discrete Wavelet Transform (DWT). The Wavelet features are then applied to a CNN to classify the input MRI image. Experimental results indicate that the proposed approach outperforms other commonly used methods and gives an overall accuracy of 99.3%.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48629906","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 : 2020-06-11DOI: 10.4236/jbise.2020.136011
R. Sakai, Takeaki Yamamoto, K. Uchiyama, Kensuke Fukushima, N. Takahira, Kazuhiro Yoshida, M. Ujihira
When a stem is inserted into the femur during total hip arthroplasty, sufficient fixation depends on the surgeon’s experience. An objective method of evaluating whether the stem has been correctly fixed may aid clinicians in their decision. We examined the relationship between the sound frequency caused by hammering the stem and the internal stress in artificial femurs, and evaluated the utility of sound frequency analysis to prevent intraoperative fracture. Surgeons inserted one of two types of cementless stems (SL-PLUS and modified CLS) using routine operational procedures into 13 artificial femurs. These are the standard Zweymullers used in Europe. The difference is the lateral shape; SL-PLUS has holes for removal and the modified CLS has fins to prevent rotation. We estimated stress in the femur via finite element analysis, measured the hammering force, and recorded the sound of hammering for frequency analysis. Finite element analysis revealed that the hammering sound frequency decreased as the maximum stress increased. A decrease in frequency suggested that fixation was sufficient and that continued hammering would increase the risk of fracture. Thus, evaluation of the change in sound frequency during stem insertion may indicate when the hammering force should be reduced, thereby preventing intraoperative periprosthetic fractures. Further frequency change may also predict fractures prior to visual confirmation. We concluded that sound frequency analysis has potential as an objective evaluation method to help prevent intraoperative periprosthetic fractures during stem insertion.
{"title":"Prediction of Intraoperative Fracture by Hammering Sound Frequency Analysis and Stress Estimation during Total Hip Arthroplasty","authors":"R. Sakai, Takeaki Yamamoto, K. Uchiyama, Kensuke Fukushima, N. Takahira, Kazuhiro Yoshida, M. Ujihira","doi":"10.4236/jbise.2020.136011","DOIUrl":"https://doi.org/10.4236/jbise.2020.136011","url":null,"abstract":"When a stem is inserted into the femur during total hip arthroplasty, sufficient fixation depends on the surgeon’s experience. An objective method of evaluating whether the stem has been correctly fixed may aid clinicians in their decision. We examined the relationship between the sound frequency caused by hammering the stem and the internal stress in artificial femurs, and evaluated the utility of sound frequency analysis to prevent intraoperative fracture. Surgeons inserted one of two types of cementless stems (SL-PLUS and modified CLS) using routine operational procedures into 13 artificial femurs. These are the standard Zweymullers used in Europe. The difference is the lateral shape; SL-PLUS has holes for removal and the modified CLS has fins to prevent rotation. We estimated stress in the femur via finite element analysis, measured the hammering force, and recorded the sound of hammering for frequency analysis. Finite element analysis revealed that the hammering sound frequency decreased as the maximum stress increased. A decrease in frequency suggested that fixation was sufficient and that continued hammering would increase the risk of fracture. Thus, evaluation of the change in sound frequency during stem insertion may indicate when the hammering force should be reduced, thereby preventing intraoperative periprosthetic fractures. Further frequency change may also predict fractures prior to visual confirmation. We concluded that sound frequency analysis has potential as an objective evaluation method to help prevent intraoperative periprosthetic fractures during stem insertion.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"13 1","pages":"113-119"},"PeriodicalIF":0.0,"publicationDate":"2020-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41344083","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 : 2020-06-11DOI: 10.4236/jbise.2020.136012
H. Tomioka, J. Masuda, A. Takada, A. Iwanami
Background: It is not well analyzed whether there are differences in plasma levels of tryptophan (TRP) metabolites between healthy control people (HC) and patients of type II bipolar depression (BDII). Methods: Ultra high-speed liquid chromatography/mass spectrometry has been used for the simultaneous determination of plasma levels of tryptophan metabolites in depressive patients. Results: Plasma levels of TRP are not different between HC and patients of BDII. Serotonin (5-HT) levels are higher in BDII than HC. Plasma levels of 5-HIAA of HC are higher than those of old women of BDII, but lower in young women of BDII. Plasma levels of kynurenine (KYN) of HC are not different from those of patients of BDII. Conclusion: Plasma levels of 5-HT are higher in patients of BDII than those of HC, which may suggest that use of drugs inhibiting the 5-HT transportation and lower transporter biding may increase plasma levels of 5-HT in patients of BD.
{"title":"Comparison of Plasma Levels of Tryptophan Metabolites between Healthy People and Patients of Bipolar Depression at Various Age and Gender","authors":"H. Tomioka, J. Masuda, A. Takada, A. Iwanami","doi":"10.4236/jbise.2020.136012","DOIUrl":"https://doi.org/10.4236/jbise.2020.136012","url":null,"abstract":"Background: It is not well analyzed whether there are differences in plasma levels of tryptophan (TRP) metabolites between healthy control people (HC) and patients of type II bipolar depression (BDII). Methods: Ultra high-speed liquid chromatography/mass spectrometry has been used for the simultaneous determination of plasma levels of tryptophan metabolites in depressive patients. Results: Plasma levels of TRP are not different between HC and patients of BDII. Serotonin (5-HT) levels are higher in BDII than HC. Plasma levels of 5-HIAA of HC are higher than those of old women of BDII, but lower in young women of BDII. Plasma levels of kynurenine (KYN) of HC are not different from those of patients of BDII. Conclusion: Plasma levels of 5-HT are higher in patients of BDII than those of HC, which may suggest that use of drugs inhibiting the 5-HT transportation and lower transporter biding may increase plasma levels of 5-HT in patients of BD.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"13 1","pages":"120-129"},"PeriodicalIF":0.0,"publicationDate":"2020-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47185949","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 : 2020-06-11DOI: 10.4236/jbise.2020.136009
J. Ochola, B. Malengier, L. Langenhove
Flexor tendon repair has conventionally been done by suturing techniques. However, in recent times, there have been attempts of using fibrous braided structures for the repair of ruptured tendons. In this regard, the numerical analysis of the flexural stiffness of a braided structure under bending moments is vital for understanding its capabilities in the repair of flexor tendons. In this paper, the bending deflection, curvature, contact stresses and flexural bending stiffness in the braided structure due to bending moments are simulated using Finite Element (FE) techniques. Three dimensional geometry and FE models of five sets of biaxial braided structures were developed using a python programming script. The FE models of the hybrid biaxial braids were imported into ABAQUS (v17) for post-processing and analysis. It was established that the braided fabric with largest braid angle, θ = 52.5˚ had the highest flexural deflection while the lowest deflection was seen in the results of the braided structure with the least braid angle, θ = 38.5˚. The results in this study also portrayed that the curvature in biaxial braids will increase with a decrease in the angle between the braided yarns. This was also consistent with the change of bending angle of the biaxial structures under a bending moment. The deformation of the structures increased with increase in the braid angles. This implies that the flexural bending stiffness decreased with increase in braid angle. The stress limits during bending of the braided structures were established to be within the range that could be handled by flexor tendons during finger bending.
{"title":"Numerical Investigation of Flexural Bending in Biaxial Braided Structures for Flexor Tendon Repair","authors":"J. Ochola, B. Malengier, L. Langenhove","doi":"10.4236/jbise.2020.136009","DOIUrl":"https://doi.org/10.4236/jbise.2020.136009","url":null,"abstract":"Flexor tendon repair has conventionally been done by suturing techniques. However, in recent times, there have been attempts of using fibrous braided structures for the repair of ruptured tendons. In this regard, the numerical analysis of the flexural stiffness of a braided structure under bending moments is vital for understanding its capabilities in the repair of flexor tendons. In this paper, the bending deflection, curvature, contact stresses and flexural bending stiffness in the braided structure due to bending moments are simulated using Finite Element (FE) techniques. Three dimensional geometry and FE models of five sets of biaxial braided structures were developed using a python programming script. The FE models of the hybrid biaxial braids were imported into ABAQUS (v17) for post-processing and analysis. It was established that the braided fabric with largest braid angle, θ = 52.5˚ had the highest flexural deflection while the lowest deflection was seen in the results of the braided structure with the least braid angle, θ = 38.5˚. The results in this study also portrayed that the curvature in biaxial braids will increase with a decrease in the angle between the braided yarns. This was also consistent with the change of bending angle of the biaxial structures under a bending moment. The deformation of the structures increased with increase in the braid angles. This implies that the flexural bending stiffness decreased with increase in braid angle. The stress limits during bending of the braided structures were established to be within the range that could be handled by flexor tendons during finger bending.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"13 1","pages":"93-101"},"PeriodicalIF":0.0,"publicationDate":"2020-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46845913","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 : 2020-05-20DOI: 10.4236/jbise.2020.135006
Wangxiang Mai, Liang Fang, Zhuoming Chen, Xiuping Wang, Wanting Li, Weiyi He
Objective: To explore the effects of the somatosensory interaction technology combined with virtual reality technology on upper limbs function and activities of daily living (ADL) in cerebrovascular disease patients. Methods: Form January, 2019 to December, 2019, 80 cerebrovascular disease patients were recruited, and had been divided into control group (n = 40) and observation group (n = 40), randomly. The control groups received conventional rehabilitation treatment, for 40 minutes per day, while observation group received conventional rehabilitation treatment, for 20 minutes per day, and virtual reality technology treatment, 20 minutes per day, 5 days a week for 4 weeks. Wolf Motor Function Test (WMFT), Fugl-Meyer Assessment-Upper Extremities (FMA-UE) and modified Barthel index (MBI) were used to assess the motor function of the upper limbs and ADL before and after treatment. Results: Before treatment, the scores of WMFT, FMA-UE and MBI were no significant difference between two groups (P > 0.05). The scores improved in both groups after treatment (P < 0.01), and were higher in the observation group than in the control group (P < 0.05). Conclusion: The somatosensory interaction technology combined with virtual reality technology could facilitate to improve the upper limbs function and ADL in cerebrovascular disease patients.
{"title":"Application of the Somatosensory Interaction Technology Combined with Virtual Reality Technology on Upper Limbs Function in Cerebrovascular Disease Patients","authors":"Wangxiang Mai, Liang Fang, Zhuoming Chen, Xiuping Wang, Wanting Li, Weiyi He","doi":"10.4236/jbise.2020.135006","DOIUrl":"https://doi.org/10.4236/jbise.2020.135006","url":null,"abstract":"Objective: To explore the effects of the somatosensory interaction technology combined with virtual reality technology on upper limbs function and activities of daily living (ADL) in cerebrovascular disease patients. Methods: Form January, 2019 to December, 2019, 80 cerebrovascular disease patients were recruited, and had been divided into control group (n = 40) and observation group (n = 40), randomly. The control groups received conventional rehabilitation treatment, for 40 minutes per day, while observation group received conventional rehabilitation treatment, for 20 minutes per day, and virtual reality technology treatment, 20 minutes per day, 5 days a week for 4 weeks. Wolf Motor Function Test (WMFT), Fugl-Meyer Assessment-Upper Extremities (FMA-UE) and modified Barthel index (MBI) were used to assess the motor function of the upper limbs and ADL before and after treatment. Results: Before treatment, the scores of WMFT, FMA-UE and MBI were no significant difference between two groups (P > 0.05). The scores improved in both groups after treatment (P < 0.01), and were higher in the observation group than in the control group (P < 0.05). Conclusion: The somatosensory interaction technology combined with virtual reality technology could facilitate to improve the upper limbs function and ADL in cerebrovascular disease patients.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46874072","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 : 2020-05-11DOI: 10.4236/jbise.2020.135005
Zhe Lu, K. Chou
The recent worldwide spreading of pneumonia-causing virus, such as Coronavirus, COVID-19, and H1N1, has been endangering the life of human beings all around the world. In order to really understand the biological process within a cell level and provide useful clues to develop antiviral drugs, information of Gram positive bacteria protein subcellular localization is vitally important. In view of this, a CNN based protein subcellular localization predictor called “pLoc_Deep-mGpos” was developed. The predictor is particularly useful in dealing with the multi-sites systems in which some proteins may simultaneously occur in two or more different organelles that are the current focus of pharmaceutical industry. The global absolute true rate achieved by the new predictor is over 99% and its local accuracy is around 92% - 99%. Both are transcending other existing state-of-the-art predictors significantly. To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_Deep-mGpos/, which will become a very powerful tool for developing effective drugs to fight pandemic coronavirus and save the mankind of this planet.
{"title":"pLoc_Deep-mGpos: Predict Subcellular Localization of Gram Positive Bacteria Proteins by Deep Learning","authors":"Zhe Lu, K. Chou","doi":"10.4236/jbise.2020.135005","DOIUrl":"https://doi.org/10.4236/jbise.2020.135005","url":null,"abstract":"The recent worldwide spreading of pneumonia-causing virus, such as Coronavirus, COVID-19, and H1N1, has been endangering the life of human beings all around the world. In order to really understand the biological process within a cell level and provide useful clues to develop antiviral drugs, information of Gram positive bacteria protein subcellular localization is vitally important. In view of this, a CNN based protein subcellular localization predictor called “pLoc_Deep-mGpos” was developed. The predictor is particularly useful in dealing with the multi-sites systems in which some proteins may simultaneously occur in two or more different organelles that are the current focus of pharmaceutical industry. The global absolute true rate achieved by the new predictor is over 99% and its local accuracy is around 92% - 99%. Both are transcending other existing state-of-the-art predictors significantly. To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_Deep-mGpos/, which will become a very powerful tool for developing effective drugs to fight pandemic coronavirus and save the mankind of this planet.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48567167","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 : 2020-05-11DOI: 10.4236/jbise.2020.135008
A. Sarhan
Computerized tomography (CT) scan is the only screening test recommended by doctors to look for lung cancer. Convolutional neural networks (CNNs) have recently proven their ability to successfully classify medical images. Due to its strong compactness property, the Discrete Wavelet transform (DWT) has been commonly used in image feature extraction applications. This paper presents a novel technique for the classification of Lung cancer in Computerized Tomography (CT) scans using Wavelets to find discriminative features in the CT images and CNN to classify the extracted features. Experimental results prove that the proposed approach outperforms other commonly used methods and gives an overall accuracy of 99.5%.
{"title":"A Novel Lung Cancer Detection Method Using Wavelet Decomposition and Convolutional Neural Network","authors":"A. Sarhan","doi":"10.4236/jbise.2020.135008","DOIUrl":"https://doi.org/10.4236/jbise.2020.135008","url":null,"abstract":"Computerized tomography (CT) scan is the only screening test recommended by doctors to look for lung cancer. Convolutional neural networks (CNNs) have recently proven their ability to successfully classify medical images. Due to its strong compactness property, the Discrete Wavelet transform (DWT) has been commonly used in image feature extraction applications. This paper presents a novel technique for the classification of Lung cancer in Computerized Tomography (CT) scans using Wavelets to find discriminative features in the CT images and CNN to classify the extracted features. Experimental results prove that the proposed approach outperforms other commonly used methods and gives an overall accuracy of 99.5%.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42640908","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 : 2020-05-11DOI: 10.4236/jbise.2020.135007
R. Sakai, K. Uchiyama, N. Takahira, M. Kakeshita, Y. Otsu, Kazuhiro Yoshida, M. Ujihira
In total hip arthroplasty, judgment of the appropriateness of stem hammering is dependent on the experience and feelings of the surgeon and no objective evaluation method has been established. In this study, a frequency analysis of the hammering sounds in total hip arthroplasty was performed to investigate objective judgment criteria capable of preventing problems during surgery. Stem hammering was applied following the surgeon’s feelings as usual in an operating room. A directional microphone was placed at a distance about 2 m from the surgical field and the peak frequency reaching the maximum amplitude was determined by Fourier analysis. It was clarified that the same peak frequency repeats when appropriate fixation is acquired during surgery, suggesting that intraoperative fracture and postoperative loosening can be prevented by stopping hammering at the time the peak frequency converged. Investigation of changes in the hammering sound frequency may serve as objective judgment criteria capable of preventing problems during surgery.
{"title":"Usefulness of Hammering Sound Frequency Analysis as an Evaluation Method for the Prevention of Trouble during Hip Replacement","authors":"R. Sakai, K. Uchiyama, N. Takahira, M. Kakeshita, Y. Otsu, Kazuhiro Yoshida, M. Ujihira","doi":"10.4236/jbise.2020.135007","DOIUrl":"https://doi.org/10.4236/jbise.2020.135007","url":null,"abstract":"In total hip arthroplasty, judgment of the appropriateness of stem hammering is dependent on the experience and feelings of the surgeon and no objective evaluation method has been established. In this study, a frequency analysis of the hammering sounds in total hip arthroplasty was performed to investigate objective judgment criteria capable of preventing problems during surgery. Stem hammering was applied following the surgeon’s feelings as usual in an operating room. A directional microphone was placed at a distance about 2 m from the surgical field and the peak frequency reaching the maximum amplitude was determined by Fourier analysis. It was clarified that the same peak frequency repeats when appropriate fixation is acquired during surgery, suggesting that intraoperative fracture and postoperative loosening can be prevented by stopping hammering at the time the peak frequency converged. Investigation of changes in the hammering sound frequency may serve as objective judgment criteria capable of preventing problems during surgery.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42027538","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 : 2020-04-30DOI: 10.4236/jbise.2020.134004
Rafiqul Islam, S. Imran, M. Ashikuzzaman, Md. Munim Ali Khan
Magnetic Resonance Imaging (MRI) is an important diagnostic technique for early detection of brain Tumor and the classification of brain Tumor from MRI image is a challenging research work because of its different shapes, location and image intensities. For successful classification, the segmentation method is required to separate Tumor. Then important features are extracted from the segmented Tumor that is used to classify the Tumor. In this work, an efficient multilevel segmentation method is developed combining optimal thresholding and watershed segmentation technique followed by a morphological operation to separate the Tumor. Convolutional Neural Network (CNN) is then applied for feature extraction and finally, the Kernel Support Vector Machine (KSVM) is utilized for resultant classification that is justified by our experimental evaluation. Experimental results show that the proposed method effectively detect and classify the Tumor as cancerous or non-cancerous with promising accuracy.
{"title":"Detection and Classification of Brain Tumor Based on Multilevel Segmentation with Convolutional Neural Network","authors":"Rafiqul Islam, S. Imran, M. Ashikuzzaman, Md. Munim Ali Khan","doi":"10.4236/jbise.2020.134004","DOIUrl":"https://doi.org/10.4236/jbise.2020.134004","url":null,"abstract":"Magnetic Resonance Imaging (MRI) is an important diagnostic technique for early detection of brain Tumor and the classification of brain Tumor from MRI image is a challenging research work because of its different shapes, location and image intensities. For successful classification, the segmentation method is required to separate Tumor. Then important features are extracted from the segmented Tumor that is used to classify the Tumor. In this work, an efficient multilevel segmentation method is developed combining optimal thresholding and watershed segmentation technique followed by a morphological operation to separate the Tumor. Convolutional Neural Network (CNN) is then applied for feature extraction and finally, the Kernel Support Vector Machine (KSVM) is utilized for resultant classification that is justified by our experimental evaluation. Experimental results show that the proposed method effectively detect and classify the Tumor as cancerous or non-cancerous with promising accuracy.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"13 1","pages":"45-53"},"PeriodicalIF":0.0,"publicationDate":"2020-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43671919","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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