G. Improta, C. Lauri, Antonio Della Vecchia, A. Borrelli, Giuseppe Russo, M. Triassi
The Emergency Department (ED) is an area of a hospital where healthcare personnel is normally faced with severe and sudden problems. Here patients and caregivers have to undertake visits, assessments, consultations and bureaucratic procedures which can be lengthy and complicated, due to inadequate or inaccurate information. In these conditions, waiting times can often be very long and patients may decide to abandon ED. In recent years, hospital process organization has had a notable improvement thanks to the implementation of the Lean Six Sigma methodology. In particular, ED processes improvement foresees the reorganization of all activities, from the patient admission to the ED upon home discharge or hospitalization. In this article we look at the data collected from the Emergency Department of the University Hospital of Salerno "San Giovanni di Dio e Ruggi D'Aragona" to demonstrate the positive influence of Lean Six Sigma (LSS) in ED in order to optimize the services offered to the patients.
急诊科(ED)是医院的一个区域，医护人员通常在这里面临严重和突发的问题。在这里，由于信息不充分或不准确，患者和护理人员必须进行访问、评估、咨询和官僚程序，这些程序可能漫长而复杂。在这种情况下，等待时间往往很长，患者可能决定放弃急诊科。近年来，由于精益六西格玛方法的实施，医院流程组织有了显著的改善。特别是，急诊科流程的改进预示着所有活动的重组，从患者入院到出院或住院的急诊科。在本文中，我们查看了从萨勒诺大学医院“San Giovanni di Dio e Ruggi D'Aragona”急诊科收集的数据，以证明精益六西格玛(LSS)在ED中的积极影响，以优化为患者提供的服务。
{"title":"A Lean Six Sigma approach to improve the Emergency Department of University Hospital “San Giovanni di Dio e Ruggi d'Aragona”","authors":"G. Improta, C. Lauri, Antonio Della Vecchia, A. Borrelli, Giuseppe Russo, M. Triassi","doi":"10.1145/3502060.3503638","DOIUrl":"https://doi.org/10.1145/3502060.3503638","url":null,"abstract":"The Emergency Department (ED) is an area of a hospital where healthcare personnel is normally faced with severe and sudden problems. Here patients and caregivers have to undertake visits, assessments, consultations and bureaucratic procedures which can be lengthy and complicated, due to inadequate or inaccurate information. In these conditions, waiting times can often be very long and patients may decide to abandon ED. In recent years, hospital process organization has had a notable improvement thanks to the implementation of the Lean Six Sigma methodology. In particular, ED processes improvement foresees the reorganization of all activities, from the patient admission to the ED upon home discharge or hospitalization. In this article we look at the data collected from the Emergency Department of the University Hospital of Salerno \"San Giovanni di Dio e Ruggi D'Aragona\" to demonstrate the positive influence of Lean Six Sigma (LSS) in ED in order to optimize the services offered to the patients.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131347117","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}
Footprints can provide much valuable information for fall prediction, the diagnosis of many diseases and rehabilitation therapy. This paper aims to propose a statistical method for footprints analysis based on a large-scale high-density piezoresistive film to replace the manual work of obtaining the main parameters of footprint data. Firstly, data acquisition devices are developed to obtain the plantar pressure distribution by measuring the voltage changes caused by the applied pressure on the piezoresistive films. Subsequently, a specific software is developed to receive the data from the designed signal acquisition devices through the serial port and visualize the footprints, and a statistical method is proposed to distinguish between left footprint and right footprint and to obtain the direction of the footprints and the step length. Eventually, a series of experiments are conducted to obtain the accuracy of the proposed method used for different people's feet and with different walking speeds.
{"title":"A Statistical Method for Footprints Analysis based on Large-scale High-density Piezoresistive Films","authors":"Bo Wang, Chengxiang Liu, Peng Shang","doi":"10.1145/3502060.3502148","DOIUrl":"https://doi.org/10.1145/3502060.3502148","url":null,"abstract":"Footprints can provide much valuable information for fall prediction, the diagnosis of many diseases and rehabilitation therapy. This paper aims to propose a statistical method for footprints analysis based on a large-scale high-density piezoresistive film to replace the manual work of obtaining the main parameters of footprint data. Firstly, data acquisition devices are developed to obtain the plantar pressure distribution by measuring the voltage changes caused by the applied pressure on the piezoresistive films. Subsequently, a specific software is developed to receive the data from the designed signal acquisition devices through the serial port and visualize the footprints, and a statistical method is proposed to distinguish between left footprint and right footprint and to obtain the direction of the footprints and the step length. Eventually, a series of experiments are conducted to obtain the accuracy of the proposed method used for different people's feet and with different walking speeds.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"602 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122989737","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}
Jianping Gao, Saina Li, Lun Zhang, Yang Zhang, Yi Chen, Fangyu Xing, Yingjun Kong, Xi Luo, Guifeng Zhang
Titanium alloys coated with collagen have been widely used to improve their biocompatibility. In this study, the titanium alloys were coated with type I collagen (Col I) and type II collagen (Col II), respectively. The coating amount was quantified with HPLC/MS. Their biocompatibility was evaluated and the effects of collagen types on cell differentiation were compared by cellular proteins identification and quantification. The quantity of Col I and Col II coated on titanium alloy were 0.813±0.015 mg and 0.774±0.013 mg, respectively. Mouse Col I and fibronectin were abundantly expressed within Col I group. The most abundant proteins in Col II group were osteopontin and prelamin-A/C. In conclusion, the collagen coating could improve the biocompatibility of titanium alloy materials, and different types of collagen could induce cell to express proteins with various functions.
{"title":"The Effect of Collagen Coating on Surface Biocompatibility of the Titanium Alloys","authors":"Jianping Gao, Saina Li, Lun Zhang, Yang Zhang, Yi Chen, Fangyu Xing, Yingjun Kong, Xi Luo, Guifeng Zhang","doi":"10.1145/3502060.3502144","DOIUrl":"https://doi.org/10.1145/3502060.3502144","url":null,"abstract":"Titanium alloys coated with collagen have been widely used to improve their biocompatibility. In this study, the titanium alloys were coated with type I collagen (Col I) and type II collagen (Col II), respectively. The coating amount was quantified with HPLC/MS. Their biocompatibility was evaluated and the effects of collagen types on cell differentiation were compared by cellular proteins identification and quantification. The quantity of Col I and Col II coated on titanium alloy were 0.813±0.015 mg and 0.774±0.013 mg, respectively. Mouse Col I and fibronectin were abundantly expressed within Col I group. The most abundant proteins in Col II group were osteopontin and prelamin-A/C. In conclusion, the collagen coating could improve the biocompatibility of titanium alloy materials, and different types of collagen could induce cell to express proteins with various functions.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125296793","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}
Teresa Angela Trunfio, A. Scala, Cristiana Giglio, Giovanni Rossi, A. Borrelli, P. Gargiulo, Maria Romano
Healthcare facilities are under constant pressure to contain costs. This goal is becoming increasingly difficult to achieve due to the rapid growth of the complexity of the services and stringent quality requirements. Therefore, several strategies are implemented that make it possible to evaluate and obtain health processes as close as possible to standards. A widely used parameter in the literature is the length of stay (LOS). A patient's LOS can be affected by a number of factors, including their particular condition, medical history, or medical needs. Being able to know this variation a priori can be very important for the management of hospital resources, such as beds. In this study, a predictive model was built for the total LOS of patients undergoing laparoscopic appendectomy, one of the most common emergency procedures. The model was obtained using multiple linear regression with an R2 value of 0.638.
{"title":"Modelling the hospital length of stay for patients undergoing laparoscopic appendectomy through a Multiple Regression Model","authors":"Teresa Angela Trunfio, A. Scala, Cristiana Giglio, Giovanni Rossi, A. Borrelli, P. Gargiulo, Maria Romano","doi":"10.1145/3502060.3503644","DOIUrl":"https://doi.org/10.1145/3502060.3503644","url":null,"abstract":"Healthcare facilities are under constant pressure to contain costs. This goal is becoming increasingly difficult to achieve due to the rapid growth of the complexity of the services and stringent quality requirements. Therefore, several strategies are implemented that make it possible to evaluate and obtain health processes as close as possible to standards. A widely used parameter in the literature is the length of stay (LOS). A patient's LOS can be affected by a number of factors, including their particular condition, medical history, or medical needs. Being able to know this variation a priori can be very important for the management of hospital resources, such as beds. In this study, a predictive model was built for the total LOS of patients undergoing laparoscopic appendectomy, one of the most common emergency procedures. The model was obtained using multiple linear regression with an R2 value of 0.638.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115802916","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}
Teresa Angela Trunfio, A. Scala, Cristiana Giglio, Giuseppe Ferrucci, A. Borrelli, P. Gargiulo
The new COVID-19 disease has swept the world in recent months, causing enormous disruption to social, economic and health systems. Given the diversity of international health systems and conditions differ from one location to another. In all cases, however, it was decided to limit the elective surgical practices considered non-urgent. Plastic surgery departments have also seen a change in their normal business. The aim of this study was to investigate how the pandemic changed the activity of the Plastic Surgery Department of the "San Giovanni di Dio and Ruggi d'Aragona" University Hospital in Salerno (Italy). In particular, starting from the hospital discharge forms for the two-year period 2019-2020, Gender, Age, Date of admission, Date of discharge, Diagnostic Related Group (DRG) weight and Hospital admission procedures for patients were extracted. Statistical analysis and logistic regression were used to compare the activity of 2019, used in this study as a reference, with that of 2020 in the midst of the pandemic. The analysis showed a statically significant reduction in the Length of Stay (LOS), thus improving appropriateness and achieving a reduction in spending.
{"title":"The Impact of Covid-19 on the Length of Stay of the Plastic Surgery Department","authors":"Teresa Angela Trunfio, A. Scala, Cristiana Giglio, Giuseppe Ferrucci, A. Borrelli, P. Gargiulo","doi":"10.1145/3502060.3503654","DOIUrl":"https://doi.org/10.1145/3502060.3503654","url":null,"abstract":"The new COVID-19 disease has swept the world in recent months, causing enormous disruption to social, economic and health systems. Given the diversity of international health systems and conditions differ from one location to another. In all cases, however, it was decided to limit the elective surgical practices considered non-urgent. Plastic surgery departments have also seen a change in their normal business. The aim of this study was to investigate how the pandemic changed the activity of the Plastic Surgery Department of the \"San Giovanni di Dio and Ruggi d'Aragona\" University Hospital in Salerno (Italy). In particular, starting from the hospital discharge forms for the two-year period 2019-2020, Gender, Age, Date of admission, Date of discharge, Diagnostic Related Group (DRG) weight and Hospital admission procedures for patients were extracted. Statistical analysis and logistic regression were used to compare the activity of 2019, used in this study as a reference, with that of 2020 in the midst of the pandemic. The analysis showed a statically significant reduction in the Length of Stay (LOS), thus improving appropriateness and achieving a reduction in spending.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122355327","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}
The natural habitat and ecology of yeast are not well understood. In this study, molecular methods like ITS-PCR, ITS-RFLP, microsatellite, and DNA sequencing were employed to analyze nature yeasts isolated from daimyo oak trees in Yunan, China. ITS primers were employed to amplify a total number of 205 samples. The length of the ITS PCR products ranged from 200 bp to 800 bp, and nine species of yeast were found via ITS sequencing. Saccharomyces paradoxus, S. kluyveri, Rhodotorula mucilaginosa, and Hanseniaspora osmophila were first found on daimyo oak trees in Yunnan, China. Differences were found between the two adjacent locations, but not between sites with each tree. Amplified using a set of microsatellites primers specific to S. cerevisiae, three types of patterns were shown among those samples, and three samples appeared to have patterns expected for S. cerevisiae. To further characterize the strains, six primer pairs were used to amplify and sequence individual genes. Ten natural hybrids between S. paradoxus and S. cerevisiae were found.
{"title":"Molecular Analysis of Yeasts Isolated from Daimyo Oak (Quercus dentata Thunb.) Trees in Yunan, China","authors":"Zhiming Zhang, Fang-xian Zhu, Xiaozhen Liu, Hanyao Zhang","doi":"10.1145/3502060.3510448","DOIUrl":"https://doi.org/10.1145/3502060.3510448","url":null,"abstract":"The natural habitat and ecology of yeast are not well understood. In this study, molecular methods like ITS-PCR, ITS-RFLP, microsatellite, and DNA sequencing were employed to analyze nature yeasts isolated from daimyo oak trees in Yunan, China. ITS primers were employed to amplify a total number of 205 samples. The length of the ITS PCR products ranged from 200 bp to 800 bp, and nine species of yeast were found via ITS sequencing. Saccharomyces paradoxus, S. kluyveri, Rhodotorula mucilaginosa, and Hanseniaspora osmophila were first found on daimyo oak trees in Yunnan, China. Differences were found between the two adjacent locations, but not between sites with each tree. Amplified using a set of microsatellites primers specific to S. cerevisiae, three types of patterns were shown among those samples, and three samples appeared to have patterns expected for S. cerevisiae. To further characterize the strains, six primer pairs were used to amplify and sequence individual genes. Ten natural hybrids between S. paradoxus and S. cerevisiae were found.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"39 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125876114","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}
Martina Profeta, G. Cesarelli, Cristiana Giglio, Giovanni Rossi, A. Borrelli, Francesco Amato, Maria Romano
Emergency medicine is a new discipline that is rapidly developing and spreading in medical practice. The central themes of emergency medicine are resuscitation, laboratory and diagnostic imaging. In the emergency department, different parameters can be associated with a prolonged Length of Stay (LOS) as, for example; the protact use of computed tomography (TAC), radiology techniques, the need for advice from external consultants (1). To improve the efficiency of the emergency department and the assessment effectiveness of the state of healthy patient, it is important to identify the factors that affect the LOS (2).This work was based on the evaluation of the impact of demographic factors, clinical information and diagnostic techniques on the LOS in emergency medicine (LOS-ED). The dataset was carried out at the Emergency Medicine Unit of the hospital “San Giovanni di Dio e Ruggi d'Aragona” of Salerno. Multiple Linear Regression model was optimized considering the hospital stay after diagnostic procedures (dLOS) as dependent variable.
急诊医学是一门在医学实践中迅速发展和普及的新兴学科。急救医学的中心主题是复苏，实验室和诊断成像。在急诊科，不同的参数可与延长住院时间(LOS)相关联，例如;计算机断层扫描(TAC)、放射学技术的正常使用、外部咨询顾问的需求(1)。为了提高急诊科的效率和患者健康状态评估的有效性，确定影响LOS的因素是很重要的(2)。本工作是基于对急诊医学中人口因素、临床信息和诊断技术对LOS的影响进行评估。该数据集是在萨勒诺的“San Giovanni di Dio e Ruggi d'Aragona”医院急诊医学部进行的。以诊断后住院时间(dLOS)为因变量，优化多元线性回归模型。
{"title":"Impact of diagnostic techniques on the length of stay in emergency medicine","authors":"Martina Profeta, G. Cesarelli, Cristiana Giglio, Giovanni Rossi, A. Borrelli, Francesco Amato, Maria Romano","doi":"10.1145/3502060.3503653","DOIUrl":"https://doi.org/10.1145/3502060.3503653","url":null,"abstract":"Emergency medicine is a new discipline that is rapidly developing and spreading in medical practice. The central themes of emergency medicine are resuscitation, laboratory and diagnostic imaging. In the emergency department, different parameters can be associated with a prolonged Length of Stay (LOS) as, for example; the protact use of computed tomography (TAC), radiology techniques, the need for advice from external consultants (1). To improve the efficiency of the emergency department and the assessment effectiveness of the state of healthy patient, it is important to identify the factors that affect the LOS (2).This work was based on the evaluation of the impact of demographic factors, clinical information and diagnostic techniques on the LOS in emergency medicine (LOS-ED). The dataset was carried out at the Emergency Medicine Unit of the hospital “San Giovanni di Dio e Ruggi d'Aragona” of Salerno. Multiple Linear Regression model was optimized considering the hospital stay after diagnostic procedures (dLOS) as dependent variable.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133941797","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}
C. Ponsiglione, Teresa Angela Trunfio, F. Bruno, A. Borrelli
Hip fracture is a serious injury associated with adverse outcomes, including mortality. It occurs mainly in older patients and is often associated with other collateral pathologies. Its treatment generally involves a surgical operation. This could lead to various complications due to long-term hospitalization and low motor capacity. All these cause complications that extend far beyond the orthopaedic injury, with negative impacts on the patient’s quality of life and health care economics. In this contest, the main goal of our work was to identify some of the most relevant parameters to take in account for the treatment of patients with hip fracture. Our analysis involved the 456 patients who were operated on fracture to the hip in 2019 and 2020 at the Complex Operative Unit (C.O.U.) of Orthopaedic and Traumatology of the University Hospital "San Giovanni di Dio e Ruggi d’Aragona" of Salerno. Through the implementation of various algorithms, our aim was to formulate a specific model that could best predict the target value of patients.
髋部骨折是一种与包括死亡在内的不良后果相关的严重损伤。它主要发生在老年患者中，并常伴有其他旁系病变。其治疗通常包括外科手术。由于长期住院和运动能力低下，这可能导致各种并发症。所有这些引起的并发症远远超出了骨科损伤，对患者的生活质量和医疗保健经济产生负面影响。在这次比赛中，我们工作的主要目标是确定一些最相关的参数，以考虑髋部骨折患者的治疗。我们的分析涉及萨勒诺大学医院“San Giovanni di Dio e Ruggi d 'Aragona”骨科和创伤科综合外科(c.o.u) 2019年和2020年接受髋部骨折手术的456例患者。通过各种算法的实现，我们的目的是制定一个最能预测患者目标值的特定模型。
{"title":"Regression and Machine Learning analysis to predict the length of stay in patients undergoing hip replacement surgery","authors":"C. Ponsiglione, Teresa Angela Trunfio, F. Bruno, A. Borrelli","doi":"10.1145/3502060.3503616","DOIUrl":"https://doi.org/10.1145/3502060.3503616","url":null,"abstract":"Hip fracture is a serious injury associated with adverse outcomes, including mortality. It occurs mainly in older patients and is often associated with other collateral pathologies. Its treatment generally involves a surgical operation. This could lead to various complications due to long-term hospitalization and low motor capacity. All these cause complications that extend far beyond the orthopaedic injury, with negative impacts on the patient’s quality of life and health care economics. In this contest, the main goal of our work was to identify some of the most relevant parameters to take in account for the treatment of patients with hip fracture. Our analysis involved the 456 patients who were operated on fracture to the hip in 2019 and 2020 at the Complex Operative Unit (C.O.U.) of Orthopaedic and Traumatology of the University Hospital \"San Giovanni di Dio e Ruggi d’Aragona\" of Salerno. Through the implementation of various algorithms, our aim was to formulate a specific model that could best predict the target value of patients.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131186358","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}
Tinnitus seriously affects the physical and mental health of patients. Some progress has been made in the study of the electrophysiological mechanism of tinnitus. The purpose of this paper is to study the identification of tinnitus by means of EEG signal analysis. Firstly, the wavelet transform was used to extract the four frequency components of δ(0.5-3.5Hz), θ(4-7.5Hz), α(8-12Hz) and β(13-30Hz) in EEG signals. Then, the power spectrum entropy of each frequency band was calculated as the eigenvalue, and the deep neural networks (DNN) model were established to train the eigenvalues. The input layer of DNN has been a 4-dimensional eigenvector. The middle layer with two hidden layers, contained 8 neurons of each layer, in which ReLU function was adopted as activation function. In the output layer, Sigmoid function was used to classify EEG signals. Resting state EEG signals were extracted from the left middle temporal lobe of 26 subjects, and classified by three neural network models of DNN, CNN and RNN, of which the DNN with the highest classification accuracy, reaching 92%. In conclusion, there has been a certain correlation between resting state EEG signals and tinnitus, and DNN model shows a certain auxiliary diagnostic value in tinnitus recognition.
{"title":"Tinnitus Recognition by EEG signals Based on Wavelet Transform and Deep Neural Networks","authors":"Su Zhou, Cui Su","doi":"10.1145/3502060.3502145","DOIUrl":"https://doi.org/10.1145/3502060.3502145","url":null,"abstract":"Tinnitus seriously affects the physical and mental health of patients. Some progress has been made in the study of the electrophysiological mechanism of tinnitus. The purpose of this paper is to study the identification of tinnitus by means of EEG signal analysis. Firstly, the wavelet transform was used to extract the four frequency components of δ(0.5-3.5Hz), θ(4-7.5Hz), α(8-12Hz) and β(13-30Hz) in EEG signals. Then, the power spectrum entropy of each frequency band was calculated as the eigenvalue, and the deep neural networks (DNN) model were established to train the eigenvalues. The input layer of DNN has been a 4-dimensional eigenvector. The middle layer with two hidden layers, contained 8 neurons of each layer, in which ReLU function was adopted as activation function. In the output layer, Sigmoid function was used to classify EEG signals. Resting state EEG signals were extracted from the left middle temporal lobe of 26 subjects, and classified by three neural network models of DNN, CNN and RNN, of which the DNN with the highest classification accuracy, reaching 92%. In conclusion, there has been a certain correlation between resting state EEG signals and tinnitus, and DNN model shows a certain auxiliary diagnostic value in tinnitus recognition.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128045901","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}
Y. Kouzmanova, I. Dimitrova, Desislava Tsanova-Tosheva
Calcium silicate-based cements (CSCs) are bioactive materials used in the repair of endodontic perforations. Treatment and 2-year follow-up of the healing process of 40 cases of endodontic perforations with various localization - furcal, lateral and apical, are presented. Clinical cases were divided into 4 groups of 10 perforations in each and repaired with 4 different CSCs: white ProRoot MTA, gray MTA-Angelus, Boiaggregate, and Biodentine. The most commonly used clinical protocol was perforation sealing, followed by endodontic root canal treatment. The healing results of the treatment were evaluated according to the following clinical and radiographic criteria: absence of complaints and pathological changes in the adjacent periodontal tissues and the neighborhood, healing of the periradicular lesions, and lack of new ones. The success rate of the four materials used was 90% with no statistically significant difference between them.
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