Pub Date : 1900-01-01DOI: 10.1051/itmconf/20203504003
P. Belonozhko, Yury V. Berchun
The methodological features of using software systems for modeling the dynamics of mechanical systems for solving educational research problems are considered. The traditionally established approach to studying the foundations of modeling the dynamics of technical systems is largely based on mastering the corresponding mathematical tools. With regard to modeling the dynamics of systems of solids, the mentioned approach involves, first of all, the development of skills in the preparation of ordinary differential equations (ODEs). At the same time, the formation of a mechanical calculation scheme as an «object of application of mathematics» becomes a natural stage of mathematical research, and the selection of simplifying assumptions that allow one or another idealization to correspond to a real object is carried out consciously taking into account the desire for certain internal properties of the mathematical model (for example, type and order of the ODE system). An important feature of modern systems for modeling the dynamics of solid’s systems is the ability to describe the object under study directly in terms of the subject area. This feature provides an increase in the effectiveness of modeling in solving design and engineering and scientific research problems and allows you to save a qualified specialist from a laborious routine. At the same time, as experience shows, in the process of solving educational and research problems, due to the mentioned features of modern software, students have certain difficulties in mastering the fundamental conceptual base of the corresponding discipline (physics, electrical engineering, theoretical mechanics, theory of automatic control, fundamentals of computer aided design). The article gives an example of an educational research task focused on overcoming these difficulties.
{"title":"Learning to Model the Dynamics of Mechanical Systems with the Method of Solving Educational and Research Problems","authors":"P. Belonozhko, Yury V. Berchun","doi":"10.1051/itmconf/20203504003","DOIUrl":"https://doi.org/10.1051/itmconf/20203504003","url":null,"abstract":"The methodological features of using software systems for modeling the dynamics of mechanical systems for solving educational research problems are considered. The traditionally established approach to studying the foundations of modeling the dynamics of technical systems is largely based on mastering the corresponding mathematical tools. With regard to modeling the dynamics of systems of solids, the mentioned approach involves, first of all, the development of skills in the preparation of ordinary differential equations (ODEs). At the same time, the formation of a mechanical calculation scheme as an «object of application of mathematics» becomes a natural stage of mathematical research, and the selection of simplifying assumptions that allow one or another idealization to correspond to a real object is carried out consciously taking into account the desire for certain internal properties of the mathematical model (for example, type and order of the ODE system). An important feature of modern systems for modeling the dynamics of solid’s systems is the ability to describe the object under study directly in terms of the subject area. This feature provides an increase in the effectiveness of modeling in solving design and engineering and scientific research problems and allows you to save a qualified specialist from a laborious routine. At the same time, as experience shows, in the process of solving educational and research problems, due to the mentioned features of modern software, students have certain difficulties in mastering the fundamental conceptual base of the corresponding discipline (physics, electrical engineering, theoretical mechanics, theory of automatic control, fundamentals of computer aided design). The article gives an example of an educational research task focused on overcoming these difficulties.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123760732","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 : 1900-01-01DOI: 10.1051/itmconf/20214003031
R. Kanase, A. Kumavat, Rohit Datta Sinalkar, Sakshi Somani
Our posture shows an impact on health both mentally and physically. Various methods have been proposed in order to detect different postures of a human being. Posture analysis also plays an essential role in the field of medicine such as finding out sleeping posture of a patient. Image processing based and sensor based approach are the leading posture analysis approaches. Sensor based approach is used by numerous models to focus on posture detection in which the person needs to wear some particular devices or sensors which is helpful in cases such as fall detection. Image processing based approach helps to analyze postures such as standing and sitting postures. Fitness exercises are exceptionally beneficial to individual health, but, they can also be ineffectual and quite possibly harmful if performed incorrectly. When someone does not use the proper posture, exercise mistakes occur. This proposed application utilizes pose estimation and detects the user’s exercise posture and provides detailed, customized recommendations on how the user can improve their posture. A pose estimator called OpenPose is used in this application. OpenPose is a pre trained model composed of a multi-stage CNN to detect a user’s posture. This application then evaluates the vector geometry of the pose through an exercise to provide helpful feedback. Pose estimation is a method in which spatial locations of key body joints is calculated using image or video of the person. This computer vision technique detects human posture in images or videos and shows the keypoints such as elbow or knee in the output image.
{"title":"Pose Estimation and Correcting Exercise Posture","authors":"R. Kanase, A. Kumavat, Rohit Datta Sinalkar, Sakshi Somani","doi":"10.1051/itmconf/20214003031","DOIUrl":"https://doi.org/10.1051/itmconf/20214003031","url":null,"abstract":"Our posture shows an impact on health both mentally and physically. Various methods have been proposed in order to detect different postures of a human being. Posture analysis also plays an essential role in the field of medicine such as finding out sleeping posture of a patient. Image processing based and sensor based approach are the leading posture analysis approaches. Sensor based approach is used by numerous models to focus on posture detection in which the person needs to wear some particular devices or sensors which is helpful in cases such as fall detection. Image processing based approach helps to analyze postures such as standing and sitting postures. Fitness exercises are exceptionally beneficial to individual health, but, they can also be ineffectual and quite possibly harmful if performed incorrectly. When someone does not use the proper posture, exercise mistakes occur. This proposed application utilizes pose estimation and detects the user’s exercise posture and provides detailed, customized recommendations on how the user can improve their posture. A pose estimator called OpenPose is used in this application. OpenPose is a pre trained model composed of a multi-stage CNN to detect a user’s posture. This application then evaluates the vector geometry of the pose through an exercise to provide helpful feedback. Pose estimation is a method in which spatial locations of key body joints is calculated using image or video of the person. This computer vision technique detects human posture in images or videos and shows the keypoints such as elbow or knee in the output image.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123773073","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 : 1900-01-01DOI: 10.1051/itmconf/20224601003
Fathallah Rerhrhaye, Ilyas Lahlouh, Y. Ennaciri, Chirine Benzazah, Ahmed El Akkary, N. Sefiani, Said Bouftane
A data logger is an electronic device that senses temperature, relative humidity, and other characteristics such as voltage and pulse by combining analog and digital measurements with programming methods. Thus, data acquisition systems (DAQSs) are frequently used in PV facilities to capture all system data to analyze and optimize plant performance. The major purpose of the project is to create a low-cost DAQS. The suggested monitoring system has been used to continuously gather and display the electrical output characteristics of a stand-alone PV system. PV produced voltage, current, and power are examples of such parameters. Furthermore, because the PV module short circuit current is directly proportional to the molar concentration, the global solar radiation may be determined by monitoring it. The proposed system is considered a good solution for collecting the system database to be ready for the analysis and optimization of the PV plant’s performance. The configurations of software and hardware of the proposed system are presented, and the proposed system's performance is tested when integrated with a small size PV system.
{"title":"IoT-Based Data Logger for solar systems applications","authors":"Fathallah Rerhrhaye, Ilyas Lahlouh, Y. Ennaciri, Chirine Benzazah, Ahmed El Akkary, N. Sefiani, Said Bouftane","doi":"10.1051/itmconf/20224601003","DOIUrl":"https://doi.org/10.1051/itmconf/20224601003","url":null,"abstract":"A data logger is an electronic device that senses temperature, relative humidity, and other characteristics such as voltage and pulse by combining analog and digital measurements with programming methods. Thus, data acquisition systems (DAQSs) are frequently used in PV facilities to capture all system data to analyze and optimize plant performance. The major purpose of the project is to create a low-cost DAQS. The suggested monitoring system has been used to continuously gather and display the electrical output characteristics of a stand-alone PV system. PV produced voltage, current, and power are examples of such parameters. Furthermore, because the PV module short circuit current is directly proportional to the molar concentration, the global solar radiation may be determined by monitoring it. The proposed system is considered a good solution for collecting the system database to be ready for the analysis and optimization of the PV plant’s performance. The configurations of software and hardware of the proposed system are presented, and the proposed system's performance is tested when integrated with a small size PV system.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125348420","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 : 1900-01-01DOI: 10.1051/itmconf/20203203015
Sanjana C Madargi, L. Ragha, V. Mane
A huge volume of information available today is in the form of images and searching the wanted images is very difficult and highly time-consuming. The search may take longer periods as the search volume on the internet is very huge and also the relevance of extracted images is still not up to the mark. The technologies like ontology and languages like OWL help us to tag the images that describe the semantic of the images. Hence, it helps in faster searching of the wanted images. Also, another challenge with OWL and Semantic web is the speed in which one can derive the relationships between various objects extracted from the images. The challenge is to extract the semantic from the images more efficiently using a parallel approach. In this paper, we explore the different techniques for generating semantic knowledge using parallel approaches like the T-box approach, merge classification, extract concept for matching ontology. We propose an enhanced method to speed-up the computation by combining T-box and merge classification techniques.
{"title":"A Parallel Environment Designing for OWL Thinking","authors":"Sanjana C Madargi, L. Ragha, V. Mane","doi":"10.1051/itmconf/20203203015","DOIUrl":"https://doi.org/10.1051/itmconf/20203203015","url":null,"abstract":"A huge volume of information available today is in the form of images and searching the wanted images is very difficult and highly time-consuming. The search may take longer periods as the search volume on the internet is very huge and also the relevance of extracted images is still not up to the mark. The technologies like ontology and languages like OWL help us to tag the images that describe the semantic of the images. Hence, it helps in faster searching of the wanted images. Also, another challenge with OWL and Semantic web is the speed in which one can derive the relationships between various objects extracted from the images. The challenge is to extract the semantic from the images more efficiently using a parallel approach. In this paper, we explore the different techniques for generating semantic knowledge using parallel approaches like the T-box approach, merge classification, extract concept for matching ontology. We propose an enhanced method to speed-up the computation by combining T-box and merge classification techniques.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125369350","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}
Twitter’s primary objective is to facilitate free expression and the exchange of ideas, allowing individuals to share their thoughts, opinions, and information with others without any limitations or constraints. It helps a human being to perceive different scopes and points of view. It is used to serve the public discussion and it should not be used to undermine individuals based on their race, nationality, public standing, rank, sexual orientation, age, disability, or health conditions. So, using hate speech is not appropriate and removal of hate speech is necessary for achieving the goal. This paper aims to utilize machine learning algorithms such as Logistic Regression, Support Vector Machine, Random Forest, CNN-LSTM, and Fuzzy method to compare and evaluate their accuracy in detecting hate speech. The objective is to determine the best model for hate speech detection.
{"title":"Hate Speech Detection in Twitter Using Different Models","authors":"Anagha Abraham, Antony J Kolanchery, Anugraha Antoo Kanjookaran, Binil Tom Jose, Dhanya Pm","doi":"10.1051/itmconf/20235604007","DOIUrl":"https://doi.org/10.1051/itmconf/20235604007","url":null,"abstract":"Twitter’s primary objective is to facilitate free expression and the exchange of ideas, allowing individuals to share their thoughts, opinions, and information with others without any limitations or constraints. It helps a human being to perceive different scopes and points of view. It is used to serve the public discussion and it should not be used to undermine individuals based on their race, nationality, public standing, rank, sexual orientation, age, disability, or health conditions. So, using hate speech is not appropriate and removal of hate speech is necessary for achieving the goal. This paper aims to utilize machine learning algorithms such as Logistic Regression, Support Vector Machine, Random Forest, CNN-LSTM, and Fuzzy method to compare and evaluate their accuracy in detecting hate speech. The objective is to determine the best model for hate speech detection.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125468654","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 : 1900-01-01DOI: 10.1051/itmconf/20224502011
Yaoqun Xu, Xin-Xin Zhen
In this paper, constructing the improved chaotic map which multiplies the output value of the chaotic map by a large value, and subtracts its integer part. Simulation results show that the chaos range of the improved chaotic map is enlarged. The generated chaotic sequence has strong randomness. A double chaotic image encryption algorithm is proposed by combining the improved chaotic maps with the permutation and diffusion encryption structure. The algorithm can reduce the complexity while ensuring the encryption effect. The simulation results show that the encryption algorithm can resist statistical attack and has excellent robustness, and has a good development prospect in information security.
{"title":"Image encryption using improved Cubic map and Henon map","authors":"Yaoqun Xu, Xin-Xin Zhen","doi":"10.1051/itmconf/20224502011","DOIUrl":"https://doi.org/10.1051/itmconf/20224502011","url":null,"abstract":"In this paper, constructing the improved chaotic map which multiplies the output value of the chaotic map by a large value, and subtracts its integer part. Simulation results show that the chaos range of the improved chaotic map is enlarged. The generated chaotic sequence has strong randomness. A double chaotic image encryption algorithm is proposed by combining the improved chaotic maps with the permutation and diffusion encryption structure. The algorithm can reduce the complexity while ensuring the encryption effect. The simulation results show that the encryption algorithm can resist statistical attack and has excellent robustness, and has a good development prospect in information security.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125612784","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 : 1900-01-01DOI: 10.1051/ITMCONF/20192601011
Lin Zhu
Nowadays, the rapid development of information technology has increasingly penetrated into all walks of society and even people’s lives. With the development of education informatization, traditional teaching can’t meet the needs of talents in the new era. Developing a new teaching mode by integrating internet, big data and traditional teaching has become the main theme of contemporary education. This paper studies the connotation of educational informatization and Blended Teaching theory and puts forward the Blended Teaching mode of College English by improving teachers’ informationized teaching ability, constructing the diversified teaching platform, and setting up informationized teaching resource base, adopting different teaching methods and strategies, so as to improve students’ enthusiasm and autonomy in College English learning and enhance the effect of College English teaching.
{"title":"A Research on the Reform of College English Blended Teaching Mode under the Background of Educational Informatization","authors":"Lin Zhu","doi":"10.1051/ITMCONF/20192601011","DOIUrl":"https://doi.org/10.1051/ITMCONF/20192601011","url":null,"abstract":"Nowadays, the rapid development of information technology has increasingly penetrated into all walks of society and even people’s lives. With the development of education informatization, traditional teaching can’t meet the needs of talents in the new era. Developing a new teaching mode by integrating internet, big data and traditional teaching has become the main theme of contemporary education. This paper studies the connotation of educational informatization and Blended Teaching theory and puts forward the Blended Teaching mode of College English by improving teachers’ informationized teaching ability, constructing the diversified teaching platform, and setting up informationized teaching resource base, adopting different teaching methods and strategies, so as to improve students’ enthusiasm and autonomy in College English learning and enhance the effect of College English teaching.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126707429","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 : 1900-01-01DOI: 10.1051/itmconf/20235302011
Vaibhav Jadhav, Namita Tiwari, Meenu Chawla
In this paper, a novel method for EEG(Electroencephalography) based emotion recognition is introduced. This method uses transfer learning to extract features from multichannel EEG signals, these features are then arranged in an 8×9 map to represent their spatial location on scalp and then we introduce a CNN model which takes in the spatial feature map and extracts spatial relations between EEG channel and finally classify the emotions. First, EEG signals are converted to spectrogram and passed through a pre-trained image classification model to get a feature vector from spectrogram of EEG. Then, feature vectors of different channels are rearranged and are presented as input to a CNN model which extracts spatial features or dependencies of channels as part of training. Finally, CNN outputs are flattened and passed through dense layer to classify between emotion classes. In this study, SEED, SEED-IV and SEED-V EEG emotion data-sets are used for classification and our method achieves best classification accuracy of 97.09% on SEED, 89.81% on SEED-IV and 88.23% on SEED-V data-set with fivefold cross validation.
本文提出了一种基于脑电图的情绪识别新方法。该方法利用迁移学习从多通道脑电信号中提取特征，然后将这些特征排列成8×9图来表示它们在头皮上的空间位置，然后引入CNN模型，该模型吸收空间特征图，提取脑电信号通道之间的空间关系，最后对情绪进行分类。首先，将脑电信号转换为频谱图，并通过预训练的图像分类模型从脑电信号的频谱图中得到特征向量。然后，将不同通道的特征向量重新排列并作为CNN模型的输入，该模型提取通道的空间特征或依赖关系作为训练的一部分。最后，对CNN输出进行平面化处理，并通过密集层进行情感分类。本研究使用SEED、SEED- iv和SEED- v EEG情绪数据集进行分类，经五重交叉验证，我们的方法在SEED、SEED- iv和SEED- v数据集上的分类准确率分别为97.09%、89.81%和88.23%。
{"title":"EEG-based Emotion Recognition using Transfer Learning Based Feature Extraction and Convolutional Neural Network","authors":"Vaibhav Jadhav, Namita Tiwari, Meenu Chawla","doi":"10.1051/itmconf/20235302011","DOIUrl":"https://doi.org/10.1051/itmconf/20235302011","url":null,"abstract":"In this paper, a novel method for EEG(Electroencephalography) based emotion recognition is introduced. This method uses transfer learning to extract features from multichannel EEG signals, these features are then arranged in an 8×9 map to represent their spatial location on scalp and then we introduce a CNN model which takes in the spatial feature map and extracts spatial relations between EEG channel and finally classify the emotions. First, EEG signals are converted to spectrogram and passed through a pre-trained image classification model to get a feature vector from spectrogram of EEG. Then, feature vectors of different channels are rearranged and are presented as input to a CNN model which extracts spatial features or dependencies of channels as part of training. Finally, CNN outputs are flattened and passed through dense layer to classify between emotion classes. In this study, SEED, SEED-IV and SEED-V EEG emotion data-sets are used for classification and our method achieves best classification accuracy of 97.09% on SEED, 89.81% on SEED-IV and 88.23% on SEED-V data-set with fivefold cross validation.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127009169","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 : 1900-01-01DOI: 10.1051/itmconf/20193005033
V. Bukharin, N. Voytovich
The main selective characteristics of a Resonant Cavity Antenna, which is a radiating element of the antenna array of a glide path station, are presented. The results of rigorous electrodynamic modeling of a resonator antenna and experimental results of studies on antenna samples are presented
{"title":"Selectivity of a resonant cavity antenna","authors":"V. Bukharin, N. Voytovich","doi":"10.1051/itmconf/20193005033","DOIUrl":"https://doi.org/10.1051/itmconf/20193005033","url":null,"abstract":"The main selective characteristics of a Resonant Cavity Antenna, which is a radiating element of the antenna array of a glide path station, are presented. The results of rigorous electrodynamic modeling of a resonator antenna and experimental results of studies on antenna samples are presented","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114941738","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 : 1900-01-01DOI: 10.1051/itmconf/20214003050
Megha M. Navada, Deepshikha Mishra, Saloni Parkar, Parag G. Patil, Chaitanya S. Jage
Parkinson’s disease is a chronic neurodegenerative condition that demonstrate the progressive loss of the ability to correlate movements mainly occurs in the elderly. For the purpose of monitoring tremors in Parkinson’s disease, a system has to be designed and developed. For coordination of movements, people with Parkinson’s, deprive of a chemical called dopamine which behaves as the messenger between the brain parts and the nervous system .Detecting Parkinson’s disease is a very arduous task as there is no evidence currently present to do this. Therefore, the main intention of our work is the designing of a system for recognizing Parkinson’s disease at an initial stage. An Android application is being designed that allows the status of PD patients to be assessed based on the tests found on the Unified Parkinson’s Disease Rating Scale approved by the Movement Disorders Society (MDS-UPDRS).
{"title":"Early Stage Detection of Parkinson Disease","authors":"Megha M. Navada, Deepshikha Mishra, Saloni Parkar, Parag G. Patil, Chaitanya S. Jage","doi":"10.1051/itmconf/20214003050","DOIUrl":"https://doi.org/10.1051/itmconf/20214003050","url":null,"abstract":"Parkinson’s disease is a chronic neurodegenerative condition that demonstrate the progressive loss of the ability to correlate movements mainly occurs in the elderly. For the purpose of monitoring tremors in Parkinson’s disease, a system has to be designed and developed. For coordination of movements, people with Parkinson’s, deprive of a chemical called dopamine which behaves as the messenger between the brain parts and the nervous system .Detecting Parkinson’s disease is a very arduous task as there is no evidence currently present to do this. Therefore, the main intention of our work is the designing of a system for recognizing Parkinson’s disease at an initial stage. An Android application is being designed that allows the status of PD patients to be assessed based on the tests found on the Unified Parkinson’s Disease Rating Scale approved by the Movement Disorders Society (MDS-UPDRS).","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115085487","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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