Pub Date : 2023-01-01DOI: 10.5220/0011593000003414
K. Smarsly, Yousuf Al-Hakim, P. Peralta, S. Beier, C. Klümper
{"title":"A Systematic Review and Recommendation of Software Architectures for SARS-CoV-2 Monitoring","authors":"K. Smarsly, Yousuf Al-Hakim, P. Peralta, S. Beier, C. Klümper","doi":"10.5220/0011593000003414","DOIUrl":"https://doi.org/10.5220/0011593000003414","url":null,"abstract":"","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"59 1","pages":"211-217"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77343944","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 : 2023-01-01DOI: 10.5220/0011665600003414
Akito Yamamoto, E. Kimura, T. Shibuya
: As the amount of biomedical and healthcare data increases, data mining for medicine becomes more and more important for health improvement. At the same time, privacy concerns in data utilization have also been growing. The key concepts for privacy protection are k -anonymity and differential privacy, but k -anonymity alone cannot protect personal presence information, and differential privacy alone would leak the identity. To promote data sharing throughout the world, universal methods to release the entire data while satisfying both concepts are required, but such a method does not yet exist. Therefore, we propose a novel privacy-preserving method, ( ε , k ) -Randomized Anonymization. In this paper, we first present two methods that compose the Randomized Anonymization method. They perform k -anonymization and randomized response in sequence and have adequate randomness and high privacy guarantees, respectively. Then, we show the algorithm for ( ε , k ) -Randomized Anonymization, which can provide highly accurate outputs with both k -anonymity and differential privacy. In addition, we describe the analysis procedures for each method using an inverse matrix and expectation-maximization (EM) algorithm. In the experiments, we used real data to evaluate our methods’ anonymity, privacy level, and accuracy. Furthermore, we show several examples of analysis results to demonstrate high utility of the proposed methods.
{"title":"(ε, k)-Randomized Anonymization: ε-Differentially Private Data Sharing with k-Anonymity","authors":"Akito Yamamoto, E. Kimura, T. Shibuya","doi":"10.5220/0011665600003414","DOIUrl":"https://doi.org/10.5220/0011665600003414","url":null,"abstract":": As the amount of biomedical and healthcare data increases, data mining for medicine becomes more and more important for health improvement. At the same time, privacy concerns in data utilization have also been growing. The key concepts for privacy protection are k -anonymity and differential privacy, but k -anonymity alone cannot protect personal presence information, and differential privacy alone would leak the identity. To promote data sharing throughout the world, universal methods to release the entire data while satisfying both concepts are required, but such a method does not yet exist. Therefore, we propose a novel privacy-preserving method, ( ε , k ) -Randomized Anonymization. In this paper, we first present two methods that compose the Randomized Anonymization method. They perform k -anonymization and randomized response in sequence and have adequate randomness and high privacy guarantees, respectively. Then, we show the algorithm for ( ε , k ) -Randomized Anonymization, which can provide highly accurate outputs with both k -anonymity and differential privacy. In addition, we describe the analysis procedures for each method using an inverse matrix and expectation-maximization (EM) algorithm. In the experiments, we used real data to evaluate our methods’ anonymity, privacy level, and accuracy. Furthermore, we show several examples of analysis results to demonstrate high utility of the proposed methods.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"184 6 1","pages":"287-297"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81046703","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 : 2023-01-01DOI: 10.5220/0011668300003414
Christian Lins, Franziska Quang, Rica Schulze, Stefanie Lins, Andreas Hein, Sebastian J. F. Fudickar
{"title":"An Android App for Posture Analysis Using OWAS","authors":"Christian Lins, Franziska Quang, Rica Schulze, Stefanie Lins, Andreas Hein, Sebastian J. F. Fudickar","doi":"10.5220/0011668300003414","DOIUrl":"https://doi.org/10.5220/0011668300003414","url":null,"abstract":"","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"34 1","pages":"307-313"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79134098","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 : 2023-01-01DOI: 10.5220/0011797100003414
Diogo Machado, Vítor Costa, Pedro Brandão
: Imbalanced data sets pose a complex problem in data mining. Health related data sets, where the positive class is connected to the existence of an anomaly, are prone to be imbalanced. Data related to diabetes management follows this trend. In the case of diabetes, patients avoid situations of hypo/hyperglycaemia, which is the anomaly we want to detect. The use of balancing methods can provide more examples of the minority class, and assist the classifier by clearing the decision boundary. Nevertheless, each over-sampling and under-sampling method can affect the data set uniquely, which will influence the classifier’s performance. In this work, the authors studied the impact of the most known data-balancing methods applied to the Ohio and St. Louis diabetes related data sets. The best and most robust approach was the use of ENN with SMOTE. This hybrid method produced significant performance gains on all the performed tests. ENN in particular had a meaningful impact on all the tests. Given the limited volume of glycaemia-based data available for diabetes management, over-sampling methods would be expected to have a greater role in improving the classifier’s performance. In our experiments, the clearing of noise values by the under-sampling methods, produced better results.
{"title":"Using Balancing Methods to Improve Glycaemia-Based Data Mining","authors":"Diogo Machado, Vítor Costa, Pedro Brandão","doi":"10.5220/0011797100003414","DOIUrl":"https://doi.org/10.5220/0011797100003414","url":null,"abstract":": Imbalanced data sets pose a complex problem in data mining. Health related data sets, where the positive class is connected to the existence of an anomaly, are prone to be imbalanced. Data related to diabetes management follows this trend. In the case of diabetes, patients avoid situations of hypo/hyperglycaemia, which is the anomaly we want to detect. The use of balancing methods can provide more examples of the minority class, and assist the classifier by clearing the decision boundary. Nevertheless, each over-sampling and under-sampling method can affect the data set uniquely, which will influence the classifier’s performance. In this work, the authors studied the impact of the most known data-balancing methods applied to the Ohio and St. Louis diabetes related data sets. The best and most robust approach was the use of ENN with SMOTE. This hybrid method produced significant performance gains on all the performed tests. ENN in particular had a meaningful impact on all the tests. Given the limited volume of glycaemia-based data available for diabetes management, over-sampling methods would be expected to have a greater role in improving the classifier’s performance. In our experiments, the clearing of noise values by the under-sampling methods, produced better results.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"92 1","pages":"188-198"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83745569","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 : 2023-01-01DOI: 10.5220/0011745100003414
A. Dias, S. Duarte, Joaquim Alvarelhão, C. Cunha
: This study aimed to investigate how patients and professionals faced telemedicine or telehealth in Centre Region in Portugal during the Sars-Cov-2 pandemic. Mixed-methods exploratory and parallel study including data from a survey of 190 healthcare patients and seven qualitative interviews with healthcare professionals from the Centre Region of Portugal were carried out. Descriptive and multiple correspondence analysis was used for survey results evaluation while healthcare professionals' perceptions were studied using a thematic analysis approach. Although few participants (15%) experienced telemedicine before the pandemic, most (73.2%) consider the health sector prepared to provide it. The most mentioned benefits of telemedicine were the avoidance of travel, convenience, and comfort for the patient. The limitations that may exist in this modality relate to patients who do not have the necessary technological devices, the lack of adequate diagnostic tools, and limitations to the patient-doctor relationship. Younger participants (<30y) were associated with characteristics of the telemedicine operating system, like the adequacy of diagnostic tools while persons more than 50 years old were associated with the lack of preparation or predisposition of professionals to provide telemedicine.
{"title":"Perceptions on Telemedicine in Portugal During Sars-Cov-2 Pandemic: A Mixed-Methods Study","authors":"A. Dias, S. Duarte, Joaquim Alvarelhão, C. Cunha","doi":"10.5220/0011745100003414","DOIUrl":"https://doi.org/10.5220/0011745100003414","url":null,"abstract":": This study aimed to investigate how patients and professionals faced telemedicine or telehealth in Centre Region in Portugal during the Sars-Cov-2 pandemic. Mixed-methods exploratory and parallel study including data from a survey of 190 healthcare patients and seven qualitative interviews with healthcare professionals from the Centre Region of Portugal were carried out. Descriptive and multiple correspondence analysis was used for survey results evaluation while healthcare professionals' perceptions were studied using a thematic analysis approach. Although few participants (15%) experienced telemedicine before the pandemic, most (73.2%) consider the health sector prepared to provide it. The most mentioned benefits of telemedicine were the avoidance of travel, convenience, and comfort for the patient. The limitations that may exist in this modality relate to patients who do not have the necessary technological devices, the lack of adequate diagnostic tools, and limitations to the patient-doctor relationship. Younger participants (<30y) were associated with characteristics of the telemedicine operating system, like the adequacy of diagnostic tools while persons more than 50 years old were associated with the lack of preparation or predisposition of professionals to provide telemedicine.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"25 1","pages":"471-476"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78425116","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 : 2023-01-01DOI: 10.5220/0011694300003414
M. Alfano, J. Kellett, B. Lenzitti, M. Helfert
{"title":"Intelligent Provision of Tailored, Easily Understood, and Trusted Health Information for Patient Empowerment","authors":"M. Alfano, J. Kellett, B. Lenzitti, M. Helfert","doi":"10.5220/0011694300003414","DOIUrl":"https://doi.org/10.5220/0011694300003414","url":null,"abstract":"","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":" 1","pages":"384-391"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91412621","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 : 2023-01-01DOI: 10.5220/0011755700003414
Linda Büker, Dennis Bussenius, Eva Schobert, Andreas Hein, S. Hellmers
{"title":"Camera-Based Tracking and Evaluation of the Performance of a Fitness Exercise","authors":"Linda Büker, Dennis Bussenius, Eva Schobert, Andreas Hein, S. Hellmers","doi":"10.5220/0011755700003414","DOIUrl":"https://doi.org/10.5220/0011755700003414","url":null,"abstract":"","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"162 1","pages":"489-496"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80252628","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 : 2023-01-01DOI: 10.5220/0011927300003414
Haadia Amjad, Mohammad Ashraf, S. Sherazi, Saad Khan, M. Fraz, Tahir Hameed, S. Bukhari
{"title":"Attention-Based Explainability Approaches in Healthcare Natural Language Processing","authors":"Haadia Amjad, Mohammad Ashraf, S. Sherazi, Saad Khan, M. Fraz, Tahir Hameed, S. Bukhari","doi":"10.5220/0011927300003414","DOIUrl":"https://doi.org/10.5220/0011927300003414","url":null,"abstract":"","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"30 1","pages":"689-696"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90252511","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 : 2023-01-01DOI: 10.5220/0011926500003414
Raul Kaizer, Leonardo Sestrem, Tiago Franco, João Gonçalves, J. Teixeira, J. Lima, J. Carvalho, Paulo Leitão
: Reliable ways to treat and monitor patients remotely have been researched and proposed by numerous people. Many of these propositions are under the wearable category due to it usually not requiring deep knowledge to be handled and its durability. Among the many applicable ways, fall monitoring has gained importance as the world population ages and countries aim to increase the quality of life. For it to be possible, there are many ways such as analyzing muscle response, body position, or brain activities, but for most of them, the result ends up being expensive and or inaccurate. With this in mind, this paper brings the development of an acquisition system for electromyography, electrocardiography, body position and temperature. The acquired data is transmitted to the smartphone through Bluetooth Low Energy (BLE) and then sent to a secure cloud to be provided to the physician. In future works, artificial intelligence codes will analyze the data patterns to predict fall occurrences and establish functional electrical stimulation (FES) routines to prevent falls and or treat the patients according to their necessities.
{"title":"Data Acquisition System for a Wearable-Based Fall Prevention","authors":"Raul Kaizer, Leonardo Sestrem, Tiago Franco, João Gonçalves, J. Teixeira, J. Lima, J. Carvalho, Paulo Leitão","doi":"10.5220/0011926500003414","DOIUrl":"https://doi.org/10.5220/0011926500003414","url":null,"abstract":": Reliable ways to treat and monitor patients remotely have been researched and proposed by numerous people. Many of these propositions are under the wearable category due to it usually not requiring deep knowledge to be handled and its durability. Among the many applicable ways, fall monitoring has gained importance as the world population ages and countries aim to increase the quality of life. For it to be possible, there are many ways such as analyzing muscle response, body position, or brain activities, but for most of them, the result ends up being expensive and or inaccurate. With this in mind, this paper brings the development of an acquisition system for electromyography, electrocardiography, body position and temperature. The acquired data is transmitted to the smartphone through Bluetooth Low Energy (BLE) and then sent to a secure cloud to be provided to the physician. In future works, artificial intelligence codes will analyze the data patterns to predict fall occurrences and establish functional electrical stimulation (FES) routines to prevent falls and or treat the patients according to their necessities.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"108 1","pages":"701-710"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87573276","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 : 2023-01-01DOI: 10.5220/0011676300003414
Haruka Kamachi, Sae Ohkubo, Anna Yokokubo, G. Lopez
: Obesity may cause lifestyle diseases such as diabetes and high blood pressure. Eating slowly and chewing well are essential to prevent obesity. This research aims to improve the consciousness of dietary behavior based on eating habits by quantifying eating behavior. It proposes “ChewReminder,” a smartphone application software that detects eating activities in real-time under a natural meal environment and gives feedback based on detected activity. ChewReminder detects four activities: chewing, swallowing, talking, and other.The smartwatch gives feedback using vibration depend on chewing count per one bite which information was linked from the smartphone. Also, the total feedback about the meal was displayed on the smartphone after finishing the meal. The chewing count for 70% subjects and chewing pace for more than half subjects was improved with using ChewReminder by the result of total chewing count, average of chewing count per bite and chewing pace. ChewReminder is effective especially people who are aware of fast eating. Also, the result of long-term experiment indicated that feedback displayed on a smartphone was effective to improve consciousness of eating activity. Therefore, the result of both experiment shows that ChewReminder is a valid system to improve consciousness of eating activity especially chewing activity.
{"title":"Eating Habit Improvement System Using Dietary Sound","authors":"Haruka Kamachi, Sae Ohkubo, Anna Yokokubo, G. Lopez","doi":"10.5220/0011676300003414","DOIUrl":"https://doi.org/10.5220/0011676300003414","url":null,"abstract":": Obesity may cause lifestyle diseases such as diabetes and high blood pressure. Eating slowly and chewing well are essential to prevent obesity. This research aims to improve the consciousness of dietary behavior based on eating habits by quantifying eating behavior. It proposes “ChewReminder,” a smartphone application software that detects eating activities in real-time under a natural meal environment and gives feedback based on detected activity. ChewReminder detects four activities: chewing, swallowing, talking, and other.The smartwatch gives feedback using vibration depend on chewing count per one bite which information was linked from the smartphone. Also, the total feedback about the meal was displayed on the smartphone after finishing the meal. The chewing count for 70% subjects and chewing pace for more than half subjects was improved with using ChewReminder by the result of total chewing count, average of chewing count per bite and chewing pace. ChewReminder is effective especially people who are aware of fast eating. Also, the result of long-term experiment indicated that feedback displayed on a smartphone was effective to improve consciousness of eating activity. Therefore, the result of both experiment shows that ChewReminder is a valid system to improve consciousness of eating activity especially chewing activity.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"583 1","pages":"346-353"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76782380","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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