Pub Date : 2022-01-01DOI: 10.5220/0010843200003123
Muhammad Sulaiman, Anne Håkansson, Randi Karlsen
Health promotion is to enable people to take control over their health. Digital health with mHealth empowers users to establish proactive health, ubiquitously. The users shall have increased control over their health to improve their life by being proactive. To develop proactive health with the principles of prediction, prevention, and ubiquitous health, artificial intelligence with mHealth can play a pivotal role. There are various challenges for establishing proactive mHealth. For example, the system must be adaptive and provide timely interventions by considering the uniqueness of the user. The context of the user is also highly relevant for proactive mHealth. The context provides parameters as input along with information to formulate the current state of the user. Automated decision-making is significant with user-level decision-making as it enables decisions to promote well-being by technological means without human involvement. This paper presents a design framework of AI-enabled proactive mHealth that includes automated decision-making with predictive analytics, Just-in-time adaptive interventions and a P5 approach to mHealth. The significance of user-level decision-making for automated decision-making is presented. Furthermore, the paper provides a holistic view of the user's context with profile and characteristics. The paper also discusses the need for multiple parameters as inputs, and the identification of sources e.g., wearables, sensors, and other resources, with the challenges in the implementation of the framework. Finally, a proof-of-concept based on the framework provides design and implementation steps, architecture, goals, and feedback process. The framework shall provide the basis for the further development of AI-enabled proactive mHealth.
{"title":"A Framework for AI-enabled Proactive mHealth with Automated Decision-making for a User's Context","authors":"Muhammad Sulaiman, Anne Håkansson, Randi Karlsen","doi":"10.5220/0010843200003123","DOIUrl":"https://doi.org/10.5220/0010843200003123","url":null,"abstract":"Health promotion is to enable people to take control over their health. Digital health with mHealth empowers users to establish proactive health, ubiquitously. The users shall have increased control over their health to improve their life by being proactive. To develop proactive health with the principles of prediction, prevention, and ubiquitous health, artificial intelligence with mHealth can play a pivotal role. There are various challenges for establishing proactive mHealth. For example, the system must be adaptive and provide timely interventions by considering the uniqueness of the user. The context of the user is also highly relevant for proactive mHealth. The context provides parameters as input along with information to formulate the current state of the user. Automated decision-making is significant with user-level decision-making as it enables decisions to promote well-being by technological means without human involvement. This paper presents a design framework of AI-enabled proactive mHealth that includes automated decision-making with predictive analytics, Just-in-time adaptive interventions and a P5 approach to mHealth. The significance of user-level decision-making for automated decision-making is presented. Furthermore, the paper provides a holistic view of the user's context with profile and characteristics. The paper also discusses the need for multiple parameters as inputs, and the identification of sources e.g., wearables, sensors, and other resources, with the challenges in the implementation of the framework. Finally, a proof-of-concept based on the framework provides design and implementation steps, architecture, goals, and feedback process. The framework shall provide the basis for the further development of AI-enabled proactive mHealth.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"9 1","pages":"111-124"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80358277","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 : 2022-01-01DOI: 10.5220/0010850000003123
Hasnae Zerouaoui, A. Idri
Breast cancer (BC) is a leading cause of death among women worldwide. It remains a critical challenge, causing over 10 million deaths globally in 2020. Medical images analysis is the most promising research area since it provides facilities for diagnosing several diseases such as breast cancer. The present paper carries out an empirical evaluation of recent deep Convolutional Neural Network (CNN) architectures for a binary classification of breast cytological images based fined tuned versions of seven deep learning techniques: VGG16, VGG19, DenseNet201, InceptionResNetV2, InceptionV3, ResNet50 and MobileNetV2. The empirical evaluations used: (1) four classification performance criteria (accuracy, recall, precision and F1score), (2) Scott Knott (SK) statistical test to select the best cluster of the outperforming architectures, and (3) borda count voting system to rank the best performing architectures. All the evaluations were over the FNAC dataset which contain 212 images. Results showed the potential of deep learning techniques to classify breast cancer in malignant and benign, therefor the findings of this study recommend the use of MobileNetV2 for the classification of the breast cancer cytological images since it gave the best results with an accuracy of
乳腺癌(BC)是全世界妇女死亡的主要原因。它仍然是一个严峻的挑战，2020年在全球造成1000多万人死亡。医学影像分析可以诊断乳腺癌等多种疾病，是最有前途的研究领域。本文对基于VGG16、VGG19、DenseNet201、InceptionResNetV2、InceptionV3、ResNet50和MobileNetV2这七种深度学习技术的精细化版本的乳腺细胞学图像二元分类的最新深度卷积神经网络(CNN)架构进行了实证评估。实证评价采用:(1)4个分类性能标准(准确率、召回率、精度和F1score)， (2) Scott Knott (SK)统计检验选择表现优异的架构的最佳聚类，(3)borda计数投票系统对表现最佳的架构进行排名。所有的评估都是在包含212张图像的FNAC数据集上进行的。结果显示深度学习技术在乳腺癌的恶性和良性分类方面的潜力，因此本研究的发现推荐使用MobileNetV2进行乳腺癌细胞学图像的分类，因为它给出了最好的结果，准确率为
{"title":"Classifying Breast Cytological Images using Deep Learning Architectures","authors":"Hasnae Zerouaoui, A. Idri","doi":"10.5220/0010850000003123","DOIUrl":"https://doi.org/10.5220/0010850000003123","url":null,"abstract":"Breast cancer (BC) is a leading cause of death among women worldwide. It remains a critical challenge, causing over 10 million deaths globally in 2020. Medical images analysis is the most promising research area since it provides facilities for diagnosing several diseases such as breast cancer. The present paper carries out an empirical evaluation of recent deep Convolutional Neural Network (CNN) architectures for a binary classification of breast cytological images based fined tuned versions of seven deep learning techniques: VGG16, VGG19, DenseNet201, InceptionResNetV2, InceptionV3, ResNet50 and MobileNetV2. The empirical evaluations used: (1) four classification performance criteria (accuracy, recall, precision and F1score), (2) Scott Knott (SK) statistical test to select the best cluster of the outperforming architectures, and (3) borda count voting system to rank the best performing architectures. All the evaluations were over the FNAC dataset which contain 212 images. Results showed the potential of deep learning techniques to classify breast cancer in malignant and benign, therefor the findings of this study recommend the use of MobileNetV2 for the classification of the breast cancer cytological images since it gave the best results with an accuracy of","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"90 1","pages":"557-564"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90714799","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 : 2022-01-01DOI: 10.5220/0010748600003123
Bushra Kundi, Dhayananth Dharmalingam, Rediet Tadesse, Alexandra Creighton, Rachel Gorman, P. Maret, Fabrice Muhlenbach, Alexis Buettgen, E. Dua, T. Mgwigwi, S. Dinca-Panaitescu, Christo El Morr
The lack of readily available disability data is a major barrier for disability advocacy globally. The collection and access to disability data is crucial to address social inequities, discrimination, and human rights violations within the disability community. The Disability Wiki project intends to use AI techniques such as Machine Learning and Semantic Web to extract and store existing disability-related data into one platform (Wikibase) and to provide a multilingual natural language enabled search engine and a screen-reader-accessible for its
{"title":"Disability Advocacy using a Smart Virtual Community","authors":"Bushra Kundi, Dhayananth Dharmalingam, Rediet Tadesse, Alexandra Creighton, Rachel Gorman, P. Maret, Fabrice Muhlenbach, Alexis Buettgen, E. Dua, T. Mgwigwi, S. Dinca-Panaitescu, Christo El Morr","doi":"10.5220/0010748600003123","DOIUrl":"https://doi.org/10.5220/0010748600003123","url":null,"abstract":"The lack of readily available disability data is a major barrier for disability advocacy globally. The collection and access to disability data is crucial to address social inequities, discrimination, and human rights violations within the disability community. The Disability Wiki project intends to use AI techniques such as Machine Learning and Semantic Web to extract and store existing disability-related data into one platform (Wikibase) and to provide a multilingual natural language enabled search engine and a screen-reader-accessible for its","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"8 1","pages":"316-319"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89219621","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 : 2022-01-01DOI: 10.5220/0010854900003123
Pedro Morais, Ana Pinheiro, M. Fonseca, Carla Quintão
{"title":"The Mindfulness Meditation Effect on States of Anxiety, Depression, Stress and Quality of Life","authors":"Pedro Morais, Ana Pinheiro, M. Fonseca, Carla Quintão","doi":"10.5220/0010854900003123","DOIUrl":"https://doi.org/10.5220/0010854900003123","url":null,"abstract":"","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"11 1","pages":"573-582"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89953454","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 : 2022-01-01DOI: 10.5220/0010742300003123
Luna El Bizri, N. Badr
Non-communicable diseases (NCDs) are still the number one killer in the world. Their economic burden is heavy, notably in low-and-middle-income countries. Lebanon is a middle-income country in the Eastern Mediterranean region. The arising COVID-19 pandemic, political and economic instability, inadequate funding, and deteriorated infrastructure have rendered the country a fragile setting, significantly affecting persons with non-communicable diseases. Improving the patient journey during the COVID-19 pandemic and a comprehensive approach to NCD management is important during emergencies.This paper used a quantitate literature review to provide a theoretical framework touching NCDs patients in their journey during emergencies and crisis. It further adopted the Sendai Framework to draw the road for these patients in Lebanon. The ultimate goal is better preparedness and response in case of emergencies and disasters. It calls for a clear and coordinated action plan addressing the challenges posed by NCDs to a resilient country's response. This paper provides an overview of the situation of NCD patients in Lebanon during the COVID19 pandemic. It suggests strategies to address noncommunicable diseases guided by the Sendai Framework's four priorities, based on previous experiences.
{"title":"Protecting Non-communicable Diseases Patients during Pandemics: Fundamental Rules for Engagement and the Case of Lebanon","authors":"Luna El Bizri, N. Badr","doi":"10.5220/0010742300003123","DOIUrl":"https://doi.org/10.5220/0010742300003123","url":null,"abstract":"Non-communicable diseases (NCDs) are still the number one killer in the world. Their economic burden is heavy, notably in low-and-middle-income countries. Lebanon is a middle-income country in the Eastern Mediterranean region. The arising COVID-19 pandemic, political and economic instability, inadequate funding, and deteriorated infrastructure have rendered the country a fragile setting, significantly affecting persons with non-communicable diseases. Improving the patient journey during the COVID-19 pandemic and a comprehensive approach to NCD management is important during emergencies.This paper used a quantitate literature review to provide a theoretical framework touching NCDs patients in their journey during emergencies and crisis. It further adopted the Sendai Framework to draw the road for these patients in Lebanon. The ultimate goal is better preparedness and response in case of emergencies and disasters. It calls for a clear and coordinated action plan addressing the challenges posed by NCDs to a resilient country's response. This paper provides an overview of the situation of NCD patients in Lebanon during the COVID19 pandemic. It suggests strategies to address noncommunicable diseases guided by the Sendai Framework's four priorities, based on previous experiences.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"74 1","pages":"306-315"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86529103","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 : 2022-01-01DOI: 10.5220/0010972300003123
A. Hausberger, B. Tappeiner, René Baranyi, T. Grechenig
: A significant part of patients who have recovered from COVID-19 has been experiencing COVID-like symptoms for weeks and months after the initial disease. These patients have been called “Long COVID patients”. Currently, guidelines are being published that inform about these symptoms and may deliver a basis for medical diagnoses. In this paper, the possibility of a Long COVID patient support app is being discussed. To gain insight into the needs and requirements of patients with Long COVID, a questionnaire was conducted with 193 participants from a self help-group in Austria. The results show that Long COVID has a profound nega-tive impact on the daily lives of people who are suffering from the disease. Also, the results show a demand for more support and indicate the role that a Long COVID symptom tracking app could play in this context. Concerning digital support, ten crucial features of a potential Long COVID support app were identified by analyzing the answers to the questionnaire. Apart from health and symptom tracking features, sharing of data with medical professionals, appointment management, and news features were considered important features to support patients suffering from Long COVID throughout their journey to get better.
{"title":"Long COVID Diary: A User Centered Approach for the Design of a Mobile Application Supporting Long COVID Patients","authors":"A. Hausberger, B. Tappeiner, René Baranyi, T. Grechenig","doi":"10.5220/0010972300003123","DOIUrl":"https://doi.org/10.5220/0010972300003123","url":null,"abstract":": A significant part of patients who have recovered from COVID-19 has been experiencing COVID-like symptoms for weeks and months after the initial disease. These patients have been called “Long COVID patients”. Currently, guidelines are being published that inform about these symptoms and may deliver a basis for medical diagnoses. In this paper, the possibility of a Long COVID patient support app is being discussed. To gain insight into the needs and requirements of patients with Long COVID, a questionnaire was conducted with 193 participants from a self help-group in Austria. The results show that Long COVID has a profound nega-tive impact on the daily lives of people who are suffering from the disease. Also, the results show a demand for more support and indicate the role that a Long COVID symptom tracking app could play in this context. Concerning digital support, ten crucial features of a potential Long COVID support app were identified by analyzing the answers to the questionnaire. Apart from health and symptom tracking features, sharing of data with medical professionals, appointment management, and news features were considered important features to support patients suffering from Long COVID throughout their journey to get better.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"47 1","pages":"769-776"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91350117","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 : 2022-01-01DOI: 10.5220/0010933900003123
S. Zarshenas, N. Bier, H. Pigot, S. Giroux, P. Semeniuk, M. Couture, C. Bottari
: In response to the long-lasting effects of cognitive impairments following acquired brain injury (ABI) on performing meal preparation safely and independently, our team has been working on developing a Cognitive Orthosis for coOKing (COOK) to meet these needs. In this paper, the concept mapping method was used to describe the processes and procedures of employing a user-centred design approach to develop this novel technology. For this purpose, a mixed methodology including qualitative and quantitative studies was conducted for needs analysis, prototype design, prototype evaluation, and technology validation via the examination of the usability and feasibility of COOK within real-life contexts. Our comprehensive studies have shown that COOK is a promising technology for meal preparation by individuals with severe ABI. Further study is warranted/in progress to develop a therapist’s interface to tailor the required type and level of assistance to a broader population with cognitive deficits of varying severity.
{"title":"An Assistive Technology for Cognition to Support Meal Preparation: The Concept Map of a User-centred Design Process and Procedure","authors":"S. Zarshenas, N. Bier, H. Pigot, S. Giroux, P. Semeniuk, M. Couture, C. Bottari","doi":"10.5220/0010933900003123","DOIUrl":"https://doi.org/10.5220/0010933900003123","url":null,"abstract":": In response to the long-lasting effects of cognitive impairments following acquired brain injury (ABI) on performing meal preparation safely and independently, our team has been working on developing a Cognitive Orthosis for coOKing (COOK) to meet these needs. In this paper, the concept mapping method was used to describe the processes and procedures of employing a user-centred design approach to develop this novel technology. For this purpose, a mixed methodology including qualitative and quantitative studies was conducted for needs analysis, prototype design, prototype evaluation, and technology validation via the examination of the usability and feasibility of COOK within real-life contexts. Our comprehensive studies have shown that COOK is a promising technology for meal preparation by individuals with severe ABI. Further study is warranted/in progress to develop a therapist’s interface to tailor the required type and level of assistance to a broader population with cognitive deficits of varying severity.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"98 1","pages":"921-928"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73204258","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 : 2022-01-01DOI: 10.5220/0010937000003123
Hui Liu, Yale Hartmann, Tanja Schultz
: Many researchers devote themselves to studying various aspects of Human Activity Recognition (HAR), such as data analysis, signal processing, feature extraction, and machine learning models. In response to the fact that few documents summarize and form intuitive paradigms for the entire HAR research pipeline, based on the purpose of sharing our years of research experience, we propose a practical, comprehensive HAR research pipeline, called HAR-Pipeline, composed of nine research aspects, aiming to reflect the overall perspective of HAR research topics to the greatest extent and indicate the sequence and relationship between the tasks. Supplemented by the outcomes of our actual series of studies as examples, we demonstrate the proposed pipeline’s rationality and feasibility.
{"title":"A Practical Wearable Sensor-based Human Activity Recognition Research Pipeline","authors":"Hui Liu, Yale Hartmann, Tanja Schultz","doi":"10.5220/0010937000003123","DOIUrl":"https://doi.org/10.5220/0010937000003123","url":null,"abstract":": Many researchers devote themselves to studying various aspects of Human Activity Recognition (HAR), such as data analysis, signal processing, feature extraction, and machine learning models. In response to the fact that few documents summarize and form intuitive paradigms for the entire HAR research pipeline, based on the purpose of sharing our years of research experience, we propose a practical, comprehensive HAR research pipeline, called HAR-Pipeline, composed of nine research aspects, aiming to reflect the overall perspective of HAR research topics to the greatest extent and indicate the sequence and relationship between the tasks. Supplemented by the outcomes of our actual series of studies as examples, we demonstrate the proposed pipeline’s rationality and feasibility.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"74 1","pages":"847-856"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74363848","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 : 2022-01-01DOI: 10.5220/0010846100003123
A. Mainz, S. Meister
One of the most common neurodegenerative disorders that affects more and more people at an advanced age is Parkinson’s disease. Patients suffer from various symptoms and especially the motor restrictions and psychological symptoms worsen the quality of life of the affected persons. The physical therapy for this disease to improve motor performance and complementary exercises is characterised by repetitive training and patients often suffer from a strong exhaustion and lack of motivation due to their disease. To address these problems, a serious game concept for Parkinson's therapy was developed. The concept was created using the Design Thinking methodology for a user-centred design. The final result is the concept and prototype of a competitive multiplayer exergame that was developed to increase the motivation of the patients to participate through social play and the idea of competition in order to support the motor therapy of Parkinson’s disease
{"title":"A Digital, Game-based Application to Support Treatment of Parkinson's Disease: A Design Thinking Approach","authors":"A. Mainz, S. Meister","doi":"10.5220/0010846100003123","DOIUrl":"https://doi.org/10.5220/0010846100003123","url":null,"abstract":"One of the most common neurodegenerative disorders that affects more and more people at an advanced age is Parkinson’s disease. Patients suffer from various symptoms and especially the motor restrictions and psychological symptoms worsen the quality of life of the affected persons. The physical therapy for this disease to improve motor performance and complementary exercises is characterised by repetitive training and patients often suffer from a strong exhaustion and lack of motivation due to their disease. To address these problems, a serious game concept for Parkinson's therapy was developed. The concept was created using the Design Thinking methodology for a user-centred design. The final result is the concept and prototype of a competitive multiplayer exergame that was developed to increase the motivation of the patients to participate through social play and the idea of competition in order to support the motor therapy of Parkinson’s disease","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"40 1","pages":"125-134"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88319852","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 : 2022-01-01DOI: 10.5220/0010912600003123
Mirco Baseniak, Tom Lorenz, Ina Schiering
mHealth applications including fitness apps are an important trend. To monitor fitness activities a broad range of personal data is processed typically including location data and vital signs. For some of these applications it is not transparent which data is processed. To foster transparency and intervenability in mobile applications the concept of privacy notifications is an opportunity to provide users with information about processed data during the use of the application. In the context of a fitness app a concept for privacy notifications is proposed and evaluated in a user study.
{"title":"Privacy Notifications for Transparency in Fitness Apps","authors":"Mirco Baseniak, Tom Lorenz, Ina Schiering","doi":"10.5220/0010912600003123","DOIUrl":"https://doi.org/10.5220/0010912600003123","url":null,"abstract":"mHealth applications including fitness apps are an important trend. To monitor fitness activities a broad range of personal data is processed typically including location data and vital signs. For some of these applications it is not transparent which data is processed. To foster transparency and intervenability in mobile applications the concept of privacy notifications is an opportunity to provide users with information about processed data during the use of the application. In the context of a fitness app a concept for privacy notifications is proposed and evaluated in a user study.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"4 1","pages":"705-710"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83663304","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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