0000000000419360
AUTHOR
Ayan Chatterjee
showing 25 related works from this author
Algorithm To Calculate Heart Rate By Removing Touch Errors And Algorithm Analysis
2018
Heart rate is one of the important physiological parameter to measure the stability of the health. This study shows analysis of a proposed algorithm to calculate heart rate with miss touch errors to make it more efficient. Android Smart phone with good quality camera has come to reach of common people and has become one of the most necessary and powerful device for today and of course, for future generation. We can use its powerful features to solve or assess heart state monitoring through capturing necessary data in the form of image. Mobile camera has a photo emitting diode and a photo detector. Light source illuminates the tissue and photo-detector calculates the small intensity variatio…
ProHealth eCoach: user-centered design and development of an eCoach app to promote healthy lifestyle with personalized activity recommendations
2022
Abstract Background Regular physical activity (PA), healthy habits, and an appropriate diet are recommended guidelines to maintain a healthy lifestyle. A healthy lifestyle can help to avoid chronic diseases and long-term illnesses. A monitoring and automatic personalized lifestyle recommendation system (i.e., automatic electronic coach or eCoach) with considering clinical and ethical guidelines, individual health status, condition, and preferences may successfully help participants to follow recommendations to maintain a healthy lifestyle. As a prerequisite for the prototype design of such a helpful eCoach system, it is essential to involve the end-users and subject-matter experts throughou…
A Comparative Study to Analyze the Performance of Advanced Pattern Recognition Algorithms for Multi-Class Classification
2021
This study aims to implement the following four advanced pattern recognition algorithms, such as “optimal Bayesian classifier,” “anti-Bayesian classifier,” “decision trees (DTs),” and “dependence trees (DepTs)” on both artificial and real datasets for multi-class classification. Then, we calculated the performance of individual algorithms on both real and artificial data for comparison. In Sect. 1, a brief introduction is given about the study. In the second section, the different types of datasets used in this study are discussed. In the third section, we compared the classification accuracies of Bayesian and anti-Bayesian methods for both the artificial and real-life datasets. In the four…
Human Coaching Methodologies for Automatic Electronic Coaching (eCoaching) as Behavioral Interventions With Information and Communication Technology:…
2021
Background We systematically reviewed the literature on human coaching to identify different coaching processes as behavioral interventions and methods within those processes. We then reviewed how those identified coaching processes and the used methods can be utilized to improve an electronic coaching (eCoaching) process for the promotion of a healthy lifestyle with the support of information and communication technology (ICT). Objective This study aimed to identify coaching and eCoaching processes as behavioral interventions and the methods behind these processes. Here, we mainly looked at processes (and corresponding models that describe coaching as certain processes) and the methods th…
An Automatic Ontology-Based Approach to Support Logical Representation of Observable and Measurable Data for Healthy Lifestyle Management: Proof-of-C…
2020
Background Lifestyle diseases, because of adverse health behavior, are the foremost cause of death worldwide. An eCoach system may encourage individuals to lead a healthy lifestyle with early health risk prediction, personalized recommendation generation, and goal evaluation. Such an eCoach system needs to collect and transform distributed heterogenous health and wellness data into meaningful information to train an artificially intelligent health risk prediction model. However, it may produce a data compatibility dilemma. Our proposed eHealth ontology can increase interoperability between different heterogeneous networks, provide situation awareness, help in data integration, and discover…
HL7 FHIR with SNOMED-CT to Achieve Semantic and Structural Interoperability in Personal Health Data: A Proof-of-Concept Study
2022
Heterogeneity is a problem in storing and exchanging data in a digital health information system (HIS) following semantic and structural integrity. The existing literature shows different methods to overcome this problem. Fast healthcare interoperable resources (FHIR) as a structural standard may explain other information models, (e.g., personal, physiological, and behavioral data from heterogeneous sources, such as activity sensors, questionnaires, and interviews) with semantic vocabularies, (e.g., Systematized Nomenclature of Medicine—Clinical Terms (SNOMED-CT)) to connect personal health data to an electronic health record (EHR). We design and develop an intuitive health coaching (eCoach…
SFTSDH: Applying Spring Security Framework with TSD-Based OAuth2 to Protect Microservice Architecture APIs
2022
The Internet of Medical Things (IoMT) combines medical devices and applications that use network technologies to connect healthcare information systems (HIS). IoMT is reforming the medical industry by adopting information and communication technologies (ICTs). Identity verification, secure collection, and exchange of medical data are essential in health applications. In this study, we implemented a hybrid security solution to secure the collection and management of personal health data using Spring Framework (SF), Services for Sensitive Data (TSD) as a service platform, and Hyper-Text-Transfer-Protocol (HTTP (H)) security methods. The adopted solution (SFTSDH = SF + TSD + H) instigated the …
Leveraging technology for healthcare and retaining access to personal health data to enhance personal health and well-being
2021
Abstract Health data are a sensitive category of personal data. They can result in a high risk to individuals and health information-handling rights and opportunities unless there is a sufficient defense. Reasonable security standards are needed to protect electronic health records (EHRs). All personal data handling needs adequate explanation. Maintaining access to medical data, even in the developing world, would favor health and well-being across the world. Unfortunately, there are still countries that hinder the portability of medical records. Numerous occurrences have shown that it still takes weeks for medical data to be ported from one general physician to another. Cross-border portab…
eHealth Initiatives for The Promotion of Healthy Lifestyle and Allied Implementation Difficulties
2019
Research in eHealth has opened a new dimension to improve personal healthcare with the help of information and communication technologies (ICT). eHealth is an ‘umbrella term’ for the use of ICT for health. Remote care-giving technologies (mHealth, Telehealth, Telemedicine) are an extended branch of eHealth initiatives. The concept of health e- Coaching is another promising initiative of eHealth research for real-time personalized lifestyle support. The focus of eHealth initiatives is to deliver high quality, evidence-based, secure, cost- effective, timely care to support people for sustaining a healthy lifestyle. However, the practical implementation of different eHealth initiatives has oft…
Identification of Risk Factors Associated with Obesity and Overweight-A Machine Learning Overview.
2020
Social determining factors such as the adverse influence of globalization, supermarket growth, fast unplanned urbanization, sedentary lifestyle, economy, and social position slowly develop behavioral risk factors in humans. Behavioral risk factors such as unhealthy habits, improper diet, and physical inactivity lead to physiological risks, and &ldquo
Personalized Recommendations for Physical Activity e-Coaching (OntoRecoModel): Ontological Modeling.
2021
Background Automatic e-coaching may motivate individuals to lead a healthy lifestyle with early health risk prediction, personalized recommendation generation, and goal evaluation. Multiple studies have reported on uninterrupted and automatic monitoring of behavioral aspects (such as sedentary time, amount, and type of physical activity); however, e-coaching and personalized feedback techniques are still in a nascent stage. Current intelligent coaching strategies are mostly based on the handcrafted string messages that rarely individualize to each user’s needs, context, and preferences. Therefore, more realistic, flexible, practical, sophisticated, and engaging strategies are needed to mod…
Digital interventions on healthy lifestyle management: Systematic review
2021
Background Digital interventions have tremendous potential to improve well-being and health care conveyance by improving adequacy, proficiency, availability, and personalization. They have gained acknowledgment in interventions for the management of a healthy lifestyle. Therefore, we are reviewing existing conceptual frameworks, digital intervention approaches, and associated methods to identify the impact of digital intervention on adopting a healthier lifestyle. Objective This study aims to evaluate the impact of digital interventions on weight management in maintaining a healthy lifestyle (eg, regular physical activity, healthy habits, and proper dietary patterns). Methods We conducted …
A Statistical Study to Analyze the Impact of External Weather Change on Chronic Pulmonary Infection in South Norway with Machine Learning Algorithms
2021
In this paper, we analyzed the holistic impact of external weather on chronic pulmonary infection in the Agder region with traditional machine learning algorithms. Millions of people are diagnosed with Chronic Obstructive Pulmonary Disease (COPD). Our study is dedicated in the Agder region, the Southern part of Norway. Norway has four seasons – winter (December-February), late winter/spring (March-May), Summer (June-August), and Autumn (September-November) in a year with average annual temperature approx. 7.5 °C | 45.5 °F and an annual rainfall of 1260 mm or 49.6 in. in Kristiansand. As predicted by the World Health Organization (WHO), in 2016, Norway suffered from 8% mortality due to c(1)h…
Calculate Pulse from Touch Error Free PPG Signal with 2ndOrder Butterworth Filter
2021
With the ongoing heart problems of the population worldwide, the medical requirements of the people are expected to increase. Electrocardiogram (ECG) is one of the proven to capture the heart response signal to assess the electrical and muscular functions of the heart. The ECG setup is expensive and needs proper training, and of course, it is not instant. For fast, accurate heart parameter monitoring, scientists pay attention to the photoplethysmogram signal (PPG), based on the light intensity of a particular wavelength. Android smartphone with a good quality camera has come to ordinary people's reach and has become one of the most necessary and rugged devices for today and future generatio…
Applying Spring Security Framework with KeyCloak-Based OAuth2 to Protect Microservice Architecture APIs: A Case Study
2022
In this study, we implemented an integrated security solution with Spring Security and Keycloak open-access platform (SSK) to secure data collection and exchange over microservice architecture application programming interfaces (APIs). The adopted solution implemented the following security features: open authorization, multi-factor authentication, identity brokering, and user management to safeguard microservice APIs. Then, we extended the security solution with a virtual private network (VPN), Blowfish and crypt (Bcrypt) hash, encryption method, API key, network firewall, and secure socket layer (SSL) to build up a digital infrastructure. To accomplish and describe the adopted SSK solutio…
Statistical Explorations and Univariate Timeseries Analysis on COVID-19 Datasets to Understand the Trend of Disease Spreading and Death
2020
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Comparing Performance of Ensemble-Based Machine Learning Algorithms to Identify Potential Obesity Risk Factors from Public Health Datasets
2021
Societal factors such as globalization, supermarket growth, rapid unplanned urbanization, sedentary lifestyle, economical distribution, and social position gradually develop behavioral risk factors in humans. Behavioral risk factors are unhealthy habits (consumption of tobacco and alcohol), improper diet (consumption of high calorific discretionary fast foods, sweet beverages), and physical inactivity. The behavioral risks may lead to physiological risks, body–energy imbalance. Obesity is one of the foremost lifestyle diseases that leads to other health conditions, such as cardiovascular disease (CVDs), chronic obstructive pulmonary disease (COPD), cancer, diabetes type II, hypertension, an…
A Proposed Access Control-Based Privacy Preservation Model to Share Healthcare Data in Cloud
2020
Healthcare data in cloud computing facilitates the treatment of patients efficiently by sharing information about personal health data between the healthcare providers for medical consultation. Furthermore, retaining the confidentiality of data and patients' identity is a another challenging task. This paper presents the concept of an access control-based (AC) privacy preservation model for the mutual authentication of users and data owners in the proposed digital system. The proposed model offers a high-security guarantee and high efficiency. The proposed digital system consists of four different entities, user, data owner, cloud server, and key generation center (KGC). This approach makes…
Additional file 1 of ProHealth eCoach: user-centered design and development of an eCoach app to promote healthy lifestyle with personalized activity …
2022
Additional file 1. StaRI checklist for completion.
Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation.
2022
AbstractLeading a sedentary lifestyle may cause numerous health problems. Therefore, passive lifestyle changes should be given priority to avoid severe long-term damage. Automatic health coaching system may help people manage a healthy lifestyle with continuous health state monitoring and personalized recommendation generation with machine learning (ML). This study proposes a semantic ontology model to annotate the ML-prediction outcomes and personal preferences to conceptualize personalized recommendation generation with a hybrid approach. We use a transfer learning approach to improve ML model training and its performance, and an incremental learning approach to handle daily growing data …
Leveraging Technology for Healthcare and Retaining Access to Personal Health Data to Enhance Personal Health and Well-being
2020
Health data is a sensitive category of personal data. It might result in a high risk to individual and health information handling rights and opportunities unless there is a palatable defense. Reasonable security standards are needed to protect electronic health records (EHR). All personal data handling needs adequate explanation. Maintaining access to medical data even in the developing world would favor health and well-being across the world. Unfortunately, there are still countries that hinder the portability of medical records. Numerous occurrences have shown that it still takes weeks for the medical data to be ported from one general physician (GP) to another. Cross border portability …
Additional file 2 of ProHealth eCoach: user-centered design and development of an eCoach app to promote healthy lifestyle with personalized activity …
2022
Additional file 2. The outcome of the focus group discussion for RQ-1 in Workshop 1.
Additional file 3 of ProHealth eCoach: user-centered design and development of an eCoach app to promote healthy lifestyle with personalized activity …
2022
Additional file 3. The outcome of the focus group discussion for RQ-2 in Workshop 1.
Additional file 5 of ProHealth eCoach: user-centered design and development of an eCoach app to promote healthy lifestyle with personalized activity …
2022
Additional file 5. The outcome of the focus group discussion for RQ-4 in Workshop 1.
Additional file 4 of ProHealth eCoach: user-centered design and development of an eCoach app to promote healthy lifestyle with personalized activity …
2022
Additional file 4. The outcome of the focus group discussion for RQ-3 in Workshop 1.