Lars Dittmann

BACKGROUND Background: Atrial fibrillation (AF) is a growing global health challenge associated with substantial morbidity, reduced quality of life, and increased healthcare utilization. Digital health technologies applied to telerehabilitation have shown the potential to support individuals’ engagement and enhanced self‑management during rehabilitation. However, little is known about how individuals with AF use digital platforms in real‑world settings, and log‑file analyses remain underexplored. OBJECTIVE Objective: This study aimed to elucidate how individuals with AF engaged with a digital connection to the healthcare system. This connection was provided through the HeartPortal, a web based platform offering clinically validated educational material, access to patient reported and device generated health data, and secure communication channels that support coordination of rehabilitation activities. The study examined how participants accessed educational materials, reviewed their personal health data, and communicated with healthcare professionals throughout a 28 week telerehabilitation program. METHODS Methods: This study analyzed log file data from 101 participants enrolled in the intervention group of the Future Patient—Telerehabilitation of Patients with AF (FP AF) randomized controlled trial. Log data was generated through participants’ use of the HeartPortal. Log data included timestamps for page visits, messaging activity, video consultations, and patients’ written narratives of goals and notes. Descriptive statistics were generated using Python to quantify usage patterns across features, weekly activity levels, and temporal trends. An additional analysis examined how activity was distributed across participants, assessing whether HeartPortal visits and messaging activity were driven by a small subset of highly active users or more evenly shared across the cohort. Data was supplemented with system level information on healthcare professional activity. RESULTS Results: HeartPortal use peaked during the first 17 weeks, when over 80% of participants accessed the platform weekly, and decreased after monitoring equipment was returned. Activity in the most frequently used sections varied markedly, with the most active 25% maintaining higher engagement throughout the intervention. Participants sent 1,167 messages and healthcare professionals sent 1,705, with messaging peaking in week 6. CONCLUSIONS Conclusions: The HeartPortal was primarily used for reviewing personal health data and communicating with healthcare professionals, indicating that digital platforms can support self management in AF telerehabilitation. Limited engagement with educational content may reflect patients’ existing knowledge at baseline or a need to refine digital learning components to better match users’ needs. These findings demonstrate the value of log file analysis for understanding real world behaviour and point to future research on how digital platforms can sustain engagement and enhance patient education. CLINICALTRIAL Name: Future Patient - Telerehabilitation of Atrial Fibrillation Patients ClinicalTrials.gov (NCT04493437) URL: https://clinicaltrials.gov/study/NCT04493437 INTERNATIONAL REGISTERED REPORT RR2-10.2196/64259

Background: Atrial fibrillation (AF) is a prevalent chronic condition with increasing incidence worldwide. AF increases the risks of stroke, heart failure, and myocardial infarction and imposes a substantial burden on the health care system. Cardiac rehabilitation programs, while effective, often have low patient adherence. Recent evidence suggests that cardiac telerehabilitation, where patients are given home monitoring devices, could enhance adherence and outcomes. The program “Future Patient—Telerehabilitation of Patients with AF” (FP-AF) was created to assess the effects and potential benefits of cardiac telerehabilitation on patients with AF. Objective: The objective of this study is to explore the experiences of patients participating in the FP-AF program. Methods: This qualitative sub-study is part of the multicenter, randomized controlled FP-AF trial, which included 208 patients. Semi-structured interviews were conducted on 14 patients, randomly selected from participants in the intervention arm of the FP-AF program. The patient interviews, guided by self-determination theory, focused on patients’ experiences with the FP-AF program, including the use of telerehabilitation technologies and a web-based portal called the “HeartPortal.” Interview responses were analyzed using NVivo software (version 14.0; QSR International), with thematic coding based on interview guides and methodological guidance elaborated by Brinkmann & Kvale. The study adhered to ethical guidelines, with informed consent obtained from all participants. Results: Based on the interviews, the following themes were identified: the home monitoring devices are viewed positively by the patients; the HeartPortal is a useful digital toolbox; patients develop new coping strategies for living with AF; the measured values are useful for the patients; the community of practice is beneficial; and the FP-AF program creates a sense of security. Conclusions: Participation in the FP-AF program enhanced patients’ sense of security, empowerment, and knowledge about AF. This improvement was due largely to a combination of patients’ use of the HeartPortal and the educational sessions at health care centers. Telerehabilitation for patients with AF may be a useful way of researching this group of patients with a focus on rehabilitation and may be an effective means of offering rehabilitation to this group in the future.

The increasing demand for enhanced communication systems, driven by applications such as real-time video streaming, online gaming, critical operations, and Internet-of-Things (IoT) services, has necessitated the optimization of cellular networks to meet evolving requirements while addressing power consumption challenges. In this context, various initiatives undertaken by industry, academia, and researchers to reduce the power consumption of cellular network systems are comprehensively reviewed. Particular attention is given to emerging technologies, including Software-Defined Networking (SDN), Network Function Virtualization (NFV), and Cloud-Radio Access Network (C-RAN), which are identified as key enablers for reshaping cellular infrastructure. Their collective potential to enhance energy efficiency while addressing convergence challenges is analyzed, and solutions for sustainable network evolution are proposed. A conceptual architecture based on SDN, NFV, and C-RAN is presented as an illustrative example of integrating these technologies to achieve significant power savings. The proposed framework outlines an approach to developing energy-efficient cellular networks, capable of reducing power consumption by approximately 40 to 50% through the optimal placement of virtual network functions.

The rapid advancement of technology has led to an increasing demand for enhanced communication systems, particularly in the realm of cellular networks. With diverse applications such as real-time video streaming, online gaming, critical operations, and Internet-of-Things (IoT) services relying more on cellular connectivity, optimizing the cellular networks to meet evolving requirements while mitigating the associated power consumption challenges is crucial. This paper provides a comprehensive overview of initiatives undertaken by industry, academia, and researchers to reduce the power consumption of cellular network systems. Special emphasis is placed on emerging technologies like Software-Defined Networking (SDN), Network Function Virtualization (NFV), and Cloud-Radio Access Network (C-RAN), which hold promise for reshaping cellular infrastructure. Additionally, the paper delves into the convergence challenges and solutions associated with SDN, NFV, and C-RAN. The paper proposes a novel cellular architecture grounded in SDN, NFV, and C-RAN paradigms. This proposed framework offers a blueprint for developing energy-efficient cellular networks capable of meeting the diverse demands of modern communication applications and able to reduce power consumption by approximately 40% to 50% with careful placement of virtual network functions.

Background: Atrial fibrillation (AF) is a chronic cardiovascular condition with a lifetime risk of 1 in 3 and a prevalence of 3% among adults. AF’s prevalence is predicted to more than double during the next 20 years due to better detection, increasing comorbidities, and an aging population. Due to increased AF prevalence, telerehabilitation has been developed to enhance patient engagement, health care accessibility, and compliance through digital technologies. A telerehabilitation program called “Future Patient—telerehabilitation of patients with AF (FP-AF)” has been developed to enhance rehabilitation for AF. The FP-AF program comprises two modules: (1) an education and monitoring module using telerehabilitation technologies (4 months) and (2) a follow-up module, where patients can measure steps and access a data and knowledge-sharing portal, HeartPortal, using their digital devices. Those patients in the FP-AF program measure their heart rhythm, pulse, blood pressure, weight, steps, and sleep. Patients also complete web-based questionnaires regarding their well-being and coping with AF. All recorded data are transmitted to the HeartPortal, accessible to patients, relatives, and health care professionals. Objective: This paper aims to describe the research design, outcome measures, and data collection techniques in a clinical trial of the FP-AF program for patients with AF. Methods: This is a multicenter, mixed methods, randomized controlled trial. Patients are recruited from AF clinics serving the North Jutland region of Denmark. The telerehabilitation group will participate in the FP-AF program, while the control group will follow the conventional care regime based on physical visits to the AF clinic. The primary outcome measure is AF-specific health-related quality of life, to be assessed using the Atrial Fibrillation Effect on Quality-of-Life Questionnaire. Secondary outcomes are knowledge of AF; measurement of vital parameters; level of anxiety and depression; degree of motivation; burden of AF; use of the HeartPortal; qualitative exploration of patients’, relatives’, and health care professionals’ experiences of participating in the FP-AF program; cost-effectiveness evaluation of the program; and analysis of multiparametric monitoring data. Outcomes are assessed through data from digital technologies, interviews, and questionnaires. Results: Patient enrollment began in January 2023 and will be completed by December 2024, with a total of 208 patients enrolled. Qualitative interviews conducted in spring 2024 will be analyzed and published in peer-reviewed journals in 2025. Data from questionnaires and digital technologies will be analyzed upon study completion and presented at international conferences and published in peer-reviewed journals by the fall of 2025. Conclusions: Results from the FP-AF study will determine whether the FP-AF program can increase quality of life for patients with AF and increase their knowledge of symptoms and living with AF in everyday life compared to conventional AF care. The cost-effectiveness evaluation will determine whether telerehabilitation can be a viable alternative for rehabilitation of patients with AF. Trial Registration: ClinicalTrials.gov NCT06101485; https://clinicaltrials.gov/study/NCT06101485 International Registered Report Identifier (IRRID): DERR1-10.2196/64259

The expanding use of Internet-of-Things (IoT) has driven machine learning (ML)-based traffic analysis. 5G networks’ standards, requiring low-latency communications for time-critical services, pose new challenges to traffic analysis. They necessitate fast analysis and response, preventing service disruption or security impact on network infrastructure. Distributed intelligence on IoT edge has been studied to analyze traffic, but introduces delays and raises privacy concerns. Federated learning can address privacy concerns, but does not meet latency requirements. In this article, we propose FLIP4: an efficient federated learning-based framework for in-network traffic analysis. Our solution introduces a lightweight federated tree-based model, offloaded and running within network devices. FLIP4 consumes less resources than previous solutions and reduces communication overheads, making it well-suited for IoT edge traffic analysis. It ensures prompt mitigation and minimal impact on services in the presence of false alerts using two approaches (metering and dropping), thereby balancing learning accuracy and privacy requirements.

BACKGROUND Atrial fibrillation (AF) is a prevalent chronic condition with increasing incidence worldwide. AF increases the risks of stroke, heart failure, and myocardial infarction and imposes a substantial burden on the healthcare system. Cardiac rehabilitation programs, while effective, often suffer from low patient adherence. Recent evidence suggests that cardiac telerehabilitation, where patients are given home monitoring devices, could enhance adherence and outcomes. The program ‘Future Patient – Telerehabilitation of patients with AF’ (FP-AF) was created to assess the effects and potential benefits of cardiac telerehabilitation on AF patients. This study explores patient experiences with the FP-AF program. OBJECTIVE To explore the experiences of patients participating in the FP-AF program. METHODS This qualitative sub-study is part of the multicenter, randomized controlled FP-AF trial, which included 208 patients. Semi-structured interviews were conducted on 14 patients, randomly selected from participants in the intervention arm of the FP-AF program. The patient interviews, guided by self-determination theory, focused on patients' experiences with the FP-AF program, including the use of telerehabilitation technologies and an interactive web portal called the ‘HeartPortal’. Interview responses were analyzed using NVivo software, with thematic coding based on interview guides and methodological guidance elaborated by Brinkmann & Kvale. The study adhered to ethical guidelines, with informed consent obtained from all participants. RESULTS Based on the interviews, the following themes were identified: The home monitoring devices are viewed positively by the patients, the HeartPortal is a useful digital toolbox, patients develop new coping strategies for living with AF, the measured values are useful for the patients, the community of practice is beneficial, the FP-AF program creates a sense of security. CONCLUSIONS Patients’ participation in the FP-AF program enhanced their sense of security, empowerment, and knowledge about AF. This improvement was largely due to a combination of patients’ use of the HeartPortal and the educational sessions held at the healthcare centers. Telerehabilitation for patients with AF has the potential to be an effective means of offering rehabilitation to this group in the future. CLINICALTRIAL The FP-AF study is listed in ClinicalTrials.gov (NCT06101485) INTERNATIONAL REGISTERED REPORT RR2-10.2196/64259

BACKGROUND Atrial fibrillation (AF) is a chronic cardiovascular condition with a lifetime risk of 1 in 3 and a prevalence of 3% among adults. AF’s prevalence is predicted to more than double during the next 20 years due to better detection, increasing comorbidities, and an aging population. Due to increased AF prevalence, telerehabilitation has been developed to enhance patient engagement, health care accessibility, and compliance through digital technologies. A telerehabilitation program called “Future Patient—telerehabilitation of patients with AF (FP-AF)” has been developed to enhance rehabilitation for AF. The FP-AF program comprises two modules: (1) an education and monitoring module using telerehabilitation technologies (4 months) and (2) a follow-up module, where patients can measure steps and access a data and knowledge-sharing portal, HeartPortal, using their digital devices. Those patients in the FP-AF program measure their heart rhythm, pulse, blood pressure, weight, steps, and sleep. Patients also complete web-based questionnaires regarding their well-being and coping with AF. All recorded data are transmitted to the HeartPortal, accessible to patients, relatives, and health care professionals. OBJECTIVE This paper aims to describe the research design, outcome measures, and data collection techniques in a clinical trial of the FP-AF program for patients with AF. METHODS This is a multicenter, mixed methods, randomized controlled trial. Patients are recruited from AF clinics serving the North Jutland region of Denmark. The telerehabilitation group will participate in the FP-AF program, while the control group will follow the conventional care regime based on physical visits to the AF clinic. The primary outcome measure is AF-specific health-related quality of life, to be assessed using the Atrial Fibrillation Effect on Quality-of-Life Questionnaire. Secondary outcomes are knowledge of AF; measurement of vital parameters; level of anxiety and depression; degree of motivation; burden of AF; use of the HeartPortal; qualitative exploration of patients’, relatives’, and health care professionals’ experiences of participating in the FP-AF program; cost-effectiveness evaluation of the program; and analysis of multiparametric monitoring data. Outcomes are assessed through data from digital technologies, interviews, and questionnaires. RESULTS Patient enrollment began in January 2023 and will be completed by December 2024, with a total of 208 patients enrolled. Qualitative interviews conducted in spring 2024 will be analyzed and published in peer-reviewed journals in 2025. Data from questionnaires and digital technologies will be analyzed upon study completion and presented at international conferences and published in peer-reviewed journals by the fall of 2025. CONCLUSIONS Results from the FP-AF study will determine whether the FP-AF program can increase quality of life for patients with AF and increase their knowledge of symptoms and living with AF in everyday life compared to conventional AF care. The cost-effectiveness evaluation will determine whether telerehabilitation can be a viable alternative for rehabilitation of patients with AF. CLINICALTRIAL ClinicalTrials.gov NCT06101485; https://clinicaltrials.gov/study/NCT06101485 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/64259

In the near future, there will be a greater emphasis on sharing network resources between roads and railways to improve transportation efficiency and reduce infrastructure costs. This could enable the development of global Cooperative Intelligent Transport Systems (C-ITSs). In this paper, a software-defined networking (SDN)-based common emergency service is developed and validated for a railway and road telecommunication shared infrastructure. Along with this, the developed application is capable of reducing the chances of distributed denial-of-service (DDoS) situations. A level-crossing scenario is considered to demonstrate the developed solution where railway tracks are perpendicular to the roads. Two cases are considered to validate and analyze the developed SDN application for common emergency scenarios. In case 1, no cross-communication is available between the road and railway domains. In this case, emergency message distribution is carried out by the assigned emergency servers with the help of the SDN controller. In case 2, nodes (cars and trains) are defined with two wireless interfaces, and one interface is reserved for emergency data communication. To add the DDoS resiliency to the developed system the messaging behavior of each node is observed and if an abnormality is detected, packets are dropped to avoid malicious activity.

The widespread use of IoT devices has unveiled overlooked security risks. With the advent of ultrareliable low-latency communications (URLLCs) in 5G, fast threat defense is critical to minimize damage from attacks. IoT gateways, equipped with wireless/wired interfaces, serve as vital frontline defense against emerging threats on IoT edge. However, current gateways struggle with dynamic IoT traffic and have limited defense capabilities against attacks with changing patterns. In-network computing offers fast machine learning (ML)-based attack detection and mitigation within network devices, but leveraging its capability in IoT gateways requires new continuous learning capability and runtime model updates. In this work, we present P4Pir, a novel in-network traffic analysis framework for IoT gateways. P4Pir incorporates programmable data plane into IoT gateway, pioneering the utilization of in-network ML inference for fast mitigation. It facilitates continuous and seamless updates of in-network inference models within gateways. P4Pir is prototyped in P4 language on raspberry pi and Dell Edge Gateway. With ML inference offloaded to gateway’s data plane, P4Pir’s in-network approach achieves swift attack mitigation and lightweight deployment compared to prior ML-based solutions. Evaluation results using three public data sets show that P4Pir accurately detects and fastly mitigates emerging attacks (>30% accuracy improvement and submillisecond mitigation time). The proposed model updates method allows seamless runtime updates without disrupting network traffic.