Dataset for damage detection retrieved from a monitored bridge pre and post verified damage.

The Vänersborg Bridge in southwest Sweden is a single-leaf bascule bridge carrying railway traffic over a canal. The load consists of passing commuter trains, occasional freight trains and leaf openings to allow ships to pass on the canal. The bridge constructed from 1914 to 1916 was built by riveted truss members in steel. Over the years, several assessments and maintenance actions have been performed to keep the bridge in service. During autumn 2021, a long-term monitoring campaign was initiated with the installation of sensors to register the load effect and possible changes in the behaviour. In March 2023, the cloud-based service employed detected an abrupt change of behaviour. An emergency inspection revealed a large crack in one of the truss members in the counter-weight part. The published dataset contains sensor data from 64 registered bridge openings, comprising accelerations, strains, inclinations, and weather conditions. Data from before the fracture, during, and after are provided. During the bridge opening events, the data was recorded continuously with a sampling rate of 200 Hz. The evidence of damage in a real case scenario makes the dataset valuable for testing and evaluation of data-driven routines for infrastructure surveillance.

The PICASO cloud platform for improved holistic care in rheumatoid arthritis treatment-experiences of patients and clinicians.

BACKGROUND: Multimorbidity raises the number of essential information needed for delivery of high-quality care in patients with chronic diseases like rheumatoid arthritis (RA). We evaluated an innovative ICT platform for integrated care which orchestrates data from various health care providers to optimize care management processes. METHODS: The Horizon2020-funded research project PICASO (picaso-project.eu) established an ICT platform that offers integration of care services across providers and supports patients' management along the continuum of care, leaving the data with the owner. Strict conformity with ethical and legal legislations was augmented with a usability-driven engineering process, user requirements gathering from relevant stakeholders, and expert walkthroughs guided developments. Developments based on the HL7/FHIR standard granting interoperability. Platform's applicability in clinical routine was an essential aim. Thus, we evaluated the platform according to an evaluation framework in an observational 6-month proof-of-concept study with RA patients affected by cardiovascular comorbidities using questionnaires, interviews, and platform data. RESULTS: Thirty RA patients (80% female) participated, mean age 59 years, disease duration 13 years, average number of comorbidities 2.9. Home monitoring data demonstrated high platform adherence. Evaluations yielded predominantly positive feedback: The innovative dashboard-like design offering time-efficient data visualization, comprehension, and personalization was well accepted, i.e., patients rated the platform "overall" as 2.3 (1.1) (mean (SD), Likert scales 1-6) and clinicians recommended further platform use for 93% of their patients. They managed 86% of patients' visits using the clinician dashboard. Dashboards were valued for a broader view of health status and patient-physician interactions. Platform use contributed to improved disease and comorbidity management (i.e., in 70% physicians reported usefulness to assess patients' diseases and in 33% potential influence on treatment decisions; risk manager was used in 59%) and empowered patients (i.e., 48% set themselves new health-related goals, 92% stated easier patient-physician communications). CONCLUSION: Comprehensive aggregation of clinical data from distributed sources in a modern, GDPR-compliant cloud platform can improve physicians' and patients' knowledge of the disease status and comorbidities as well as patients' management. It empowers patients to monitor and positively contribute to their disease management. Effects on patients' outcome, behavior, and changes in the health care systems should be explored by implementing ICT-based platforms enriched by upcoming Artificial Intelligence features where possible. TRIAL REGISTRATION: DRKS-German Clinical Trials Register, DRKS00013637 , prospectively registered. 17 January 2018.

Diabetes management using modern information and communication technologies and new care models.

BACKGROUND: Diabetes, a metabolic disorder, has reached epidemic proportions in developed countries. The disease has two main forms: type 1 and type 2. Disease management entails administration of insulin in combination with careful blood glucose monitoring (type 1) or involves the adjustment of diet and exercise level, the use of oral anti-diabetic drugs, and insulin administration to control blood sugar (type 2). OBJECTIVE: State-of-the-art technologies have the potential to assist healthcare professionals, patients, and informal carers to better manage diabetes insulin therapy, help patients understand their disease, support self-management, and provide a safe environment by monitoring adverse and potentially life-threatening situations with appropriate crisis management. METHODS: New care models incorporating advanced information and communication technologies have the potential to provide service platforms able to improve health care, personalization, inclusion, and empowerment of the patient, and to support diverse user preferences and needs in different countries. The REACTION project proposes to create a service-oriented architectural platform based on numerous individual services and implementing novel care models that can be deployed in different settings to perform patient monitoring, distributed decision support, health care workflow management, and clinical feedback provision. RESULTS: This paper presents the work performed in the context of the REACTION project focusing on the development of a health care service platform able to support diabetes management in different healthcare regimes, through clinical applications, such as monitoring of vital signs, feedback provision to the point of care, integrative risk assessment, and event and alarm handling. While moving towards the full implementation of the platform, three major areas of research and development have been identified and consequently approached: the first one is related to the glucose sensor technology and wearability, the second is related to the platform architecture, and the third to the implementation of the end-user services. The Glucose Management System, already developed within the REACTION project, is able to monitor a range of parameters from various sources including glucose levels, nutritional intakes, administered drugs, and patient's insulin sensitivity, offering decision support for insulin dosing to professional caregivers on a mobile tablet platform that fulfills the need of the users and supports medical workflow procedures in compliance with the Medical Device Directive requirements. CONCLUSIONS: Good control of diabetes, as well as increased emphasis on control of lifestyle factors, may reduce the risk profile of most complications and contribute to health improvement. The REACTION project aims to respond to these challenges by providing integrated, professional, management, and therapy services to diabetic patients in different health care regimes across Europe in an interoperable communication platform.