The Congenital Cardiology Cloud - optimizing long-term care by connecting ambulatory and hospital medical attendance via telemedicine.

BACKGROUND: Patients with complex congenital heart disease frequently undergo a life-long ambulatory therapy with the need for repeated hospital interventions. To optimize this manifold interplay, we designed and implemented a tele-medical service, the Congenital Cardiology Cloud (CCC). This study aims to analyse the requirements for its implementation through the comprehensive assessment of design, installation and impact on patient´s care. METHODS: CCC's development comprised the analysis of historically raised admission and discharge management and the definition of technical and organizational requirements. Elaboration of procedural flow charts, description of data formats and technical processes as well as distribution of patient structure formed part of this process. RESULTS: Analysis of existing workflows uncovered a need for the rebuilding of admission and discharge process and decision making for further treatment. The CCC reduces conference-meetings in general and repetitive meetings up to less than a third. Real-time dispatch of discharge documents guarantees an instantaneous access to patient-related data. Comparative analyses show a more complex patient group to be involved in tele-medical services. CONCLUSIONS: The CCC enables the sharing of complex clinical information by overcoming sectoral barriers and improves mutual patient advice. Implementation of a tele-medical network requires willingness, perseverance and professional engagement. Future application analysis and possible introduction of refinancing concepts will show its long-term feasibility.

Adaptation Strategies for Personalized Gait Neuroprosthetics.

Personalization of gait neuroprosthetics is paramount to ensure their efficacy for users, who experience severe limitations in mobility without an assistive device. Our goal is to develop assistive devices that collaborate with and are tailored to their users, while allowing them to use as much of their existing capabilities as possible. Currently, personalization of devices is challenging, and technological advances are required to achieve this goal. Therefore, this paper presents an overview of challenges and research directions regarding an interface with the peripheral nervous system, an interface with the central nervous system, and the requirements of interface computing architectures. The interface should be modular and adaptable, such that it can provide assistance where it is needed. Novel data processing technology should be developed to allow for real-time processing while accounting for signal variations in the human. Personalized biomechanical models and simulation techniques should be developed to predict assisted walking motions and interactions between the user and the device. Furthermore, the advantages of interfacing with both the brain and the spinal cord or the periphery should be further explored. Technological advances of interface computing architecture should focus on learning on the chip to achieve further personalization. Furthermore, energy consumption should be low to allow for longer use of the neuroprosthesis. In-memory processing combined with resistive random access memory is a promising technology for both. This paper discusses the aforementioned aspects to highlight new directions for future research in gait neuroprosthetics.