The goal of the project is the development of a mobile EIT-ECG combination system. With its help, a non-invasive monitoring of a patient’s respiratory activity and heartbeat shall be realized, while employing only one wearable, performing both measurements. Users, regardless of their technical background knowledge, should be able to perform non-invasive examinations of heart and lung functions in a very short time. The relevant vital parameters, such as lung activity, regionally resolved ventilation visualization, relative tidal volume, respiratory rate or heart rate, should be presented in an understandable way without invasive methods. One of the main components of the system will be an electrode attachment that can be used on patients of different sizes.
Annually more than 270,000 people suffer from acute strokes in Germany, out of which roughly 200,000 experience it for the first time. Further consequences follow after the acute event for the majority of the afflicted patients, including physical handicaps and emotional distress. This often leads to the stroke evolving into a chronic illness.
In order to support patients in the often difficult time after the stroke, the PostStroke Manager represents a patient-oriented, digital system that uses common everyday communication channels in order to enable a coordinated preventive long-term care of stroke patients. The system integrates stroke pilots (Schlaganfalllotsen), patients and general practitioners as well as mobile sensors (so-called wearables) and, thus, creates the basis for innovative digital services, new forms of care and a structured disease management program for strokes. It serves as a supplement to stroke pilot care from the first year on after the acute event, but can also be used in areas without an established program of that kind directly after the incident. In addition, the PostStroke-Manager can help with secondary prophylaxis matters by i.e. reminding the patient to take their medications and – provided that the patient enabled the function – recording important parameters like heart rate or systolic and diastolic blood pressure via Bluetooth blood pressure monitors.
The project aims to develop a non-invasive, multimodal monitoring system that will enable first responders to obtain informative objective feedback on the quality of executed cardipulmonary resuscitation. Regardless of their technical or medical background knowledge, users should be able to quickly bring the system into an operational state, attach it to the patient’s body and receive an evaluation of the resuscitation activity performed. The user should be shown the qualitative changes in the arterial blood flow in the neck that occurs as a result of thoracic compressions. In addition, several preclinical measurements on the phantom are to be used to establish ranges for measured values in the laboratory environment, which will support the user in assessing the displayed blood flow values.
‘Multiparametric Spectral Patient Imaging’ is a project in cooperation with the Diaspective Vision GmbH. The aim of the project is the development of a flexible and safely applicable monitoring system for several clinical use cases based on an innovative HSI camera. This new monitoring system will determine relevant parameters of cutaneous perfusion and surface moisture and appropriately visualizes them. Hyperspectral Imaging (HSI) is a combination of spectroscopy and digital imaging and divides the electromagnetic spectrum into many bands. Therefore, hyperspectral images provide more information per pixel than the results of every other imaging technology.
Thus, the treating physician can make use of a further informative approach for individual process assessment of the overall condition of the patient in several clinical environments. Such an advanced monitoring system for anesthesia is not available yet and constitutes a crucial clinical development.
The surgical navigation process in minimally-invasive endoscopic surgery is time- and resource- constrained and conventional navigation assistance technology is reduced to a passive-supportive role. In the project COMPASS, a new technology for immersive assistance in minimally-invasive and microscopic interventions is developed to convert navigation systems into fully-acknowledged surgical actors. (read more)
The project ENSEMBLE encompasses the development of a scalable and magnetic resonance-compatible cardiovascular system model. This closed-loop system shall be available as a self-contained trainings module, allowing the practicing of multiple surgical procedures, e.g. catheter-based operations. Using the developed model, future surgeons will be able to simulate realistic operations, so they can develop and expand their cognitive and motoric skills during the course of multiple practice sessions.
In order to present a trainings model, which is as realistic as possible, a pump, an artificial blood vessel tree and a blood-like fluid will be combined with auxiliary components. The developed system will allow for a simulated blood circulation, so that it will be possible to create an artificial operating situation, which immerses the trainee as best as possible. The deployed pump will be able to measure pressure, recognize changes in the pressure curve and adjust its regulation parameters automatically. Furthermore, it will be small, adaptable and powerful enough to drive the fluid inside of the circulatory system. This branched system will be composed of single arteries, capillaries and veins with additional valves, whose layout will be developed by an automatic segmentation algorithm. The permeability, thickness, elasticity and diameters of the artificial vessels will be comparable to their real counterparts. That way, the model shall provide a realistic reaction, when surgeons practice cuts or sutures with their instruments on it. The blood-like fluid, that the model is filled with, will possess a viscosity which shall be displayable to the user as well as adjustable to use-case-specific requirements.
The initial goal is to establish a general understanding of the coiling patterns and their impact on the convalescence of spinal perfusion and the clinical outcome. Initially, an extensible patient model needs to be developed including multi-modal imaging & procedure parameters, e. g. blood pressure, heart rhythm, CVP, rMAP as well as anatomical parameters, such as Crawford classification, calcification status and artery kinking. (read more)
Patients with tracheostomy tubes require devices for mechanical aspiration to extract solids and fluids that accumulate above the cuff balloon. In order to increase the success of the treatment and the patient’s health, the AutoCuff project aims to develop a new medical device that enables a more comprehensive care of the patient by means of digital control and monitoring functions as well as an interface for interoperable communication. By combining a cuff controller and a device for subglottic suction, the mutually influencing regularization cycles of the pressure management are to be coordinated to enable a gentler therapy. In order to support an efficient integration of the developed device into a clinical environment, the target system shall be equipped with an interoperable interface. The resulting communication between the system and other medical devices will contribute to the coordination of therapy-relevant parameters, which significantly improve the medical outcome of the treatment.
Healthcare is changing due to social challenges in the area of tension between cost efficiency through standardization and therapy effectiveness through personalization. Therapy-relevant information, for example in interdisciplinary oncological treatment, covers the entire range from omics data, imaging and laboratory values to the inclusion of living conditions. For efficient healthcare, the data must be available in daily clinical practice and decision support systems must seamlessly integrate into established clinical workflows.
The aim of the project is therefore to create a scientific and methodological basis for model-based, personalized cancer treatments that can be used in a large variety of clinical settings. The project addresses scientific questions in the field of knowledge modeling and data semantics as a starting point for the development of applications for personalized tumor therapy. So that we can provide a common understanding of work processes, patient data and decision-making processes as the basis for integration into clinical practice. The complexity of medical data and clinical processes requires the development of tailored applications for the respective clinical scenarios and user groups along the tumor treatment chain. The project demonstrates the applicability and added value of selected assistance systems as well as the integration of these applications based on interoperable models in cooperation with regional SME-partners and the clinical users.