Minimally-invasive endoscopic surgery is a well-established surgical practice. However, decoupled hand-eye-coordination, limited field-of-view and operating space as well as decreased depth perception, are demanding for both surgeon and equipment. Faced with this complex intraoperative environment, surgeons are required to train their spatial awareness and instrumentation skill from training and live operations. Since training effects on spatial cognition and orientation capabilities vary individually, the quality of laparoscopic training with physical and virtual simulators is dependent on the predisposition of trainees. The training effectiveness and a potential skill transfer to the operating room is generally not predictable.

As a consequence, the purpose of this project is the development of a novel training assistance systems that acquires a continuous multimodal representation of a trainees’ individual laparoscopic exercises to predict the current and overall training progression and, in response, provide aural and visual feedback cues. A physical simulator extended with multiple sensor components will be used to generate a knowledge base of basic bimanual laparoscopic skills. Training progression and quality, currently assessed through subjective skill questionnaires, will be extended through the introduction of objective, machine-readable metrics as a form of unbiased description of laparoscopic expertise.

The European medical response system is comprised of first responder units that are operating quickly and lightly. On occurring disasters (e.g. earthquakes, tsunamis, floods, etc.), these Emergency Medical Teams (EMT) are deployed on disaster relief missions to support the local medical system and avert humanitarian crises.
The “EMT Operating System” (EOS) is a field hospital information system, which is tailored to the requirements of EMT on disaster relief missions. Its idea was created and designed during the EUMFH-Project. The system supports the whole patient treatment process from triage to discharge and is highly configurable to adapt to the needs of the EMT. Despite EOS being primarily designed as an electronic patient record, it also includes essential functions for EMT mission and field hospital management. Besides patient management and treatment documentation, EOS enables quick department configuration, visualization of important hospital key performance indicators (patient admissions, triage category count, department workload, etc.) and reporting functionalities (e.g. to local government or WHO). Thus, EOS plays an essential role in monitoring and assessing the current situation and performance on a strategic and tactical level.
EOS provides highly customizable functionalities. They can be adjusted to the specific frameworks of different EMT entities or other requirements by specialized teams, e.g. Burn Assessment Teams. Generally speaking, EOS includes digital documentation and management of the usual processes within an EMT. However, detailed characteristics can differ.
EOS relies heavily on structured data entry and storage (in contrast to free texts). This ensures high information quality and supports fast and easy data input as well as automatic information aggregation in databases. The latter benefits the reporting obligation and allows for comparison between different missions or EMT installations.
The system is under continuous development in close collaboration with different first responder organizations. It will be free of charge for civil first responder organizations. Designed as a web application, EOS can be used with modern browsers (e.g. Chrome, Firefox, etc.) and can be utilized easily on PCs, laptops or touch devices like tablet pcs or smartphones. You are interesting in using EOS or wanting to try it out? Then contact us: eos@iccas.de.

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The medical field of hematology is characterized by highly heterogeneous diseases and disease courses. Nevertheless, clinical trial design, drug development and subsequent therapy are mostly based on the administration of identical therapeutic regimens. As treatment strategies become more precisely tailored to patients, this process becomes more effective, but at the same time causes an enormous amount of complexity in the information that must be considered.  Thus, clinical decision-making also depends on whether the treating physician has the appropriate therapeutic experience and access to novel therapies. The goal of KAIT, an artificial intelligence-based platform for therapeutic decision support for patients with myelodysplastic syndrome, acute myeloid leukemia and multiple myeloma, is to support the clinical decision-making process by providing and evaluating relevant information to enable patient-specific and personalized treatment for all patients.

Link to project website (German)

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.

Link to project website

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.

In the MOMENTUM project, medical technology is being developed that can be used not only in the hospital (eg in the trauma room, operating theater, intensive care unit), but also in preclinical care at the scene of the accident and in the ambulance. (read more)

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.