Assistive Medical Robotics for Very Early Mobilization of Critical Care Patients

Informazioni relative al progetto

VEMOtion

ID dell’accordo di sovvenzione: 190171705

DOI

10.3030/190171705

Progetto chiuso

Data della firma CE 19 Dicembre 2022

Data di avvio 1 Gennaio 2023

Data di completamento 31 Dicembre 2024

Finanziato da

• The European Innovation Council (EIC)

Costo totale

€ 3 557 625,00

Contributo UE

€ 2 490 337,50

Coordinato da

REACTIVE ROBOTICS GMBH
Germany

Periodic Reporting for period 1 - VEMOtion (Assistive Medical Robotics for Very Early Mobilization of Critical Care Patients)

Periodo di rendicontazione: 2023-01-01 al 2023-12-31

Sintesi del contesto e degli obiettivi generali del progetto

Early mobilisation in the ICU is a highly effective tool in patient rehabilitation, clinically proven and acknowledged by major international medical bodies. Despite the clear financial advantages for healthcare systems and health benefits for patients, it is
currently performed with only 25% of ICU patients due to lack of resources and hazardous nature of the manual procedure. Reactive Robotics has developed VEMOTION, the world’s first AI-driven robotic assistance system for early mobilisation in ICUs. VEMOTION enables the clinically proven benefits of early mobilisation to be delivered safely to all ICU patients, accelerating recovery by 20%, reducing treatment costs, increasing ICU capacity by 27%, and improving patient outcomes. Introduction creates a >€5bn market for ICU robotics. The EIC project (€2.5M grant, €15M equity) delivers crucial product development and large-scale clinical trials to validate the clinical/business case and accelerate scale-up.

Lavoro eseguito dall’inizio del progetto fino alla fine del periodo coperto dalla relazione e principali risultati finora ottenuti

The project focused on the development of a 2nd generation system with the goal of enhancing usability, expanding AI and digitalisation features, and reducing Costs of Goods sold (CoGs).

Significant achievements of the project include the successful certification for bariatric patients, the optimization of patient adapters which connect the patient with the robot: for instance, a one-size-fits-all Leg Adapter was already successful introduced into the market.

Further key activities comprise the successful development of prototypes for a new embedded control system and a hospital bed platforms that will optimise the interaction between the bed and robot and enable functions that are in high demand on the market. Moreover, a prototype of a revised graphical user interface that facilitates time-optimized workflows has been developed. Additionally, the project achieved an upgrade of the underlying data warehouse, incorporating analysis tools for service and maintenance purposes. These accomplishments collectively contribute to the overall improvement of the system's performance and user experience.

To strengthen the clinical data case, two suitable KOLs were identified in two different German hospitals. With the first partner (patient population: pulmonological), a contract for a small clinical trial was signed, and the study protocol was created and submitted. The ramp-in phase has already started. With the second partner (patient population: neurological), a first draft of the study protocol was defined, and administrative topics are now being finalized.

Progressi oltre lo stato dell’arte e potenziale impatto previsto (incluso l’impatto socioeconomico e le implicazioni sociali più ampie del progetto fino ad ora)

The introduction of the one-size-fits-all patient leg adapter marks a significant leap beyond the current state-of-the-art in mobilisation robotics. This innovative adapter, meticulously engineered to accommodate a diverse range of patient legs, including those of bariatric individuals, sets a new standard for versatility and ease of use. In contrast to the multitude of size-specific solutions employed by our first-generation systems and competitor devices, this adaptation represents a clear improvement, streamlining the patient experience and enhancing overall efficiency.