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THEartificial intelligence, Neuroimages and home devices for cognitive rehabilitation and MOTORCYCLEhome care.

Research focus
The IN-MOTO project – Artificial Intelligence, Neuroimaging, and Home Devices for Innovative Home-Based Cognitive and Motor Rehabilitation in Patients with Neurological Damage – aims to create a data-driven digital healthcare ecosystem. It integrates rehabilitation devices, environmental sensors, and wearables to collect and analyze large volumes of clinical and behavioral data. The approach is geared toward personalized medicine, remote care, and telemedicine, with tools for continuous monitoring, rehabilitation management, and clinical decision support. The focus is on ensuring interoperability, security, and scalability, in line with international standards (HL7 FHIR, GDPR).
Solution found
The project's goal is to create a next-generation digital platform based on microservices architecture and designed to natively integrate clinical data, streams from rehabilitation devices, wearable sensors, and environmental sensors.
The innovative core of the solution lies in advanced machine learning and deep learning models, capable of processing large volumes of heterogeneous data to extract clinically relevant patterns. These algorithms go beyond descriptive analysis to enable a full-fledged decision support system, providing physicians and therapists with dynamic and predictive recommendations for personalizing rehabilitation programs. The goal is to transform data into actionable evidence, reducing clinical variability and improving therapeutic efficacy.

To ensure responsiveness and service continuity even in home environments, the platform adopts a hybrid edge-cloud architecture: an edge computing gateway performs pre-processing and local data analysis in real time, reducing latency and ensuring operational resilience. The cloud layer, on the other hand, manages scalability, model training, and secure data persistence.
The entire system is designed according to the principles of security-by-design and privacy-by-default, complying with HL7 FHIR interoperability standards and GDPR regulations, thus ensuring security, reliability, and integration with existing healthcare ecosystems.
Advanced technological solution
The In Moto project uses cutting-edge technologies such as:
AI Engine

Implementation of predictive models and Clinical Decision Support systems based on Machine Learning and Deep Learning, capable of dynamically adapting rehabilitation protocols to patient conditions.

Data Management & Advanced Analytics

Infrastructure for the secure management of multimodal clinical datasets and the application of advanced analysis algorithms to extract diagnostic patterns and insights with high clinical value.

Edge Computing

Local processing of streams from rehabilitation devices and sensors to ensure ultra-low latency, business continuity, and resilience in home settings.

Interoperability

Secure protocols for integration with existing healthcare systems, ensuring reliable and compliant data exchange

Security by Design

Architecture designed with privacy-by-default principles, with end-to-end encryption, strong authentication, and granular access controls, in full compliance with GDPR.

Financing
The project is supported under the Innovation Agreements provided for by the Ministerial Decree of 31 December 2021, a measure that promotes research and development projects in the strategic areas of health technologies and personalized medicine.
With concession decree no. 0003198 of October 13, 2023, the IN MOTO project will be implemented over a three-year period, from September 1, 2023, to August 31, 2026, with the support of the Ministry of Enterprise and Made in Italy and the participating Regions. The project's total budget is approximately €7.2 million.
Partnership

The project involves the collaboration of partners with complementary skills:

  • S. Anna Institute of Crotone – Lead partner and experimental entity, responsible for defining clinical requirements, designing autonomous devices, and clinical validation of the developed solutions.
  • Relatech SpA – Digital Enabler Solution Provider, responsible for the design and development of the AI-IN MOTO platform, device integration, and data management according to security and interoperability standards.
  • Khymeia Srl – Specializing in telerehabilitation solutions, it designs and builds IoT devices for home-based motor and postural rehabilitation.
  • Magna Graecia University of Catanzaro (UNICZ) – Contributes to the definition of neuroimaging protocols and the design of personalized cognitive rehabilitation programs.
  • University of Brescia (UNIBS) – Deals with the design of mechatronic interfaces and integration protocols between devices.
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