SORTT

Project

the SORTT project envisages a smart space where a variety of sensors acquire a grid of motor, physiological and stress-related conditions, to describe and monitor patient’s performance during a well-defined motor rehabilitation session.

The smart space consists of a set of wearable sensors and features integration of an IoT system and an ontology-based modeling system.
The IoT system:

  • Collects the sensor data sources available in the environment, which can be dedicated or generic and may differ in type, collection rate, data quality, and the like;
  • Establishes whether the incoming data is sufficient to safely monitor the patient, in particular by comparing pathological and normal subjects data;
  • Elaborates on the edge data into digital biomarker that are significant to healthcare professionals.

The ontology-based modelling system:

  • Collects the biomarkers, possibly suggesting data types to monitor more closely;
  • Integrates biomarkers and environment data to evaluate the patient’s context and her/his state during rehabilitation exercises;
  • Generates an Ontology-based Human Digital Twin of the patient in the language of healthcare professionals, and uses it to monitor the situation and alert when professional intervention is needed.

The project develops arounds fife inter-related milestones:

MS1 – Project management (CNR)

  • Coordination (M1-24)
  • Dissemination (M1-24)

MS2 – Scenarios and requirements (UNIPR)

  • User requirements, system model definition and use–cases (M1-4)
  • Physiotherapy protocols definition & biomarkers data identification (M3-6)
  • Analysis of the state–of–art and of the enabling ICT solutions (M3-6)

MS3 – IoT–based patient and scenario monitoring architecture (UNIBO)

  • Sensor data collection (M5-12)
  • Edge-based data analytics and physical activity recognition (M7-16)

MS4– Ontology-based modelling and OHDT (CNR)

  • Ontology–based modelling of the patient’s state and rehabilitation session (M7-18)
  • Development of the Ontology-based Human Digital Twin (M7-18)

MS5 – Proof–of–concept implementation, calibration and validation (UNIBO)

  • Input/output towards the medical professional (M13-20)
  • Testbed calibration (M15-24)
  • Experimental assessment and performance evaluation (M18-24)