Study, development and testing in an operational environment of a tool aimed at offering a personal care service for domestic monitoring of the elderly with mild cognitive decline, individuals affected by Parkinson’s disease and individuals dealing with the effects of transient ischemic attack (TIA). The area of application is domestic safety, detecting activity, movements and falls through activation of preventive measures and a remote-care service activated by alerts from specific artificial-intelligence algorithms that comprise the DSS (decision support system) and the monitoring of development of the disease through temporal verification of motor function and vital statistics of patients.

OBJECTIVES

Creation of an integrated system for domestic safety and home assistance through preventive measures and personal remote care, enhanced by machine-learning algorithms used within a process that supports clinical and care-related decisions. These elements make the system highly scalable and replicable in various usage contexts through customization of clinical and care requirements.

RESULTS

Industrial research
Fine-tuning of protocols for issue of the dedicated remote-care service (identification of parameters to monitor and suitable devices) and creation of algorithms and models to identify anomalies.

Experimental development
Creation and validation of the experimental platform for the remote-care service and wearable device capable of detecting falls and patterns of movement, through design, build, integration and testing in representative usage contexts.

DURATION
17.06.2019 – 16.12.2020 (18 months)

PARTNERS
Feature Jam srl – LP
Televita spa
UNITS – Department of Engineering and Architecture
ASUITs – Integrated University Healthcare Establishment
Area Science Park

Michela Cinello
Research Valorisation Unit
Area Science Park
michela.cinello@areasciencepark.it