Company info:

Name: Sleep Advice Technologies S.r.l.
Date founded: 2018
Number of employees: 4
Location: Corso Vinzaglio 12 bis
10121 Torino (TO) Italy

Platforms & testbeds:

IODP

Partners:

PRESLEEP “A wearable CPS for the automatic detection and prediction of the awake, drowsiness and sleeping stages”

Challenge

Sleep medicine is a medical specialty focused on the analysis, diagnosis and therapy of sleep disturbances and disorders and, more generally, about awake-drowsiness-sleep functioning. A very innovative approach focused on the early detection of drowsiness and, more generally, about fatigue and tiredness, has been developed by Sleep Advice Technologies (SAT).

Solution

The methodology is based on the non-invasive real-time measurement of a reduced set of physiological parameters, thus supporting the automatic detection and prediction of awake, drowsiness and sleeping stages through modern Artificial Intelligence techniques. The real time detection and prediction algorithm will be implemented into a wearable CPS prototype featuring a rich set of communication channels as well as GPS functionality. A very important aspect of the project is related to the capability of the proposed methodology/technology to detect additional high level emotional stages of the drivers (e.g. stress, anxiety, etc..) which can support the development of advanced control strategies for automated vehicle at AVL.

FED4SAE Support

The proposed system integration Application Experiment, run in tight cooperation with AVL, will accelerate the development process toward the most effective technological transfer into a successful mass market product.

The “System integration Application Experiment” will cover HW/SW integration and access enablement to both the Integrated and Open Development Platform (AVL) and the complementary skills from the competence centre (AVL).

The outcome of such an AE will be an integrated CPS prototype demonstrator verified and validated in realistic conditions at AVL.

Impact

The project aims at bridging health and transportation domains by fully developing the exclusive methodology and the related CPS technology which can be successfully applied in a wide range of applications in the respective domains. More specifically, this system integration AE is focused on the fine assessment and validation of the proposed methodology/technology in a realistic automotive environment through the support of AVL.

The wearable CPS will be based on a flexible and modular architecture in order to meet the target (i.e. cost, performance) of different applications.

The societal impact is very relevant (see also next paragraph for additional details) since it can drastically improve the quality of life by reducing the amount of risky situations due to loss of control of the subject while performing an action.