EPO Patent: Smart Sensor, Wearable Device, and Data Processing Method

ChangeBridge: EPO Bulletin - AI & Computing (G06N)

Published March 18th, 2026

Detected March 24th, 2026

Summary

The European Patent Office has published patent application EP4710844A1 for a smart sensor, wearable device, and data processing method developed by Luxottica S.r.l. The patent describes a system for continuously detecting physical quantities and processing the data using an incremental neural network.

View original document View source feed page

What changed

The European Patent Office (EPO) has published patent application EP4710844A1, filed by Luxottica S.r.l., detailing a smart sensor, a wearable device incorporating it, and a method for processing the detected data. The invention involves a detector for continuously sampling physical quantities and an embedded electronic unit that executes an incremental neural network to process these samples. The output is transmitted to a second electronic unit if a predefined condition is met, suggesting a focus on efficient, on-device data processing for wearable applications.

This publication represents a new patent filing and does not impose immediate compliance obligations on regulated entities. However, companies involved in developing wearable technology, smart sensors, or AI-driven data processing for health and consumer electronics should be aware of this patent's scope. It may impact future product development and intellectual property strategies in the wearable technology sector.

Source document (simplified)

← EPO Patent Bulletin

SMART SENSOR, WEARABLE DEVICE COMPRISING SAID SMART SENSOR AND METHOD FOR PROCESSING THE DATA DETECTED THROUGH SAID SMART SENSOR

Publication EP4710844A1 Kind: A1 Mar 18, 2026

Applicants

Luxottica S.r.l.

Inventors

Trojaniello, Diana, Ongarello, Tommaso, Shalby, Hazem Hesham Yousef, De Vecchi, Arianna, Villa, Federica, Roveri, Manuel, Palermo, Francesca

Abstract

Smart sensor (200) comprising:
- a detector (210) configured for continuously detecting a physical quantity, sampled with a predefined sampling time tc, thus obtaining a plurality of the detected physical quantity samples xt-i with i∈[0, T-1] of size Nin where
• xt-i ∈ RNin with i∈[0, T-1] is the sample acquired at discrete time t-i and is a vector of size Nin,
• T is the number of samples acquired in a predetermine time size T x tc of an observation window;

an embedded first electronic unit (220) configured for receiving the acquired samples xt-i with i∈ [0, T-1] and for executing, each time a new sample xt-i with i∈ [0, T-1] is received, an incremental Neural Network g(incr) (·) having such a received new sample xt-i with i∈ [0, T-1] as an input, wherein such an incremental Neural Network g(incr) (·) provides the application of a number of n convolutional filters to each sample xt-i obtaining a corresponding first output output matrix Y having elements yt−ijkwith j∈ [1, n] and k ∈ [1, Nin] according to the following equation: yt−ijk=yt−i−1jk+cij×xt−i ∀j ∈ [1, n] and ∀k ∈ [1, Nin] wherein cij is the weight of the j-th filter applied to the sample at time t-i, said first output matrix Y having size n x Nin and being initialized to 0, and wherein the embedded first electronic unit (220) is configured to transmit the first output matrix Y to a second electronic unit (300) if a predefined condition is satisfied.

IPC Classifications

A61B 5/00 20060101AFI20250219BHEP G06N 3/0464 20230101ALI20250219BHEP

Designated States

AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LI, LT, LU, LV, MC, ME, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR

View original document →