WO2023110678 - METHOD FOR DETERMINING A LEVEL OF CERTAINTY OF A PATIENT'S RESPONSE TO A STIMULUS PERCEPTION OF A SUBJECTIVE MEDICAL TEST AND A DEVICE THEREFORE
National phase entry:
Publication Number
WO/2023/110678
Publication Date
22.06.2023
International Application No.
PCT/EP2022/085228
International Filing Date
09.12.2022
Title **
[English]
METHOD FOR DETERMINING A LEVEL OF CERTAINTY OF A PATIENT'S RESPONSE TO A STIMULUS PERCEPTION OF A SUBJECTIVE MEDICAL TEST AND A DEVICE THEREFORE
[French]
PROCÉDÉ DE DÉTERMINATION D'UN NIVEAU DE CERTITUDE D'UNE RÉPONSE D'UN PATIENT À LA PERCEPTION D'UN STIMULUS D'UN TEST MÉDICAL SUBJECTIF ET DISPOSITIF ASSOCIÉ
Applicants **
ESSILOR INTERNATIONAL
Inventors
STARYNKEVITCH, Helene
MACHAIRAS, Vaïa
Priority Data
21306756.4
13.12.2021
EP
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Quotation for National Phase entry
| Country | Stages | Total | |
|---|---|---|---|
| China | Filing, Examination, Granting | 2052 | |
| EPO | Filing, Examination, Granting | 8387 | |
| Japan | Filing, Examination, Granting | 2247 | |
| South Korea | Filing, Examination, Granting | 2251 | |
| USA | Filing, Examination, Granting | 4740 |
Total:
19,677
The term for entry into the National Phase has expired. This quotation is for informational purposes only
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Abstract[English]
A computer implemented method for determining a level of certainty of a patient's response to a stimulus perception of a subjective medical test, the method comprising: detecting at least one physiological signal from the patient (15) while the patient is providing a response to the stimulus perception; determining the level of certainty of a patient's response to the stimulus perception (16) from the at least one physiological signal (15); the at least one physiological signal (15) being an input data to a machine learning model (10) trained based on a set of training data; the set of training data comprising at least one physiological signal (11) associated to a level of certainty (12) of a patient's response; the determined level of certainty being the output of the trained machine learning model.[French]
Procédé mis en œuvre par ordinateur pour déterminer un niveau de certitude d'une réponse d'un patient à la perception d'un stimulus d'un test médical subjectif, le procédé consistant à : détecter au moins un signal physiologique du patient (15) pendant que le patient fournit une réponse à la perception du stimulus ; déterminer le niveau de certitude de la réponse d'un patient à la perception du stimulus (16) à partir du ou des signaux physiologiques (15) ; le ou les signaux physiologiques (15) constituant une donnée d'entrée d'un modèle d'apprentissage automatique (10) entraîné sur la base d'un ensemble de données d'apprentissage ; l'ensemble de données d'apprentissage comprenant au moins un signal physiologique (11) associé à un niveau de certitude (12) de la réponse d'un patient ; le niveau de certitude déterminé constituant la sortie du modèle d'apprentissage automatique entraîné.