公开(公告)号：US12016698B2

公开(公告)日：2024-06-25

申请号：US16008102

申请日：2018-06-14

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Gary Nelson Garcia Molina ,  Edouard Robert Marcus Gebski ,  Mark Choi ,  Annette Kapitan ,  Stefan Pfundtner ,  Tsvetomira Kirova Tsoneva ,  Anandi Mahadevan ,  Megan King ,  Diane Kosobud ,  Jessica Weeden ,  Guy Anthony Brown

IPC: A61B5/00 ,  A61M21/02 ,  G16H20/70 ,  G16H50/20 ,  G16H50/30 ,  A61M21/00

CPC classification number: A61B5/4815 ,  A61B5/4806 ,  A61M21/02 ,  G16H20/70 ,  G16H50/20 ,  G16H50/30 ,  A61B5/4812 ,  A61M2021/0022 ,  A61M2021/0027 ,  A61M2021/0044 ,  A61M2021/0055 ,  A61M2021/0066 ,  A61M2021/0083 ,  A61M2205/332 ,  A61M2205/3375 ,  A61M2205/3553 ,  A61M2205/3584 ,  A61M2205/505 ,  A61M2230/06 ,  A61M2230/10 ,  A61M2230/18 ,  A61M2230/42 ,  A61M2230/63

Abstract: The present disclosure pertains to facilitating sleep improvement for a user. In a non-limiting embodiment, user data associated with a sleep session of a user is received from one or more sensors. Based on the user data, one or more sleep metrics associated with the sleep session are generated. One or more reference sleep metrics are determined based on prior user data obtained from one or more prior sleep sessions. One or more immediate values related to the sleep session is/are determined based on a comparison of the sleep metrics with the reference sleep metrics. A sleep session score value is generated based on the immediate values, and the sleep session score value and the sleep metrics are caused to be presented on via an output device.

公开(公告)号：US11172865B2

公开(公告)日：2021-11-16

申请号：US16466357

申请日：2017-12-01

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Gary Nelson Garcia Molina ,  Anandi Mahadevan ,  Surya Subrahmanya Sreeram Vissapragada Venkata Satya ,  Annette Kapitan

IPC: A61B5/38 ,  A61M21/00 ,  A61B5/00

Abstract: The present disclosure pertains to a reference slow wave activity metric determination system. Instead of collecting information during sleep sessions without stimulation (e.g., baseline and/or sham sessions) to determine a reference amount of slow wave activity in a subject, the present system is configured to build a model between stimulation properties and slow wave enhancement, and determine the reference amount of slow wave activity in the subject (e.g., corresponding to what would occur during baseline sleep and/or sham sessions) using the model. Advantageously, this approach does not require performance of baseline and/or sham sleep sessions, and enables personalization of the reference amount of slow wave activity, which dynamically increases its accuracy as more information is collected.