Bose Corporation

Drowsy Digital, Inc.

Jeffrey M Ellenbogen

Matthew Chace Carpenter

Kathleen Elizabeth Kremer

Steven Carl Pletcher

Chia-Ling Li

Dale McElhone

Michael Patrick O'Connell

Christopher R Paetsch

Adam C Furman

Jonathan Zonenshine

Dale Mcelhone

Chrisopher R Paetsch

Aspects of the present disclosure provide methods, apparatuses, and systems for closed-loop sleep protection and/or sleep regulation. According to an aspect, sleep disturbing noises are predicted and a biosignal parameter is measured to dynamically mask predicted disturbing environmental noises in the sleeping environment with active attenuation. Environmental noises in a sleeping environment of a subject are detected, input, or predicted based on historical data of the sleeping environment collected over a period of time. The biosignal parameter is used to determine sleep physiology of a subject. Based on the environmental noises in the sleeping environment and the determined sleep physiology, the noises are predicted to be disturbing or non-disturbing noises. For predicted disturbing noises, one or more actions are taken to regulate sleep and avoid sleep disruption by using sound masking prior to or concurrently with the occurrence of the predicted disturbing noises.

Dynamic sound masking based on monitoring biosignals and environmental noises

Aspects of the present disclosure provide methods, apparatuses, and systems for closed-loop sleep protection and/or sleep regulation. According to an aspect, a biosignal parameter and ambient noise are measured. The biosignal parameter is used to determine sleep condition of a subject. The sleep condition is determined based on one or more of personalized sleep data or historical sleep data collected using a subset of society. Based on the sleep condition, an arousal threshold is determined. Based on the ambient noise and the determined sleep condition, one or more actions are taken to regulate sleep and avoid sleep disruption.

Biometric feedback as an adaptation trigger for active noise reduction, masking, and breathing entrainment

Aspects of the present disclosure provide methods, apparatuses, and systems for a personalized wake-up system. A sleep assistance device outputs a sound. In response to detecting a sound that exhibits one or more predetermined sound properties, actions are taken to adjusting the sound in an effort to wake the subject. Examples of predetermined sound properties include any sound detected over a threshold decibel level, sounds detected at a certain frequency spectrum. According to aspects, subject may further configure the system to alert the subject based on a set of personalized sounds the subjects considers to be important. According to aspects, the audio device or system is configured to determine the subject is awake based on collected biosignal parameters. The audio device or system takes further actions to disrupt the subject's sleep until the subject is determined to be awake.

Smart-safe masking and alerting system

Aspects of the present disclosure provide methods, apparatuses, and systems for dynamically masking audible breathing noises determined to be generated by one or more sleeping partners. According to aspects, a subject's sleep is protected by detecting audible breathing noises in a sleeping environment, determining the audible breathing noises are not generated by the subject, and mitigating the perception of the audible breathing noises that are determined to originate from another subject, such as a bed partner, pet, etc. The dynamic masking reduces the subject's exposure to unnecessary sounds and reduces the chances of masking sounds disturbing the subject's sleep.

Dynamic masking depending on source of snoring

Aspects of the present disclosure provide methods, apparatuses, and systems for closed-loop sleep protection and/or sleep regulation. According to an aspect, a biosignal parameter and ambient noise are measured. The biosignal parameter is used to determined sleep condition of a subject. The sleep condition is determined based on: (1) one or more of personalized sleep data, (2) historical sleep data collected for a subset of society, or (3) a combination of both. Based on the sleep condition, an arousal threshold is determined. Based on the ambient noise and the determined sleep condition, one or more actions are taken to regulate sleep and avoid sleep disruption by using sound masking or active noise reduction (ANR).

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Towson, MD, United States of America

Jeffrey M Ellenbogen