IP Library Granted Patent US 12,527,411
Granted Patent B2
US 12,527,411 · App. 17/984,752 · Granted Jan 20, 2026

Air mattress with features for determining ambient temperature

Inventors: Kody Lee Karschnik (Plymouth, MN); Gary N. Garcia Molina (Madison, WI); Cory Lee Grabinger (Maple Grove, MN)
Assignee: Sleep Number Corporation
A47C27/083G01K13/02
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Quick Facts
Patent No.
US 12,527,411
App. No.
17/984,752
Granted
Jan 20, 2026
Kind
B2
Abstract

Bladder pressure readings of bladder pressure inside an air bladder of a mattress are received for a particular time. Barometric pressure readings of barometric pressure in an ambient environment outside the mattress are received for the particular time. The bladder pressure and the barometric pressure readings are used as input to an ambient temperature classifier. Output from the ambient temperature classifier is received as an ambient temperature value for the particular time.

Claims (45)

1 . A system for measuring ambient temperature, the system comprising:

a mattress for supporting a sleeper, the mattress comprising at least one air bladder;

a bladder pressure sensor fluidically coupled to the air bladder, the bladder pressure sensor configured to:

sense bladder pressure inside the air bladder for a particular time;

transmit bladder pressure readings for the particular time;

a barometric sensor in an ambient environment outside the mattress, the barometric sensor configured to:

sense barometric pressure in the ambient environment for the particular time;

transmit barometric pressure readings for the particular time;

a computing device comprising at least one processor and memory, the computing device configured to:

receive the bladder pressure readings;

receive the barometric pressure readings;

provide, as input to an ambient temperature classifier, the bladder pressure and the barometric pressure readings; and

receive, as output from the ambient temperature classifier, an ambient temperature value for the particular time, wherein the ambient temperature classifier is configured to determine temperature in the ambient environment by removing influence of the barometric pressure on the bladder pressure.

2 . The system of claim 1 , wherein the ambient temperature classifier is configured to:

determine a thermal pressure value for the air bladder by reducing the bladder pressure readings based on the barometric pressure readings; and

determine the ambient temperature value in a model of contents of the air bladder that relates thermal pressure to the ambient temperature.

3 . The system of claim 2 , wherein the model is based on an ideal gas law.

4 . The system of claim 3 , wherein the contents of the air bladder include both a gas and an open cell foam, and wherein the model is further based on thermal expansion properties of the open cell foam.

5 . The system of claim 1 , wherein the ambient temperature classifier is configured to find the ambient temperature by looking up the ambient temperature in a lookup table indexed by bladder pressure and barometric pressure.

6 . The system of claim 1 , wherein the ambient temperature classifier was trained with machine learning processes using training data comprising i) bladder pressure reading: barometric pressure reading pairs and ii) training ambient temperature values.

7 . The system of claim 1 , wherein:

the system further comprises a temperature sensor configured to:

sense microclimate temperature in a microclimate around the sleeper;

transmit the microclimate temperature readings for the particular time;

the computing device is further configured to:

receive the microclimate temperature readings; and

provide, as further input to the ambient temperature classifier, the microclimate temperature readings, wherein the ambient temperature classifier is configured to determine temperature in the ambient environment by removing influence of the barometric pressure and of the microclimate temperature on the bladder pressure.

8 . The system of claim 1 , where the computing device is further configured to identify discontinuities, greater than a threshold value, in a record of ambient pressure values over time as bed entry/exit events.

9 . The system of claim 1 , where the computing device is further configured to initiate a home automation event based on the received ambient temperature value for the particular time.

10 . A non-transitory computer-readable medium tangibly storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: receive bladder pressure readings of bladder pressure inside an air bladder of a mattress for a particular time; receive barometric pressure readings of barometric pressure in an ambient environment outside the mattress for the particular time; provide, as input to an ambient temperature classifier, the bladder pressure and the barometric pressure readings; wherein the ambient temperature classifier is configured to determine temperature in the ambient environment by removing influence of the barometric pressure on the bladder pressure and receive, as output from the ambient temperature classifier, an ambient temperature value for the particular time.

11 . The computer-readable medium of claim 10 , wherein the ambient temperature classifier is configured to:

determine a thermal pressure value for the air bladder by reducing the bladder pressure readings based on the barometric pressure readings; and

determine the ambient temperature value in a model of contents of the air bladder that relates thermal pressure to the ambient temperature.

12 . The computer-readable medium of claim 11 , wherein the model is based on an ideal gas law.

13 . The computer-readable medium of claim 12 , wherein the contents of the air bladder include both a gas and an open cell foam, and wherein the model is further based on thermal expansion properties of the open cell foam.

14 . A method for measuring ambient temperature, the method comprising:

receiving bladder pressure readings of bladder pressure inside an air bladder of a mattress for a particular time;

receiving barometric pressure readings of barometric pressure in an ambient environment outside the mattress for the particular time;

providing, as input to an ambient temperature classifier, the bladder pressure and the barometric pressure readings;

receiving, as output from the ambient temperature classifier, an ambient temperature value for the particular time; and

determining, by the ambient temperature classifier, temperature in the ambient environment by removing influence of the barometric pressure on the bladder pressure.

15 . The method of claim 14 , further comprising:

determining, by the ambient temperature classifier, a thermal pressure value for the air bladder by reducing the bladder pressure readings based on the barometric pressure readings; and

determining, by the ambient temperature classifier, the ambient temperature value in a model of contents of the air bladder that relates thermal pressure to the ambient temperature.

16 . The method of claim 15 , wherein the model is based on an ideal gas law.

Assignments (3)
SECURITY INTEREST Recorded May 4, 2026
From: SLEEP NUMBER CORPORATION
To: U.S. BANK NATIONAL ASSOCIATION
Reel/Frame 074555/0856 →
SECURITY INTEREST Recorded Nov 4, 2025
From: SLEEP NUMBER CORPORATION
To: U.S. BANK NATIONAL ASSOCIATION
Reel/Frame 073507/0051 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 23, 2022
From: KARSCHNIK, KODY LEE; GARCIA MOLINA, GARY N.; GRABINGER, CORY LEE
To: SLEEP NUMBER CORPORATION
Reel/Frame 061863/0685 →
Continuity (2)
Provisional Application 63279427 · Nov 15, 2021
Related Publication 20230148762A1 · May 18, 2023
References Cited (119)
US 7204041B1 · Bailey et al. · 2007 [cited by applicant]
US 7918134B2 · Hedtke et al. · 2011 [cited by applicant]
US 8444558B2 · Young et al. · 2013 [cited by applicant]
US 8672853B2 · Young · 2014 [cited by applicant]
US 8984687B2 · Stusynski et al. · 2015 [cited by applicant]
US 9370457B2 · Nunn et al. · 2016 [cited by applicant]
US 9392879B2 · Nunn et al. · 2016 [cited by applicant]
US 9445751B2 · Young et al. · 2016 [cited by applicant]
US 9504416B2 · Young et al. · 2016 [cited by applicant]
US 9510688B2 · Nunn · 2016 [cited by examiner]
US 9635953B2 · Nunn et al. · 2017 [cited by applicant]
US 9770114B2 · Brosnan et al. · 2017 [cited by applicant]
US 9844275B2 · Nunn et al. · 2017 [cited by applicant]
US 9931085B2 · Young et al. · 2018 [cited by applicant]
US 10058467B2 · Stusynski et al. · 2018 [cited by applicant]
US 10092242B2 · Nunn et al. · 2018 [cited by applicant]
US 10149549B2 · Erko et al. · 2018 [cited by applicant]
US 10182661B2 · Nunn et al. · 2019 [cited by applicant]
US 10201234B2 · Nunn et al. · 2019 [cited by applicant]
US 10251490B2 · Nunn et al. · 2019 [cited by applicant]
US 10342358B1 · Palashewski et al. · 2019 [cited by applicant]
US 10441086B2 · Nunn et al. · 2019 [cited by applicant]
US 10441087B2 · Karschnik et al. · 2019 [cited by applicant]
US 10448749B2 · Palashewski et al. · 2019 [cited by applicant]
US 10492969B2 · Stusynski et al. · 2019 [cited by applicant]
US 10632032B1 · Stusynski et al. · 2020 [cited by applicant]
US 10646050B2 · Nunn et al. · 2020 [cited by applicant]
US 10674832B2 · Brosnan et al. · 2020 [cited by applicant]
US 10716512B2 · Erko et al. · 2020 [cited by applicant]
US 10729255B2 · Erko et al. · 2020 [cited by applicant]
US 10736432B2 · Brosnan et al. · 2020 [cited by applicant]
US 10750875B2 · Palashewski et al. · 2020 [cited by applicant]
US 10827846B2 · Karschnik et al. · 2020 [cited by applicant]
US 10881219B2 · Nunn et al. · 2021 [cited by applicant]
US 10957335B2 · Demirli et al. · 2021 [cited by applicant]
US 10959535B2 · Karschnik et al. · 2021 [cited by applicant]
US D916745S · Stusynski et al. · 2021 [cited by applicant]
US 10980351B2 · Nunn et al. · 2021 [cited by applicant]
US 11096849B2 · Stusynski et al. · 2021 [cited by applicant]
US 11122909B2 · Palashewski et al. · 2021 [cited by applicant]
US 11160683B2 · Nunn et al. · 2021 [cited by applicant]
US 11206929B2 · Palashewski et al. · 2021 [cited by applicant]
US 11246747B2 · Paradis et al. · 2022 [cited by applicant]
US D954725S · Stusynski et al. · 2022 [cited by applicant]
US D968436S · Stusynski et al. · 2022 [cited by applicant]
US D975121S · Stusynski et al. · 2023 [cited by applicant]
US 20080077020A1 · Young et al. · 2008 [cited by applicant]
US 20100170043A1 · Young et al. · 2010 [cited by applicant]
US 20110144455A1 · Young et al. · 2011 [cited by applicant]
US 20130031725A1 · Riley · 2013 [cited by examiner]
US 20140007656A1 · Mahoney · 2014 [cited by applicant]
US 20140277822A1 · Nunn et al. · 2014 [cited by applicant]
US 20150164236A1 · Driscoll, Jr. · 2015 [cited by examiner]
US 20150265065A1 · Creekmuir et al. · 2015 [cited by applicant]
US 20160015184A1 · Nunn et al. · 2016 [cited by applicant]
US 20160367039A1 · Young et al. · 2016 [cited by applicant]
US 20170065220A1 · Young et al. · 2017 [cited by applicant]
US 20170128001A1 · Torre et al. · 2017 [cited by applicant]
US 20170143269A1 · Young et al. · 2017 [cited by applicant]
US 20190053761A1 · Torre et al. · 2019 [cited by applicant]
US 20190069840A1 · Young et al. · 2019 [cited by applicant]
US 20190200777A1 · Demirli et al. · 2019 [cited by applicant]
US 20190201265A1 · Sayadi et al. · 2019 [cited by applicant]
US 20190201266A1 · Sayadi et al. · 2019 [cited by applicant]
US 20190201267A1 · Demirli et al. · 2019 [cited by applicant]
US 20190201268A1 · Sayadi et al. · 2019 [cited by applicant]
US 20190201270A1 · Sayadi et al. · 2019 [cited by applicant]
US 20190201271A1 · Grey et al. · 2019 [cited by applicant]
US 20190328146A1 · Palashewski et al. · 2019 [cited by applicant]
US 20190328147A1 · Palashewski et al. · 2019 [cited by applicant]
US 20200315367A1 · Demirli et al. · 2020 [cited by applicant]
US 20200336010A1 · Holmvik et al. · 2020 [cited by applicant]
US 20200359807A1 · Brosnan et al. · 2020 [cited by applicant]
US 20200367663A1 · Nunn et al. · 2020 [cited by applicant]
US 20200405070A1 · Palashewski et al. · 2020 [cited by applicant]
US 20200405240A1 · Palashewski et al. · 2020 [cited by applicant]
US 20210000261A1 · Erko et al. · 2021 [cited by applicant]
US 20210034989A1 · Palashewski et al. · 2021 [cited by applicant]
US 20210045541A1 · Nunn et al. · 2021 [cited by applicant]
US 20210068552A1 · Palashewski et al. · 2021 [cited by applicant]
US 20210076834A1 · Driscoll · 2021 [cited by examiner]
US 20210112992A1 · Nunn et al. · 2021 [cited by applicant]
US 20210267380A1 · Stusynski · 2021 [cited by applicant]
US 20210268226A1 · Youngblood et al. · 2021 [cited by applicant]
US 20210282570A1 · Karschnik et al. · 2021 [cited by applicant]
US 20210289947A1 · Karschnik et al. · 2021 [cited by applicant]
US 20210314405A1 · Demirli et al. · 2021 [cited by applicant]
US 20210346218A1 · Stusynski et al. · 2021 [cited by applicant]
US 20220000273A1 · Palashewski et al. · 2022 [cited by applicant]
US 20220000654A1 · Nunn et al. · 2022 [cited by applicant]
US 20220225786A1 · Palashewski et al. · 2022 [cited by applicant]
US 20220265059A1 · Palashewski et al. · 2022 [cited by applicant]
US 20220305231A1 · Stusynski et al. · 2022 [cited by applicant]
US 20220346565A1 · Karschnik et al. · 2022 [cited by applicant]
US 20220354431A1 · Molina et al. · 2022 [cited by applicant]
US 20220386947A1 · Molina et al. · 2022 [cited by applicant]
US 20220395233A1 · Siyahjani et al. · 2022 [cited by applicant]
US 20230018558A1 · Demirli et al. · 2023 [cited by applicant]
US 20230035257A1 · Karschnik et al. · 2023 [cited by applicant]
US 20230037482A1 · Demirli et al. · 2023 [cited by applicant]
WO WO2016183311 · 2016 [cited by applicant]
U.S. Appl. No. 16/719,177, Nunn et al., filed Dec. 18, 2019. [cited by applicant]
U.S. Appl. No. 17/523,349, Dixon et al., filed Nov. 10, 2021. [cited by applicant]
U.S. Appl. No. 17/745,508, Nunn et al., filed May 16, 2022. [cited by applicant]
U.S. Appl. No. 17/891,597, Holmvik et al., filed Aug. 19, 2022. [cited by applicant]
U.S. Appl. No. 17/903,150, Young et al., filed Sep. 2, 2022. [cited by applicant]
U.S. Appl. No. 17/984,752, Karschnik et al., filed Nov. 10, 2022. [cited by applicant]
U.S. Appl. No. 17/986,351, Nunn et al., filed Nov. 14, 2022. [cited by applicant]
U.S. Appl. No. 18/075,913, Johnston et al., filed Dec. 6, 2022. [cited by applicant]
U.S. Appl. No. 18/084,944, Molina, filed Dec. 20, 2022. [cited by applicant]
U.S. Appl. No. 18/086,003, Kirk et al., filed Dec. 21, 2022. [cited by applicant]
U.S. Appl. No. 18/086,104, Hill et al., filed Dec. 21, 2022. [cited by applicant]
U.S. Appl. No. 18/087,078, Hill et al., filed Dec. 22, 2022. [cited by applicant]
U.S. Appl. No. 18/087,973, Hill et al., filed Dec. 23, 2022. [cited by applicant]
U.S. Appl. No. 18/091,713, MacLachlan et al., filed Dec. 30, 2022. [cited by applicant]
U.S. Appl. No. 29/814,835, Dixon et al., filed Nov. 9, 2021. [cited by applicant]
U.S. Appl. No. 29/837,293, Stusynski et al., filed May 4, 2022. [cited by applicant]
International Search Report and Written Opinion in International Appln. No. PCT/US2022/049550, mailed on Mar. 14, 2023, 13 pages. [cited by applicant]
International Preliminary Report on Patentability in International Appln. No. PCT/US2022/049550, mailed on May 2, 2024, 8 pages. [cited by applicant]