Home automation with features to improve sleep

Abstract

The bed includes a mattress, a sensor configured to sense sleep readings of a user sleeping on the bed, an automation controller configured to transmit the sleep readings to a cloud service, and hardware providing the cloud service configured to compare the sleep readings with trend data to generate adjustments to the user's sleep environment.

Description

Technical Field

[0001] [Cross - Reference to Related Applications] This application claims the benefit of priority to U.S. Provisional Patent Application No. 62 / 786,799, filed Dec. 31, 2018. The entire contents of the U.S. Provisional Patent Application are incorporated herein by reference.

[0002] This disclosure relates to the automation of consumer devices such as air beds.

Background Art

[0003] Generally, a bed is furniture used as a place to sleep or relax. Many modern beds include a soft mattress on a bed frame. The mattress may include springs, foam, and / or air chambers to support the weight of one or more occupants.

Summary of the Invention

[0004] The technology described herein advances the state of home automation and sleep devices. For example, personalized analysis, population - based analysis, and sub - population analysis of sleep data can be used to generate personalized automation and recommendations for the user. This can generate a technology that provides the user with human - readable information about sleep, along with practical information that is specifically and concretely created based on the actual interactions the user has with their environment. Also, the automation of the user's environment can be performed within the same sleep session where problems have been found that could otherwise negatively impact the user's sleep. Other features, aspects, and potential advantages will become apparent from the accompanying description and drawings.

Brief Description of the Drawings

[0005] [Figure 1]Figure 1 shows an exemplary airbed system.

[0006] [Figure 2] Figure 2 is a block diagram of an example of various components of an airbed system.

[0007] [Figure 3] Figure 3 shows an exemplary environment that includes a bed communicating with multiple devices within and around the home.

[0008] [Figure 4A] Figures 4A and 4B are block diagrams of exemplary data processing systems that may be associated with a bed. [Figure 4B] Figures 4A and 4B are block diagrams of exemplary data processing systems that may be associated with a bed.

[0009] [Figure 5] Figures 5 and 6 are block diagrams of example motherboards that may be used in a data processing system that may be associated with a bed. [Figure 6] Figures 5 and 6 are block diagrams of example motherboards that may be used in a data processing system that may be associated with a bed.

[0010] [Figure 7] Figure 7 is a block diagram of an example of a daughterboard that may be used in a data processing system that may be associated with a bed.

[0011] [Figure 8] Figure 8 is a block diagram of an example of a motherboard without a daughterboard, which may be used in a data processing system that may be associated with a bed.

[0012] [Figure 9] Figure 9 is a block diagram of an example of a sensor array that may be used in a data processing system that may be associated with a bed.

[0013] [Figure 10] Figure 10 is a block diagram of an example of a controller array that can be used in a data processing system associated with a bed.

[0014] [Figure 11] Figure 11 is a block diagram of an example of a computing device that can be used in a data processing system associated with a bed.

[0015] [Figure 12] Figures 12 to 16 are block diagrams of exemplary cloud services that can be used in a data processing system associated with a bed. [Figure 13] Figures 12 to 16 are block diagrams of exemplary cloud services that can be used in a data processing system associated with a bed. [Figure 14] Figures 12 to 16 are block diagrams of exemplary cloud services that can be used in a data processing system associated with a bed. [Figure 15] Figures 12 to 16 are block diagrams of exemplary cloud services that can be used in a data processing system associated with a bed. [Figure 16] Figures 从12至16 are block diagrams of exemplary cloud services that can be used in a data processing system associated with a bed.

[0016] [Figure 17] Figure 17 is a block diagram of an example of automating peripheral devices around a bed using a data processing system associated with the bed.

[0017] [Figure 18] Figure 18 is a schematic diagram showing an example of a computing device and a mobile computing device.

[0018] 注:原文中“図12乃至図16”翻译时出现了重复表述,可能原文存在一定问题,这里按照要求忠实翻译。另外,“从12至16”这种表述在中文里不太准确,但为了符合原文结构保留了这种翻译方式。 [Figure 19] Figure 19 is a block diagram of an exemplary system for home automation.

[0019] [Figure 20] Figure 20 is a block diagram of an exemplary system for home automation.

[0020] [Figure 21] Figure 21 is a flowchart of an exemplary process for data processing.

[0021] [Figure 22] Figure 22 is a block diagram of an exemplary process for data processing.

[0022] [Figure 23] Figure 23 is a block diagram of an exemplary process for data processing.

[0023] [Figure 24] Figure 24 is a flowchart of an exemplary process for receiving and transmitting data.

[0024] [Figure 25] Figure 25 is a flowchart of an exemplary process for receiving and transmitting data.

[0025] [Figure 26] Figure 26 is a flowchart of an exemplary process for home automation.

[0026] [Figure 27] Figure 27 is an exemplary process flowchart for home automation.

[0027] [Figure 28] Figure 28 is an exemplary process flowchart for controlling a graphical user interface.

[0028] [Figure 29] Figure 29 shows an example of a graphical user interface. [Modes for carrying out the invention]

[0029] In various drawings, similar reference symbols represent the same elements.

[0030] This specification discloses a sleep monitoring technology. Individual sleep can be enhanced through text-based suggestions and automated actions guided by machine learning, potentially leading to more and better quality sleep for either the population or the individual.

[0031] [Example Airbed Hardware]

[0032] Figure 1 shows an exemplary airbed system 100 including a bed 112. The bed 112 includes at least one air chamber 114, surrounded by an elastic boundary 116 and encapsulated by a durable cotton fabric 118 for the bed. The elastic boundary 116 may include any suitable material, such as foam.

[0033] As shown in Figure 1, the bed 112 may be a two-chamber design having first and second fluid chambers, such as a first air chamber 114A and a second air chamber 114B. In alternative embodiments, the bed 112 may include chambers for use with fluids other than air, as appropriate for the application. In some embodiments, such as a single bed or a children's bed, the bed 112 may include a single air chamber 114A or 114B, or multiple air chambers 114A and 114B. The first and second air chambers 114A and 114B may be in fluid communication with a pump 120. The pump 120 may electrically communicate with a remote control 122 via a control box 124. The control box 124 may include wired or wireless communication interfaces for communicating with one or more devices, including the remote control 122. The control box 124 may be configured to operate the pump 120 to increase or decrease the fluid pressure in the first and second air chambers 114A and 114B based on commands entered by the user using the remote control 122. In some implementations, the control box 124 is integrated into the housing of the pump 120.

[0034] The remote control 122 may include a display 126, an output selection mechanism 128, a pressure increase button 129, and a pressure decrease button 130. The output selection mechanism 128 may allow the user to switch the airflow generated by the pump 120 between the first and second air chambers 114A and 114B, thereby enabling control of multiple air chambers with a single remote control 122 and a single pump 120. For example, the output selection mechanism 128 can be a physical control unit (e.g., a switch or button) or an input control unit displayed on the display 126. Alternatively, separate remote control units may be provided for each air chamber, each including the ability to control multiple air chambers. The pressure increase button 129 and the pressure decrease button 130 may allow the user to increase or decrease the pressure in the air chamber selected by the output selection mechanism 128, respectively. Adjusting the pressure in the selected air chamber may result in a corresponding adjustment to the stiffness (hardness) of each air chamber. In some embodiments, the remote control 122 may be omitted or modified as appropriate depending on the application. For example, in some embodiments, the bed 112 may be controlled by a computer, tablet, smartphone, or other device that is wired or wirelessly connected to the bed 112.

[0035] Figure 2 is a block diagram of an example of various components of an airbed system. For example, these components may be used in an exemplary airbed system 100. As shown in Figure 2, the control box 124 may include a power supply 134, a processor 136, memory 137, a switching mechanism 138, and an analog-to-digital (A / D) converter 140. The switching mechanism 138 may be, for example, a relay or a solid-state switch. In some implementations, the switching mechanism 138 may be located in the pump 120 rather than in the control box 124.

[0036] Pump 120 and remote control 122 can communicate bidirectionally with control box 124. Pump 120 includes a motor 142, a pump manifold 143, a relief valve 144, a first control valve 145A, a second control valve 145B, and a pressure transducer 146. Pump 120 is fluidly connected to a first air chamber 114A and a second air chamber 114B via a first pipe 148A and a second pipe 148B, respectively. The first and second control valves 145A and 145B can be controlled by a switching mechanism 138 and are operable to adjust the fluid flow between pump 120 and the first and second air chambers 114A and 114B, respectively.

[0037] In some implementations, the pump 120 and the control box 124 may be supplied and packaged as a single unit. In some alternative implementations, the pump 120 and the control box 124 may be supplied as physically separate units. In some implementations, the control box 124, the pump 120, or both thereof, may be integrated into or contained within the bed frame or bed support structure supporting the bed 112. In some embodiments, the control box 124, the pump 120, or both thereof, may be located outside the bed frame or bed support structure (as shown in the example in Figure 1).

[0038] The exemplary airbed system 100 shown in Figure 2 includes two air chambers 114A and 114B and a single pump 120. However, other embodiments may include an airbed system having two or more air chambers and one or more pumps incorporated within the airbed system to control the air chambers. For example, a separate pump may be associated with each air chamber of the airbed system, or a single pump may be associated with multiple chambers of the airbed system. The separate pump may allow each air chamber to be inflated or deflated independently and simultaneously. Furthermore, additional pressure transducers may also be incorporated within the airbed system, for example, a separate pressure transducer may be associated with each air chamber.

[0039] During use, the processor 136 may, for example, send a depressurization command to one of the air chambers 114A, 114B, and the switching mechanism 138 may be used to convert the low-voltage command signal sent by the processor 136 into a higher operating voltage sufficient to activate the relief valve (safety valve) 144 of the pump 120 and open the control valves 145A, 145B. Opening the relief valve 144 may allow air to escape from the air chamber 114A or 114B through the respective air pipes 148A or 148B. During deflation, the pressure transducer 146 may transmit pressure readings to the processor 136 via the A / D converter 140. The A / D converter 140 may receive analog information from the pressure transducer 146 and convert this analog information into digital information usable by the processor 136. The processor 136 may transmit this digital signal to the remote control 122 to update the display 126 in order to inform the user of the pressure information.

[0040] As another example, the processor 136 may send a pressure increase command. The pump motor 142 may be energized in response to the pressure increase command and electronically actuate the corresponding valves 145A, 145B to supply air to the designated one of the air chambers 114A, 114B via the air pipes 148A, 148B. While air is being supplied to the designated air chamber 114A or 114B to increase the chamber's stiffness (rigidity), the pressure transducer 146 may sense the pressure in the pump manifold 143. In this case as well, the pressure transducer 146 may transmit the pressure reading to the processor 136 via the A / D converter 140. The processor 136 may use the information received from the A / D converter 140 to determine the difference between the actual pressure in the air chamber 114A or 114B and the desired pressure. The processor 136 may transmit the digital signal to the remote control 122 to update the display 126 in order to inform the user of the pressure information.

[0041] Generally speaking, during the expansion or contraction process, the pressure sensed within the pump manifold 143 can provide an approximation of the pressure in each air chamber that is in fluid communication with the pump manifold 143. An exemplary method for obtaining a pump manifold pressure reading substantially equal to the actual pressure in the air chambers comprises the steps of turning off the pump 120, allowing the pressures in the air chambers 114A or 114B and the pump manifold 143 to equalize, and then sensing the pressure in the pump manifold 143 using a pressure transducer 146. This allows sufficient time for the pressures in the pump manifold 143 and the chambers 114A or 114B to equalize, which can result in a pressure reading that is an accurate approximation of the actual pressure in the air chambers 114A or 114B. In some implementations, the pressures in the air chambers 114A and / or 114B may be continuously monitored using multiple pressure sensors (not shown).

[0042] In some implementations, the information collected by the pressure transducer 146 can be analyzed to determine various states of a person lying in bed 112. For example, the processor 136 may use the information collected by the pressure transducer 146 to determine the heart rate or respiratory rate of a person lying in bed 112. For example, the user may be lying on one side of bed 112, which includes a chamber 114A. The pressure transducer 146 may monitor pressure fluctuations in the chamber 114A, and this information may be used to determine the user's heart rate and / or respiratory rate. As another example, additional processing may be performed using the collected data to determine the person's sleep state (e.g., wakefulness, light sleep, deep sleep). For example, the processor 136 may determine when a person falls asleep, when they are asleep, and the person's various sleep states.

[0043] Additional information relating to the user of the airbed system 100, which can be determined using the information collected by the pressure transducer 146, includes the user's movements, the user's presence on the surface of the bed 112, the user's weight, the user's cardiac arrhythmia, and temporary apnea. Taking the detection of the user's presence as an example, the pressure transducer 146 may be used to detect the presence of a user on the bed 112, for example, by determining a change in total pressure and / or by one or more of the respiratory rate signal, heart rate signal, and / or other biometric signals. For example, a simple pressure sensing process may identify an increase in pressure as indicating the presence of a user on the bed 112. As another example, the processor 136 may determine that a user is present on the bed 112 if the detected pressure increases above a certain threshold (a threshold to indicate that a person or other object exceeding a certain weight is placed on the bed 112). As yet another example, the processor 136 may identify an increase in pressure in combination with detected slight rhythmic fluctuations in pressure as corresponding to the presence of a user on the bed 112. The presence of rhythmic fluctuations can be identified as being attributable to the user's breathing or heartbeat (or both). Breathing or heartbeat detection can distinguish the user present in bed from other objects (such as a suitcase) placed on the bed.

[0044] In some implementations, pressure fluctuations can be measured in the pump 120. For example, one or more pressure sensors may be placed in one or more internal cavities of the pump 120 to detect pressure fluctuations within the pump 120. Pressure fluctuations detected in the pump 120 may indicate pressure fluctuations in one or both chambers 114A and 114B. One or more sensors placed in the pump 120 may be in fluid communication with one or both chambers 114A and 114B, and the sensors may operate to determine the pressures within chambers 114A and 114B. The control box 124 may be configured to determine at least one vital sign (e.g., heart rate, respiratory rate) based on the pressure in chamber 114A or chamber 114B.

[0045] In some implementations, the control box 124 may analyze pressure signals detected by one or more pressure sensors to determine the heart rate, respiratory rate, and / or other vital signs of a user lying or sitting on the chamber 114A or chamber 114B. More specifically, when a user lies on the bed 112 positioned above the chamber 114A, each of the user's heart rate, respiration, and other movements may generate forces on the bed 112 that are transmitted to the chamber 114A. As a result of the force input to the chamber 114A due to the user's movements, waves may propagate through the chamber 114A into the pump 120. Pressure sensors located in the pump 120 may detect these waves, and the pressure signals output by the sensors may indicate heart rate, respiratory rate, or other information about the user.

[0046] Regarding sleep state, the airbed system 100 can determine the user's sleep state by using various biometric signals, such as heart rate, respiration, and / or user movement. While the user is sleeping, the processor 136 can receive one or more of the user's biometric signals (e.g., heart rate, respiration, and movement) and determine the user's current sleep state based on the received biometric signals. In some implementations, signals indicating pressure fluctuations in one or both chambers 114A and 114B may be amplified and / or filtered to allow for more accurate detection of heart rate and respiration.

[0047] The control box 124 may execute a pattern recognition algorithm or other calculation method based on the amplified and filtered pressure signal to determine the user's heart rate and respiratory rate. For example, the algorithm or calculation method may be based on the assumption that the heart rate portion of the signal has a frequency in the range of 0.5 to 4.0 Hz and the respiratory rate portion of the signal has a frequency in the range of less than 1 Hz. The control box 124 may also be configured to determine other user characteristics based on the received pressure signal, such as blood pressure, rocking and rotational movements, rolling movements, limb movements, weight, the presence or absence of the user, and / or the user's identity. A technique for monitoring a user's sleep using heart rate information, respiratory rate information, and other user information is disclosed in U.S. Patent Application Publication No. 2010 / 0170043 by Stephen J. Young et al., entitled “Apparatus for Monitoring Vital Signs.” The entire contents of that publication are incorporated herein by reference.

[0048] For example, a pressure transducer 146 may be used to monitor the air pressure in chambers 114A and 114B of bed 112. When the user on bed 112 is not moving, changes in the air pressure in air chamber 114A or 114B may be relatively small and may be due to breathing and / or heartbeat. However, when the user on bed 112 is moving, the air pressure in the mattress may fluctuate by a much larger amount. Therefore, the pressure signal generated by the pressure transducer 146 and received by the processor 136 may be filtered and shown as corresponding to movement, heartbeat, or breathing.

[0049] In some implementations, instead of performing data analysis within the control box 124 using processor 136, a digital signal processor (DSP) may be provided to analyze the data collected by the pressure transducer 146. Alternatively, the data collected by the pressure transducer 146 may be sent to a cloud-based computing system for remote analysis.

[0050] In some implementations, the exemplary airbed system 100 further comprises a temperature controller configured to raise, lower, or maintain the bed temperature for, for example, user comfort. For example, a pad may be placed on or as part of the top of the bed 112, or on or as part of the top of one or both of the chambers 114A and 114B. Air may be pushed through the pad to provide ventilation to cool the user of the bed. Conversely, the pad may include a heating element that can be used to keep the user warm. In some implementations, the temperature controller may receive temperature readings from the pad. In some implementations, separate pads may be used on different sides of the bed 112 (e.g., corresponding to the locations of the chambers 114A and 114B) to provide different temperature control on different sides of the bed.

[0051] In some implementations, a user of the airbed system 100 may use an input device such as a remote control 122 to input a desired temperature for the surface (or part of the surface) of the bed 112. The desired temperature may be encapsulated in a command data structure that includes the desired temperature and identifies the temperature controller as the desired controlled component. This command data structure may then be transmitted to the processor 136 via Bluetooth® or another suitable communication protocol. In various examples, the command data structure may be encrypted before transmission. The temperature controller may then be configured to increase or decrease the temperature of the pad in response to the temperature input by the user to the remote control 122.

[0052] In some implementations, data may be sent back from a component to the processor 136, or to one or more display devices such as the display 126. For example, the current temperature, bed pressure, current position of the base, or other information determined by the temperature controller's sensor element may be sent to the control box 124. The control box 124 may then send the received information to the remote control 122, where it can be displayed to the user (for example, on the display 126).

[0053] In some implementations, the exemplary airbed system 100 further comprises an adjustable base and an articulated controller configured to adjust the position of the bed (e.g., bed 112) by adjusting the adjustable base that supports the bed. For example, the articulated controller can adjust the bed 112 from a flat position to a position in which the head portion of the mattress of the bed is tilted upward (e.g., to facilitate the user sitting on the bed and / or watching television). In some implementations, the bed 112 includes several independently articulated sections. For example, portions of the bed corresponding to the positions of chambers 114A and 114B may be articulated independently of each other to allow one person to rest in a first position (e.g., a flat position) while a second person rests in a second position (e.g., a reclined position with the head tilted diagonally above the waist) while one person rests on the surface of the bed 112. In some implementations, two different beds (e.g., two twin beds placed next to each other) may have separate positions. The base of the bed 112 may include two or more zones that can be adjusted independently. The joint movement controller may also be configured to provide different levels of massage to one or more users on the bed 112.

[0054] [Example of a bed in a bedroom environment]

[0055] Figure 3 shows an exemplary environment 300 including a bed 302 that communicates with multiple devices in and around the home. In the illustrated example, the bed 302 includes a pump 304 for controlling the air pressure in two air chambers 306a and 306b (as previously described with respect to air chambers 114A-114B). The pump 304 further includes a circuit for controlling the inflation and deflation functions performed by the pump 304. The circuit is further programmed to detect fluctuations in the air pressure of air chambers 306a-b, and uses these detected fluctuations to identify the presence of user 308 in the bed, user 308's sleep state, user 308's movements, and user 308's biometric signals such as heart rate and respiratory rate. In the illustrated example, the pump 304 is located within the support structure of the bed 302, and a control circuit 334 for controlling the pump 304 is integrated with the pump 304. In some implementations, the control circuit 334 is physically separate from the pump 304 and communicates with the pump 304 wirelessly or via a wired connection. In some implementations, the pump 304 and / or the control circuit 334 are located outside the bed 302. In some implementations, various control functions can be performed by systems located in various physical locations. For example, the circuit for controlling the operation of the pump 304 may be located inside the pump casing of the pump 304, while the control circuit 334 for performing other functions related to the bed 302 may be located inside another part of the bed 302 or outside the bed 302. As another example, the control circuit 334 located inside the pump 304 may communicate with a remote control circuit 334 via a LAN or WAN (e.g., the Internet). As yet another example, the control circuit 334 may be included in the control box 124 shown in Figures 1 and 2.

[0056] In some implementations, one or more devices other than, or in addition to, pump 304 and control circuit 334 may be used to identify the user's presence, sleep state, movement, and biocharacteristic signals in the bed. For example, bed 302 may include a second pump in addition to pump 304, and each of the two pumps may be connected to one of the air chambers 306a and 306b, respectively. For example, pump 304 may be in fluid communication with air chamber 306b and control the expansion and contraction of air chamber 306b, and may detect user signals of the user located on air chamber 306b, such as presence, sleep state, movement, and biocharacteristic signals. On the other hand, the second pump may be in fluid communication with air chamber 306a and control the expansion and contraction of air chamber 306a, and may also detect user signals of the user located on air chamber 306a.

[0057] As another example, the bed 302 may include one or more pressure-sensitive pads or pressure-sensitive surface portions that are operable to detect movement, including the presence of a user, user movement, breathing, and heart rate. For example, a first pressure-sensitive pad may be incorporated into the surface of the bed 302 on the left side of the bed 302 where a first user normally sleeps, and a second pressure-sensitive pad may be incorporated into the surface of the bed 302 on the right side of the bed 302 where a second user normally sleeps. The movement detected by the one or more pressure-sensitive pads or pressure-sensitive surface portions may be used by the control circuit 334 to identify the user's sleep state, presence in the bed, or biometric signals.

[0058] In some implementations, information detected by the bed (e.g., motion information) is processed by a control circuit 334 (e.g., a control circuit 334 integrated with the pump 304) and provided to one or more user devices, such as a user device 310, for presentation to user 308 or other users. In the example shown in Figure 3, user device 310 is a tablet device. However, in some implementations, user device 310 may be a personal computer, a smartphone, a smart TV (e.g., TV 312), or another user device capable of wired or wireless communication with the control circuit 334. User device 310 may communicate with the control circuit 334 of bed 302 via a network or via direct point-to-point communication. For example, the control circuit 334 may be connected to a LAN (e.g., via a Wi-Fi router) and communicate with user device 310 via the LAN. In another example, both the control circuit 334 and user device 310 may be connected to the Internet and communicate via the Internet. For example, the control circuit 334 may connect to the internet via a WiFi router, and the user device 310 may connect to the internet via communication with a cellular communication system. As another example, the control circuit 334 may communicate directly with the user device 310 via a wireless communication protocol such as Bluetooth®. As yet another example, the control circuit 334 may communicate with the user device 310 via a wireless communication protocol such as ZigBee, Z-Wave, infrared, or other wireless communication protocols appropriate for the application. As yet another example, the control circuit 334 may communicate with the user device 310 via a wired connection such as a USB connector, serial / RS232, or other wired connection appropriate for the application.

[0059] The user device 310 may display various information and statistics related to sleep or user 308's interaction with bed 302. For example, the user interface displayed by the user device 310 may present information including the amount of sleep user 308 has over a certain period (e.g., one night, one week, one month), the amount of deep sleep, the ratio of deep sleep to restless sleep, the time elapsed between user 308 getting into bed and falling asleep, the total time spent in bed 302 over a given period, user 308's heart rate over a certain period, user 308's respiratory rate over a certain period, or other information related to user interaction with bed 302 by user 308 or one or more other users of bed 302. In some implementations, information from multiple users may be presented to the user device 310; for example, information from a first user located on air chamber 306a may be presented together with information from a second user located on air chamber 306b. In some implementations, the information presented on the user device 310 may change depending on the user's age. For example, the information presented on the user device 310 may evolve with the user's age, and different information may be presented on the user device 310 as the user 308 ages from child to adult.

[0060] The user device 310 may also be used as an interface for the control circuit 334 of the bed 302 to allow user 302 to input information. Information input by user 308 may be used by the control circuit 334 to provide better information to the user or to various control signals for controlling the functions of the bed 302 or other devices. For example, user 308 may input information such as weight, height, and age, and the control circuit 334 may use this information to provide the user with a comparison of the user's tracked sleep information with the sleep information of other people with similar weight, height, and / or age. As another example, user 308 may use the user device 310 as an interface to control the air pressure of the air chambers 306a and 306b, to control various reclining or tilting positions of the bed 302, to control the temperature of one or more surface temperature control devices of the bed 302, or to allow the control circuit 334 to generate control signals for other devices (as described in more detail below).

[0061] In some implementations, the control circuit 334 of the bed 302 (for example, the control circuit 334 integrated into the pump 304) may communicate with other first, second, or third-party devices or systems in addition to, or instead of, the user device 310. For example, the control circuit 334 may communicate with the television 312, the lighting system 314, the thermostat 316, the security system 318, or other household appliances such as the oven 322, the coffee maker 324, the lamp 326, and the night light 328. Other examples of devices and / or systems that the control circuit 334 may communicate with include a system for controlling the blinds 330, one or more devices for detecting or controlling the state of one or more doors 332 (e.g., detecting whether a door is open or not, detecting whether a door is locked or not, or automatically locking a door), and a system for controlling the garage door 320 (e.g., a control circuit 334 integrated with a garage door opener to identify the open / closed state of the garage door 320 and cause the garage door opener to open or close the garage door 320). Communication between the control circuit 334 of the bed 302 and other devices may occur via a network (e.g., LAN or the Internet) or as point-to-point communication (e.g., Bluetooth®, wireless communication, or wired connection). In some implementations, the control circuit 334 of different beds 302 may communicate with different sets of devices. For example, a kids' bed may not communicate with and / or control the same devices as an adult bed. In some embodiments, the bed 302 may evolve with the user's age such that the control circuit 334 of the bed 302 communicates with different devices as a function of the user's age.

[0062] The control circuit 334 may receive information and inputs from other devices / systems and use such received information and inputs to control the operation of the bed 302 or other devices. For example, the control circuit 334 may receive information from a thermostat 316 indicating the current ambient temperature of the house or room in which the bed 302 is located. The control circuit 334 may use this received information (along with other information) to determine whether to raise or lower the temperature of all or part of the surface of the bed 302. The control circuit 334 may then instruct the heating or cooling mechanism of the bed 302 to raise or lower the surface temperature of the bed 302. For example, user 308 may indicate a desired sleep temperature of 74 degrees Fahrenheit, while a second user of the bed 302 may indicate a desired sleep temperature of 72 degrees Fahrenheit. The thermostat 316 may indicate to the control circuit 334 that the current temperature of the bedroom is 72 degrees Fahrenheit. The control circuit 334 may recognize that user 308 has indicated a desired sleep temperature of 74 degrees Fahrenheit and may send a control signal to a heating pad on the user 308's side of the bed 302 to raise the temperature of a portion of the bed surface. It is positioned to raise the temperature of the user 308's sleeping surface to the desired temperature.

[0063] The control circuit 334 may also generate control signals to control other devices and propagate such control signals to those other devices. In some implementations, the control signals are generated based on information collected by the control circuit 334, including information about user interactions with the bed 302 by user 308 and / or one or more other users. In some implementations, information collected from one or more other devices other than the bed 302 is used when generating control signals. For example, information about environmental occurrences (e.g., ambient temperature, ambient noise level, ambient light level), time, year, day of the week, or other information may be used when generating control signals for various devices that communicate with the control circuit 334 of the bed 302. For example, information about the time may be combined with information about user 308's movement and presence in the bed to generate a control signal for the lighting system 314. In some implementations, instead of providing control signals to one or more other devices, or in addition to doing so, the control circuit 334 may transmit collected information (e.g., information related to user movement, presence in bed, sleep state, or user 308's bio-characteristic signals) to one or more other devices, allowing those devices to utilize the collected information when generating control signals. For example, the control circuit 334 of bed 302 may provide a central controller (not shown) with information regarding user interaction with bed 302 by user 308. The central controller may utilize the provided information to generate control signals for various devices, including bed 302.

[0064] Continuing with Figure 3, the control circuit 334 of bed 302 may generate control signals to control the operation of other devices in response to information collected by the control circuit 334, including the presence of user 308 in bed, the user's sleep state 308, and other factors, and may transmit such control signals to the other devices. For example, the control circuit 334 integrated with the pump 304 may detect features of the bed 302 mattress, such as an increase in pressure in the air chamber 306b, and use this detected increase in air pressure to determine that user 308 is on bed 302. In some implementations, the control circuit 334 may identify user 308's heart rate or respiratory rate to identify that the increase in pressure is due to a person sitting, lying down, or resting on bed 302, rather than an inanimate object (such as a suitcase) being placed on the bed. In some implementations, information indicating the user's presence in bed may be combined with other information to identify user 308's current or future possible state. For example, a user's presence in bed detected at 11:00 AM may indicate that the user is sitting in bed (e.g., tying their shoelaces or reading a book) and is not yet planning to sleep. On the other hand, a user's presence in bed detected at 10:00 PM may indicate that user 308 is in bed and intends to sleep soon. As another example, if control circuit 334 detects that user 308 has left bed 302 at 6:30 AM (e.g., that user 308 has woken up for the day), and then detects user 308's presence in bed at 7:30 AM, control circuit 334 may use (understand) this information not as an indication that user 308 intends to stay in bed for an extended period, but rather as the newly detected presence of the user in bed is likely to be temporary (e.g., while user 308 is tying their shoelaces before going to work).

[0065] In some implementations, the control circuit 334 may use the collected information (including information related to user interaction with bed 302 by user 308, environmental information, time information, and input received from user) to identify user 308's usage patterns. For example, the control circuit 334 may use information collected over a period of time indicating user 308's presence in bed and sleep state to identify the user's sleep patterns. For example, based on information indicating the user's presence collected over a week and user 308's biometric signaling, the control circuit 334 may identify that user 308 generally goes to bed between 9:30 p.m. and 10:00 p.m., generally falls asleep between 10:00 p.m. and 11:00 p.m., and generally wakes up between 6:30 a.m. and 6:45 a.m. The control circuit 334 may use the user's identification patterns to better process and identify user interaction with bed 302 by user 308.

[0066] For example, given the bed presence, sleep, and wake patterns of user 308 in the above example, if it is detected that user 308 is in bed at 3:00 p.m., the control circuit 334 may determine that the user's presence in bed is merely temporary and use this determination to generate a different control signal than one that would be generated if the control circuit 334 determined that user 308 was in bed in the evening. In another example, if the control circuit 334 detects that user 308 has gotten out of bed at 3:00 a.m., the control circuit 334 may use user 308's identification pattern to determine that the user was only temporarily awake (for example, to use the toilet or get a glass of water) and not to have gotten up for the day. In contrast, if the control circuit 334 identifies that user 308 got out of bed 302 at 6:40 a.m., the control circuit 334 may determine that the user has woken up for the day and may generate a different set of control signals than would be generated if it were determined that user 308 had only temporarily gotten out of bed (as in the case of user 308 getting out of bed 302 at 3:00 a.m.). For other users 308, getting out of bed 302 at 3:00 a.m. may be a normal time to wake up, so the control circuit 334 may learn and respond accordingly.

[0067] As described above, the control circuit 334 of bed 302 can generate control signals for the control functions of various other devices. The control signals can be generated, at least in part, based on the detected interaction between user 308 and bed 302, and other information including time, date, and temperature. For example, the control circuit 334 can communicate with television 312, receive information from television 312, and generate control signals to control the functions of television 312. For example, the control circuit 334 can receive an indication from television 312 that television 312 is currently on. If television 312 is located in a different room from bed 302, the control circuit 334 can generate a control signal to turn off television 312 when it determines that user 308 has gone to sleep at night. For example, if the presence of user 308 on bed 302 is detected within a specific time range (e.g., between 8:00 PM and 7:00 AM) and lasts longer than a threshold time (e.g., 10 minutes), the control circuit 334 may use this information to determine that user 308 is in bed for sleep. If television 312 is on (indicated by communication received by control circuit 334 on bed 302 from television 312), control circuit 334 may generate a control signal to turn off television 312. The control signal can then be transmitted to television (e.g., via a directed communication link between television 312 and control circuit 334, or via a network). As another example, instead of turning off television 312 in response to the detection of a user's presence in bed, control circuit 334 may generate a control signal to lower the volume of television 312 by a predetermined amount.

[0068] As another example, when the control circuit 334 detects that user 308 has left bed 302 within a specified time range (for example, between 6:00 AM and 8:00 AM), it may generate a control signal to turn on television 312 and tune it to a pre-specified channel (for example, user 308 indicates a preference to watch the morning news when getting out of bed in the morning). The control circuit 334 may generate a control signal and transmit it to television 312 to turn on television 312 and tune it to a desired channel (which may be stored in the control circuit 334, television 312, or another location). As yet another example, when the control circuit 334 detects that user 308 has woken up that day, it may generate and transmit a control signal to turn on television 312 and start playback of a previously recorded program from a digital video recorder (DVR) communicating with television 312.

[0069] As another example, if the television 312 is in the same room as the bed 302, the control circuit 334 does not turn off the television 312 in response to detecting the user's presence in bed. Rather, the control circuit 334 may turn off the television 312 by generating and transmitting a control signal in response to determining that the user 308 is asleep. For example, the control circuit 334 may monitor the user 308's biometric signals (e.g., movement, heart rate, respiratory rate) to determine that the user 308 has fallen asleep. When it detects that the user 308 is asleep, the control circuit 334 generates and transmits a control signal to turn off the television 312. As another example, the control circuit 334 may generate a control signal to turn off the television 312 after a threshold time has elapsed since the user 308 fell asleep (e.g., 10 minutes after the user fell asleep). As yet another example, the control circuit 334 generates a control signal to lower the volume of the television 312 after determining that the user 308 is asleep. As yet another example, the control circuit 334, in response to the determination that user 308 is asleep, generates and transmits a control signal to gradually lower the volume of the television over a period of time, and then turns off the television.

[0070] In some implementations, the control circuit 334 can interact with other media devices such as computers, tablets, smartphones, and stereo systems. For example, when the control circuit 334 detects that user 308 is asleep, it may generate a control signal and send it to the user device 310, which may turn off the user device 310 or lower the volume of a video or audio file being played on the user device 310.

[0071] The control circuit 334 can further communicate with the lighting system 314, receive information from the lighting system 314, and generate control signals to control the functions of the lighting system 314. For example, when it detects the presence of a user on bed 302 for a longer period than a threshold time (e.g., 10 minutes) within a specific time frame (e.g., between 8:00 p.m. and 7:00 a.m.), the control circuit 334 of bed 302 may determine that user 308 is in bed for sleep. In response to this determination, the control circuit 334 may generate a control signal to turn off the lights in one or more rooms other than the room where bed 302 is located. The control signal can then be transmitted to the lighting system 314, which may execute it to turn off the lights in the indicated room. For example, the control circuit 334 may generate and transmit a control signal to turn off the lights in all general rooms, rather than other bedrooms. As another example, in response to the determination that user 308 is in bed for sleep, the control signal generated by the control circuit 334 may indicate that the lights in all rooms except the room where bed 302 is located should be turned off, and that one or more lights located outside the house, including bed 302, should also be turned off. Furthermore, in response to the determination that user 308 is in bed or that user 308 is asleep, the control circuit 334 may generate and transmit a control signal to turn on the night light 328. As yet another example, the control circuit 334 may generate a first control signal to turn off a first set of lights (e.g., lights in general rooms) in response to the detection of the user's presence in bed, and a second control signal to turn off a second set of lights (e.g., lights in the room where bed 302 is located) in response to the detection that user 308 is asleep.

[0072] In some implementations, in response to the determination that user 308 is in bed for sleep, the control circuit 334 of bed 302 may generate a control signal that causes the lighting system 314 to implement a sunset lighting pattern in the room where bed 302 is located. The sunset lighting pattern may include dimming the lights (gradually over time or abruptly) in combination with changing the color of the lighting in the bedroom environment, such as adding an amber hue to the bedroom lighting. The sunset lighting pattern may help user 308 fall asleep when the control circuit 334 determines that user 308 is in bed for sleep.

[0073] The control circuit 334 may also be configured to implement a sunrise illumination pattern when user 308 wakes up in the morning. The control circuit 334 may determine that user 308 has woken up for the day by detecting, for example, that user 308 has left bed 302 (i.e., is no longer in bed 302) during a specified time frame (e.g., between 6:00 a.m. and 8:00 a.m.). Alternatively, the control circuit 334 may monitor user 308's movement, heart rate, respiratory rate, or other biometric signals to determine that user 308 is awake even if user 308 has not left bed. If the control circuit 334 detects that the user is awake during the specified time frame, the control circuit 334 may determine that user 308 has woken up for the day. The specified time frame may be based, for example, on previously recorded information about the user's presence in bed collected over a period of time (e.g., two weeks). This may indicate that user 308 typically wakes up between 6:30 a.m. and 7:30 a.m. In response to the control circuit 334 determining that user 308 is awake, the control circuit 334 may generate a control signal to cause the lighting system 314 to implement a sunrise lighting mode in the bedroom where the bed 302 is located. The sunrise lighting mode may include, for example, turning on a light (e.g., lamp 326, or other lights in the bedroom). The sunrise lighting mode may further include gradually increasing the level of lighting in the room where the bed 302 is located (or one or more other rooms). The sunrise lighting mode may also include turning on only lights of a specified color. For example, the sunrise lighting mode may include illuminating the bedroom with blue light to gently assist user 308 in waking up and becoming active.

[0074] In some implementations, the control circuit 334 may generate different control signals to control the operation of one or more components, such as the lighting system 314, depending on the time when user interaction with the bed 302 is detected. For example, the control circuit 334 may use historical user interaction information about the interaction between user 308 and bed 302 to determine that user 308 usually falls asleep between 10:00 p.m. and 11:00 p.m. and wakes up between 6:30 a.m. and 7:30 a.m. Using this information, the control circuit 334 may generate a first set of control signals to control the lighting system 314 if it is detected that user 308 got out of bed at 3:00 a.m., and a second set of control signals to control the lighting system 314 if it is detected that user 308 got out of bed after 6:30 a.m. For example, if user 308 gets out of bed before 6:30 a.m., the control circuit 334 may turn on the lights that guide user 308 to the toilet. As another example, if user 308 gets out of bed before 6:30 a.m., the control circuit 334 may turn on lights to guide user 308 to the kitchen (this may include, for example, turning on the night light 328, the under-bed light, or the lamp 326).

[0075] As another example, if user 308 gets out of bed after 6:30 a.m., control circuit 334 may generate a control signal to cause the lighting system 314 to start sunrise lighting mode, or to turn on one or more lights in the bedroom or other rooms. In some implementations, if it is detected that user 308 gets out of bed before a designated morning wake-up time for that user, control circuit 334 may cause the lighting system 314 to turn on a light that is weaker (dimmer) than the light that would be turned on by the lighting system 314 if it were detected that user 308 gets out of bed after the designated morning wake-up time. Turning on only weak (dim) lighting when user 308 gets out of bed at night (i.e., before user 308's normal wake-up time) can prevent other residents of the house from being woken by the lights, while still allowing user 308 to see (provide a view) to reach the toilet, kitchen, or another destination within the house.

[0076] The history of user interaction information regarding the interaction between user 308 and bed 302 can be used to identify the user's sleep and wake timeframes. For example, the user's time spent in bed and sleep time can be determined for a set period (e.g., two weeks, one month). The control circuit 334 can then identify the typical time range or timeframe in which user 308 goes to bed, the typical timeframe in which user 308 falls asleep, and the typical timeframe in which user 308 wakes up (in some cases, the timeframe in which user 308 wakes up may differ from the timeframe in which user 308 actually gets out of bed). In some implementations, buffer time may be added to these timeframes. For example, if it is identified that the user typically goes to bed between 10:00 p.m. and 10:30 p.m., a 30-minute buffer may be added to the timeframe in each direction, and detection of the user getting into bed between 9:30 p.m. and 11:00 p.m. may be interpreted as user 308 going to bed at night. As another example, the detection of user 308's presence in bed within a time frame that begins 30 minutes before the earliest typical time user 308 goes to bed and extends until the user's typical wake-up time (e.g., 6:30 a.m.) may be interpreted as user 308 going to bed at night. For example, if a user typically goes to bed between 10:00 p.m. and 10:30 p.m., then if the user's presence in bed is detected at 12:30 a.m. (0:30 a.m.) on a given night, this may be interpreted as user 308 going to bed at night, even though it is beyond the user's typical bedtime frame, because it occurs before the user's usual wake-up time. In some implementations, different time frames are identified for different times of the year (e.g., bedtime is earlier in winter than in summer) or different days of the week (e.g., users wake up earlier on weekdays than on weekends).

[0077] The control circuit 334 can distinguish between short-term presence on the bed 302 (such as a nap) and prolonged sleep (such as at night) by sensing the duration of the user 308's presence. In some cases, the control circuit 334 can distinguish between short-term sleep (such as a nap) and prolonged sleep (such as at night) by sensing the duration of the user 308's sleep. For example, the control circuit 334 may set a time threshold so that if the user 308 is detected on the bed 302 for longer than the threshold, the user 308 is considered to have slept at night. In some cases, the threshold may be approximately 2 hours, so if the user 308 is detected on the bed 302 for more than 2 hours, the control circuit 334 registers it as a prolonged sleep event. In other cases, the threshold may be longer or shorter than 2 hours.

[0078] The control circuit 334 can detect recurring long-duration sleep events in order to automatically determine the user 308's typical bedtime range without requiring the user 308 to input a bedtime range. This allows the control circuit 334 to accurately estimate the times when the user 308 is likely to go to bed due to long-duration sleep events, regardless of whether the user 308 typically goes to bed using a traditional or non-traditional sleep schedule. The control circuit 334 can then use its knowledge of the user 308's bedtime range to control one or more components (including the bed 302 and / or non-bed peripherals) differently based on its perception of being in bed within or outside the bedtime range.

[0079] In some examples, the control circuit 334 may automatically determine the user 308's bedtime range without requiring user input. In some examples, the control circuit 334 may automatically determine the user 308's bedtime range in combination with user input. In some examples, the control circuit 334 may directly set the bedtime range according to user input. In some examples, the control circuit 334 may associate different bedtimes with different days of the week. In each of these examples, the control circuit 334 may control one or more components (such as the lighting system 314, thermostat 316, security system 318, oven 322, coffee maker 324, lamp 326, and night light 328) as a function of the detected presence in bed and the bedtime range.

[0080] The control circuit 334 can further communicate with the thermostat 316, receive information from the thermostat 316, and generate control signals to control the functions of the thermostat 316. For example, user 308 may indicate different temperature preferences at different times depending on user 308's sleep state or presence in bed. For example, user 308 may prefer ambient temperatures of 72 degrees Fahrenheit when getting out of bed, 70 degrees Fahrenheit when in bed but awake, and 68 degrees Fahrenheit when asleep. The control circuit 334 of bed 302 can detect user 308's presence in bed at night and determine that user 308 is asleep. In response to this determination, the control circuit 334 can generate a control signal to the thermostat to change the temperature to 70 degrees Fahrenheit. Next, the control circuit 334 can transmit this control signal to the thermostat 316. If the control circuit 334 detects that user 308 is asleep or in bed during the designated bedtime range, it may generate and transmit a control signal to cause the thermostat 316 to change the temperature to 68 degrees Fahrenheit. The following morning, if the control circuit 334 determines that the user has gotten up (for example, that user 308 got out of bed after 6:30 a.m.), it may generate and transmit a control signal to cause the thermostat 316 to change the temperature to 72 degrees Fahrenheit.

[0081] In some implementations, the control circuit 334 may also generate control signals to change the temperature of one or more heating or cooling elements on the surface of the bed 302 at various points in time, in response to user interaction with the bed 302 or at various pre-programmed times. For example, when the control circuit 334 detects that the user 308 has fallen asleep, it may activate a heating element to raise the temperature of one side of the bed 302's surface to 73 degrees Fahrenheit. As another example, when it determines that the user 308 has woken up for the day, the control circuit 334 may turn off the heating or cooling element. As yet another example, the user 308 may pre-program various times at which the bed surface temperature should rise or fall. For example, the user may program the bed 302 to raise the surface temperature to 76 degrees Fahrenheit at 10:00 p.m. and lower it to 68 degrees Fahrenheit at 11:30 p.m.

[0082] In some implementations, in response to the detection of user 308's presence in bed and / or the detection that user 308 is asleep, the control circuit 334 may cause the thermostat 316 to change the temperature of different rooms to different values. For example, in response to the determination that user 308 is in bed at night, the control circuit 334 may generate and transmit a control signal that causes the thermostat 316 to set the temperature of one or more bedrooms in the house to 72 degrees Fahrenheit and the temperature of other rooms to 67 degrees Fahrenheit.

[0083] The control circuit 334 may also receive temperature information from the thermostat 316 and use this temperature information to control the function of the bed 302 or other devices. For example, as described above, the control circuit 334 may adjust the temperature of the heating elements included in the bed 302 in response to the temperature information received from the thermostat 316.

[0084] In some implementations, the control circuit 334 may generate and transmit control signals to control other temperature control systems. For example, in response to a determination that user 308 has woken up for the day, the control circuit 334 may generate and transmit a control signal to activate the underfloor heating element. For instance, in response to a determination that user 308 has woken up for the day, the control circuit 334 may turn on the underfloor heating system in the master bedroom.

[0085] The control circuit 334 can further communicate with the security system 318, receive information from the security system 318, and generate control signals to control the functions of the security system 318. For example, in response to detection that user 308 has gone to sleep at night, the control circuit 334 can generate a control signal to cause the security system to activate or deactivate its security functions. The control circuit 334 can then transmit this control signal to the security system 318 to activate it. As another example, in response to determination that user 308 has woken up that day (for example, that user 308 is no longer in bed 302 after 6:00 a.m.), the control circuit 334 can generate and transmit a control signal to disable the security system 318. In some implementations, the control circuit 334 may, in response to the detection of the presence of user 308 in bed, generate and transmit a first set of control signals to the security system 318 to activate a first set of security functions, and in response to the detection that user 308 has fallen asleep, generate and transmit a second set of control signals to the security system 318 to activate a second set of security functions.

[0086] In some implementations, the control circuit 334 may receive alerts from the security system 318 (and / or a cloud service associated with the security system 318) and display these alerts to the user 308. For example, the control circuit 334 may detect that the user 308 is in bed at night and, in response, generate and transmit control signals to activate or deactivate the security system 318. The security system may then detect a security breach (e.g., someone opens the door 332 without entering a security code, or someone opens a window while the security system 318 is activated). The security system 318 may communicate the security breach to the control circuit 334 of the bed 302. In response to receiving the communication from the security system 318, the control circuit 334 may generate a control signal to warn the user 308 about the security breach. For example, the control circuit 334 may vibrate the bed 302. As another example, the control circuit 334 may articulate a part of the bed 302 (e.g., raise or lower the head section) to wake the user 308 and warn the user of a security breach. As yet another example, the control circuit 334 may generate and transmit a control signal to cause the lamp 326 to flash at regular intervals to warn the user 308 of a security breach. As yet another example, the control circuit 334 may warn the user 308 in one bed 302 of a security breach in another bed's bedroom, such as an open window in a child's bedroom. As yet another example, the control circuit 334 may send a warning to a garage door controller (e.g., to close and lock the door). As yet another example, the control circuit 334 may send a warning to deactivate the security.

[0087] The control circuit 334 can further generate and transmit control signals to control the garage door 320 and receive information indicating the state of the garage door 320 (i.e., whether it is open or closed). For example, in response to the determination that user 308 is in bed at night, the control circuit 334 can generate and transmit a request to a garage door opener or another device capable of sensing whether the garage door 320 is open or closed. The control circuit 334 can request information regarding the current state of the garage door 320. If the control circuit 334 receives a response (e.g., from the garage door opener) indicating that the garage door 320 is open, the control circuit 334 can notify user 308 that the garage door is open, or generate a control signal to cause the garage door opener to close the garage door 320. For example, the control circuit 334 can send a message to user device 310 indicating that the garage door is open. As another example, the control circuit 334 can vibrate the bed 302. As yet another example, the control circuit 334 may generate and transmit a control signal causing the lighting system 314 to flash one or more lights in the bedroom and alert user 308 to check user device 310 for a warning (in this example, a warning about the garage door 320 being open). Alternatively or additionally, the control circuit 334 may generate and transmit a control signal causing the garage door opener to close the garage door 320 in response to the identification that user 308 is in bed at night and that the garage door 320 is open. In some implementations, the control signal may vary depending on the age of user 308.

[0088] The control circuit 334 may also transmit and receive communications to control or receive state information related to the door 332 or the oven 322. For example, if it detects that user 308 is in bed at night, the control circuit 334 may generate and transmit a request to a device or system for detecting the state of the door 332. The information returned in response to the request may indicate various states of the door 332, such as open, closed but unlocked, or closed and locked. If the door 332 is open or closed but unlocked, the control circuit 334 may warn user 308 about the state of the door, for example, as described above for the garage door 320. Alternatively or in addition to the warning to user 308, the control circuit 334 may generate and transmit a control signal to lock or close and lock the door 332. If the door 332 is closed and locked, the control circuit 334 may determine that no further action is required.

[0089] Similarly, when the control circuit 334 detects that user 308 is in bed at night, it may generate and send a request to oven 322 to request the oven's state (e.g., on or off). If oven 322 is on, the control circuit 334 may warn user 308 and / or generate and send a control signal to turn oven 322 off. If oven is already off, the control circuit 334 may determine that no further action is required. In some implementations, various alerts may be generated for various events. For example, the control circuit 334 may flash lamp 326 (or one or more other lights via the lighting system 314) in a first pattern if the security system 318 detects a breach, in a second pattern if the garage door 320 is open, in a third pattern if door 332 is open, in a fourth pattern if the oven 322 is on, and in a fifth pattern if another bed detects that the user of that bed has woken up (for example, when a sensor in the child's bed 302 detects that user 308's child has gotten out of bed in the middle of the night). Other examples of warnings that can be processed by the control circuit 334 of bed 302 and communicated to the user include a smoke detector that detects smoke (and communicates the detection of such smoke to the control circuit 334), a carbon monoxide tester that detects carbon monoxide, a heater malfunction, or any other device that can communicate with the control circuit 334 and is capable of detecting the occurrence of an event that should draw the attention of user 308.

[0090] The control circuit 334 may also communicate with a system or device for controlling the state of the blinds 330. For example, in response to a determination that user 308 is in bed at night, the control circuit 334 may generate and transmit a control signal to close the blinds 330. As another example, in response to a determination that user 308 has gotten up that day (for example, the user got out of bed after 6:30 a.m.), the control circuit 334 may generate and transmit a control signal to open the blinds 330. In contrast, if user 308 gets out of bed before the user 308's usual wake-up time, the control circuit 334 may determine that user 308 has not yet gotten up that day and will not generate a control signal to open the blinds 330. As yet another example, the control circuit 334 may generate and transmit a control signal to close the first set of blinds in response to the detection of user 308's presence in bed, and to close the second set of blinds in response to the detection that the user is asleep.

[0091] The control circuit 334 may generate and transmit control signals to control the functions of other household appliances in response to detection of user interaction with the bed 302. For example, in response to a determination that user 308 has woken up for the day, the control circuit 334 may generate and transmit a control signal to the coffee maker 324 to cause the coffee maker 324 to start brewing coffee. As another example, the control circuit 334 may generate and transmit a control signal to the oven 322 to cause the oven to start preheating (for users who like freshly baked bread in the morning). As yet another example, the control circuit 334 may use information indicating that user 308 has woken up for the day, along with information indicating that it is currently winter and / or that the outside temperature is below a threshold, to generate and transmit a control signal to turn on the car's engine block heater.

[0092] As another example, the control circuit 334 may generate and transmit control signals to put one or more devices into sleep mode in response to detection of the presence of user 308 in bed or in response to detection that user 308 is asleep. For example, the control circuit 334 may generate a control signal to switch user 308's mobile phone into sleep mode. The control circuit 334 may then transmit this control signal to the mobile phone. Further later, if it is determined that user 308 has woken up that day, the control circuit 334 may generate and transmit a control signal to switch the mobile phone out of sleep mode (to normal mode).

[0093] In some implementations, the control circuit 334 may communicate with one or more noise control devices. For example, if it is determined that user 308 is in bed at night or is asleep, the control circuit 334 may generate and transmit control signals to activate one or more noise cancellation devices. The noise cancellation devices may be included as part of the bed 302, for example, or placed in the bedroom where the bed 302 is located. As another example, if it is determined that user 308 is in bed at night or is asleep, the control circuit 334 may generate and transmit control signals to turn the volume on, off, up, or down for one or more sound-generating devices, such as a stereo system radio, computer, or tablet.

[0094] Furthermore, the functions of the bed 302 are controlled by the control circuit 334 in response to user interaction with the bed 302. For example, the bed 302 may include an adjustable base and an articulated controller configured to adjust the position of one or more parts of the bed 302 by adjusting the adjustable base that supports the bed. For example, the articulated controller may adjust the bed 302 from a flat position to a position in which the head portion of the mattress of the bed 302 is tilted upward (for example, to facilitate the user sitting on the bed and / or watching television). In some implementations, the bed 302 includes several independently articulated sections. For example, parts of the bed corresponding to the positions of air chambers 306a and 306b may be articulated independently of each other to allow one person to rest in a first position (e.g., a flat position) while a second person rests in a second position (e.g., a reclined position with their head tilted diagonally above their waist) while one person rests on the surface of the bed 302. In some implementations, separate positions may be set for two different beds (e.g., two twin beds placed next to each other). The base of the bed 302 may include two or more zones that can be adjusted independently. The joint motion controller may also be configured to provide different levels of massage to one or more users on the bed 302, or to vibrate the bed to alert the user 308 as described above.

[0095] The control circuit 334 may adjust the position (e.g., tilt and lowering positions for user 308 and / or additional users of the bed 302) in response to user interaction with the bed 302. For example, the control circuit 334 may cause the joint motion controller to adjust the bed 302 to a first reclining position for user 308 in response to sensing the presence of user 308 in the bed. The control circuit 334 may cause the joint motion controller to adjust the bed 302 to a second reclining position (e.g., a less reclined or flat position) in response to determining that user 308 is asleep. As another example, the control circuit 334 may receive a communication from the television 312 indicating that user 308 has turned off the television 312, and in response, the control circuit 334 may cause the joint motion controller to adjust the position of the bed 302 to a preferred user sleeping position (e.g., user 308 turning off the television 312 while in bed indicates that user 308 wants to fall asleep).

[0096] In some implementations, the control circuit 334 may control the joint motion controller to wake one user of bed 302 without waking another user of bed 302. For example, user 308 and the second user of bed 302 may each set different wake-up times (e.g., 6:30 AM and 7:15 AM, respectively). When it is user 308's wake-up time, the control circuit 334 may cause the joint motion controller to vibrate only one side of the bed where user 308 is located, or to change its position, thereby waking user 308 without disturbing the second user. When it is the second user's wake-up time, the control circuit 334 may cause the joint motion controller to vibrate only the side of the bed where the second user is located, or to change its position. Alternatively, when it is the second user's wake-up time, the control circuit 334 may use other methods (e.g., an audio alarm or turning on a light) to wake the second user. This is because when the control circuit 334 attempts to wake up the second user, user 308 is already awake and therefore cannot be disturbed.

[0097] Continuing to refer to Figure 3, the control circuit 334 of bed 302 can use information about the interactions between multiple users with bed 302 to generate control signals to control the functions of various other devices. For example, the control circuit 334 may wait to generate control signals to activate, for example, the security system 318 or to instruct the lighting system 314 to turn off the lights in various rooms, until it is detected that both user 308 and the second user are present on bed 302. As another example, upon detecting the presence of user 308 on bed, the control circuit 334 may generate a first set of control signals to turn off a first set of lights in the lighting system 314, and in response to detecting the presence of the second user on bed, it may generate a second set of control signals to turn off a second set of lights. As yet another example, the control circuit 334 may wait to generate a control signal to open the blinds 330 until it is determined that both user 308 and the second user have woken up for the day. As yet another example, in response to the determination that user 308 is awake and out of bed that day, but second user is still asleep, the control circuit 334 may generate and transmit a first set of control signals, causing the coffee maker 324 to start brewing coffee, the security system 318 to be deactivated, the lamp 326 to be turned on, the night light 328 to be turned off, the thermostat 316 to raise the temperature of one or more rooms to 72 degrees Fahrenheit, and the blinds (e.g., blinds 330) in rooms other than the bedroom where the bed 302 is located. Subsequently, in response to the detection that second user is no longer in bed (or second user is awake), the control circuit 334 may generate and transmit a second set of control signals, for example, causing the lighting system 314 to turn on one or more lights in the bedroom, open the bedroom blinds, and turn on the television 312 to a predetermined channel.

[0098] [Example of a data processing system associated with a bed]

[0099] Here, examples of systems and components that may be used for data processing tasks associated with a bed are described. In some cases, multiple examples of a particular component or group of components are presented. Some of these examples are redundant and / or mutually exclusive substitutes. Connections between components are shown as examples illustrating possible network configurations for allowing communication between components. Various forms of connections may be used as technically required or desired. Such connections generally represent logical connections that can be created in any technically feasible manner. For example, a network on a motherboard may be created with printed circuit boards, wireless data connections, and / or other types of network connections. Some logical connections are not illustrated for clarity. For example, many or all elements of a particular component may need to be connected to power and / or computer-readable memory, but for clarity, connections to power and / or computer-readable memory may not be illustrated.

[0100] Figure 4A is a block diagram of an example of a data processing system 400 that may be associated with a bed system. It includes those described above with respect to Figures 1 to 3. The system 400 includes a pump motherboard 402 and a pump daughterboard 404. The system 400 also includes a sensor array 406, which may include one or more sensors configured to sense environmental and / or physical phenomena of the bed and report such senses to the pump motherboard 402, for example, for analysis. The system 400 also includes a controller array 408, which may include one or more controllers configured to control logical control devices of the bed and / or environment. The pump motherboard 400 may communicate with one or more computing devices 414 and one or more cloud services 410 via a local network, via the internet 412, or via other technically appropriate means. Each of these components will be described in more detail below, along with several exemplary forms.

[0101] In this example, the pump motherboard 402 and the pump daughterboard 404 are connected in a communicative manner. They can be conceptually described as the center or hub of system 400, and the other components can be conceptually described as spokes of system 400. In some forms, this may mean that each of the spoke components communicates primarily or exclusively with the pump motherboard 402. For example, the sensors of a sensor array may not be configured to communicate directly with their corresponding controllers, or may not be able to. Instead, each spoke component can communicate with the motherboard 402. The sensors of sensor array 406 may report sensor readings to the motherboard 402, which in turn may determine whether the controllers of controller array 408 should adjust some parameters of the logic control devices or correct the state of one or more peripheral devices. If, in some case, the bed temperature is determined to be too high, the pump motherboard 402 may determine that the temperature controller should cool the bed.

[0102] One advantage of a hub-spoke network configuration (sometimes called a star network) is reduced network traffic compared to, for example, a mesh network using dynamic routing. Even if a particular sensor generates a large, continuous stream of traffic, that traffic may only be sent to the motherboard 402 via one spoke of the network. The motherboard 402 may, for example, marshal the data, condense it into a smaller data format, and retransmit it for storage in the cloud service 410. Additionally or alternatively, the motherboard 402 may, in response to a large stream, generate a single small command message to be sent via different spokes of the network. For example, if the large data stream is pressure readings sent several times per second from the sensor array 406, the motherboard 402 may respond to the controller array with a single command message to increase the pressure in the air chamber. In this case, the single command message may be orders of magnitude smaller than the stream of pressure readings.

[0103] Another advantage is that the hub-spoke network configuration can accommodate a scalable network that can handle the addition, removal, and failure of components. This could, for example, allow for more, fewer, or different sensors in the sensor array 406, more, fewer, or different controllers in the controller array 408, more, fewer, or different computing devices 414, and / or more, fewer, or different cloud services 410. For example, if a particular sensor fails or is superseded by a newer version of that sensor, the system 400 could be configured such that only the motherboard 402 needs to be updated for the replacement sensor. This could allow for product differentiation, for example, that the same motherboard 402 can support entry-level products with fewer sensors and controllers, higher-value products with more sensors and controllers, and customer personalization where customers can add their own selected components to the system 400.

[0104] Furthermore, a series of airbed products may utilize system 400 with various components. In applications where all airbeds in the product line include both a central logic unit and a pump, the motherboard 402 (and optionally the daughterboard 404) can be designed to fit within a single universal housing. Subsequently, with each product upgrade within the product line, additional sensors, controllers, cloud services, etc., can be added. Designing all products in the product line from such a base can reduce design, manufacturing, and testing times compared to a product line where each product has a custom logic control system.

[0105] Each of the aforementioned components can be implemented in various technologies and forms. Several examples of each component are described below. In some alternatives, two or more components of system 400 may be implemented by a single alternative component, some components may be implemented by multiple separate components, and / or some functions may be provided by different components.

[0106] Figure 4B is a block diagram showing several communication paths for the data processing system 400. As previously mentioned, the motherboard 402 and the pump daughterboard 404 can function as hubs for peripheral devices and cloud services of the system 400. When the pump daughterboard 404 communicates with cloud services or other components, the communication from the pump daughterboard 404 can be routed through the pump motherboard 402. This allows, for example, the bed to have only a single connection to the internet 412. The computing device 414 may also have a connection to the internet 412, sometimes via the same gateway used by the bed and / or sometimes via a different gateway (e.g., a cell service provider).

[0107] Several cloud services 410 have been described previously. As shown in Figure 4B, some cloud services, such as cloud services 4l0d and 4l0e, can be configured so that the pump motherboard 402 can communicate directly with them. That is, the motherboard 402 can communicate with the cloud services 410 without needing to use another cloud service 410 as an intermediary. Additionally or alternatively, some cloud services 410, such as cloud service 410f, may be reachable by the pump motherboard 402 only through an intermediary cloud service, such as cloud service 410e. Although not shown here, some cloud services 410 may be reachable by the pump motherboard 402 directly or indirectly.

[0108] Furthermore, some or all of the cloud services 410 may be configured to communicate with other cloud services. This communication may include the transfer of data and / or remote function calls in any technically appropriate format. For example, one cloud service 410 may request a copy of 410 data from another cloud service, for example, for backup, coordination, migration purposes, or for performing computation or data mining. In another example, many cloud services 410 may contain data indexed according to specific users tracked by user account clouds 410c and / or bed data clouds 410a. These cloud services 410 may communicate with the user account clouds 410c and / or bed data clouds 410a when accessing data specific to a particular user or bed.

[0109] Figure 5 is a block diagram of an example of a motherboard 402 that may be used in a data processing system that may be associated with a bed system, including those described above in relation to Figures 1 to 3. In this example, the motherboard 402 may be limited to having relatively few components and providing a relatively limited set of features compared to other examples described below.

[0110] The motherboard includes a power supply unit 500, a processor 502, and computer memory 512. Generally, the power supply unit includes hardware used to receive power from an external power source and supply it to the components of the motherboard 402. The power supply unit may include, for example, a battery pack and / or a wall outlet adapter (plug), an AC-DC converter, a DC-AC converter, a power regulator, a capacitor bank, and / or one or more interfaces for providing power in terms of current type, voltage, etc., as required by the other components of the motherboard 402.

[0111] A processor 502 is generally a device for receiving inputs, performing logical decisions, and providing outputs. A processor 502 can be a central processing unit, a microprocessor, a general-purpose logic circuit, an application-specific integrated circuit (ASIC), a combination of these, and / or other hardware for performing the required functions.

[0112] Memory 512 is generally one or more devices for storing data. Memory 512 may include long-term stable data storage (e.g., on a hard disk), short-term unstable data storage (e.g., on random-access memory), or any other technically appropriate configuration.

[0113] The motherboard 402 includes a pump controller 504 and a pump motor 506. The pump controller 504 may receive commands from the processor 502 and, in response, control the function of the pump motor 506. For example, the pump controller 504 may receive a command from the processor 502 to increase the pressure in the air chamber by 0.3 pounds per square inch (PSI). In response, the pump controller 504 may actuate a valve so that the pump motor 506 is configured to pump air into the selected air chamber and operate the pump motor 506 for a time corresponding to 0.3 PSI, or until a sensor indicates that the pressure has increased by 0.3 PSI. In an alternative form, the message may specify that the chamber should be inflated to a target PSI, and the pump controller 504 may operate the pump motor 506 until that target PSI is reached.

[0114] The valve solenoid 508 can control which air chamber the pump is connected to. In some cases, the solenoid 508 may be directly controlled by the processor 502. In some cases, the solenoid 508 may be controlled by the pump controller 504.

[0115] The remote interface 510 of the motherboard 402 may allow the motherboard 402 to communicate with other components of the data processing system. For example, the motherboard 402 may be able to communicate with one or more daughterboards, peripheral sensors, and / or peripheral controllers via the remote interface 510. The remote interface 510 may provide any technically appropriate communication interface, including but not limited to multiple communication interfaces such as WiFi, Bluetooth®, and copper wired networks.

[0116] Figure 6 is a block diagram of an example of a motherboard 402 that may be used in a data processing system that may be associated with a bed system, including those described above with reference to Figures 1 to 3. Compared to the motherboard 402 described with reference to Figure 5, the motherboard in Figure 6 may contain more components and may offer more functionality in some applications.

[0117] In addition to the power supply unit 500, processor 502, pump controller 504, pump motor 506, and valve solenoid 508, the motherboard 402 is shown together with a valve controller 600, pressure sensor 602, universal serial bus (USB) stack 604, WiFi radio 606, Bluetooth® Low Energy (BLE) radio 608, ZigBee radio 610, Bluetooth® radio 612, and computer memory 512.

[0118] Similar to how the pump controller 504 translates commands from the processor 502 into control signals for the pump motor 506, the valve controller 600 may translate commands from the processor 502 into control signals for the valve solenoid 508. For example, the processor 502 may issue a command to the valve controller 600 to connect the pump to a specific air chamber among a group of air chambers in an airbed. The valve controller 600 may control the position of the valve solenoid 508 so that the pump is connected to the indicated air chamber.

[0119] The pressure sensor 602 can read pressure readings from one or more air chambers of the airbed. The pressure sensor 602 can also perform digital sensor calibration.

[0120] Motherboard 402 may include a set of network interfaces, including but not limited to those illustrated herein. These network interfaces may allow the motherboard to communicate with any number of devices, including but not limited to peripheral sensors, peripheral controllers, computing devices, and devices and services connected to the Internet 412, via a wired or wireless network.

[0121] Figure 7 is a block diagram of an example of a daughterboard 404 that may be used in a data processing system that may be associated with a bed system, including those described above with respect to Figures 1 to 3. In some forms, one or more daughterboards 404 may be connected to a motherboard 402. Some daughterboards 404 may be designed to offload specific tasks and / or partitioned tasks from the motherboard 402. This may be advantageous, for example, if a particular task is computationally intensive, proprietary, or subject to future revisions. For example, a daughterboard 404 may be used to calculate a specific sleep data metric. This metric may be computationally intensive, and calculating the sleep metric on the daughterboard 404 may free up resources on the motherboard 402 while the metric is being calculated. Additionally and / or alternatively, the sleep metric may be subject to future revisions. It is possible that to update system 400 with a new sleep metric, only the daughterboard 404 that calculates the metric needs to be replaced. In this case, since the same motherboard 402 and other components may be used, it is not necessary to perform unit testing on additional components as well as daughterboard 404.

[0122] The daughterboard 404 is illustrated together with a power supply 700, a processor 702, computer-readable memory 704, a pressure sensor 706, and a WiFi radio 708. The processor may use the pressure sensor 706 to collect information about the pressure in one or more air chambers of the airbed. From this data, the processor 702 may execute an algorithm to calculate a sleep metric. In some examples, the sleep metric may be calculated from the air chamber pressure alone. In other examples, the sleep metric may be calculated from one or more other sensors. In examples where various data are required, the processor 702 may receive such data from appropriate one or more sensors. These sensors may be located inside the daughterboard 404, may be accessible via the WiFi radio 708, or may be communicating with the processor 702. Once the sleep metric is calculated, the processor 702 may report the sleep metric to, for example, the motherboard 402.

[0123] Figure 8 is a block diagram of an example of a motherboard 800 without a daughterboard, which may be used in a data processing system that may be associated with a bed system, including those described above with respect to Figures 1 to 3. In this example, the motherboard 800 may perform almost all, all, or more of the functions described with reference to the motherboard 402 in Figure 6 and the daughterboard 404 in Figure 7.

[0124] Figure 9 is a block diagram of an example of a sensor array 406 that may be used in a data processing system that may be associated with a bed system, including those described above with respect to Figures 1 to 3. Generally, the sensor array 406 is a conceptual group of some or all of the peripheral sensors that communicate with the motherboard 402 but are not native to the motherboard 402.

[0125] Peripheral sensors of the sensor array 406 may communicate with the motherboard 402 via one or more network interfaces of the motherboard, including but not limited to a USB stack 604, a WiFi radio 606, a Bluetooth® Low Energy (BLE) radio 608, a ZigBee radio 610, and a Bluetooth® radio 612, as appropriate for the specific sensor configuration. For example, a sensor that outputs readings via a USB cable may communicate via the USB stack 604.

[0126] Some of the peripheral sensors 900 of the sensor array 406 may be mounted on the bed. These sensors may, for example, be embedded within the bed structure and sold with the bed, or may be mounted on the bed structure at a later date. Other peripheral sensors 902, 904 may communicate with the motherboard 402 but may not be selectively mounted on the bed. In some cases, some or all of the bed-mounted sensors 900 and / or peripheral sensors 902, 904 may share networking hardware. This includes conductors (wires) from each sensor, including wires, multiwire cables, or plugs, which connect all the associated sensors to the motherboard 402 when mounted on the motherboard 402. In some embodiments, one, some, or all of the sensors 902, 904, 906, 908, 910 may be capable of sensing one or more features of the mattress, such as pressure, temperature, light, sound, and / or one or more other features of the mattress. In some embodiments, one, some, or all of the sensors 902, 904, 906, 908, and 910 are capable of sensing one or more external features of the mattress. In some embodiments, while some or all of the sensors 902, 904, 906, 908, and 910 are capable of sensing one or more features of the mattress and / or one or more external features of the mattress, the pressure sensor 902 is capable of sensing the pressure of the mattress.

[0127] Figure 10 is a block diagram of an example controller array 408 that may be used in a data processing system that may be associated with a bed system, including those described above with respect to Figures 1 to 3. Generally, the controller array 408 is a conceptual group of some or all peripheral controllers that communicate with the motherboard 402 but are not native to the motherboard 402.

[0128] Peripheral controllers of the controller array 408 may communicate with the motherboard 402 via one or more network interfaces of the motherboard, including but not limited to a USB stack 604, a WiFi radio 606, a Bluetooth® Low Energy (BLE) radio 608, a ZigBee radio 610, and a Bluetooth® radio 612, as appropriate for a particular sensor configuration. For example, a controller that receives commands via a USB cable may communicate via the USB stack 604.

[0129] Some of the controllers 1000 of the controller array 408 may be mounted on the bed and include, but are not limited to, a temperature controller 1006, a lighting controller 1008, and / or a speaker controller 1010. These controllers may, for example, be embedded within the bed structure and sold with the bed, or may be mounted on the bed structure at a later date. Other peripheral controllers 1002, 1004 may communicate with the motherboard 402 but may not be selectively mounted on the bed. In some cases, some or all of the bed-mounted controllers 1000 and / or peripheral controllers 1002, 1004 may share networking hardware. This includes conductors (wires), including wires, multi-wire cables, or plugs for each controller, which, when mounted on the motherboard 402, connect all the associated controllers to the motherboard 402.

[0130] Figure 11 is a block diagram of an example of a computing device 414 that may be used in a data processing system that may be associated with a bed system, including those described above with respect to Figures 1 to 3. The computing device 414 may include, for example, a computing device used by the bed user. The exemplary computing device 414 includes, but is not limited to, mobile computing devices (e.g., mobile phones, tablet computers, laptops) and desktop computers.

[0131] The computing device 414 includes a power supply unit 1100, a processor 1102, and computer-readable memory 1104. User inputs and outputs may be transmitted by, for example, a speaker 1106, a touchscreen 1108, or other components not shown, such as a pointing device or keyboard. The computing device 414 may run one or more applications 1110. These applications may include, for example, applications that allow a user to interact with the system 400. These applications may allow the user to view information about the bed (such as sensor readings and sleep metrics) or configure the operation of the system 400 (for example, setting a desired firmness for the bed or setting a desired operation for peripheral devices). In some cases, the computing device 414 may be used in addition to, or to replace, the remote control 122 described above.

[0132] Figure 12 is a block diagram of an example of a bed data cloud service 410a that may be used in a data processing system that may be associated with a bed system, including those described above with respect to Figures 1 to 3. In this example, the bed data cloud service 410a is configured to collect sensor data and sleep data from a specific bed and to match the sensor data and sleep data with one or more users who were using the bed when the sensor data and sleep data were generated.

[0133] The bed data cloud service 410a is shown together with a network interface 1200, a communication manager 1202, server hardware 1204, and server system software 1206. Furthermore, the bed data cloud service 410a is shown together with a user identification module 1208, a device management module 1210, a sensor data module 1212, and an advanced sleep data module 1214.

[0134] The network interface 1200 generally includes hardware and low-level software used to allow one or more hardware devices to communicate over a network. For example, the network interface 1200 may include network cards, routers, modems, and other hardware required to allow components of the bed data cloud service 410a to communicate with each other and with other destinations, for example, over the internet 412. The communication manager 1202 generally includes hardware and software operating on the network interface 1200. This includes software for initiating, maintaining, and ending network communications used by the bed data cloud service 410a. This includes, for example, TCP / IP, SSL or TLS, torrent, and other communication sessions over local or wide area networks. The communication manager 1202 may also provide load balancing and other services to other elements of the bed data cloud service 410a.

[0135] Server hardware 1204 generally includes physical processing units used to instantiate and maintain the bed data cloud service 410a. This hardware includes, but is not limited to, processors (e.g., central processing units, ASICs, graphics processors) and computer-readable memory (e.g., random access memory, stable hard disks, tape backups). One or more servers may be configured in a cluster, multicomputer, or data center, which may be geographically separated or connected.

[0136] The server system software 1206 generally includes software that runs on the server hardware 1204 to provide an operating environment for applications and services. The server system software 1206 may include an operating system that runs on the physical server, virtual machines that are instantiated on the physical server to generate many virtual servers, and server-level operations such as data migration, redundancy, and backup.

[0137] The user identification module 1208 may include or refer to data relating to users of beds equipped with associated data processing systems. For example, a user may include a customer, owner, or other user registered with the bed data cloud service 410a or other services. Each user may have, for example, a unique identifier, user credentials, contact information, billing information, demographic information, or other technically appropriate information.

[0138] The device management module 1210 may include or reference data related to beds or other products associated with the data processing system. For example, a bed may include product information (product information) sold or registered in the system associated with the bed data cloud service 410a. Each bed may have, for example, a unique identifier, model and / or serial number, sales information, geographical information, delivery information, a list of associated sensors and peripheral control devices, etc. Furthermore, one or more indexes stored by the bed data cloud service 410a may identify users associated with a bed. For example, this index may record sales of a bed to one or more users sleeping in the bed.

[0139] The sensor data module 1212 may record raw (unprocessed) or compressed (processed) sensor data recorded by a bed equipped with an associated data processing system. For example, the bed's data processing system may include a temperature sensor, a pressure sensor, and a light sensor. Readings from these sensors, either in their raw sensor form or in a format generated from the raw data (e.g., sleep metrics), may be communicated by the bed's data processing system to the bed data cloud service 410a and stored in the sensor data module 1212. Furthermore, one or more indices stored by the bed data cloud service 410a may identify the user and / or bed associated with the sensor data module 1212.

[0140] The bed data cloud service 410a may generate advanced sleep data 1214 using any of its available data. Generally, advanced sleep data 1214 includes sleep metrics and other data generated from sensor readings. Some of these calculations may be performed in the bed data cloud service 410a instead of being performed locally in the bed data processing system, for example, if the calculations are complex or require a large amount of memory or processor power that is not available in the bed data processing system. This can be useful in allowing the bed system to operate with a relatively simple controller while still being part of a system that performs relatively complex tasks and calculations.

[0141] Figure 13 is a block diagram of an example of a sleep data cloud service 410b that may be used in a data processing system that may be associated with a bed system, including those described above in relation to Figures 1 to 3. In this example, the sleep data cloud service 410b is configured to record data related to the user's sleep experience.

[0142] The sleep data cloud service 410b is shown together with a network interface 1300, a communication manager 1302, server hardware 1304, and server system software 1306. Furthermore, the sleep data cloud service 410b is shown together with a user identification module 1308, a pressure sensor management module 1310, a pressure-based sleep data module 1312, a raw pressure sensor data module 1314, and a non-pressure sleep data module 1316.

[0143] The pressure sensor management module 1310 may include or refer to data related to the configuration and operation of pressure sensors in the bed. For example, this data may include identifiers of the sensor type for a particular bed, their settings and calibration data, and so on.

[0144] The pressure-based sleep data 1312 can be used with the raw pressure sensor data 1314 to calculate sleep metrics, particularly those associated with the pressure sensor data. For example, the user's presence, movement, weight change, heart rate, and respiratory rate can all be determined from the raw pressure sensor data 1314. Furthermore, one or more indices stored by the sleep data cloud service 410b can identify the user associated with the pressure sensor, the raw pressure sensor data, and / or the pressure-based sleep data.

[0145] Non-pressure sleep data 1316 can be used to calculate sleep metrics using other data sources. For example, user-entered preferences, light sensor readings, and acoustic sensor readings can all be used to track sleep data. Furthermore, one or more indices stored by the sleep data cloud service 410b can identify users associated with other sensors and / or non-pressure sleep data 1316.

[0146] Figure 14 is a block diagram of an example of a user account cloud service 410c that may be used in a data processing system that may be associated with a bed system, including those described above with respect to Figures 1 to 3. In this example, the user account cloud service 4l0c is configured to record a list of users and identify other data associated with those users.

[0147] The user account cloud service 410c is shown together with the network interface 1400, the communication manager 1402, the server hardware 1404, and the server system software 1406. Furthermore, the user account cloud service 410c is shown together with the user identification module 1408, the purchase history module 1410, the engagement module 1412, and the application usage history module 1414.

[0148] The user identification module 1408 may include or refer to data relating to a user of a bed equipped with an associated data processing system. For example, a user may include a customer, owner, or other user registered with the user account cloud service 410c or other services. Each user may have, for example, a unique identifier, user credentials, demographic information, or other technically appropriate information.

[0149] The purchase history module 1410 may contain or reference data related to user purchases. For example, purchase data may include sales contact information, invoice information, and sales representative information. Furthermore, one or more indexes stored by the user account cloud service 410c may identify the user associated with the purchase.

[0150] The engagement module 1412 may track user interactions with manufacturers, vendors, and / or administrators of beds and / or cloud services. This engagement data may include communications (e.g., emails, service calls, etc.), sales data (e.g., receipts, configuration logs), and social network interactions.

[0151] The usage history module 1414 may contain data on user interactions with one or more applications and / or remote controls of the bed. For example, a monitoring and configuration application may be distributed to run on multiple computing devices 412, for example. This application may log and report user interactions for storage in the application usage history module 1414. Furthermore, one or more indices stored by the user account cloud service 410c may identify the user associated with each log entry.

[0152] Figure 15 is a block diagram of an example of a point-of-sale (POS) cloud service 1500 that may be used in a data processing system that may be associated with a bed system, including those described above in relation to Figures 1 to 3. In this example, the point-of-sale cloud service 1500 is configured to record data related to user purchases.

[0153] The point-of-sale (POS) cloud service 1500 is shown together with a network interface 1502, a communications manager 1504, server hardware 1506, and server system software 1508. Furthermore, the point-of-sale (POS) cloud service 1500 is shown together with a user identification module 1510, a purchase history module 1512, and a setup module 1514.

[0154] The purchase history module 1512 may include, or refer to, data related to purchases made by a user identified by the user identification module 1510. Purchase information may include, for example, data on the sale, price, place of sale, delivery address, and configuration options selected by the user at the time of sale. These configuration options may include the user's choices regarding how they want the newly purchased bed to be set up, and may also include, for example, an expected sleep schedule, a list of peripheral sensors and controllers that the user has or will install, etc.

[0155] The bed setup module 1514 may include or refer to data related to the setup of a bed purchased by the user. The bed setup data may include, for example, the date and address on which the bed will be delivered, the person receiving the delivery, the configuration applied to the bed at the time of delivery, the names of one or more people who will sleep on the bed, and which side of the bed each person will use.

[0156] Data recorded in the point-of-sale (POS) cloud service 1500 can later be referenced by the user's bed system to control the functions of the bed system and / or send control signals to peripheral components according to the data recorded in the PSOS cloud service 1500. This allows salespeople to collect information from users at the point of sale, which facilitates the later automation of the bed system. In some examples, some or all features of the bed system can be automated, and little to no user input data is required after the point of sale. In other examples, data recorded in the PSOS cloud service 1500 can be used in relation to various additional data collected from user input data.

[0157] Figure 16 is a block diagram of an example of an environmental cloud service 1600 that may be used in a data processing system that may be associated with a bed system, including those described above in relation to Figures 1 to 3. In this example, the environmental cloud service 1600 is configured to record data related to the user's home environment.

[0158] The environmental cloud service 1600 is shown together with a network interface 1602, a communication manager 1604, server hardware 1606, and server system software 1608. Furthermore, the environmental cloud service 1600 is shown together with a user identification module 1610, an environmental sensor module 1612, and an environmental factor module 1614.

[0159] The environmental sensor module 1612 may include a list of sensors installed in the bed by the user of the user identification module 1610. These sensors may include any sensors capable of detecting environment variables, such as light sensors, noise sensors, vibration sensors, and thermostats. Furthermore, the environmental sensor module 1612 may store past readings or reports from those sensors.

[0160] The environmental factors module 1614 may include reports generated based on data from the environmental sensor module 1612. For example, for a user with a light sensor, the environmental factors module 1614 may hold reports indicating the frequency and duration of instances of increased lighting while the user is sleeping.

[0161] In the examples described herein, each cloud service 410 is shown with some identical components. In various forms, these identical components may be shared partially or completely between services, or they may be separate. In some forms, each service may have separate copies of some or all of the components that are the same or different in some respects. Furthermore, these components are provided only as illustrative examples. In other examples, each cloud service may have a different number, type, and style of components, depending on what is technically possible.

[0162] Figure 17 is a block diagram of an example of automating peripheral devices around a bed using a data processing system that may be associated with the bed (such as a bed in the bed system described herein). Shown here is a behavior analysis module 1700 running on the pump motherboard 402. For example, the behavior analysis module 1700 may be one or more software components stored in computer memory 512 and executed by processor 502. Generally, the behavior analysis module 1700 may collect data from a wide variety of sources (e.g., sensors, non-sensor local sources, cloud data services) and use behavior algorithms 1702 to generate one or more actions to be taken (e.g., commands to send to peripheral controllers, data to send to cloud services). This may be useful, for example, for tracking user behavior or automating devices that communicate with the user's bed.

[0163] The behavioral analysis module 1700 may collect data from any technically appropriate source to collect data about, for example, the bed's characteristics, the bed's environment, and / or the bed's user. Some such sources include any of the sensors in the sensor array 406. For example, this data may provide the behavioral analysis module 1700 with information about the current state of the environment surrounding the bed. For example, the behavioral analysis module 1700 may access readings from the pressure sensor 902 to determine the pressure in the air chamber within the bed. From these readings, and possibly other data, the presence of a user in the bed may be determined. In another example, the behavioral analysis module 1700 may access the light sensor 908 to detect the amount of light in the bed's environment.

[0164] Similarly, the behavioral analysis module 1700 may access data from cloud services. For example, the behavioral analysis module 1700 may access the bed cloud service 410a and access historical sensor data 1212 and / or advanced sleep data 1214. Other cloud services 410, including those not previously described, may be accessed by the behavioral analysis module 1700. For example, the behavioral analysis module 1700 may access weather reporting services, third-party data providers (e.g., traffic and news data, emergency broadcast data, user travel data), and / or clock and calendar services.

[0165] Similarly, the behavioral analysis module 1700 may access data from non-sensor sources 1704. For example, the behavioral analysis module 1700 may access local clock and calendar services (e.g., components of the motherboard 402 or processor 502).

[0166] The behavior analysis module 1700 can aggregate and prepare this data for use by one or more behavior algorithms 1702. The behavior algorithms 1702 can be used to learn user behavior and / or to perform certain actions based on the state of the accessed data and / or predicted user behavior. For example, the behavior algorithm 1702 can use available data (e.g., pressure sensor, non-sensor data, clock and calendar data) to create a model of when the user goes to sleep each night. The same or different behavior algorithms 1702 can then be used to determine whether an increase in air chamber pressure is likely to indicate the user is going to sleep, and if so, some data can be sent to a third-party cloud service 410 and / or to activate devices such as, for example, a pump controller 504, a base actuator 1706, a temperature controller 1008, under-bed lighting 1010, or peripheral controllers 1002 or 1004.

[0167] In the illustrated example, the behavioral analysis module 1700 and the behavioral algorithm 1702 are shown as components of the motherboard 402. However, other configurations are possible. For example, the same or similar behavioral analysis module and / or behavioral algorithm may run on one or more cloud services, and the resulting output may be transmitted to the motherboard 402, the controller of the controller array 408, or any other technically appropriate recipient.

[0168] Figure 18 shows an example of a computing device 1800 and an example of a mobile computing device that may be used to implement the techniques described herein. The computing device 1800 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal information terminals, servers, blade servers, mainframes, and other suitable computers. The mobile computing device is intended to represent various forms of mobile devices, such as personal information terminals, mobile phones, smartphones, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are for illustrative purposes only and are not intended to limit the implementation of the invention as described and / or claimed herein.

[0169] The computing device 1800 includes a processor 1802, memory 1804, storage device 1806, a high-speed interface 1808 connected to memory 1804 and several high-speed expansion ports 1810, and a low-speed interface 1812 connected to a low-speed expansion port 1814 and storage device 1806. Each of the processor 1802, memory 1804, storage device 1806, high-speed interface 1808, high-speed expansion ports 1810, and low-speed interface 1812 can be interconnected using various buses and mounted on a common motherboard or in other forms as needed. The processor 1802 processes instructions for execution within the computing device 1800, including instructions stored in memory 1804 or storage device 1806, and can display graphic information for a GUI on an external input / output device such as a display 1816 coupled to the high-speed interface 1808. In other implementations, multiple processors and / or multiple buses may be used, along with multiple memories and memory types, as needed. Furthermore, multiple computing devices may be connected so that each computing device provides some of the necessary functionality (e.g., as a server bank, a group of blade servers, or a multiprocessor system).

[0170] Memory 1804 stores information within the computing device 1800. In some implementations, memory 1804 is one or more volatile memory units. In some implementations, memory 1804 is one or more non-volatile memory units. Memory 1804 may also be another form of computer-readable medium, such as a magnetic disk or an optical disk.

[0171] The storage device 1806 can provide large-capacity storage to the computing device 1800. In some implementations, the storage device 1806 may be or include computer-readable media such as floppy disk drives, hard disk drives, optical disk drives, tape drives, flash memory, or other similar solid-state memory devices, or an array of multiple devices including a storage area network or other forms of multiple devices. The computer program product may be tangibly embodied within the information carrier. The computer program product may also include instructions that, when executed, perform one or more methods such as those described above. The computer program product may also be tangibly embodied within computer-readable media or machine-readable media such as memory 1804, storage device 1806, or memory on the processor 1802.

[0172] The high-speed interface 1808 manages bandwidth-intensive operation for the computing device 1800, while the low-speed interface 1812 manages lower bandwidth-intensive operation. Such function assignments are merely illustrative. In some implementations, the high-speed interface 1808 is coupled to memory 1804, a display 1816 (e.g., via a graphics processor or accelerator), and a high-speed expansion port 1810 that can accept various expansion cards (not shown). In such implementations, the low-speed interface 1812 is coupled to storage device 1806 and the low-speed expansion port 1814. The low-speed expansion port 1814 may include various communication ports (e.g., USB, Bluetooth®, Ethernet, Wireless Ethernet) and may be coupled to one or more input / output devices such as a keyboard, pointing device, scanner, or network devices such as switches or routers via a network adapter.

[0173] The computing device 1800 can be implemented in several different forms, as shown in the figure. For example, it can be implemented as a standard server 1820, or multiple times in a group of such servers. Furthermore, it can be implemented in a personal computer such as a laptop computer 1822. It can also be implemented as part of a rack server system 1824. Alternatively, components from the computing device 1800 can be combined with other components of a mobile device (not shown), such as a mobile computing device 1850. Each of such devices may include one or more of the computing device 1800 and the mobile computing device 1850, and the entire system may consist of multiple computing devices communicating with each other.

[0174] The mobile computing device 1850 includes, among other things, an input / output device such as a processor 1852, memory 1864, and display 1854, a communication interface 1866, and a transceiver 1868. The mobile computing device 1850 may also be provided with storage devices such as a microdrive or other devices to provide additional storage (recording devices). Each of the processor 1852, memory 1864, display 1854, communication interface 1866, and transceiver 1868 is interconnected using various buses, and some of these components may be mounted on a common motherboard or in other manner as needed.

[0175] The processor 1852 can execute instructions in the mobile computing device 1850, including instructions stored in memory 1864. The processor 1852 may be implemented as a chipset of a chip including several separate analog and digital processors. The processor 1852 may provide coordination of other components of the mobile computing device 1850, such as control of the user interface, applications run by the mobile computing device 1850, and wireless communication by the mobile computing device 1850.

[0176] The processor 1852 can communicate with the user via a control interface 1858 and a display interface 1856 coupled to the display 1854. The display 1854 may be, for example, a TFT display (thin-film transistor liquid crystal display), an OLED (organic light-emitting diode) display, or other suitable display technology. The display interface 1856 may have suitable circuitry for driving the display 1854 to present graphic information and other information to the user. The control interface 1858 may receive commands from the user and translate them for presentation to the processor 1852. Furthermore, an external interface 1862 may provide communication with the processor 1852 and enable short-range communication of the mobile computing device 1850 with other devices. The external interface 1862 may provide, for example, wired communication in some implementations or wireless communication in other implementations, and multiple interfaces may be used.

[0177] Memory 1864 stores information within the mobile computing device 1850. Memory 1864 may be implemented as one or more computer-readable media, one or more volatile memory units, or one or more non-volatile memory units. Extended memory 1874 may also be provided and connected to the mobile computing device 1850 via an extended interface 1872, which may include, for example, a SIMM (Single In-Line Memory Module) card interface. Extended memory 1874 may provide additional storage space for the mobile computing device 1850, or it may store applications or other information for the mobile computing device 1850. Specifically, extended memory 1874 may include instructions for executing or supplementing the aforementioned processes, and may also include security information. Thus, for example, extended memory 1874 may be provided as a security module for the mobile computing device 1850 and may be programmed with instructions that allow the secure use of the mobile computing device 1850. Furthermore, secure applications can be provided via the SIMM card, along with additional information such as identification information placed on the SIMM card in a manner that prevents hacking.

[0178] The memory may include, for example, flash memory and / or NVRAM memory (non-volatile random access memory), as described below. In some implementations, the computer program product is tangibly embodied within an information carrier. The computer program product includes instructions that, when executed, perform one or more methods as described above. The computer program product may be a computer-readable or machine-readable medium, such as memory 1864, extended memory 1874, or memory on processor 1852. In some implementations, the computer program product may be received as a propagated signal, for example, via transceiver 1868 or external interface 1862.

[0179] The mobile computing device 1850 can communicate wirelessly via a communication interface 1866. The communication interface 1866 may optionally include digital signal processing circuitry. The communication interface 1866 can provide communication under various modes or protocols, including, in particular, GSM (Global System for Mobile Communications), SMS (Short Message Service), EMS (Extended Messaging Service), MMS (Multimedia Messaging Service), CDMA (Code Division Multiple Access), TDMA (Time Division Multiple Access), PDC (Personal Digital Cellular), WCDMA (Wideband Code Division Multiple Access), CDMA2000, or GPRS (General-Purpose Packet Radio Service). Such communication may occur, for example, via a transceiver 1868 using radio frequencies. Furthermore, short-range communication may occur using Bluetooth (Registered Trademark), WiFi, or other such transceivers (not shown). Furthermore, the GPS (Global Positioning System) receiver module 1870 may provide additional navigation and location-related radio data to the mobile computing device 1850. This data can be appropriately used by applications running on the mobile computing device 1850.

[0180] The mobile computing device 1850 may also communicate audibly using the audio codec 1860. The audio codec 1860 may receive spoken information from the user and convert it into usable digital information. Similarly, the audio codec 1860 may generate audible sound for the user, for example, through a speaker in the handset of the mobile computing device 1850. Such sound may include sounds from voice calls, recorded sounds (e.g., voice messages, music files, etc.), and sounds generated by applications running on the mobile computing device 1850.

[0181] The mobile computing device 1850 can be implemented in several different forms, as shown in the figure. For example, it can be implemented as a mobile phone 1880. Alternatively, it can be implemented as part of a smartphone 1882, a personal information terminal, or other similar mobile device.

[0182] Various implementations of the systems and technologies described herein can be realized in digital electronic circuits, integrated circuits, specially designed ASICs (application-specific integrated circuits), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs executable and / or interpretable on a programmable system including at least one programmable processor. It may be coupled to receive data and instructions from and transmit data and instructions to a storage system, at least one input device, and at least one output device, for a specific or general purpose.

[0183] These computer programs (also called programs, software, software applications, or code) contain machine language instructions for a programmable processor and may be implemented in high-level procedural and / or object-oriented programming languages ​​and / or in assembly / machine language. As used herein, the terms machine-readable medium and computer-readable medium refer to any computer program product, apparatus and / or device (e.g., magnetic disks, optical disks, memory, programmable logic devices (PLDs)) used to provide machine instructions and / or data to a programmable processor. This includes machine-readable medium that receives machine instructions as machine-readable signals. The term machine-readable signal refers to any signal used to provide machine instructions and / or data to a programmable processor.

[0184] To provide user interaction, the systems and technologies described herein may be implemented in a computer equipped with a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) and a keyboard and pointing device (e.g., a mouse or trackball) to which the user can provide input to the computer. Other types of devices may also be used to provide user interaction. For example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or haptic feedback). Input from the user may be received in any form, including acoustic, speech, or haptic input.

[0185] The systems and technologies described herein may be implemented within a computing system that includes backend components (e.g., data servers), middleware components (e.g., application servers), or frontend components (e.g., client computers with a graphical user interface or web browser through which a user can interact with an implementation of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the internet.

[0186] A computing system can include clients and servers. Clients and servers are generally geographically separated from each other and typically interact via a communication network. The client-server relationship arises from computer programs running on each computer that have a client-server relationship with one another.

[0187] Figure 19 is a block diagram of an exemplary system 1900 for home automation. The system 1900 includes a device 1902, a computing cloud 1904, a user interface (UI) 1906, a bed sensor 1908, and a sleep data storage unit 1910.

[0188] The device 1902 may include a controller for the bed or home automation, such as a hub, computer, or dedicated controller. Some dedicated controllers are voice-activated and allow the user to issue voice commands and receive voice feedback. The device 1902 may receive an output signal from the bed sensor 1908, generate information about the presence in the bed (e.g., pressure fluctuations) from the output signal, and process the generated information to identify the sleep parameters of one or more sleepers in the bed.

[0189] Sleep parameters may include all, any, or any combination of the following: bed status (e.g., in or out of bed), biometric features (body movement, cardiac activity such as heart rate and variability, respiratory activity such as respiratory rate), sleep stage (e.g., N1 stage, N2 stage, REM sleep, falling asleep, deep sleep), sleeper's position (e.g., side-lying, supine, curled), and sleep onset (e.g., time of falling asleep). Client processing may include any, all, or some of the following features (functions): digital filters such as bandpass filters, time series analysis elements, model-based elements, source separation elements such as independent component analysis (ICA), wavelet transforms, spectral analysis elements, trend removal analysis elements, pattern matching elements, threshold-based analysis elements, linear or nonlinear interpolation elements for calculating surrogate indices, and / or machine learning elements.

[0190] The computing cloud 1904 may include computing resources that provide one or more services to other elements of system 1900. The computing cloud 1904 may receive inputs, settings, commands, configurations, and / or statuses from network-connected devices such as mobile phone applications, desktop applications, or cloud-based applications. The cloud 1904 may transmit inputs, settings, commands, configurations, and / or statuses from various devices to client devices 1902. The cloud 1904 may receive presence information (e.g., pressure) from client devices 1902 and process the generated information to identify, for example, pressure trends or real-time events related to a bed. The computing cloud 1904 may transmit such trends and events to the sleep database 1910 and communicate with various devices and applications to send and receive information, summaries, scores, events, notifications, charts, images, reports, commands, and decisions.

[0191] Cloud 1904 may include an artificial intelligence (AI) feature unit that accesses other elements of the system, identifies patterns, links, correlations, causes and / or relationships between data, calculates quantitative values ​​(e.g., sleep scores or health scores) or generates qualitative sleep insight messages, derives trends, builds personalized or population-level models, and makes inferences from the data. The interface may include, but is not limited to, the following: i) Identify sleep factors that negatively affect sleep quality, such as sleep interruptions (e.g., frequent getting out of bed or prolonged periods away from bed during sleep), excessive movement or restlessness, longer-than-usual time to fall asleep, insufficient restful sleep, and increased sleep debt. ii) To detect whether the user has difficulty falling asleep or maintaining sleep. iii) To detect changes in biological characteristics (biometrics) and sleep health factors, such as changes in sleep stages, heart rate, heart rate variability, respiratory rate, and movement. iv) Detecting abnormal changes in sleep parameters or health parameters in relation to the sleeper's past history. v) To detect sleep disorders and health problems such as snoring, sleep apnea, movement disorders, heart rate disorders, pain, stress, teeth grinding, etc. v) To provide insights into sleep and health of sleepers (personalized segments), comparisons with similar demographics such as sleepers of the same age, sex, and weight (comparable segments), and insights into geographical data such as sleepers in the same city, state, or country (population segments). vi) Access user data (alarms and calendar) to adjust alarms based on optimal sleep duration and optimal sleep stages. vii) Recommend tips for improving sleep, such as the optimal time to go to bed, the optimal position to start sleep, and the optimal duration of sleep. and / or, viii) Recommend optimal bed and bedroom environmental parameters, such as the optimal mattress firmness (adjusted using sleep number settings), optimal bed temperature, and optimal bedroom temperature. Using the results of this AI analysis, the device 1902 may be configured to automatically make changes to the bed or bedroom features in order to enhance sleep.

[0192] The artificial intelligence component can combine inference and analysis, and use the aforementioned inference along with the sleeper's historical data to generate intelligent, personalized sleep enhancement recommendations. This may include, but is not limited to, the following messages: i) "You slept x percent better than your monthly average. You had a restful night's sleep. Having a consistent routine will help regulate your body clock and further improve your sleep." ii) "You did not get enough restful sleep, so your sleep score was lower than your weekly average. You need at least 7 hours of sleep to allow your body and brain to recover." iii) "Your sleep was interrupted all night. Try to minimize sleep interruptions so that your body has a chance to progress through the sleep stages in order to fully recover." iv) "You found that it took you longer to fall asleep and you weren't getting enough sleep. To allow your body and brain to recover, try to establish a consistent sleep routine and aim for at least 7 hours of restful sleep." v) "For the past month, you have consistently slept less than your goal. We recommend that you adjust your sleep goals and maintain a consistent sleep schedule of 7 hours or more." vi) "We've found that you consistently wake up at 6 a.m. on weekdays. Adjust your routine so that you can go to bed by 10 p.m. to get a good night's sleep." vii) "We've noticed that your sleep isn't as restful during the winter. Try lowering the firmness of your mattress for more comfortable and restorative sleep." and / or, viii) "You sleep better than other women your age in California. We adjusted your bed temperature last night to maximize deep REM sleep and restful sleep."

[0193] Artificial intelligence components may use one or more classifiers, one or more regressors, or a combination of both. The system may be configured to store trained classifiers, regressors, and inference models in the cloud for future access. Classifiers may be unsupervised or supervised. In the unsupervised approach, classification (clustering) may be used to derive inferences from unlabeled input data. Classification may use any database in the database unit and may include one, all, or a combination of the following learning algorithms: k-means clustering, mixed model clustering, hierarchical clustering, self-organizing mapping, and hidden Markov modeling. In the supervised approach, classifiers or regressors may use any database in the database unit and may include one, all, or a combination of the following models: support vector machines, artificial neural networks, decision trees, and regression models. Supervised classification and regression may be organized to include two main tasks: training and testing.

[0194] The training is, i) Acquisition of pre-classified data from large sets, or annotation of data from large sets. ii) Generation of one or more feature parts, iii) Combination or reduction of the above-mentioned feature parts, iii) Processing of the feature portion, and / or, iv) Training of the classifier or regressor This may include testing a model using a pre-classified subset of data.

[0195] The artificial intelligence component may be further configured to receive input from UI1906 and provide interactive, personalized insights to guide the user through sleep enhancement options. For example, the user interface unit may display options (such as slider bars) for changing the values ​​of one or more sleep parameters (such as sleep duration, bedtime, or time to fall asleep). The user can change the values ​​of one or more parameters, and the artificial intelligence component will determine the impact of the changed parameters on the sleeper's sleep or health quality and provide updated quantitative values ​​(such as a sleep score or health score) or updated messages that reflect the impact of such changes on the individual user's sleep or health.

[0196] UI1906 can be incorporated into devices such as mobile phones, computers, automation hubs, or any other technically appropriate devices. UI1906 can operate in different modes, such as in-range communication mode (e.g., via Bluetooth®) and out-of-range communication mode (e.g., via a WiFi network), to communicate inputs, settings, commands, configurations, and / or statuses to client devices 1902 and / or computing clouds 1904, and to indicate sleep information collected or generated during sleep.

[0197] Sleep information may include quantitative scores (e.g., health scores or sleep quality scores presented as numerical scales or colors), one or more values ​​of sleep parameters and / or biocharacteristic parameters (e.g., sleep duration, movement, restful sleep duration, average heart rate, average respiratory rate), one or more sleep and / or health insights (e.g., sleep tips), and charts and graphs displaying sleep and health information and / or notifications from sleep duration.

[0198] The bed sensor 1908 may include a pressure transducer, a sensor pad, or other technically appropriate device configured to sense the user's body during sleep. For example, a pressure transducer may measure pressure fluctuations during sleep from the air chamber of the mattress. The bed sensor 1908 may additionally include acoustic and temperature sensors integrated within the bed system. For simplicity, the following description will only discuss pressure, but other signals may be used as well.

[0199] The sleep data storage unit 1910 can receive and store sleep information related to the person sleeping in the bed.

[0200] System 1900 is modifiable and expandable. Figure 20 is a block diagram of an exemplary system 2000 for home automation. System 2000 includes elements 1902-1910, as well as other data storage units 2012 and 2014, other sensors 2016, and user configuration information 2018.

[0201] Other data storage units 2012 and 2014 may store and make available other data used by system 2016.

[0202] Other sensors 2016 may communicate with UI1906 via one or more application programming interfaces (APIs) that function as an integration layer for requesting, accessing, retrieving, storing, or modifying data related to those other sensors 2016. Data transferred via APIs may include, but are not limited to, user data such as alarms, calendar events, personal medical history, and medication information. Such data may include, but are not limited to, user and environmentally sensed data such as temperature readings, humidity, air quality, exercise, steps, calories consumed or burned, weight, sound, and light, as well as interaction with devices such as the user's phone, and health-related data such as CPAP, PPG, SP02, blood pressure, and blood glucose levels (from medical or non-medical devices). Such data may also include, but are not limited to, geographical data such as weather, lunar phases, humidity, heat index, wind, seismic activity, and disease outbreaks.

[0203] User settings information 2018 may include information configured by the user in the application. This may include calendar information, alarms set to wake the user, etc.

[0204] Figure 21 is a flowchart of an exemplary process 2100 for data processing. Since this process 2100 can be executed using, for example, system 1900 or 2000, it will be described using elements of these systems.

[0205] In the process 2100, the device 1902 may sense data from the bed sensor 1908 (2102), receive input from the UI 1906 (2104), receive data from the cloud 1904 (2106), and receive data from other sensors 2016 or other peripheral devices (2016).

[0206] With respect to this data, device 1902 may process this data and generate data (2112) to be sent to cloud 1904 and / or data (2114) to be sent to UI 1906. Data transfer may use any technically appropriate type of network link, including but not limited to Bluetooth®, Wi-Fi, copper wire, and optical fiber media.

[0207] Process 2110 may include any of the following features (functions), all of the following features (functions), or a combination of the following features (functions): i) Digital filters such as bandpass filters, ii) Time series analysis methods, iii) Model-based methods, iv) Source separation operations such as independent component analysis (ICA), v) Wavelet transform, spectral analysis operation, vi) Trend removal analysis operation, vii) Pattern matching operation, viii) Threshold-based analysis operation, ix) Linear or nonlinear interpolation operation for calculating a surrogate index, and / or, x) Machine learning will run. The client actions performed by the device 1920 in response to process 2100 may include adjustments to adjustable features of the bed system or bedroom environment.

[0208] Figure 22 is a block diagram of an exemplary process 2200 for data processing. Process 2200 may be executed by a cloud, such as Cloud 1904, and may have access to the sleep data storage unit 1910 and the AI ​​data storage unit 2202, which contains data related to the AI ​​operation of Cloud 1904. In process 2200, the cloud receives data from device 1902 (2204) and receives data from UI 1906 (2206). The cloud also retrieves data and models from data storage units 1910 and 2202 for use in cloud processing 2210 (2208). Cloud processing 2210 may include identifying patterns, links, correlations, causes and / or associations between data, calculating quantitative values ​​(e.g., sleep score or health score) or generating qualitative sleep insight messages or hints, deriving trends, building personalized learning models or population learning models, and performing inferences.

[0209] The cloud may be prepared to store the data generated by process 2210 (2212), and the data storage units 2202, 1901 may store any data as needed. Furthermore, the cloud can prepare the data (2214), transmit the data to device 1902 (2216), and transmit the data to UI 1906 (2218).

[0210] Figure 23 is a block diagram of an exemplary process 2300 for data processing. Process 2300 may be executed by a cloud such as Cloud 1904 and may have access to the sleep data storage unit 1910, the AI ​​data storage unit 2202, and another data storage unit 2012. In process 2300, the cloud receives data from device 1902 (2204), receives data from UI 1906 (2206), and receives data from one or more API sources (2320). The cloud also retrieves data and models from data storage units 1910, 2202, and 2012 for use in cloud processing 2210 (2208). Cloud processing 2210 may include identifying patterns, links, correlations, causes and / or relationships between data; calculating quantitative values ​​(e.g., sleep scores or health scores) or generating qualitative sleep insight messages or hints; deriving trends; building personalized or population learning models; and making inferences.

[0211] The cloud may be prepared to store the data generated by process 2210 (2212), and the data storage units 2202, 1901 may store any data as needed. Furthermore, the cloud can prepare the data (2214), transmit the data to device 1902 (2216), and transmit the data to UI 1906 (2218).

[0212] Figure 24 is a flowchart of an exemplary process 2400 for sending and receiving data. Process 2400 may be performed by a UI device, such as UI 1906. The UI can operate in both in-range and out-of-range modes to send and receive inputs, settings, commands, configurations, and / or statuses from the WiFi device to the cloud 1902 and / or to the device 1902, and can operate to display sleep information from one or more sleep sessions.

[0213] Sleep information may include quantitative scores (e.g., sleep score or health score), one or more values ​​of sleep parameters and / or biometric parameters (e.g., sleep duration, movement, restful sleep duration, average heart rate, average respiratory rate), one or more sleep and / or health insights (e.g., sleep tips), and charts and graphs displaying sleep and health information and / or notifications during sleep.

[0214] Process 2400 includes receiving data from device 1902 (2402) and receiving data from cloud 1904 (2404). The UI displays information (e.g., numbers, graphs, colored indicators) and control functions (e.g., buttons, sliders, input boxes) (2406), sends data to device 1902 (2408), and sends data to cloud 1904 (2410).

[0215] Figure 25 is a flowchart of an exemplary process 2500 for sending and receiving data. Process 2500 may be performed by a UI device, such as UI 1906. The UI can operate in both in-range and out-of-range modes to send and receive inputs, settings, commands, configurations, and / or statuses from the WiFi device to the cloud 1902 and / or to the device 1902, and can operate to display sleep information from one or more sleep sessions.

[0216] Sleep information may include quantitative scores (e.g., sleep score or health score), one or more values ​​of sleep parameters and / or biometric parameters (e.g., sleep duration, movement, restful sleep duration, average heart rate, average respiratory rate), one or more sleep and / or health insights (e.g., sleep tips), and charts and graphs displaying sleep and health information and / or notifications during sleep.

[0217] Process 2400 includes receiving data from device 1902 (2402), receiving data from cloud 1904 (2404), and receiving data from API (2512). The UI displays information (e.g., numbers, graphs, colored indicators) and control functions (e.g., buttons, sliders, input boxes) (2406), sends data to device 1902 (2408), and sends data to cloud 1904 (2410).

[0218] Communication from the API (2512) may include messages to request, access, retrieve, store (save), or modify data other than data provided by the bed system. Such messages may also transmit data received from the API to the cloud unit. Such data is, i) User data such as alarms, calendar events, personal medical history, medication information, etc. ii) Sensor data such as temperature readings, humidity, air quality, exercise, steps, calories, weight, sound, light, etc., as well as interaction with the user's phone, and health-related data such as CPAP, PPG, SP02, blood pressure, blood glucose levels, etc. iii) Geographical data such as weather, lunar phases, humidity, heat index, wind, seismic activity, disease outbreaks, etc. Includes.

[0219] Figure 26 is a flowchart of an exemplary process 2600 for home automation. This process may be performed, for example, by elements of system 1900 and / or system 2000. In process 2600, selected data sent from the client is processed and written to a sleep database. Process 2600 also retrieves data from the sleep database and uses it in an AI processing component to learn individual trends and perform inference, including comparison of real-time data with trend data, to identify correlations, causes, associations, and anomaly patterns. The inference output is then used to (i) adjust the adjustable functions of the bed system (i.e., personalized sleep enhancement) if the sleeper is in bed, or (ii) provide individual recommendations and insights if the sleeper is out of bed.

[0220] Data is received from the client device (2602). For example, the client device may access data from one or more sensors to identify the user's parameters while the user is sleeping. These parameters may include direct measurements of the user (e.g., movement, bio-activity) or measurements of the environment in which the user is (e.g., bed firmness, ambient temperature, bed temperature).

[0221] The data is processed for analysis (2604). For example, a strict subset of all available data may be identified and used for analysis, while other data is not used for analysis. The identified data may include data previously identified as useful for determining sleep quality or providing insights or automated actions designed to improve the user's sleep. These determinations may include, but are not limited to, the results of machine learning processes performed on the user or on surveys of the population and subpopulations.

[0222] The data is processed (2606). For example, aggregate values ​​may be created from a larger dataset of raw values, and biometric values ​​or other values ​​may be extracted from signal analysis of one or more sets of raw values. Generally, the set of raw values ​​may be larger than the processed data, thus allowing for more advantageous and efficient processes that can be run on existing hardware. Furthermore, processing may extract signals from noise within the set of raw data. For example, heart movement may be extracted from raw pressure readings of a bed, and the number of beats per minute may be extracted from heart movement data.

[0223] The data is written to the sleep data storage unit (2608). For example, processing data may be written to the sleep data storage unit for use in the latter half of process 2600.

[0224] Individual trends are learned (2610) from data received (2609) from the sleep data storage unit. For example, trends specific to one user (e.g., unrelated to the bed the user sleeps in and not mixed with data from other users) can be analyzed by an AI operation to identify individually learned trends. For example, a user with a particularly low body temperature (e.g., due to adaptive heat generation due to healthy weight loss or simply normal biological fluctuations) may have a very different set of trends from the entire user population or all users of the same weight, etc. Similarly, a user with a particularly high body temperature (e.g., due to a metabolic response to a particularly strenuous workout (training) every night before bed, taking a cold shower before bed, or simply normal biological fluctuations) may also have a very different set of trends from the entire user population or all users of the same weight, etc. Learning individualized trends (2610) allows process 2600 to provide useful data to these users and to users in a more typical entire population or equivalent subpopulations.

[0225] Real-time data is compared to trend data (2612). For example, actual data measured for a current sleep session is compared to trend information learned for the user, a subpopulation of the user, and / or the entire population (2610). A goodness of fit between the real-time data and the trend data may be found, which can be used as a measure of how close or far the sleep environment and experience a user is experiencing in their current sleep session is from ideal ones.

[0226] If the sleeper is not in bed (2614), the user may be provided with personalized recommendations and / or insights (2620). For example, one or more parameters contributing to poor fit may be identified, and insights related to those parameters may be provided. This could be direct advice, in which case the user is suggested to directly change the parameter, e.g., "Your bedroom is too bright. Be sure to turn off the lights when you go to sleep." Alternatively, this could be indirect advice, in which case the user is suggested to indirectly change the parameter by changing another characteristic of their sleep, e.g., "You've been restless lately. Why not try sleeping on your back tonight and see if that helps you relax more and move less?"

[0227] If the sleeper is in bed (2614), the time to adjust the user's bed and / or environment is determined (2616). For example, it may be determined that a user may benefit from a decrease in bed firmness, but the bed pressure should be changed when the user enters REM sleep to avoid waking the user while they are in light sleep. These times determined may be based on clock time (e.g., 11:45 p.m.), sleep events (e.g., entering a sleep stage), or other events (e.g., playing white noise to mitigate the impact of a loud noise when one is detected).

[0228] Adjustments are made (2618). For example, a bed controller may send one or more commands to one or more components or peripherals at a determined time to trigger a specified adjustment.

[0229] Figure 27 is a flowchart of an exemplary process 2700 for home automation. This process may be performed, for example, by elements of system 1900 and / or system 2000. In process 2700, sleep data and automation commands are used to provide personalized sleep enhancement. For clarity, this process is described with reference to a specific set of components. However, one or more other systems may also be used to perform the same or similar process.

[0230] In process 2700, data transmitted from the client is processed and stored in the sleep database. To enhance real-time client data, data from other sensors besides the bed system (temperature readings, humidity, air quality, exercise, steps, calories, weight, sound, light, interaction with the user's phone, and health-related data such as CPAP, PPG, SP02, blood pressure, and blood glucose levels), as well as data from other databases besides the sleep database and AI database (weather, lunar phases, humidity, heat index, wind, seismic activity, and disease outbreaks) may be used. For example, if temperature data indicates a setting of no one being home, the real-time client data of bed status will be forced to "out of bed." In another example, if the weather database indicates an extreme rise in temperature, the real-time client data may be post-processed with updated thresholds, parameters, settings, or patterns to provide a more accurate analysis of pressure readings from the client.

[0231] Data from a sleep database can be retrieved and used in an AI processing component along with enhanced client data to learn individual trends and perform inference, including comparison of real-time data against trend data, to identify correlations, causes, associations, and anomaly patterns. The inference output is then used to (i) adjust the adjustable functions of the bed system (i.e., personalized sleep enhancement) if the sleeper is in bed, or (ii) provide individual recommendations and insights if the sleeper is out of bed. Examples include: i) identifying sleep factors that negatively affect sleep quality, such as sleep interruptions (e.g., frequent getting out of bed or prolonged bed leave during sleep), excessive movement or restlessness, longer-than-usual time to fall asleep, insufficient restful sleep, and increased sleep debt; ii) detecting whether someone has difficulty falling asleep or difficulty maintaining sleep; and iii) detecting changes in biometrics and sleep health factors, such as changes in sleep stages, heart rate, heart rate variability, respiratory rate, and movement. iv) To detect abnormal changes in sleep parameters or health parameters in relation to the sleeper's past history. v) To detect sleep disorders and health disorders such as snoring, apnea, movement disorders, heart rate disorders, pain, stress, teeth grinding, etc.

[0232] In process 2700, the AI ​​processing (2610, 2612) may include data received from other data storage units (2722, 2724). This data may include any technically appropriate type of data that could influence the user's sleep experience, such as weather, geography, and schedule data. The data may be augmented to link sleep data with non-sleep data (2726). For example, the timestamps of sleep and non-sleep data may be normalized so that simultaneous data have the same timestamp, allowing the AI ​​to more robustly identify trends in the data.

[0233] Correlations between sleep and non-sleep data can be identified (2728). For example, relatively simple correlations can be identified, as opposed to more complex (often resource-intensive) processing. For instance, for the majority of a population, noise exceeding a certain threshold (e.g., a very loud sound of 135 decibels) will wake almost all users. In less extreme cases, a simple correlation may exist between temperature within normal room temperature and sleep quality.

[0234] Using client data, sleep data, and user preference data, process 2700 may determine whether or not adjustments to the user preference data would be beneficial (2730). For example, if the user is getting less sleep or is not getting restful sleep, changes may be made to early morning meetings scheduled in the calendar, or early alarms may be changed to be beneficial.

[0235] If the user is not yet in bed 2614, a suggestion may be made to the user. For example, the user may be given a message such as, "Your first meeting is not until 10:00 AM. Would you like to set your alarm back 30 minutes to help you catch up on sleep?" Optionally, an interface element (button) may be used to allow the user to perform the suggested change.

[0236] If the user is already in bed (2614), process 2700 may perform different actions depending on whether the user has given permission for automatic adjustments to user preference data. If the user has not given permission (2734), process 2700 may perform adjustments to the user's sleep environment (2618). If the user has given permission (2734), process 2700 may adjust user preference data (2736) (optionally, with additional adjustments to the sleep environment). For example, if the user is already asleep and unable to act on the suggestion to set the alarm back 30 minutes, and the user has explicitly given permission to adjust the alarm, process 2700 may adjust the user's alarm (2736). In other situations, user data that may be adjusted includes meetings scheduled in the calendar, the ordering of items in the to-do list, etc.

[0237] Figure 28 is a flowchart of an exemplary process 2800 for controlling a graphic user interface. Process 2800 can be used to provide the user with interactive, personalized insights based on data generated about the user's sleep. The user interface unit may be configured to receive changes from the user to the values ​​of one or more sleep parameters (e.g., by displaying slider bars for changing the values ​​of one or more sleep parameters). The UI unit may then send the received values ​​(i.e., changes by the user) to a cloud unit, where an AI component may determine the impact of the changed parameters on the sleeper's sleep or health quality. The AI ​​component then provides updated quantitative values ​​(such as a sleep score or health score) or updated messages to reflect the impact of such changes on the individual user's sleep or health. This is sent back to the UI unit, and the display is updated with the updated information.

[0238] Information is displayed (2802). For example, a score for the quality of nighttime sleep is provided to the user via the GUI, along with a list of factors that influenced that score. Each factor is associated with a GUI control element (e.g., a slider, a dropdown list entry) that the user can use to input data. By default, the actual values ​​for each of these factors are displayed. As shown, manipulating the control elements displays data for a new virtual sleep session, along with the virtual sleep metric or the metric for that virtual sleep session.

[0239] Changes made by the user are received (2804). For example, to understand the effect of heat on sleep, the user may adjust the interface elements of the heat parameters from actual readings between 68°F and 72°F.

[0240] Changes made by the user are sent to the cloud (2806), and changes made by the user are received by the cloud (2808). For example, new parameters for a virtual night (in this case, the same as a real night except for the heat value) are sent to the cloud, where they are analyzed and made available for use.

[0241] AI processing is performed (2810). For example, virtual parameters are processed using the same AI processing used to generate sleep metrics for actual sleep sessions. Corresponding actual sleep parameters may also be transmitted and processed so that relative information can be tracked. Exemplary relative information may take the form of "3% improvement" or "better."

[0242] The updated information is transmitted (2812). For example, new sleep metrics and / or relative information for a virtual night may be displayed to the user in a graphical user interface as shown in Figure 29.

Claims

1. A bed with a mattress, A sleep-related sensor configured to sense sensor readings related to information concerning the quality of sleep of a user who is sleeping or scheduled to sleep on the bed, An automation controller configured to transfer the sensor readings to a cloud service, receive both commands and text-based suggestions from the cloud service to modify the user's sleep environment, apply the commands to modify the user's sleep environment if it is determined that the user is in bed, and provide the text-based suggestions via a GUI if it is determined that the user is not in bed, Hardware providing the cloud service, configured to compare real-time data of the sensor readings with trend data representing trends related to the user's sleep quality, which are pre-generated by AI processing from historical data relating to the past history of the sensor readings, in order to generate both the instructions and the text-based suggestions for modifying the user's sleep environment to be personalized for the user. A system characterized by having the following features.

2. The system further comprises: An interface device configured to display the GUI, A data storage unit that stores the aforementioned historical data, The system according to claim 1, characterized by comprising:

3. The hardware that provides the aforementioned cloud service further, The hardware providing the cloud service is configured to use data entered by the user in addition to the historical data when generating the commands to modify the user's sleep environment. The system according to feature 2.

4. The automation controller is one of a group consisting of a bed controller, a pump controller, and a voice-activated home automation controller. The system according to claim 1 or 2, characterized in that it is the same as described in claim 1 or 2.

5. The instructions for modifying the user's sleep environment include machine-readable instructions for one of the group consisting of the bed and peripheral devices. The system according to claim 1 or 2, characterized in that it is the same as described in claim 1 or 2.

6. The cloud service is further configured to transfer the commands to the automation controller for modifying the user's sleep environment. The system according to claim 1 or 2, characterized in that it is the same as described in claim 1 or 2.

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