Combination output sleep system

Abstract

A sleep system can include a control system for a bed apparatus, the bed apparatus including a platform that can support an individual thereon. The sleep system can include a plurality of input sources that trigger a combined output action mode with respect to the control system and the bed apparatus. The plurality of input sources can include sensors positioned to collect input data with respect to a subject, the bed apparatus, and / or a surrounding environment, such as motion sensors, presence sensors, proximity sensors, sound sensors, temperature sensors, biological sensors, and / or light sensors.

Description

Technical Field

[0001] This disclosure relates to a sleep system including an input sensor and an output source, the output source responding to data collected by the input sensor to provide a combined output pattern. Summary of the Invention

[0002] A sleep system may include a control system for a bed device including a platform. The control system may be standalone or integrated wholly or partially with the bed device. The sleep system may include multiple input sources that trigger combined output action patterns with respect to the control system and the bed device. The multiple input sources may include one or more input sensors positioned to collect input data about the subject, the bed device, and / or the surrounding environment. Example input sensors may include motion sensors, presence sensors, proximity sensors, sound sensors, temperature sensors, biosensors, and / or light sensors. The control system may include one or more of the input sensors and / or be configured to receive the input data collected by the input sensors. In some embodiments, the sleep system includes a bed device.

[0003] The control system can analyze collected input data and select combined output action patterns. The input sources analyzed by the control system to trigger the combined output action patterns can be single or combined. For example, brain biofeedback, respiration, pulse rate, body temperature, etc., can be analyzed to understand the subject's condition. The control system can then translate the subject's condition into a state, which may include a sleep state. In one embodiment, the control system can then map the state to an output action pattern defined as including motion and sound, or motion, sound, and light. Based on the analysis of the collected input data—such as motion, sound, lighting, temperature, or any combination thereof—the control system can also select other combined output patterns.

[0004] The sleep system includes one or more output devices that can be triggered by operation of the control system to perform selected output actions specified by the control system. The control system can be configured to communicate data with one or more output devices to trigger the specified output actions. In some embodiments, the control system and / or bed device includes one or more of the output devices. For example, the control system and / or bed device may include one or more actuators operatively coupled to the platform to perform one or more movements of the platform. As an example, these movements may include one or more of sliding back and forth (from head to toe, from side to side, and / or other angles) or pivoting about an axis. Sliding back and forth may be within a single plane or may be relative to multiple planes (arctic movement, rocking, up and down, etc., of a single or multiple planes). One or more speakers may be positioned relative to the bed device to direct sound to the platform or a subject located on the platform. One or more light-modifying devices and / or one or more temperature-modifying devices may also be positioned relative to the bed device to modify and / or maintain lighting and / or temperature conditions relative to the subject, the bed device, or the surrounding environment. In some embodiments, the control system may include a machine learning engine that analyzes collected input data as feedback on environmental factors and automatically adjusts the output to obtain a target value.

[0005] In one example, an output pattern regarding the snoring state can be triggered based on measurements collected by sound and / or motion sensors. For instance, the control system can identify the snoring state and specify a particular combination of output patterns to address it, such as triggering one or more actuators to tilt the upper end of the platform relative to the lower end, corresponding to the upper torso of a subject positioned on the platform.

[0006] The control system can analyze collected input data to detect sleep apnea states. For example, analysis of input data collected by sound sensors, motion sensors, and / or other sensors suitable for measuring attributes associated with the detection of breathing, breathing patterns, and / or breathing gaps can correspond to sleep apnea states. The control system can identify sleep apnea states and then specify output action patterns to minimize or otherwise resolve them. For example, the control system triggers actuators to move the platform, such as triggering irregular movements of the platform or other patterns.

[0007] The sleep system may include a temperature modification device. For example, the temperature modification device may be triggered to heat and / or cool the platform.

[0008] The sleep system may include one or more variable white noise settings, which may be built into the control system. The variable white noise settings can be accessed via a user interface through an interface with the control system. The user interface may be local or remote relative to the bed device.

[0009] In one embodiment, a sleep system includes a bed device. The bed device may include a platform for supporting a subject. The sleep system may also include one or more input sensors positioned to collect input data about the subject, the bed device, and / or the environment surrounding the subject and / or the bed device. The sleep system may also include a control system for receiving and analyzing the collected input data. The sleep system may also include one or more output devices operable to perform output actions specified by the control system. The output devices may include one or more actuators configured to cause movement of the platform, one or more speakers directing sound to the subject, one or more light-modifying devices modifying illumination relative to the subject, one or more temperature-modifying devices modifying the temperature of the platform, or combinations thereof. The control system may specify an output action pattern based at least in part on the analysis of the collected input data. The output action pattern may include a combination of at least two output actions selected from movement of the platform, directing sound to the subject, modification of illumination, or modification of the platform temperature.

[0010] In any of the above examples or in another example, the analysis can identify the subject's condition, and the control system can be configured to transform the condition into one or more states.

[0011] In any of the above examples or in another example, the control system may determine the subject's condition based on the analysis of the collected input data.

[0012] In any of the above examples or in another example, the control system may select at least two output actions based at least in part on one or more states.

[0013] In any of the above examples or in another example, the input sensor may include one or more sensors selected from motion sensors, presence sensors, proximity sensors, sound sensors, temperature sensors, biosensors, or light sensors.

[0014] In any of the above examples or in another example, the subject's state may include snoring, and the output action pattern may specify actions, such as tilting the upper end of the sleep platform relative to the lower end of the platform.

[0015] In any of the above examples or in another example, the subject's state may include a sleep apnea event, and the output action pattern may specify the onset of irregular or violent movement of the sleep platform.

[0016] In any of the above examples or in another example, the analysis of the collected input data may include determining the condition of the subject.

[0017] In any of the above examples or in another example, the analysis of the collected input data may include determining the subject's condition, and the subject's condition may be selected from the subject's movement over time, the subject's acceleration, the overall movement of the subject and / or the surrounding environment, the subject's body position, changes in body position over time, sound frequency and / or amplitude related to the subject, sound frequency and / or amplitude related to the environment, ambient light intensity / amplitude and / or wavelength / frequency, heart rate, heart rhythm, respiratory rate, respiratory depth, respiratory rhythm, respiratory quality, subject temperature, plateau temperature, blood pressure, subject weight, brain waves, or a combination thereof.

[0018] In any of the above examples or in another example, the analysis of the collected input data may include determining the subject's condition, and the input data analyzed by the control system to determine the subject's condition may include a combined analysis of multiple subject conditions. In another example, the multiple subject conditions used to determine the subject's condition may be selected from one or more biofeedback sensors, one or more respiratory sensors, one or more pulse rate sensors, one or more temperature sensors, or a combination thereof.

[0019] In any of the above examples or in another example, the analysis of the collected input data may include determining the condition of the subject, and the control system may determine the subject's condition by transforming one or more of the subject's conditions into one or more of the subject's states.

[0020] In any of the examples above or in another example, the output motion pattern may include platform movement and a guided subject's voice. In one example, the guided subject's voice may include variable white noise. In another example, movement may include sliding the platform back and forth or pivoting the platform about an axis. In yet another example, the output motion pattern may also include modifying the lighting for the guided subject.

[0021] In one embodiment, a control system for a sleep system includes a bed device having a movable platform for supporting a subject. The control system includes an input module detection module that receives input data collected by a plurality of input sensors. The input sensors may be configured to collect input data about the subject, the bed device, and / or the environment surrounding the subject and / or the bed device. The control system may also include a processing module that analyzes the collected input data and specifies an output action mode based at least in part on the analysis of the collected input data. The control system may also include an output module that causes one or more output devices to perform the specified output action mode. The output devices may include one or more actuators that cause movement of the platform, one or more speakers that direct sound to the subject, one or more light-modifying devices that modify illumination for the subject, one or more temperature-modifying devices that modify the temperature of the platform, or a combination thereof. The output action mode may include a combination of at least two output actions selected from movement of the platform, sound directed to the subject, modification of illumination, or modification of the temperature of the platform.

[0022] In one embodiment, a method of controlling a bed device having a movable platform for supporting a subject includes: collecting input data from one or more input sensors positioned to measure attributes about the subject; analyzing the collected input data; using at least a portion of the analysis to determine one or more conditions of the subject; converting one or more of the determined conditions into a state of the subject; identifying an output action pattern corresponding to the state of the subject, wherein the output action pattern includes a combination of at least two output actions selected from movement of the platform, sound guiding the subject, modification of lighting, or modification of the temperature of the platform; and executing the output action pattern using one or more output devices.

[0023] In one example, the output device includes one or more actuators that cause movement of the platform, one or more speakers that direct sound to the subject, one or more light-modifying devices that modify illumination relative to the subject, one or more temperature-modifying devices that modify the temperature of the platform, or a combination thereof.

[0024] In another example of the above example, or in yet another example, the input sensor may include one or more sensors selected from motion sensors, presence sensors, proximity sensors, sound sensors, temperature sensors, biosensors, or light sensors.

[0025] In any of the above examples or in another example, one or more of the subject's conditions may include the subject's movement over time, the subject's acceleration, the overall movement of the subject and / or the surrounding environment, the subject's body orientation, changes in body orientation over time, sound frequency and / or amplitude related to the subject, sound frequency and / or amplitude related to the environment, ambient light intensity / amplitude and / or wavelength / frequency, heart rate, heart rhythm, respiratory rate, respiratory depth, respiratory rhythm, respiratory quality, subject temperature, plateau temperature, blood pressure, subject weight, brain waves, or a combination of the above.

[0026] In any of the examples above or in another example, the output motion pattern may include platform movement and the guiding subject's voice. In another example, the guiding subject's voice may include variable white noise. In another example, movement includes sliding the platform back and forth or pivoting the platform about an axis. In another example, the output motion pattern may also include modifying the lighting for the guiding subject. Attached Figure Description

[0027] The novel features of the embodiments are specifically set forth in the appended claims. However, the organization and operation of the described embodiments can be best understood by referring to the following description in conjunction with the accompanying drawings, in which:

[0028] Figure 1 Sleep systems according to various embodiments described herein are illustrated;

[0029] Figure 2 An example input detection module for a control system for a bed device according to various embodiments described herein is shown. The control system is used to control operations relating to a sleep system.

[0030] Figure 3 Example processing modules for a control system for a bed apparatus according to various embodiments described herein are shown, the control system being used to control operations relating to a sleep system; and

[0031] Figure 4 Example input modules for a control system for a bed device according to various embodiments described herein are shown, the control system being used to control operations relating to a sleep system. Detailed Implementation

[0032] refer to Figure 1 The sleep system 10 may include a bed device 20, which includes a platform 22 for supporting the subject.

[0033] The sleep system 10 may include one or more input devices 30, each including an input sensor 32 operable to collect data about the subject, the bed device 20, and / or the surrounding environment. Input sensors may include, for example, optical or imaging sensors (such as cameras or light sensors), pressure sensors, temperature sensors, vibration sensors, sound sensors, biosensors, motion sensors, and / or third-party sensors. Input sensors may be integrated with the bed device, positioned around the bed device, located away from the bed device, embedded in fabric, and / or worn by the subject, for example, in clothing, a watch, a strap, or a headdress, as examples.

[0034] The sleep system 10 may also include one or more output devices 40 for performing output actions. The output devices 40 may be integrated with the bed apparatus and / or positioned relative to the platform 22 to achieve corresponding output actions relative to the platform 22 and / or the subject. The output devices 40 may include one or more motion actuators 42 for generating movement of the platform 22, one or more speakers 44 for generating audible sounds guiding the bed apparatus or the subject, one or more temperature modification devices 46 for modifying or maintaining the temperature of the bed or the subject, and / or one or more light modification devices 48 for generating or modifying illumination of the bed apparatus 20 or the subject. The bed apparatus and / or control system may be integrated with and / or associated with input devices, output devices, or any combination thereof.

[0035] The sleep system 10 may include a control system 50 configured to control the operation of the sleep system 10. The control system 50 may include an input detection module 60 configured to detect—for example, measure—one or more attributes selected from motion, sound, environmental, and / or biological properties. For example, the input detection module 60 may include one or more input sensors 32, or be operatively associated with measurement data collected by the input sensors 32, such as receiving measurement data.

[0036] The control system 50 may also include a processing module 70 configured to receive and analyze the collected input data. Based at least in part on the analysis, the processing module 70 may specify an output action pattern that includes one or more output actions.

[0037] The control system 50 may further include an output module 80 that executes a specified output action pattern, thereby causing the execution of one or more output actions. The output module 80 may include or be operatively in communication with one or more output devices 40 to execute the output action pattern. For example, output actions may include movement of the sleep platform 22 or portions thereof using one or more motion actuators 42, directed sound from one or more speakers 44, temperature modification of the sleep platform 22 using one or more temperature modification devices 46, and / or illumination modification of the directed illumination from one or more light modification devices 48. In some embodiments, output actions may include air movement modification devices, such as fans and / or haptic feedback devices. Output actions may be targeted at eliciting desired outcomes for a subject using the sleep system 10, typically an adult. For example, output actions may be targeted at stimuli relaxation, initiation of sleep, continuation or duration of sleep, sleep depth, cessation of snoring, and / or smoothness of breathing.

[0038] The control system 50 may also include a communication module 90 configured to perform communication tasks. The communication module 90 may include one or more receivers, transmitters, or transceivers configured to facilitate wired and / or wireless communication. In some examples, the communication module 90 may provide a communication link to one or more networks, such as private networks, local area networks, personal area networks, wireless networks, wide area networks, Bluetooth networks, or other networks. The communication module 90 may import system updates, machine learning / artificial intelligence protocols and / or data, and engage with remote user interfaces, remote peripheral devices (which may include sensors and / or output devices), and / or user equipment. The communication module 90 may be associated with local or remote data storage devices. The communication module 90 may engage with cloud capabilities and / or teleprocessing. The communication module 90 may transmit data to a central data analysis repository for specific and / or global analysis. As described above, the processing module 70 may specify output action patterns based at least in part on the analysis of input data. For example, the processing module 70 may determine the subject's condition in relation to the subject, bed, and / or their environment based at least in part on the analysis of the collected input data. In one embodiment, processing module 70 can transform one or more subject conditions into one or more subject states. Processing module 70 can utilize one or more subject conditions to specify an output action pattern, including one or more output actions, based at least in part on analysis. In some embodiments, the specification of the output action pattern by processing module 70 also includes consideration of one or more subject condition or attribute measurements, which may or may not have been utilized when transforming one or more subject conditions into one or more subject states.

[0039] The output action pattern may include one or more output actions. Output actions may include various parameters associated with the action, such as amplitude, frequency, wavelength, direction, style, type, degree, intensity, volume, rhythm, variation, consistency, interlude, etc. The output action pattern may include a combination of output actions and associated parameters, which may be triggered by the processing module 70 in response to analysis of the collected input data. In some embodiments, the processing module 70 may include and / or generate one or more output action patterns, which include one or more output actions and associated parameters of such output actions, which may be specified relative to the identified subject state.

[0040] The control system 50 may also include an output module 80 configured to execute an output action mode specified by the processing module 70. The output action mode specified by the processing module 70 may be for devices of the output module 80 or devices operable via the operation of the output module 80, such as one or more sound generating devices for generating specified audio—e.g., a speaker 44; a motion actuator 42 for generating specified movement of the sleep platform 22 or structure where the subject is positioned; a temperature modifying device 46 for modifying or maintaining a specified ambient temperature or the temperature of the sleep platform 22 or structure where the subject is positioned; and / or a lighting device 48 for modifying or maintaining specified illumination for the subject. For example, the output module 80 may include a speaker operable to generate specified audio; a lamp operable to generate specified illumination; a fan controlling airflow—which may include a movable fan; and / or a heater or cooler controlling the temperature of the airflow generated by the fan; a heater operable to increase a specified temperature of the bed equipment or its platform, clothing, or the environment adjacent to the bed equipment; a cooler operable to decrease the temperature of the bed, clothing, or the environment adjacent to the bed; and an actuator operable to actuate one or more parts of the bed equipment. The input device 30 or its sensor 32 can also be used to provide feedback on the action of the output module 80 and the effect of such action on the subject's condition.

[0041] Figures 2 to 4 Various example modules for a control system of a bed device are shown, which may be similar to and / or adapted to the above-mentioned... Figure 1 The control system 50 described herein operates together. It should be understood that the control system 50 may include various components operable to control the sleep system described herein, including various combinations of motors, drivers, sensing circuits, processors / microprocessors, databases, software, hardware, firmware, etc., depending on the implementation requirements.

[0042] Figure 2An example input detection module 60 for a control system of a bed apparatus is shown. The input detection module 60 may include a motion detection unit 62 configured to detect motion, which may include proximity or presence. The detected motion may be relative to the subject, the bed apparatus, and / or the subject and / or the surrounding environment of the bed apparatus. The motion detection unit 62 may include and / or incorporate one or more input devices 30, each including one or more motion input sensors 32a configured to detect such motion. Example motion input sensors 32a may include vibration sensors, accelerometers, gyroscopes, light sensors, force or weight sensors, piezoelectric sensors, optical sensors, infrared sensors, electro-optic sensors, photodiodes, and / or capacitive sensors. Data obtained from the motion input sensors 32a may be transmitted to a processing module.

[0043] Motion input sensor 32a can be integrated with or otherwise associated with the bed device, such as being positioned or locatable within and / or around the sleep platform of the bed device. For example, a weight sensor can be integrated into the sleep platform to determine the presence of a subject, weight for continuous health monitoring, and / or movement. In one example, a device or accessory containing an accelerometer or gyroscope can be worn by the subject. In one example, clothing, sheets, pillows, or another object associated with the subject or the bed device can include markers that can be identified and / or tracked by motion input sensor 32a to detect movement. Motion input sensor 32a can be embedded in fabric and can include, for example, a flexible sensor. In one example, motion input sensor 32a embedded in fabric includes a flexible sensor. In the above or another example, motion input sensor 32a including an imaging sensor can be positioned to capture images of the subject on the sleep platform. For example, video can be used to capture video images of the subject for image analysis to determine the subject's position, orientation, presence, proximity, respiratory movement, and / or other movement or orientation. In the above or other examples, thermal or infrared imaging can be used to measure the subject's movement, temperature, presence, proximity, position, and / or orientation. In some embodiments, one or more motion input sensors 32a may be located remotely from the sleep platform and may be positioned to detect movement with respect to the subject, the bed, and / or the surrounding environment. As described above, motion detection can be used to determine sleep states, such as REM sleep, NREM sleep, and / or N1 to N3 stages of NREM. Motion detection can also be used to detect other related conditions, for example, breathing, snoring, sleep apnea, sleepwalking, insomnia, or narcolepsy. Based on the collected information, other conditions and symptoms, such as coughing, irregular movement, agitation, or twitching, may also be detected, as examples.

[0044] In various embodiments, the input detection module 60 may include a sound detection unit 64 configured to detect sound. The detected sound may be related to the subject, the bed equipment, and / or the environment surrounding the bed and / or the subject.

[0045] The sound detection unit 64 may include or incorporate one or more input devices 30, each including one or more sound input sensors 32b configured to detect sound. The sound input sensors 32b may include, for example, a microphone, a pressure sensor, and / or a vibration sensor. Data obtained by the sound input sensors 32b can be transmitted to a processing module.

[0046] The sound input sensor 32b may be integrated with or otherwise associated with the bed apparatus, such as being located or locatable within and / or around the sleep platform of the bed apparatus. In one example, a microphone may be integrated with or otherwise associated with clothing, pillow, or sleep platform worn by the subject for detecting audio about the subject, such as breathing, snoring, or coughing. The sound input sensor 32b may be embedded in fabric and may include, for example, a flexible sensor. In some embodiments, one or more sound input sensors 32b may be located remotely from the sleep platform and may be positioned to detect sounds about the subject, the bed, and / or the surrounding environment.

[0047] In some embodiments, the input detection module 60 may include an environmental detection unit 66 configured to measure environmental properties with respect to the bed equipment, the subject, and / or the surrounding environment.

[0048] The environmental properties measured by the environmental detection unit 66 may include temperature, light, atmospheric pressure, and humidity. The environmental detection unit 66 may include one or more input devices 30, which may include one or more environmental input sensors 32c, such as thermometers, photoelectric sensors, barometers, pressure sensors, photodetectors, electro-optic sensors, contact sensors, photodiodes, hygrometers, and / or other sensors suitable for measuring environmental properties. Data obtained from the environmental input sensors 32c can be transmitted to the processing module.

[0049] The environmental input sensor 32c can be integrated with or otherwise associated with the bed device, such as being positioned or locatable within and / or around the sleep platform of the bed device. For example, a temperature sensor can be integrated into the sleep platform to measure the temperature of the sleep platform. The temperature sensor can be integrated with or otherwise associated with a pillow or the subject's clothing. The environmental input sensor 32c can be embedded in fabric and can include, for example, a flexible sensor. In the above or another example, the temperature sensor can be positioned around the sleep platform to measure the ambient temperature. In one example, one or more light sensors can be integrated and / or positioned around the sleep device. In some embodiments, one or more environmental input sensors 32c can be positioned remotely from the sleep platform and can be positioned to measure the environment with respect to the bed device and the subject.

[0050] The input detection module 60 may include a biodetection unit 68 configured to measure the biological attributes of the subject.

[0051] Example biometrics that can be measured may include heart rate, heart rhythm, respiratory rate, respiratory depth, body temperature, blood pressure, the subject's electrical characteristics—such as the skin's electrical properties O, brain waves (α, β, δ, θ, and / or γ brain waves), and / or other biometrics. The biometric detection unit 68 may include and / or acquire data collected by one or more input devices 30, which include one or more bio-input sensors 32d for measuring the subject's biometrics. The one or more bio-input sensors 32d may include a respiratory monitor, such as an infrared finger cuff, SpO2 sensor, CO2 sensor, optical imaging sensor—such as a visible wavelength or infrared video for measuring respiratory-related movement; a cardiac monitor for monitoring heartbeat, such as a Holt monitor; a vibration sensor for detecting heartbeat and / or respiration, such as a piezoelectric sensor; a blood pressure sensor, such as a blood pressure cuff or an implanted transducer assembly; a thermometer; a skin conductance response (GSR) sensor; an infrared sensor; a biosensor, such as an implanted biosensor, a capacitive sensor; a local or remote electroencephalogram (EEG) device; and / or other suitable sensors for measuring biometrics. Data acquired by the biosensor 32d can be transmitted to a processing module. In an embodiment, the biosensor 32d may include an accelerometer or other vibration sensor that measures the subject's breathing by measuring vibrations in a sleep platform or fabric worn by the subject.

[0052] The bio-input sensor 32d can be integrated with or otherwise associated with the bed device, such as being located or locatable within and / or around the sleep platform of the bed device. For example, a microphone can be integrated with or otherwise associated with clothing, pillow, or sleep platform worn by the subject for detecting audio about breathing and / or heartbeat. The bio-input sensor 32d can be embedded in fabric, for example, the fabric may include flexible sensors. The subject can wear a watch, belt, waistband, or helmet, for example, including one or more bio-input sensors 32d, such as one or more pulse monitors, GSR sensors, or body temperature thermometers. In some embodiments, one or more bio-input sensors 32d can be located remotely from the sleep platform and can be positioned to remotely acquire biometric results. For example, remote EEG and / or infrared imaging can be positioned to remotely measure brain waves or body temperature.

[0053] Figure 3 An example processing module 70 for a control system of a bed device is shown. Processing module 70 may include one or more processing units, a generator, an engine, etc., for controlling various operations of the sleep system. Controlling the various operations of the sleep system may include a control and / or support input detection module 60. Figure 2 ) and / or output module 80 ( Figure 4 One or more operations.

[0054] The processing module 70 may include various processing and / or control-related components for receiving and processing inputs and generating outputs. Inputs may include data or control signals from various sensors or devices, such as user interfaces, microphones or sound sensors, motion sensors, presence sensors, environmental sensors such as temperature sensors and / or light sensors, biosensors, etc.

[0055] Processing module 70 may include or be configured to access one or more databases. The databases may include, for example, a pattern library 75 and / or one or more output action databases. Processing module 70 may receive collected input data from the input detection module, specify an output action pattern based at least in part on the analysis of the collected input data, and transmit the specified output action pattern to the output module. The transmitted output action pattern may include data signals providing instructions and / or control signals for, for example, executing the specified output action through a corresponding output module unit.

[0056] In some embodiments, the processing module 70 includes a preprocessing unit 72 configured to preprocess the collected input data. For example, the preprocessing unit 72 may adjust the collected input data, which may include signal or format conversion and / or filtering of the collected input data.

[0057] In one embodiment, the preprocessing unit 72 filters collected motion data; sound data; environmental data, such as temperature and / or light data; and / or biological data. Filtering can be used to remove signal noise, remove unwanted portions of the data, and / or identify portions of the data relevant to the generated output motion pattern.

[0058] For example, collected motion data can be filtered to identify and / or remove noise. Collected motion data can also be filtered to identify or isolate motion associated with the subject's movement and / or remove motion associated with the environment, such as the movement of a fan, caregiver, or object. In some embodiments, the movement of objects such as clothing, blankets, or pillows can be used to correspond to the subject's movement. As another example, sound data can be filtered to remove frequencies and / or amplitudes not associated with the subject, such as ambient noise or sounds associated with the subject's environment, such as televisions, radios, electronic devices, fans, motors, dogs, etc. Directional filters can be used to filter sounds originating from distances from the sleep platform and / or the subject. In some embodiments, control module 70 does not include preprocessing unit 72.

[0059] Processing module 70 may include a state unit 73 configured to analyze collected input data, which may be preprocessed by preprocessing unit 72 or not, to determine one or more conditions of the subject. A condition may include the quantification of one or more measured attributes. Some measured attributes may be grouped and / or determined using combination formulas. For example, the input sources being analyzed may be single or combined. A condition may also include threshold determinants regarding attributes and / or their measurements (e.g., presence). In some embodiments, certain measured attributes may be excluded when one or more other measured attributes are identified as present or within a specific range or threshold. In some embodiments, a condition may be represented by one or more scores, which may be scaled and / or standardized.

[0060] In various embodiments, collected input data can be analyzed for one or more subject conditions related to the subject's heart rate, temperature, respiration, sound, and / or movement. For example, heart rate status can be determined from one or a combination of collected sound data, vibration data, electrocardiogram (ECG), and / or imaging data—such as photoplethysmography (PPG). Consciousness status can be determined from brain biofeedback data. In one example, alpha and / or delta brain waves or their rhythms can be compared and / or measured with beta, gamma, and / or theta brain waves. In embodiments, respiratory rate status can be obtained from the analysis of motion data, vibration data, and / or sound data.

[0061] In various embodiments, state unit 73 can determine one or more conditions relating to the subject's movement over time, the subject's acceleration, coarse motion of the subject and / or the surrounding environment, the subject's body orientation, changes in body orientation over time, sound frequency and / or amplitude relating to the subject, sound frequency and / or amplitude relating to the environment, ambient light intensity / amplitude and / or wavelength / frequency, heart rate, heart rhythm, respiratory rate, respiratory depth, respiratory rhythm, respiratory quality, subject temperature, plateau temperature, blood pressure, subject weight, brain waves, the subject's electrical characteristics, or combinations thereof. In one embodiment, state unit 73 can analyze motion data to determine the subject's position and / or orientation. For example, infrared imaging data can be analyzed to determine the subject's position and / or body orientation.

[0062] State unit 73 can also convert one or more conditions into a subject state. Converting one or more conditions into a subject state may include comparing the condition with criteria for one or more subject states. For example, one or more of the following may be combined with environmental and time factors to determine whether the subject is in a specified state: measured respiratory status, subject temperature status, bedding and / or environment, duration of one or more conditions, liver status, orientation status, sound status, light status, pulse rate status, movement status, or brain biofeedback status.

[0063] Sleep states can include the identification of specific sleep periods and / or sleep stages. Sleep can be divided into two periods—non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep. NREM sleep has three stages: N1 to N3. Stage N1 occurs immediately after falling asleep and is very short, typically less than 10 minutes. In this N1 stage, an individual may be easily awakened and is characterized by alpha and theta waves and slowed eye movements. Stage N2 may include a sudden increase in brain wave frequency, sleep spindles or σ waves, followed by slow wave or delta wave activity. Stage N2 typically lasts about 30 to 60 minutes. Stage N3 is deep sleep and lasts about 20 to 40 minutes. During N2, slower delta waves are generated and increase. There are no eye movements, and even if there is body or muscle movement, it is minimal. REM sleep occurs about 1 to 2 hours after falling asleep. During this period, sleep is deep, the eyes may rapidly turn in different directions, and brain activity increases. REM sleep may be accompanied by an increase in blood pressure and heart rate. Breathing may become shallow, irregular, and more frequent. Brief episodes of sleep apnea may also occur. Dreaming occurs during REM sleep, and the brain paralyzes the muscles. The progression of sleep stages repeats throughout the night, with the duration of REM sleep typically increasing from about 10 minutes to over an hour. The proportion of REM sleep decreases with age, with adults spending about 20% of their sleep time in REM sleep, while infants may spend up to 50% of their sleep time in REM sleep.

[0064] Snoring status may include comparing, for example, a subject’s status regarding sound conditions corresponding to the frequency and / or amplitude of snoring with one or more conditions corresponding to sleep status. In some embodiments, one or more conditions corresponding to sleep status may include respiratory rate status, heart rate status, and / or brain biofeedback status.

[0065] Apnea event states may include one or more breathing-related conditions—such as respiratory rate, heart rate, and motion data—and one or more conditions corresponding to sleep. In some embodiments, the breathing-related conditions may be obtained from collected sound data, vibration data, and / or motion data, and in some embodiments, the sleep-related conditions may be obtained from collected motion data, heart rate data, and / or brain biofeedback data. A cold state may include one or more breathing-related conditions—such as respiratory rate, depth, frequency, and / or fluency—and one or more sound-related conditions—such as coughing, congestion, wheezing, and / or airway obstruction. A cold state may also include one or more conditions related to motion data, such as detected coughing. A fever state may include body temperature status. A sleepwalking state may include motion status during sleep, indicating a state of unconsciousness in the subject; this may include brain activation status, such as wave status. A narcolepsy state may include detecting rapid transitions between wakefulness and sleep states. An insomnia state may include motion status, heart rate status, respiratory status, and / or duration during other sleep periods.

[0066] In some embodiments, state unit 73 may be configured to define new subject states based on observations and / or understanding of the subject. In this or another embodiment, state unit 73 may be configured to define new subject states based on machine learning / artificial intelligence. Processing unit 70 may also be upgraded; for example, communication module 90 may receive updates and / or upgrades to include new subject states based on requests, pre-defined updates, when available, or based on analysis of input data indicating the existence of previously unspecified subject states. In one embodiment, state unit 73 may be configured to combine two or more subject states to describe an additional subject state.

[0067] It can also analyze one or more conditions of the surrounding environment to modify the conditions, status and / or output actions of its specified parameters.

[0068] The processing module 70 may further include an output action designation unit 74. The output action designation unit 74 may be responsible for mapping one or more identified states to one or more output action patterns, which may include one or more output actions. In one example, the output action pattern includes a designated output action, which may include movement of the sleep platform or a series of movements. In another example, the output action pattern includes one or more designated output actions, such as adjustment of the sleep platform's position or single, compound, discrete, continuous, or variable movement; adjustment of ambient lighting; adjustment of the sleep platform's temperature; and / or initiation or modification of a sound guiding the subject. In the above or another example, the output action pattern includes sound output selected from white noise, variable white noise, noise cancellation, music, ambient sound, natural sound, variable frequency and / or amplitude sound, and repetitive sound.

[0069] Processing module 70 may also include or access a pattern library 75 storing one or more output action patterns for selection and / or modification. One or more output action patterns may include previously generated or pre-programmed output action patterns. In one embodiment, output action specifying unit 74 includes or accesses the action pattern library 75 to specify one or more of a plurality of output action patterns for specification. Output action patterns may include defined actions or action patterns, such as motion, sound, temperature, and / or light patterns. Some output action patterns may additionally or alternatively include airflow or tactile patterns. Output action patterns or one or more specific output actions of output action patterns may be predefined or calculated based on one or more conditions of the subject. In one embodiment, the pattern library includes a plurality of selectable output action patterns. Output action patterns may include one or more output actions, wherein the output pattern generator 76 and / or machine learning engine 78 modify parameters of the output actions based on measured attribute values, states, and / or conditions of the subject. Parameters may be adjusted in real time or may be determined before the output action pattern or one or more of its output actions are initiated.

[0070] Therefore, using a defined state, the output action specifying unit 74 can access the pattern library 75 and identify output action patterns. These output action patterns can include multiple output actions or variations thereof corresponding to the state for specification. The specified output action pattern can be transmitted to the output module for execution as described herein. The specified output action pattern can include one or more signals for executing one or more output actions of the identified or calculated output action pattern.

[0071] The identification of subject state mapping and / or corresponding output action patterns may include a combination of subject-specific parameters. For example, a subject may be identified by inputting their identity into a user interface, biometrically, or by detecting an identification card or chip worn by or near the subject. In some embodiments, the state unit 73 and / or the output action designation unit 74 do not consider the subject's identity in mapping, designating output actions, and / or generating output action patterns.

[0072] In one example, an output pattern regarding the snoring state can be triggered based on measurements collected by sound and / or motion sensors. For instance, the control system can identify the snoring state and specify a particular combination of output patterns to address it, such as triggering one or more actuators to tilt the upper end of the platform relative to the lower end of the platform corresponding to the upper torso of the subject positioned on the platform, altering the bed's motion pattern, outputting audio, and other measures that the person has already actively responded to in reducing snoring events.

[0073] The control system can also analyze the collected input data to detect sleep apnea states. For example, analysis of input data collected by sound sensors, motion sensors, and / or other sensors suitable for measuring attributes associated with the detection of breathing, breathing patterns, and / or breathing absence can correspond to sleep apnea states. The control system can identify sleep apnea states and then specify output action patterns to minimize or resolve them. For example, the control system can trigger actuators to move the platform, such as triggering irregular movements or other patterns of the platform.

[0074] As described above, in some configurations, the output action specifying unit 74 can generate—for example, calculate an output action pattern for a determined state, which may include one or more output actions. For example, the output action specifying unit 74 may include a pattern generator 76 configured to generate an output action pattern.

[0075] Pattern generator 76 can generate output patterns by constructing and / or modifying one or more output action patterns stored in pattern library 75 using one or more aspects of collected input data, which may include one or more states. For example, in one embodiment, processing module 70 includes pattern generator 76 for generating output action patterns. Pattern generator 76 can generate output action patterns based at least in part on one or more values ​​associated with measured attributes, subject condition, and / or subject state. For example, pattern generator 76 can apply predefined rules to output action pattern templates to generate generated output action patterns with modified output actions and / or modified parameters of the output actions. In one embodiment, the output pattern and / or its parameters can be modified based on user-controlled variables, such as personal preferences.

[0076] The output action patterns created or modified by pattern generator 76 may include currently selectable output patterns for specifying, or may include output pattern templates for generating specific output patterns. For example, pattern generator 76 may use predefined rules that utilize one or more measured attributes present in the collected input data; these measured attributes may include states. The generated output action patterns may be specified for the current state and / or stored in pattern library 75 for later specification or further modification. In one embodiment, pattern generator 76 does not construct from existing output action patterns.

[0077] The output action patterns stored in pattern library 75 for specifying can include predefined patterns or generated patterns. In some embodiments, generated patterns include output action patterns programmed for specifying and executing during a learning cycle, wherein pattern generator 76 is implemented to introduce variations in the patterns. For example, pattern generator 76 may include or be coupled to machine learning engine 78, which is configured to analyze input data collected after pattern initiation, and the patterns may be pre-programmed or user-generated output action patterns. In some embodiments, machine learning engine 78 may also analyze input data collected before output action patterns are initiated. In the above or another embodiment, machine learning engine 78 may analyze conditions and / or states, as well as input data collected after and / or before output action patterns are initiated. In one embodiment, machine learning engine 78 analyzes historical data, such as input data collected regarding previous conditions, states, specified output actions, and / or the impact of measured characteristics, conditions, and / or states on the outcome of specified output actions during or after execution, to determine the effectiveness of the output action patterns and their permutations of the target. In one example, this data may be obtained from other users or the general population. The target may include, for example, conditions, states, and / or baseline data values ​​corresponding to relaxation, sleep, breathing smoothness, heart rate, and / or reduced snoring. Using this information, the pattern generator 76 can further customize the output action pattern through appropriate modifications.

[0078] As described above, the pattern generator 76 includes or is coupled to a machine learning engine 78, which can be configured to generate output motion patterns using machine learning and / or artificial intelligence protocols. The output motion patterns may include their parameters. The machine learning engine 78 can be local to the bed device or can be remote, for example, cloud-based or accessible via communication with one or more machine learning and / or data computing servers. The machine learning engine 78 can generate and / or modify the output motion patterns. In one embodiment, the machine learning engine 78 can modify the output patterns based on user input, such as preferences, and / or based on feedback collected by sensors during past output combinations. For example, the machine learning engine 78 can determine the validity of one or more values ​​of motion and / or sound for a subject—such as values ​​associated with measured attributes, subject condition, and / or subject state. The validity of motion and / or sound may include one or more parameters of the output motion and / or sound and / or its pattern. This information can be used to modify the output patterns and / or, together with the pattern generator 76, generate new output patterns to influence one or more attributes, conditions, or states. In some embodiments, the machine learning engine 78 can modify or generate the output motion patterns in real time during execution. In various embodiments, different output modes can be selected or generated based on the subject's state. For example, the output action designation unit 74 can designate the output action mode based on how long the subject has slept, what sleep state they are in, or other factors such as when the subject wakes up or whether the subject has a condition such as a fever. For example, snoring may be caused by a cold and is not part of their normal sleep pattern. In this case, an output mode different from the output mode designated for typical snoring can be specified.

[0079] Processing module 70 may include a user interface 79 for receiving input from a user—such as a subject or caregiver and / or other sources. User interface 79 may be configured to allow the user to input subject-related data, such as age, weight, sex, preferences, medical condition, and / or target mode selection. Target mode selection may, for example, specify one or more specific modes or categories for which processing module 70 targets a specified output action. For example, the user may specify a snoring mode, where processing module 70 specifies an output action aimed at reducing snoring, or a sleep apnea mode, where processing module 70 specifies an output action aimed at minimizing sleep apnea. Target mode selection may also include relaxation, sleep, and / or soothing modes corresponding to the output action mode or output action mode program, such as utilizing machine learning engine 78, configured to target relaxation, sleep, or soothing parameters, conditions, and / or states. In some embodiments, processing module 70 operates in multiple modes or in a general mode based on input data, such as conditions and / or states, targeting all programmed goals. For example, processing module 70 may target the minimization of sleep apnea, snoring, relaxation, and stable sleep. The output pattern used to pursue a goal or target value can be predefined and / or generated as described above, which can include integrated machine learning.

[0080] Components of the processing unit 70 and / or user interface 79 may be located on or away from the bed apparatus or a portion thereof in the sleep system. For example, the user interface 79 may be an integral part of the bed apparatus, or may include a separate unit that can be connected to the bed apparatus via wired, wireless, or other means, such as a separate unit on a mobile peripheral device. Wireless connectivity may be Wi-Fi, Bluetooth, etc. In some embodiments, the user interface 79 or a portion thereof may include a remote user interface provided by an application running on a computing device, which may include a smartphone. The remote user interface may be associated with the bed apparatus directly or indirectly via the communication module 90. Cloud-based capabilities may also be utilized to store user preferences and historical data for offline processing or archiving. Offline processing may allow for more in-depth analysis that might otherwise overwhelm the processing module 70, and incorporate global data from multiple users and / or sources into the analysis. Such results can then be sent back to the processing module 70 to enhance or upgrade its responsiveness, functionality, or accuracy.

[0081] The user interface 79 may include controls, settings input, and other input data that can be sent to the processing module 70. Controls may include on / off controls, sound controls, motion controls, light controls, etc. Controls can be enabled or disabled.

[0082] User interface 79 can provide cloud-based functionality. Cloud-based functionality may include account management, the ability to invite other account holders to manage profiles, adding friends, comparing session data with friends, anonymous posting to world data, comparing session / episode / epic data with world data, social commenting, web views of data, and more.

[0083] In one embodiment, the control system 50 incorporates one or more user-controlled variables. These user-controlled variables may relate to parameters of one or more output actions and / or specific output actions or their patterns. For example, a user may interact with the user interface 79 to select and / or define one or more output actions to be performed. In some embodiments, output actions may be added to an output action pattern, or the corresponding output action of an output action pattern may be modified. Without user selection and / or definition of user-controlled variables, the control system 50 may execute an output action pattern according to the specified pattern. The output of the machine learning engine 78 and / or the pattern generator 76 may be based on, incorporated into, and / or constrained by user-controlled parameter variables—such as personal preferences—to modify or generate output action patterns. In the above or another embodiment, the machine learning engine 78 may be configured to receive user-controlled parameter variables, such as sound amplitude, frequency, pitch, style, rhythm, transition, and / or their patterns; light wavelength / color, intensity, transition, and / or their patterns; temperature start point, end point, rate of change, and / or temperature modification patterns; airflow speed, volume, direction, temperature, and / or their patterns; and / or motion frequency, amplitude, direction, transition, single-axis pattern, multi-axis pattern, and / or their patterns. In some embodiments, the user can choose which parameters to control. When the user defines specific parameter variables, the processing module 70 can override the parameters of the executed output pattern and / or another parameter to conform to the user-defined parameter variables. In some embodiments, user-specified parameters can be used to modify other output actions or their associated parameters. In one embodiment, the pattern generator 76 and / or machine learning engine 78 can use user-controlled variables to guide the generation and / or modification of output patterns. For example, user preferences or other data inputs can be used to generate and / or modify patterns using such data, along with feedback collected by sensors during past output combinations and / or currently collected data and / or parameters, such as biological, environmental, or other parameters, conditions, or states.

[0084] In some embodiments, system 10 may be configured to provide reports on a subject's use of system 10. For example, processing module 70 may include a report generator 77. Report generator 77 may access data stored and / or collected by system 10. In some embodiments, user interface 79 includes a display for showing information to a user. In one such embodiment, report generator 77 may engage with user interface 79 to generate a display including a report or report summary. In another example, report generator 77 and / or user interface 79 may engage with communication module 90 to transmit a report or portions thereof via email, text messaging, video display, voice, or other suitable reporting media. In one embodiment, communication module 90 may distribute or make reports available directly or indirectly to a user application running on a user device, such as a laptop, smart device, television, or smartphone. The user application may be dedicated to the operation of the bed device or may include third-party applications. For example, the application may be used to input control operations, preferences, personal data, and / or provide additional input data resources. The application may be used to receive reports, analyze data, and share reports with social networks or healthcare networks.

[0085] Reports can be about measured attributes, states, conditions, and / or output actions. For example, reports may include values ​​for measured attributes such as heart rate, respiratory rate, respiratory rate, blood pressure, brain waves, temperature, sleep duration, sleep state, and / or sleep period / stage duration and / or pattern. These values ​​may be provided over time, averaged, statistically analyzed, compared with historical data, or compared with the general population and / or preset targets. Reports may include information about how the subject responded to specific output actions or patterns, such as the values ​​of the measured attributes. For example, reports may include output actions, which may also include relevant parameters and how the subject responded.

[0086] The report may include differences in measured attributes over time, such as differences within a single session or across multiple sessions. In some embodiments, the report may identify or provide data for or to identify potential health conditions corresponding to values ​​of the measured attributes. For example, processing module 70 may include a health status module configured to analyze measured characteristics and provide indications of potential health conditions, such as cough or sleep apnea.

[0087] Figure 4 An example output module 80 for a control system of a bed device is shown. As described above, a sleep system may include an output module 80 configured to execute an output action mode. Also as described above, a processing module is configured to transmit or otherwise provide an output action mode or corresponding control signal to the output module 80 to output a specified output action.

[0088] In various embodiments, the output module 80 may include a motion generation unit 82, a sound generation unit 84, a temperature modification unit 86, and / or a lighting modification unit 88. The motion generation unit 82 may be configured to perform a moving portion of an output motion pattern by generating or causing the generation of a specified motion. The motion generation unit 82 may include or be configured to signal-communicate with one or more motion actuators 42, which are operable to move one or more parts of the bed device, such as a sleep platform. The motion actuators 42 may include, but are not limited to, motors, transmissions, airbags, motion transmitters, belts, pulleys, gears, robots, solenoids, pneumatic pistons, etc. The motion generation unit 82 may include or be configured to communicate wired or wirelessly with one or more motion actuators 42 via a suitable communication port, which includes a corresponding wired or wireless transmitter, receiver, and / or transceiver for inducing a specific movement of the sleep platform or a portion thereof. Motion actuator 42 may be arranged relative to the sleep platform to cause movement of the platform. Movement may include, but is not limited to, back-and-forth movement, such as linear (e.g., head-to-toe) movement, lateral (e.g., side-to-side) movement, vertical (up-down) movement, side-to-side and / or head-to-toe tilting movement, and / or other movements, including combinations thereof. Movement may be along a plane relative to the platform or along multiple planes, such as up-and-down, rocking, or swaying. In another example, such movement may include or incorporate low-amplitude movement, which may be provided at a high frequency to cause vibratory movement. In one embodiment, motion actuator 42 may be arranged to cause the sleep platform to pivot about an axis in an arcuate motion, or about an axis intersecting the platform. In some instances, the axis may intersect the central portion, side portion, upper portion, or lower portion of the platform.

[0089] In various embodiments, the motion actuator 42 may be arranged to tilt the sleep platform or a portion thereof. For example, the sleep platform may be tilted laterally, upwards, or downwards. In one example, the motion generation unit 82 is configured to tilt and / or lower the upper end relative to the lower end. Thus, the motion generation unit 82 may tilt and / or lower the upper body of a subject positioned on the sleep platform relative to the lower body of the subject. In this or another example, the motion generation unit 82 is configured to tilt and / or lower the lower end relative to the upper end. Thus, in some embodiments, the motion generation unit 82 may be configured to tilt and / or lower the lower body of a subject positioned on the sleep platform relative to the upper body of the subject. In various embodiments, the sleep platform may move about or relative to multiple axes. Additionally or alternatively, one or more motion actuators 42 may be positioned to move the subject independently of the sleep platform. For example, an airbag may be positioned relative to the platform to lift / push the subject's body. Movement patterns may include movement within one, two, three, four, five, or six degrees of freedom. Movement patterns may be provided relative to the platform and / or the subject. In some examples, the sleep platform is operable to yaw, roll, pitch, undulate, and / or rock. Movement patterns can combine complex combinations of movements within these degrees of freedom to generate proprioceptive and / or vestibular system responses in the subject. In addition to or different from the motion actuator 42 positioned to move the subject, the motion actuator 42 may be used, such as an actuator or motor for pushing / pulling the platform left and right. In one example, the motion actuator 42 includes pistons operably coupled to multiple locations on the platform, such as at multiple corners or other locations. In one such example, the pistons are located at four or more corners of the platform. The platform can be of any shape, such as circular, elliptical, square, rectangular, or any other geometric or non-geometric shape. In one example, the actuator is coupled to the platform at one or more locations. In another embodiment, the platform is mounted on a frame or other platform, thereby transmitting movement to the platform. In various embodiments, such a frame or platform can also be considered a platform. These and other configurations can be used to generate complex movements in place within a small footprint to advantageously produce most movement patterns without requiring additional real estate. Movement can be singular, rhythmic, repetitive, dynamic, varied, or irregular. Combinations of movements within one or more degrees of freedom can be designed to affect the inner ear with limited bodily movements to produce a sensation of movement.

[0090] The sound generation unit 84 can be configured to perform the sound portion of the output action mode by generating or causing the generation of a specified audio track. The sound generation unit 84 may include or be configured to communicate signalally with one or more speakers 44, which are operable to emit sound from the specified audio track in the sound portion of the output action mode. The sound generation unit 84 can be configured to communicate wired or wirelessly with one or more speakers 44 via a suitable communication port, including a corresponding wired or wireless transmitter, receiver, and / or transceiver.

[0091] The speaker 44 or other sound generating device of the sound generating unit 84 may be integrated with or otherwise associated with the bed device or its sleep platform. For example, one or more speakers 44 may be located on or around the bed device. In another example, one or more speakers 44 may be positioned around a portion of the sleep platform corresponding to the intended position of the subject's head during use, such as an end of the sleep platform. In these or other embodiments, one or more speakers 44 may be located away from the bed device. In the above or additional embodiments, one or more speakers 44 may be integrated with or otherwise associated with clothing or pillows worn by the subject. In one example, the speaker is a directional speaker to specifically direct sound towards the subject, e.g., so that it reaches only the subject.

[0092] The temperature modification unit 86 can be configured to perform a temperature portion of an output operating mode by generating or causing a specified modification of the temperature of the subject, sleep platform, or ambient air relative to the bed apparatus including the sleep platform. The temperature modification unit 86 may include or be configured to signal-communicate with one or more temperature modification devices 46—e.g., heaters or coolers—operable to heat, cool, and / or maintain a specified temperature in the output operating mode. The temperature modification unit 86 can be configured to wired or wirelessly communicate with one or more temperature modification devices 46 via a suitable communication port, including a corresponding wired or wireless transmitter, receiver, and / or transceiver. In some embodiments, the temperature modification unit 86 may be integrated with a temperature control system associated with the location of system 10. For example, the temperature modification unit 86 may communicate with a house temperature control system, such as a smart thermostat, via a wired or wireless connection to change the ambient temperature around the bed apparatus 20.

[0093] One or more temperature modification devices 46 may be integrated with or otherwise associated with the bed equipment or its sleep platform. In some embodiments, one or more temperature modification devices 46 may be located on or around the bed equipment. For example, the sleep platform may include or be lined with heating and / or cooling elements operable to change the temperature of the sleep platform. In another example, clothing, sheets, or pillows may be equipped with heating and / or cooling elements. In some embodiments, a heater or air conditioner may be located near the bed equipment and may be controlled by the temperature modification unit 86 to modify the ambient temperature. In some cases, the temperature portion of the output operating mode may need to be maintained by the temperature modification device 46.

[0094] In some embodiments, the temperature modification device includes a fan. The fan may be configured to generate airflow. The bed device or its platform may be configured to control the direction, speed, and / or amount of airflow. These and other parameters / characteristics may be user-controlled and / or controlled or modifiable by an output action generator, which may include a pattern generation unit 76 and / or a machine learning engine 78. In various embodiments, the processing module 70 analyzes data collected by the input detection module 50—such as the environmental detection unit 66 and / or the biological detection unit 68—to automatically adjust the output in real time. For example, the output action specification unit 74 may compare a target value with a measured value and determine one or more output parameters to be modified to achieve the target value. In some embodiments, the machine learning engine 78 may be used to analyze the measured values ​​as feedback on environmental conditions and automatically adjust the output parameters.

[0095] The lighting modification unit 88 can be configured to perform the lighting portion of the output action mode by generating or causing the generation of specified lighting with respect to the subject and / or sleep platform.

[0096] The lighting modification unit 88 may include or be configured to communicate signalingly with one or more lighting modification devices 48, which are operable to increase, decrease, and / or modify the lighting specified in an output operating mode. The lighting modification unit 88 may be configured to communicate wired or wirelessly with one or more lighting modification devices 48 via a suitable communication port, which includes a corresponding wired or wireless transmitter, receiver, and / or transceiver.

[0097] One or more lighting modification devices 48 may be integrated with or otherwise associated with the bed device or its sleep platform. In some embodiments, one or more lighting modification devices may be located on or around the bed device. For example, the area around the sleep platform may include or be lined with one or more light modification devices, such as lamps. In some embodiments, the lamps may be powered on and off, which may include lighting patterns. The light may include different frequencies and / or intensities. In one embodiment, the lighting modification unit 88 includes one or more actuators configured to move light to different locations or translate light along a path, which may include patterns of movement. In the above or another embodiment, the lighting modification unit 88 may include one or more light modification devices, the light modification devices including actuators operable to control light by blocking a portion of light emitted from a light source, the light source may include lamps of the lighting modification unit 88, ambient light, and / or natural light. For example, the lighting modification unit 88 may employ actuators to translate a light shield relative to a light source to modify the amount or characteristics of light transmitted from the light source to the area of ​​the sleep system. Therefore, the light modification device 48 may include a light shield, light blocker, or filter that can be converted into an optical path to filter all or a portion of the illumination reaching one or more areas of the bed device, sleep platform, or subject, or can be converted to not obstruct light transmission to one or more areas of the bed device, sleep platform, or subject. In some embodiments, the illumination modification unit 88 may include or be operatively associated with a wearable head unit, glasses, or goggles, the wearable head unit, glasses, or goggles including one or more lamps for providing light to the subject and / or one or more light modification devices configured to increase, block, and / or filter light transmitted to the subject.

[0098] As described above, output module 80 may include and / or otherwise operatively coupled to one or more tactile devices. The tactile devices are operable to evoke tactile sensations in a user. The tactile devices may include weights or other force-providing devices. The tactile devices may include blankets and / or wearable devices, such as straps, bands, sleeves, and / or other garments that can contract, actuate, move, and / or vibrate in a tactilely perceptible manner. For example, a tactile device including a shirt may be worn by the user to provide a comfortable, enveloping feel; the shirt may include a retractable torso section. Blankets and / or wearable devices may also include integrated massage devices that contract, stimulate, vibrate, and / or move to massage the user. Vibration may be generated by piezoelectric devices, eccentric rotating mass actuators, or other suitable devices. The tactile devices may also include devices not worn by the user, such as concentrated air vortex devices and / or unworn massage devices. Such devices may be integrated or accessory-like. For example, one or more massage devices may be integrated with a bed frame, mattress, or pillow, or may include extensions thereof. The massage devices may be positioned to directly or indirectly contact the user. Massage devices may include vibrating devices for generating vibrations. In some embodiments, the tactile device includes a pump or actuator configured to change the firmness of a mattress or pillow. The tactile device may also include an ultrasonic device configured to direct tactilely perceptible ultrasound waves to the user. The tactile device can be used as an aid to soothing, inducing sleep, and / or inducing relaxation. The tactile device can be used to move the subject during sleep and / or wake the user.

[0099] It should be understood that one or more modules, units, and / or databases may be remote and / or distributed relative to one or more other modules, units, and / or databases. For example, a motion generation unit, a sound generation unit, a temperature modification unit, and / or a lighting modification unit may be local or remote relative to a processing module or one or more units thereof. As another example, a processing module or one or more units thereof may be remote relative to one or more units of an input detection module. The transmission of data described herein between distributed and / or remote modules, units, and / or databases may be performed via wired or wireless communication. For example, a module, unit, and / or database may include a communication port, which includes a transmitter, receiver, and / or transceiver adapted to perform such data transmission. In one example, an input detection module, an output module, or one or more units thereof may communicate with a processing module and / or one or more databases via a Wi-Fi connection. Similarly, in various embodiments, one or more units of an output module may communicate with execution hardware via wired or wireless communication. For example, a motion generation unit may transmit control operations to motion generation hardware via wired or wireless communication. In this or another example, a sound generation unit may transmit audio track data to a speaker via wired or wireless communication. In the above or another example, the temperature modification unit can transmit temperature modification data to the temperature modification hardware via wired or wireless communication. In the above or another example, the lighting modification unit can transmit lighting data to the lighting hardware via wired or wireless communication.

[0100] It should be understood that an output action pattern may include a single or combined output, and all specified output actions of an output action pattern do not need to be transmitted together as a single unit. For example, specified output actions may be provided to the output module unit individually or in one or more groups for execution. Therefore, the output module or its units may include a receiver or transceiver for receiving signals including the output action pattern or portions thereof. Signals may include data signals containing specified output actions. For example, a processing module may include or access one or more databases and transmit data signals including specified actions, which include instructions for performing the specified actions.

[0101] In some examples, the desired movement, sound, temperature, and / or lighting can be specified. In some such examples, a corresponding database can provide instructions on the execution of unit functions required to achieve the specified desired actions. The relevant units can be obtained or provided, for example, in the form of output action patterns, current temperature conditions, sleep platform configuration / orientation, lighting, or sound. In some embodiments, the output action pattern can be based on the current situation and provide instructions and / or specify appropriate actions.

[0102] In one example, the sleep system may include a movement database that includes instructions for generating multiple movements and / or patterns thereof that can be specified in an output movement pattern. Such instructions may be provided in the movement portion of the output movement pattern, or may be otherwise identified, for example, directly or indirectly based on a specified movement or position, enabling the motion unit to execute the movement portion of the output movement pattern.

[0103] In the above or another example, the control system may include a sound database comprising multiple audio tracks that can be specified in an output action mode. Such audio tracks may be provided in the sound portion of the output action mode, or may be identified directly or indirectly, for example, based on specified sounds and / or audio tracks, enabling the sound generation unit to execute the sound portion of the output action mode. In various embodiments, the sound database includes one or more audio tracks selected from white noise, variable white noise, noise cancellation, music, ambient sounds, natural sounds, variable frequency and / or amplitude sounds, and repetitive sounds.

[0104] In the above or another example, the control system may include a temperature database containing instructions for generating multiple temperature modifications and / or patterns thereof, which may be specified in an output action mode. Such instructions may be provided in the temperature portion of the output action mode, or may be otherwise identified, for example, directly or indirectly based on a specified temperature or temperature modification, such that a temperature modification unit may execute the temperature portion of the output action mode.

[0105] In the above or another embodiment, the control system may include a lighting database, which includes instructions for generating multiple lighting configurations, modifications, and / or modes that can be specified in an output operating mode. Such instructions may be provided in the lighting portion of the output operating mode, or may be identified directly or indirectly, for example, based on a specified lighting or lighting modification, enabling a lighting modification unit to execute the lighting portion of the output operating mode.

[0106] This disclosure may include dedicated hardware implementations, including but not limited to application-specific integrated circuits (ASICs), programmable logic arrays, and other hardware devices that can also be constructed to implement the methods described herein. Applications of the apparatuses and systems, which may include various embodiments, broadly encompass a wide range of electronic and computer systems. Some embodiments implement functionality in two or more specific interconnected hardware modules or devices, wherein associated control and data signals are transmitted between or through modules, or as part of an ASIC. Therefore, the example networks or systems are applicable to software, firmware, and hardware implementations.

[0107] According to various embodiments of this disclosure, the processes described herein are intended to operate as software programs running on a computer processor. Furthermore, software implementations may include, but are not limited to, distributed processing or component / object distributed processing, parallel processing, or virtual machine processing, which may be constructed to implement the methods described herein.

[0108] This disclosure describes various systems, modules, units, devices, components, etc. Such systems, modules, units, devices, components, and / or their functions may include one or more electronic processors, such as microprocessors, operable to execute instructions corresponding to the functions described herein. Such instructions may be stored on a computer-readable medium. Such systems, modules, units, devices, components, etc., may include function-related hardware, instructions, firmware, or software. For example, a module or unit that may include a generator or engine may include physical or logical groups of function-related applications, services, resources, assets, systems, programs, databases, etc. Systems, modules, and units that may include data storage devices such as databases and / or schema libraries may include hardware storing instructions configured to perform the disclosed functions, and this hardware may be physically located at one or more physical locations. For example, systems, modules, units, or their components or functions may be distributed across one or more networks, systems, devices, or combinations thereof. It should be understood that the various functions of these features may be modular, distributed, and / or integrated on one or more physical devices. It should be understood that such logical partitioning may not correspond to physical partitioning of data. For example, all or part of various systems, modules, units, or devices may reside or be distributed in one or more hardware locations.

[0109] This disclosure envisions a machine-readable medium containing instructions that enable a device connected to a communication network, another network, or a combination thereof to send or receive voice, video, or data, and to communicate using the instructions via the communication network, another network, or a combination thereof. The instructions may additionally be sent or received via a network interface device through the communication network, another network, or a combination thereof. The term “machine-readable medium” should be understood to include a single medium or multiple media (e.g., a centralized or distributed database, and / or associated caches and servers) storing one or more sets of instructions. The term “machine-readable medium” should also be understood to include any medium capable of storing, encoding, or carrying a set of instructions executable by a machine and enabling the machine to perform any one or more methods of this disclosure. Accordingly, the terms “machine-readable medium,” “machine-readable device,” or “computer-readable device” should include, but are not limited to: storage devices, solid-state storage such as memory cards or other packages accommodating one or more read-only (non-volatile) memories, random access memories, or other rewritable (volatile) memories; magneto-optical or optical media such as magnetic disks or magnetic tapes; or other self-contained information archives or collections of archives considered equivalent to tangible storage media. "Machine-readable medium," "machine-readable device," or "computer-readable device" may be non-transitory and, in some embodiments, may not include the wave or signal itself. Therefore, this disclosure is intended to include any one or more of machine-readable media or distributed media as listed herein, and includes equivalents and successor media recognized in the art in which the software implementation herein is stored.

[0110] This specification has been prepared with reference to various non-limiting and non-exhaustive embodiments. However, those skilled in the art will recognize that various substitutions, modifications, or combinations can be made to any disclosed embodiments (or portions thereof) within the scope of this specification. Therefore, it is contemplated and understood that this specification supports additional embodiments not expressly set forth herein. For example, such embodiments can be obtained by combining, modifying, or reorganizing any disclosed steps, components, elements, features, aspects, characteristics, limitations, etc., of the various non-limiting and non-exhaustive embodiments described herein.

[0111] The various elements described herein have been described as alternatives or combinations thereof, for example, in a list of alternative active substances, ingredients, or compositions. It should be understood that embodiments may include one, more, or all of any such elements. Therefore, this description includes embodiments of all such elements individually, as well as embodiments including combinations of all such elements.

[0112] Unless otherwise stated, the grammatical articles “one,” “a,” “an,” and “the” used in this specification are intended to include “at least one” or “one or more.” Therefore, the articles used in this specification refer to one or more (i.e., “at least one”) grammatical objects. For example, “a component” means one or more components; therefore, more than one component may be contemplated, and more than one component may be employed or used in the application of the described embodiments. Furthermore, the use of singular nouns includes plural nouns, and the use of plural nouns includes singular nouns, unless the context of usage requires otherwise. Additionally, the grammatical conjunctions “and” and “or” are used herein according to accepted usage. For example, “x and y” means “x” and “y.” On the other hand, “x or y” corresponds to “x and / or y” and refers to “x,” “y,” or both “x” and “y,” while “x or y” indicates exclusivity.

Claims

1. A sleep system, the system comprising: Bed equipment, which includes a platform for supporting the subject; Input sensors, configured to collect input data about the subject, the bed apparatus, and / or the environment surrounding the subject and / or the bed apparatus, include a respiratory sensor for measuring respiration, a motion sensor, and a sound sensor; A control system for receiving and analyzing collected input data to determine multiple conditions, wherein the control system is configured to determine one or more states of the subject based on one or more of the conditions; and One or more output devices, including one or more actuators that cause movement of the platform, one or more speakers that direct sound to the subject, one or more light-modifying devices that modify illumination with respect to the subject or bed equipment, one or more temperature-modifying devices that modify the temperature of the platform, or a combination thereof. The control system is configured to specify an output action pattern based at least in part on one or more states of the subject, wherein the one or more output devices are operable to execute the output action pattern specified by the control system, and wherein the output action pattern includes a combination of at least two output actions selected from movement of the platform, sound directed to the subject, modification of lighting, or modification of the temperature of the environment surrounding the platform or the bed device. The control system is configured to determine whether the subject is snoring by combining analysis of the subject's vocalizations and movement patterns. The control system is configured to determine whether the subject has a cold by analyzing one or a combination of the subject's vocal condition, the subject's movement, and the subject's respiratory rate or respiratory depth. The output action pattern specified when snoring is caused by a cold and is not part of the normal sleep pattern is different from the output action pattern specified for typical snoring.

2. The sleep system of claim 1, wherein the plurality of defined conditions further includes The subjects' movement over time, The acceleration status of the subjects, The overall movement status of the subjects, The subject's body orientation, The changes in the subject's body orientation over time Regarding the ambient sound frequency, sound amplitude, or both. The subjects' heart rate status, The subjects' respiratory rhythm status, The subjects' respiratory quality status, The subject's body temperature, Platform temperature status, The subjects' blood pressure status, The subject's weight status, The subject's brain biofeedback status or Combination of each The input sensor further includes a light sensor, and The input data analyzed by the control system further includes determined light conditions, which include ambient light conditions, including intensity and wavelength.

3. The sleep system of claim 1, wherein the control system is configured to specify an output action mode, the output action mode including movement of the platform in six degrees of freedom to generate one or both of a proprioceptive or vestibular system response in the subject, and a sound directed at the subject, the sound including variable white noise.

4. The sleep system of claim 1, wherein the state of the subject includes a sleep apnea event, and wherein the specified output action pattern includes irregular movement of the platform in response to the sleep apnea event.

5. The sleep system of claim 1, wherein the output action pattern is designed to elicit a target outcome regarding the subject.

6. The sleep system of claim 5, wherein the target outcome includes one or more of the following: stimulation relaxation, initiation of sleep, continuation of sleep, duration of sleep, sleep depth, cessation of snoring, or smoothness of breathing.

7. The sleep system of claim 1, wherein the control system includes a machine learning engine and a pattern generator, the machine learning engine and the pattern generator being configured to modify parameters of the output action in real time based on measured attribute values, state and / or condition of the subject.

8. The sleep system of claim 1, wherein the vocal condition of the subject in relation to determining a cold illness includes one or more vocal conditions, including cough, congestion, wheezing, and / or respiratory obstruction.

9. The sleep system of claim 8, wherein the movement status of the subject in relation to determining a cold illness status includes cough movement status from movement data indicating that a cough was detected.

10. The sleep system according to any one of claims 1, 8 or 9, wherein determining the snoring state comprises comparing the subject’s vocal status with respect to the frequency and / or amplitude of snoring with one or more of respiratory rate status, heart rate status and / or brain biofeedback status.

11. A method for controlling a bed device having a movable platform for supporting a subject, the method comprising: Input data is collected from one or more input sensors, which are positioned to measure one or more properties relating to the subject and the bed device or the environment surrounding the bed device, wherein the input sensors include a respiratory sensor for measuring respiration, a motion sensor, and a sound sensor. Analyze the collected input data to determine various conditions; Transforming one or more of the identified conditions into one or more states of the subject, wherein the transformation includes determining whether the subject is snoring by combining analysis of the subject's vocal condition and the subject's movement condition, and wherein the transformation further includes determining whether the subject is suffering from a cold based on analysis of one or a combination of the subject's vocal condition, the subject's movement condition, and the subject's respiratory rate condition or respiratory depth condition. Identify output action patterns corresponding to one or more states of the subject, wherein the output action pattern includes a combination of at least two output actions selected from movement of the platform, sound directed to the subject, modification of lighting, or modification of the temperature of the environment surrounding the platform or the bed device; as well as The output action mode is executed using one or more output devices operable to execute the output action mode, wherein the output devices include actuators that cause movement of the platform, one or more speakers that direct sound to the subject, one or more light-modifying devices that modify illumination with respect to one or more of the subject or the bed apparatus, one or more temperature-modifying devices that modify the temperature of the environment surrounding the platform or the bed apparatus, and wherein the output action mode specified in cases where snoring is caused by a cold and is not part of a normal sleep pattern is different from the output action mode specified for typical snoring.

12. The method of claim 11, wherein the multiple conditions of the subject further include the subject's heart rate, the subject's respiratory depth, the subject's respiratory rhythm, the subject's respiratory quality, the subject's blood pressure, the subject's weight, the subject's brain biofeedback, or a combination thereof.

13. The method of claim 11, wherein the input sensor further comprises an electroencephalogram (EEG) sensor for measuring the brain waves of the subject.

14. The method of claim 13, wherein the determined state further comprises a state of consciousness determined by comparing the brain waves or rhythms of alpha, delta, or both with beta, gamma, theta waves, or combinations thereof.

15. The method of claim 11, further comprising modifying the output action mode in real time based on feedback collected by the input sensor during output in a previous output mode.

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