IL279781A - Smart sleep system - Google Patents

Description

SMART SLEEP SYSTEM BACKGROUND OF THE INVENTION Technical Field The present invention relates to sleep systems in general and more particularly to mattresses having supporting surfaces which may be selectively adjusted for a maximum comfort.

Description of the Related Art In mattresses, a need has been recognized for mattresses’ configurations which provide comfortable supporting surfaces. However, different users of mattresses require different supporting surfaces for comfort; one user may desire a less firm sleeping surface while another may desire a firmer surface.

Therefore, a need exists for a mattress which provides an improved supporting surface which may be adjustable to satisfy the various needs of its users.

SUMMARY OF THE INVENTION In one aspect, the present disclosure describes a sleep system. The sleep system includes a mattress having a plunger matrix comprised of individually and independently computer-controlled plungers, and wherein the surface of said plunger matrix is based on the measurements and 3D scan of an occupant and matches the contour of the occupant body.

In another aspect, the present disclosure describes a sleep system comprising a mattress having a plunger matrix comprised of individually and independently computer-controlled plungers, and wherein the surface of said plunger matrix is based on data received by a computer from force sensors embedded in said mattress.

In yet another aspect, a sleep system is described which includes one or more sensors embedded within a mattress. The sleep system also includes one or more sensors provided in a peripheral that is external to the mattress. The sleep system includes a computer receiving data from the one or more sensors embedded within the mattress and the one or more sensors provided in the peripheral. The computer is configured to determine sleep environment information based on the data from one or more of the sensors embedded within the mattress and the data from the one or more sensors provided in the peripheral.

In yet another aspect, a method of obtaining a mattress surface that matches the contour of an occupant body comprises the steps of obtaining a 3D scan of the occupant’s body and his weight measurement, adjusting the height of each plunger in the plunger matrix of the mattress, wherein said adjusting is based on the 3D scan and weight measurements and wherein said adjusting of the height of the plungers results in a plunger matrix surface that matches the contour of the occupant’s body.

Other example embodiments of the present disclosure will be apparent to those of ordinary skill in the art from a review of the following detailed description in conjunction with the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS The above-mentioned and other features and advantages of the invention, and the manner of attaining them, will become more apparent and the disclosure will be better understood by reference to the following description of embodiments of the invention taken in conjunction with the accompanying drawings, wherein: FIG. 1 is a diagram of an example sleep system of the present invention; FIG. 2 is a block diagram of an example sleep system of the present invention; FIG. 3 is a perspective view of a mattress of an example sleep system of the present invention; FIG. 4 is a sectional side view of a mattress of an example sleep system of the present invention.

FIG. 5 is a sectional side view of a mattress of another example sleep system of the present invention.

The exemplifications set out herein illustrate preferred embodiments of the invention, and such exemplifications are not to be construed as limiting the scope of the invention in any manner.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS For a better understanding of the invention and to show how the same may be carried into effect, reference will now be made, purely by way of example, to the accompanying drawings. With specific reference to the drawings in detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of preferred embodiments of the present invention only, and are presented for the purpose of providing what is believed to be the most useful and readily understood description of the principles and conceptual aspects of the invention. In this regard, no attempt is made to show structural details of the invention in more detail than is necessary for a fundamental understanding of the invention. From the description taken together with the drawings it will be apparent to those skilled in the art how the several forms of the invention may be embodied in practice. Moreover, it is to be understood that the phraseology and terminology employed herein is for the purpose of description and should not be regarded as limiting the scope of the invention hereof.

Referring now to FIG. 1 and FIG. 2, an example sleep system 100 in accordance with example embodiments of the present disclosure is illustrated. The sleep system 100 may, in at least some embodiments, be referred to as a smart sleep system.

The sleep system 100 includes a mattress 101. The mattress 101 provides support for an occupant 10 while sleeping or laying down. The mattress 101 may, for example, be sized according to any one of a plurality of traditional or custom mattress sizes.

The mattress 101 comprises a plunger matrix 104 covered with a flexible and elastic cover 105. The plunger matrix 104 and the elastic cover 105 are designed to support the body of the occupant 10. The plunger matrix 104 is comprised of individually and independently movable plungers 111 which may be hydraulically or electronically (or by any other means) controlled by a computer 130 via a microcontroller 119. An upper part of the plunger matrix 104 comprises a compressible material 102 (such as foam or sponge).

The height of the plungers 111 may be varied to match the contour of the occupant body and/or it can be varied to account for variations in the sizes of occupants. In some embodiments, the height of the plungers 111 may be customized for an individual. For example, measurements of an individual may be obtained and the plungers 111 are arranged in accordance with the obtained measurements. That is, a computer 130 may determine plunger 111 height based on the measurements. The measurements may, for example, be obtained by performing a 3D scanning and weight measurement of the individual at a mattress sales point and these measurements are then uploaded from a 3D scanner 200 to a memory 170 of the computer 130.

In other embodiments, a designated computer application may upload the measurements into the computer 130. In other embodiments, the measurements data may be sent to the computer 130 from a remote server.

In yet another embodiment, plungers 111 may be positioned on ball joints/bearings 106 in order to allow a tilt of the plungers 111 and the plunger matrix 104 in a desired direction. The tilt of the plungers 111 and the plunger matrix 104 is achieved by pulling or pushing the ball joints/bearings 106 by an actuator or a motor coupled to the ball joints/bearings 106. The pushing or pulling of the ball joints/bearings 106 causes a tilt in the opposite direction of the plunger matrix 104.

The tilt of the plunger matrix 104 provides a more adjustable mattress 101 for a better movement of the occupant body on the mattress surface.

Occupant Monitoring Sensors In addition to the mattress 101, the sleep system 100 may include one or more sensors which may be used for monitoring an occupant of the mattress. These occupant monitoring sensors may include wireless IR cameras 150 and/or force sensors 120, which may be used to detect movement and positioning of an occupant, and a body temperature sensor 122 used to detect a body temperature of an occupant. These sensors will be discussed in greater detail below.

Force Sensors As noted above, the sleep system 100 may include one or more force sensors 120.

The force sensors 120 are embedded within the mattress 101 in at least some embodiments. In at least some embodiments, one or more of the force sensors 1 are positioned within the mattress to sense movement of an occupant of the mattress.

The force sensors 120 may be of a variety of different forms. In at least some embodiments, the force sensors 120 may include force sensitive resistors. A force sensitive resistor is a material whose resistance changes when a force is applied.

Other force sensors could be pressure sensitive foams (such as a polyurethane foam doped with carbon) or conductive threads/fabrics that change resistance with deformation, as an example.

Furthermore, in other embodiments, other sensors could be used to sense movement and position of an occupant instead of or in addition to the force sensors 120. For example, in some embodiments, one or more accelerometers could be embedded into the mattress.

IR Cameras As noted above, the sleep system 100 may include one or more wireless IR cameras 150. The IR cameras 150 are placed in the room where the sleep system 100 is located. The IR cameras 150 are used to capture the position of an occupant and transfer this data to the computer 130 in order to adjust the height of the plungers 111 accordingly.

Temperature Sensor(s) Referring again to the drawings, the mattress 101 may include other sensors instead of or in addition to the force sensors 120 described above. For example, in at least some embodiments, a body temperature sensor 122 may be included. The body temperature sensor 122, which is embedded into the mattress 101, is positioned to obtain temperature readings associated with an occupant of the mattress. That is, the body temperature sensor 122 detects an occupant's body temperature.

In order to accurately measure an occupant's body temperature, the body temperature sensor 122 is placed in a region of the mattress in which an occupant frequently sleeps. In at least some embodiments, the body temperature sensor 122 may be located in a middle body region of the mattress 101. The middle body region of the mattress 101 is a region of the mattress that is located generally nearer the middle of an occupant's body; for example, near their lower back region.

The body temperature sensor 122 may generally be in a middle third of the mattress 101.

The body temperature sensor 122 may be of a variety of different types. In one embodiment, the body temperature sensor includes a thermistor. It will be appreciated that other temperature sensors may also be used.

In will be appreciated that, in at least some embodiments, a plurality of temperature sensors 122 may be embedded into the mattress 101 at a plurality of different locations. For example, a first temperature sensor may be located at a first location and a second temperature sensor may be located at a second location.

Furthermore, in at least some embodiments, the sleep system 100 may include a room temperature sensor 121 which is utilized to obtain temperature readings associated with the room where the sleep system 100 is located so that the temperature of a sleep environment may be assessed.

Furthermore, in at least some embodiments, the sleep system 100 may include a room humidity sensor 125 which is located to obtain humidity readings associated with the room where the sleep system 100 is located so that the humidity of a sleep environment may be assessed The computer 130 may be an AI based computer and it may be used to analyse data obtained from sensors and cameras associated with the sleep system 100, such as the force sensors 120, the wireless IR cameras 150, the temperature sensor 122, a microphone 123, a room humidity sensor 125 and a room temperature sensor 121. 1 Furthermore, in some embodiments, some of the analysis described herein may be performed using a computer that is remote from the mattress 101. For example, the sleep system 100 may be equipped with a communication subsystem, such as a wireless communication subsystem 140. The wireless communication subsystem 140 may, for example, be a Wi-Fi connection and/or a Bluetooth connection. This connection may be used for sending data to a remote server 160 or computer. By way of example, in some embodiments, data may be collected and periodically sent to the remote server 160 or computer for analysis.

The computer 130 and the wireless communication subsystem 140 may be located inside the mattress 101 in some embodiments of the invention. In other embodiments, the computer 130 and the wireless communication subsystem 1 may be located outside the mattress 101.

The computer 130 may be used, in at least some embodiments, for storing data obtained or derived from the sensors. For example, information derived from the sensor data may be stored in the memory 170 of the computer 130 for further analysis or reporting. Further, in at least some embodiments, the computer 1 may store sleep state information for an occupant of the mattress 101. The sleep state information may be of various types. For example, in at least some embodiments, the computer 130 may store information regarding times associated with various sleep stages of the occupant. For example, the time when an occupant fell asleep and/or woke up may be recorded in the memory. Similarly, in at least 1 some embodiments, sleep disorder information for an occupant may be stored in the computer 130. This information may indicate whether a user/occupant has or is likely to have a sleep disorder. The sleep disorder may, for example, include any one or combination of: insomnia, sleep apnea, etc.

Furthermore, in some embodiments, the computer 130 may store information about a sleeping environment associated with the mattress 101. The sleeping environment information may, for example, include a measure of a humidity level in the room where the mattress is located, or a measure of a temperature level in the room where the mattress is located.

The sleep system 100 may also include sensors configured to obtain information about the environment where the mattress 101 is located.

Room humidity information may be obtained from a room humidity sensor 125. The room humidity sensor 125 generates an electrical signal based on the amount of humidity in the region of the humidity sensor 125. That is, the electrical signal output by the humidity sensor includes humidity information. This humidity information may be provided to the computer 130 for analysis.

Room temperature information may be obtained from a room temperature sensor 121. The room temperature sensor 121 may be of the type described above with reference to the body temperature sensor 122. However, in at least some embodiments, the room temperature sensor 121 may be located away from a region of the mattress in which an occupant typically sleeps, to prevent the temperature 1 sensor 121 from capturing temperature information associated with the occupant.

For example, in some embodiments, the room temperature sensor 121 may be included in the external peripheral described above. The room temperature sensor 121 generates an electrical signal based on the temperature in the region of the room temperature sensor 121. That is, the electrical signal output by the temperature sensor includes temperature information. This temperature information may be provided to the computer 130 for analysis.

In some embodiments, the sleeping system 100 may include a microphone 123. The microphone 123 may, for example, be used to obtain sound information. As is known, the microphone may convert sound waves into electrical energy variations, which may be provided as an electrical signal to the computer 130 (this signal may be converted to a digital signal by an ADC before input to the computer 130 in some embodiments). This electrical signal may be said to contain sound information. The microphone 123 is located near the occupant to detect occupant-generated audio, such as snoring, breathing, etc.

Sleep State Information Determination In at least some embodiments, the computer 130 may be configured to determine sleep state information for an occupant based on data obtained from one or more of the force sensors 120 and/or IR cameras 150. 1 Extraction of Movement Component In at least some embodiments, the sleep system 100 may extract a movement component from the data obtained from the force sensors 120 and/or IR cameras 150. This extraction may, for example, obtain a movement component which represents movements of the occupant which are not caused by heart or breathing induced movements. That is, the movement component may represent movements that are caused by an occupant shifting in bed, changing positions in bed, moving a limb, etc.

In some embodiments, the sleep system 100 may determine whether a given sample obtained from force sensors 120 represents movement of the occupant. In at least some embodiments, this determination may be performed based on changes of force over time using a moving average difference method. That is, sudden changes of force measured at one of the force sensors may be interpreted as a movement.

Determine Sleep Stage and/or Whether Occupant is Awake As noted above, in at least some embodiments, sleep state information may be determined by the computer 130 based on data obtained from the force sensors 1 and/or IR cameras 150. This sleep state information is information about an occupant's sleep. In some embodiments, this sleep state information may indicate whether an occupant is asleep. In some embodiments, this sleep state information may indicate the sleep stage of the occupant. 1 In at least some embodiments, the computer 130 may use movement information to determine a sleep stage of an occupant and/or to determine whether the occupant is asleep or awake. That is, based on the frequency of movements of an occupant, the sleep stage and/or waking status of that occupant may be determined.

More specifically, the computer 130 determines the amount of movements for an occupant that have occurred within an epoch of a predetermined duration. That is, the computer 130 may determine the amount of movements that have occurred within a predetermined period of time. By way of example, in some embodiments, this period of time may be one minute. In some embodiments, this period of time may be in the range of thirty seconds to one minute. Other ranges are possible in other embodiments.

The computer 130 may determine the sleep stage of the occupant by comparing the amount of movements of the occupant within the epoch to one or more predetermined thresholds.

Similarly, in at least some embodiments, the computer 130 may determine the waking status (i.e. whether the occupant is awake or asleep) by comparing the amount of movements of the occupant within the epoch to one or more predetermined thresholds.

In at least some embodiments, in determining a sleep stage which an occupant is in during a given epoch and/or in determining a waking status, the computer 130 may either determine: 1) that the occupant is awake; 2) that the occupant is in a non- 1 rapid eye movement (NREM) stage 1 state; 3) that the occupant is in a NREM stage 2 state; 4) that the occupant is in a NREM stage 3 state; or 5) that the occupant is in a rapid eye movement (REM) state. These various states and the respective thresholds associated with these states will now be described.

An awake state occurs when the occupant is not sleeping. During this state, the occupant's movement tends to have a higher relative frequency than other states.

Accordingly, the computer 130 may determine that the occupant was in a waking state during an epoch if the measure of movements of the occupant during the epoch exceeds a first predetermined threshold. The first predetermined threshold is relatively higher than the thresholds associated with the other states described below.

The NREM stage 1 state is a sleep stage which is between sleep and wakefulness.

An occupant's muscles are active during this state and the movement of the occupant tends to be more frequent than in the REM, NREM stage 2, and NREM stage 3 states. The amount of movement is, however, typically less than in the waking state. Accordingly, the computer 130 may determine that the occupant was in the NREM stage 1 state during the epoch if the measure of movements of the occupant during the epoch exceeds a second predetermined threshold and is less than the first predetermined threshold associated with the waking state. The second predetermined threshold is relatively lower than the first predetermined 1 threshold but is relatively higher than the thresholds associated with the REM, NREM stage 2, and NREM stage 3 states.

REM sleep occurs when most muscles are paralyzed. Thus, the frequency of movements during REM sleep tends to be less than in the waking state and less than in the NREM stage 1 state, but more than in the NREM stage 2, and NREM stage 3 states. Accordingly, the computer 130 may determine that the occupant was in the REM state during the epoch if the measure of movements of the occupant during the epoch exceeds a third predetermined threshold and is less than the second predetermined threshold associated with the NREM stage 1 state. The third predetermined threshold is relatively lower than the first predetermined threshold and the second predetermined threshold but is relatively higher than the thresholds associated with the NREM stage 2, and NREM stage 3 states.

NREM stage 2 sleep is a period of theta activity, where it is difficult to awaken the occupant. NREM stage 2 sleep is typically characterized by less frequent movements than the waking, NREM stage 1 and REM states, but more frequent movements than in the NREM stage 3 state. Accordingly, the computer 130 may determine that the occupant was in the NREM stage 2 state during the epoch if the measure of movements of the occupant during the epoch exceeds a fourth predetermined threshold and is less than the third predetermined threshold associated with the REM state. The fourth predetermined threshold is relatively lower than the first, second and third predetermined thresholds. 1 NREM stage 3 is a slow wave sleep (SWS) stage. During this stage, the occupant is less responsive to the environment. This stage was formerly divided into two stages—3 and 4. Accordingly, the NREM stage 3 state may be referred to or separated into NREM stage 3 and NREM stage 4 states in some embodiments.

NREM stage 3 sleep is typically characterized by less frequent movements than in the other sleep states referred to above. Accordingly, the computer 130 may determine that the occupant was in the NREM stage 3 state during the epoch if the measure of movements of the occupant during the epoch is less than the fourth predetermined threshold.

Accordingly, in at least some embodiments, four predetermined thresholds may be used to determine which of the five sleep states discussed above an occupant is in during the epoch. It will be appreciated that a different number of thresholds may be used in other embodiments. For example, in some embodiments, the computer 130 may be configured to determine whether the occupant is either in: 1) an asleep state; or 2) an awake state. An asleep state may be a state in which the occupant is either in the REM, NREM stage 2 or NREM stage 3 state. In some embodiments, the asleep state may also include the NREM stage 1 state. That is, if an occupant is in NREM stage 1, then they may be considered to be asleep. In some embodiments, such relationships may be used to determine that an occupant is asleep; for example, if the user is in either the REM, NREM stage 2, NREM stage 3 (and in some embodiments NREM stage 1) states, then the computer 130 may determine that the occupant is asleep. However, in other embodiments, the determination of 1 whether an occupant is asleep or awake may be performed in another manner. For example, a single threshold may be used in some embodiments. That is, the measure of movements of an occupant during an epoch may be compared to this threshold, and if the movements exceed the threshold then the occupant may be determined to be awake, but if the movements do not exceed the threshold then the occupant may be determined to be asleep.

Accordingly, in at least some embodiments, the computer 130 may determine sleep state information which indicates whether the occupant is asleep during an epoch and/or a stage of sleep which the occupant was in during the epoch.

In some embodiments, other information may be used instead of or in addition to the movement information described above to predict the sleep stage of an occupant.

For example, in some embodiments, body temperature, heart rate and/or respiration rate may be used to predict the sleep stage of the occupant. Accordingly, the computer 130 may be configured to determine the sleep state information based on temperature readings, heart rate, respiration rate, and/or other information, in some embodiments.

Heart Rate Determination Due to the principle of ballistocardiography, the pumping of the heart causes oscillatory body motion and mechanical forces to be produced. This force can be measured using the force sensors 120 over time and a heart rate determined. 1 In some embodiments, the computer 130 determines, from the data obtained from the one or more force sensors 120, a heart rate for an occupant. The heart rate may, for example, be determined based on data from the upper body force sensors. More specifically, in at least some embodiments the lower body force sensors are not used for the determination of the heart rate. Furthermore, in at least some embodiments, the middle body force sensors are not used for the determination of the heart rate.

To determine the heart rate the computer 130 may filter out large changes in force measured at the force sensors 120 which are caused by movement of an occupant.

Voluntary body movement typically occurs in the frequency range of 0.25-4 Hz, which overlaps with the heart rate frequency range, so these signals must be discriminated. Changes in force measured at the force sensors that are caused when an occupant shifts positions tend to be greater in magnitude than the changes caused by the occupant's breathing or heart activity. This filtering may be done by comparing the change in force to one or more predetermined thresholds. The computer 130 may also perform smoothing on the data obtained, and may filter out lower frequency components, such as a component caused by respiration or movement, which will be described in greater detail below. Filtering of the frequency to remove frequencies outside of the range of the heart rate (0.5-4 Hz) may be done using linear cut-off filters or bandpass filters designed based on Window functions. Furthermore, the data may be smoothed, amplified, or otherwise processed to obtain a high-quality heart rate signal. The heart rate can be extracted using a variety of techniques that can detect the peaks in the data, which can be 2 used to find the interpeak separation and hence the heart rate. Peak detection can be done in a variety of ways such as detection of local minima or maxima in a moving window or by using a fast Fourier transform (FFT) and examining the harmonics. The heart rate may be determined at predetermined intervals to obtain heart rate information for an extended period of time and to monitor for changes in the heart rate.

Respiration Rate Determination In at least some embodiments, the computer 130 determines, from the data obtained from the one or more force sensors, a respiration rate for an occupant. The respiration rate may, for example, be determined based on data from the upper body force sensors. More specifically, in at least some embodiments the lower body force sensors are not used for the determination of the respiration rate.

To determine the respiration rate the computer 130 may filter out large changes in force measured at the force sensors 120 which are caused by movement of an occupant. Voluntary body movement typically occurs in the frequency range of 0.25- 4 Hz, which may overlap with the respiration rate frequency range, so these signals are discriminated. Changes that are caused when an occupant shifts positions tend to be greater in magnitude than the changes caused by the occupant's breathing or heart activity. This filtering may be done by comparing the change in force to one or more predetermined thresholds. The computer 130 may also perform smoothing on the data obtained, and may filter out higher frequency components, such as 2 movement components and may, in some embodiments, filter out higher frequency components, such as a component caused by heart activity. Filtering of the frequency to remove frequencies outside of the range of the respiration rate (0.1-0.

Hz) may be done using linear cut-off filters or bandpass filters designed based on Window functions. As noted above, respiration rate is typically in the range of 0.1- 0.5 Hz and heart rate is typically in the range of 0.5-4 Hz. These ranges may be used to separate the respiration component from the heart rate component. For example, one or more thresholds may be established based on these ranges to separate the heart rate component from the respiration component. Furthermore, the data may be smoothed, amplified, or otherwise processed to obtain a high- quality respiration rate signal. The respiration rate can be extracted using a variety of techniques that can detect the peaks in the data, which can be used to find the interpeak separation and hence the respiration rate. Peak detection can be done in a variety of ways such as detection of local minima or maxima in a moving window or by using a fast Fourier transform (FFT) and examining the harmonics. The respiration rate may be determined at predetermined intervals to obtain respiration rate information for an extended period of time and to monitor for changes in the respiration rate.

Sleep Position Monitoring In at least some embodiments, the computer 130 may be configured to determine sleep state information which identifies a sleep position of an occupant of the 2 mattress 101 (such information may also be referred to as sleep position information). In at least some embodiments, the computer 130 may be configured to determine the most common sleep position of the occupant.

The various sleep positions may create different force distributions across the force sensors 120. Thus, the sleep position of an occupant may be determined, by the computer 130, by examining the distribution of forces across the force sensors.

Detection of Sleep Disorder(s) In some embodiments, computer 130 may be configured to detect one or more sleep disorders.

A method for detecting a sleep disorder comprises steps of obtaining data from one or more of the sensors of the sleep system 100. For example, data may be obtained from the force sensors 120, the temperature sensor 122, the microphone 123, or any of the other sensors described above. As will be understood from the discussion of the various sleep disorders below, the specific sensors from which data will be obtained will depend on the specific sleep disorders which the sleep system 100 is configured to detect.

Sleep Apnea Detection In at least some embodiments, the computer 130 may be configured to detect sleep apnea. In some embodiments, the computer 130 may further be configured to detect 2 a sleep apnea classification type. Sleep apnea is a sleep disorder in which an occupant experiences pauses in breathing or instances of infrequent or shallow breathing during sleep. The pauses may be referred to as apnea and the abnormally shallow breathing events may be referred to as hypoapnea.

Sleep apnea may, in some embodiments, be classified as either obstructive sleep apnea (OSA) or central sleep apnea (CSA). That is, the computer 130 may determine whether an occupant of the sleep system 100 suffers from OSA and/or whether the occupant of the sleep system 100 suffers from CSA.

OSA is more common than CSA. Central sleep apnea is a neurological condition which occurs when a person's brain does not send the appropriate signals to the muscles which control breathing. This may be contrasted with OSA which is caused due to an obstruction of the upper airway.

In at least some embodiments, sound may be used by the computer 130 to detect sleep apnea. More particularly, in at least some embodiments, an electrical signal (which may be referred to as an audio signal) representing received sound waves may be generated by the microphone 123 associated with the sleep system 100.

Based on this electrical signal, the computer 130 may determine whether an occupant has sleep apnea. In at least some embodiments, the computer 130 may determine whether the electrical signal includes snoring and/or gasping events. In at least some embodiments, the computer 130 may perform audio processing on the electrical signal to distinguish non-apnea snoring (i.e. snoring which is not caused 2 by sleep apnea, which may be referred to as normal snoring) from apnea-caused snoring (i.e. from snoring caused by sleep apnea). The signal from the microphone is, in at least some embodiments, converted into the frequency domain through the use data processing techniques such as fast Fourier transforms, wavelet analysis, or linear predictive coding. Cut off filters and bandpass filters may be used to narrow the frequency range, such as 70-2000 Hz, where snoring and breathing typically occur. Numerous techniques can be used by the computer 130 to identify snoring/breathing sounds that are characteristic of OSA or CSA. For example, the data can be characterized with a spectral envelope determined using linear prediction autoregressive modeling. Formant frequencies can be determined by finding the local maxima of the spectra envelope. The formant frequencies of OSA patients typically have greater variability in both snoring and breathing, so identifying these frequencies can be used by the computer 130 to determine the presence of OSA. Other techniques involve looking at the frequency characteristics of the snoring. Simple snoring has a spectrum characterized by a fundamental frequency with harmonics, whereas OSA snoring has a spectrum centered around a fundamental frequency without harmonics. To distinguish between these two types of snoring, in some embodiments, the computer 130 may consider the ratio of the power above 800 Hz to the power below 800 Hz in the electrical signal generated by the microphone. OSA snoring typically produces sound with higher power above 8 Hz, so ratios greater than one may represent OSA in some embodiments.

Identification of intra-snoring pitch jumps can also be indicative of OSA. Also, OSA 2 snoring typically has peak intensity above 1000 Hz, while simple snoring typically has a peak intensity between 100-300 Hz. Other techniques may utilize hidden Markov models or higher order statistics for analysis of the sound data to determine snoring/breathing sounds and those that are distinct for OSA. Thus, in at least some embodiments, the computer 130 may detect apnea events in the audio signal.

In at least some embodiments, an apnea event may be characterized by loud snoring or gasping followed by a quiet period of twenty to thirty seconds in duration and the computer 130 may analyze the audio signal to detect such characteristics.

Apnea events typically occur when an occupant is in certain stages of sleep. More particularly, apnea events typically occur during NREM stage 3 and REM sleep.

Bed Sores Prevention In some embodiments, the sleep system 100 may prevent bed sores formation by analyzing data obtained from the force sensors 120 and adjusting the height of the plungers 111 in order to reduce pressure in specific areas of the mattress 101 there exists a high or abnormal pressure.

The mattress surface in some embodiments may be a dynamic surface, i.e. the height of the plungers 111 may be varied as a function of time in order to provide a dynamic mattress surface. This feature could be used for a massage or for any other useful purpose.

Cardiac Arrest 2 In some embodiments, the sleep system 100 may detect a cardiac arrest by analyzing a real-time data obtained from the force sensors 120. If the cardiac arrest occurs, the sleep system 100 will contact the emergency services and may perform a cardiac massage on the occupant by actuating the relevant plungers 111.

Snoring Detection and Prevention In some embodiments, the sleep system 100 may detect snoring by analyzing a real- time data obtained from the microphone 123. If snoring is detected, the sleep system 100 will actuate plungers 111 and change the surface of the plunger matrix 104 to cause a change in sleeping position of the occupant. The change of the sleeping position is known to halt snoring.

The sleep system 100 of the invention may be used in armchairs, recliners or any other furniture designed to support human occupants.

While this disclosure has been described as having a preferred design, the present embodiments can be further modified within the scope of this disclosure. This application is therefore intended to cover any variations, uses, or adaptations of the embodiments using their general principles. Further, this application is intended to cover such departures from the present disclosure as come within known or customary practice in the art to which this disclosure pertains and which fall within the limits of the appended claims. 2 ABSTRACT The sleep system comprises a mattress connected to a computer and comprising a plunger matrix comprised of individually and independently computer-controlled plungers, and wherein the height of said plungers is based on the 3D body scan and the measurements of the occupant body, and matches the contour of the occupant body.

Claims (8)

2 WHAT IS CLAIMED IS:

1. A smart sleep system comprising: a. a mattress comprising a plunger matrix comprised of individually and independently computer-controlled plungers, and wherein the surface of said plunger matrix is based on a 3D scan of the occupant body and his weight, and wherein said plunger matrix surface matches the contour of the occupant body; b. a computer connected to the plungers and containing measurements of the occupant body, wherein said measurements comprise a 3D scan of the occupant and his weight.

2. A smart sleep system, comprising a mattress comprising a plunger matrix comprised of individually and independently computer-controlled plungers, and wherein the surface of the plunger matrix is varied according to an occupant data received by a computer from force sensors embedded in the mattress.

3. The smart sleep system according to claim 2, wherein said occupant data is a heartbeat of the occupant, and wherein the computer is configured to detect a cardiac arrest of the occupant from the said data and activate the plungers to provide a cardiac massage to the occupant. 2

4. A smart sleep system, comprising a mattress comprising a plunger matrix comprised of individually and independently computer-controlled plungers, and wherein the surface of the plunger matrix is varied according to an occupant data received by a computer from IR cameras.

5. A smart sleep system, comprising a mattress comprising a plunger matrix comprised of individually and independently computer-controlled plungers, and wherein the surface of the plunger matrix is varied according to an occupant data received by a computer from a microphone.

6. The smart sleep system of claim 1, wherein the surface of the plunger matrix is varied as a function of time.

7. The smart sleep system according to any one of the previous claims, wherein said plunger matrix is adapted to tilt.

8. A method of obtaining a mattress surface that matches the contour of an occupant body, comprising: obtaining a 3D scan data and weight data of the occupant; adjusting the height of each plunger in the plunger matrix of the mattress, wherein said adjusting is based on the 3D scan data and on the weight data, and wherein said adjusting of the height of the plungers results in a plunger matrix surface that matches the contour of the occupant’s body.