DEVICE AND METHOD FOR SOUND MASKING

Abstract

A sound masking device and method are provided. The sound masking device includes a sensing device that measures image information and biometric information of a passenger in a vehicle. The device also includes a controller connected to the sensing device. The controller determines a sleep state of the passenger based on the biometric information and determines whether the passenger is disturbed during sleep based on the image information of the passenger's sleep state. The controller measures sounds in the vehicle in response to determining that the passenger is disturbed during sleep and determines whether there is a need for sound masking based on the measured sounds. The controller performs sound masking based on the sleep state in response to determining that there is a need for sound masking.

Description

TECHNICAL FIELD

[0001] The present invention relates to a sound masking device and a sound masking method. BACKGROUND OF THE INVENTION

[0002] Various technologies can be used in an autonomous vehicle to provide ease and comfort in the vehicle, as well as safety and driving performance. A noise reduction device can be deployed as one of these technologies. The noise reduction device can analyze noise or noise components generated while the vehicle is driving in real time and generate an anti-phase sound wave to attenuate the noise. SUMMARY

[0003] Aspects of the present invention provide a sound masking apparatus and a sound masking method for determining a sleep state of a user to guide the user to sleep and for masking a sleep disturbance sound. Other aspects of the present invention provide a

[0004] A sound masking device and a sound masking method for determining a sleep level and a sleep quality based on image information and / or biometric information and for playing a masking sound (or a masking sound source) based on the determined sleep level and / or the determined sleep quality.

[0005] The technical problems to be solved by the present invention are not limited to the above-mentioned problems. Other technical problems not mentioned here should be more clearly understood by those of ordinary skill in the art to which the present invention pertains from the following description.

[0006] According to one aspect of the present invention, a sound masking device is provided. The sound masking device may include a sensing device that measures image information and biometric information of a passenger in a vehicle. The sound masking device may also include a controller connected to the sensing device. The controller may determine a sleep state of the passenger based on the biometric information. The controller may also determine whether the passenger is disturbed during sleep based on the image information. The controller may measure sounds in the vehicle in response to determining that the passenger is disturbed during sleep. The controller may determine whether there is a need for sound masking based on the measured sounds.The controller may perform sound masking based on the sleep state in response to determining that there is a need for sound masking.

[0007] The controller can analyze a pattern of an electroencephalogram (EEG) signal measured by an EEG measuring device. The controller can determine the passenger's sleep state based on the analyzed pattern of the EEG signal.

[0008] The controller can monitor changes in a passenger's body organ and a passenger's body movement by analyzing the image information. The controller can also determine whether the passenger's sleep is disturbed based on the changes in a passenger's body organ and / or a body movement pattern, or any combination thereof.

[0009] The controller may determine that the passenger is sleep-disturbed if an eye blink duration of the passenger is less than or equal to a predetermined reference time and / or a body movement pattern is a rapid eye movement (REM) sleep behavior disturbance pattern, or any combination thereof.

[0010] The controller may compare a magnitude of the measured noise with a predetermined reference value. The controller may also determine that sound masking is necessary if the magnitude of the measured noise is greater than or equal to the predetermined reference value.

[0011] The controller can select white noise as a masking sound source when the sleep state transitions from a sleep threshold level to a sleep level. The controller can also play and output the selected white noise.

[0012] The controller can play the selected white noise randomly.

[0013] The controller can select pink noise as a masking sound source when the sleep state transitions from a sleep stage to a deep sleep stage. The controller can also play and output the selected pink noise.

[0014] The controller can control a size of pink noise based on a size of the measured noise.

[0015] The controller can select and play a masking sound source based on a sound masking purpose.

[0016] According to another aspect of the present invention, a sound masking method is provided. The sound masking method may include determining a sleep state of a passenger in a vehicle based on biometric information of the passenger. The biometric information may be measured by a detection device. The sound masking method may also include determining whether the passenger is disturbed during sleep based on image information of the passenger. The image information may be obtained by the detection device during the passenger's sleep. The sound masking method may further include measuring sounds in the vehicle in response to determining that the passenger is disturbed during sleep. The sound masking method may additionally include determining whether sound masking is required based on the measured sounds.The sound masking method may further comprise performing sound masking based on the sleep state in response to determining that there is a need for sound masking.

[0017] Determining the sleep state of the passenger may include analyzing a pattern of an EEG signal measured by an EEG measuring device and determining the sleep state of the passenger based on the analyzed pattern of the EEG signal.

[0018] Determining whether the passenger is disturbed during sleep may include monitoring a change in a body organ of the passenger and a body movement of the passenger by analyzing the image information, and may include determining whether the passenger is disturbed during sleep based on the change in a body organ of the passenger and / or a body movement pattern, or any combination thereof.

[0019] Determining whether the passenger is sleep-disturbed may include determining that the passenger is sleep-disturbed if an eye blink duration (also referred to as eye blink duration) of the passenger is less than or equal to a predetermined reference time and / or a body movement pattern is a REM sleep behavior disorder pattern, or any combination thereof.

[0020] Determining whether sound masking is necessary may include comparing a magnitude of the measured noises with a predetermined reference value and determining that sound masking is necessary if the magnitude of the measured noises is greater than or equal to the predetermined reference value.

[0021] Performing sound masking may include selecting white noise as a masking sound source when the sleep state transitions from a sleep threshold stage to a sleep stage, and may include playing and outputting the selected white noise.

[0022] Playing and outputting the selected white noise may include randomly playing the selected white noise.

[0023] Performing sound masking may include selecting pink noise as a masking sound source when the sleep state transitions from a sleep stage to a deep sleep stage, and may include playing and outputting the selected pink noise.

[0024] Playing and outputting the selected pink noise may include controlling a magnitude of the pink noise based on a magnitude of the measured sounds.

[0025] Performing sound masking may include selecting and playing a masking sound source based on a purpose of the sound masking. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The above and other objects, features and advantages of the present invention should become more apparent from the following detailed description taken in conjunction with the accompanying drawings in which: Fig. 1 is a block diagram illustrating a configuration of a sound masking apparatus according to embodiments of the present invention; Fig. 2 is a drawing for describing a process for determining a sleep state according to embodiments of the present invention; Fig. 3 is a drawing for describing a process for determining a sleep level according to embodiments of the present invention; Fig.4 is a drawing for describing a method for determining a sleep disorder according to embodiments of the present invention; Fig. 5 is a drawing for describing a process for determining whether sound masking is required according to embodiments of the present invention; Fig. 6 is a drawing illustrating the result of analyzing a contribution of white noise according to embodiments of the present invention; Fig. 7 is a drawing illustrating the result of analyzing a pink noise contribution according to embodiments of the present invention; Fig. 8 is a drawing for describing a process for applying a cocktail party effect according to embodiments of the present invention; Fig.9 is a drawing for describing a sound masking concept according to embodiments of the present invention; Fig. 10 is a drawing for describing a sound masking algorithm according to embodiments of the present invention; Fig. 11 is a drawing for describing passive sound masking according to embodiments of the present invention; Fig. 12 is a drawing for describing active sound masking according to embodiments of the present invention; Fig. 13 is a flowchart illustrating a sound masking method according to embodiments of the present invention; and Fig. 14 is a block diagram illustrating a configuration of a sound masking system according to embodiments of the present invention. DETAILED DESCRIPTION

[0027] Embodiments of the present invention will now be described in detail with reference to the accompanying drawings. In the drawings, the same reference numerals are used throughout to designate the same or equivalent elements. In addition, detailed descriptions of well-known features or functions have been omitted in order not to unnecessarily obscure the gist of the present invention. When a component, device, element, or the like of the present invention is described as having a purpose or performing an operation, function, or the like, the component, device, or element should be considered to be "configured" to fulfill that purpose or perform that operation or function.

[0028] In describing the components of the embodiment according to the present invention, terms such as first, second, "A," "B," (a), (b), and the like may be used. These terms are used only to distinguish one element from another. These terms do not limit the respective elements regardless of the order or priority of the respective elements. Furthermore, unless otherwise defined, all terms used herein, including technical and scientific terms, should be interpreted as commonly understood in the art to which the present invention relates.It is to be understood that terms used herein should be construed to have a meaning consistent with their meaning in the context of this disclosure and the relevant field, and should not be interpreted in an idealized or overly formal sense unless expressly so defined.

[0029] Fig. 1 is a block diagram illustrating a configuration of a sound masking apparatus according to embodiments of the present invention.

[0030] A sound masking device 100 may be mounted on a vehicle equipped with an autonomous driving function. The autonomous driving function may be Level 3 or higher among the automation levels 0 to 5 defined by the Society of Automotive Engineers (SAE). Level 3 (partial automation) is a level at which the system takes over driving on a road or section of road under a specific condition, for example, a highway, and at which a driver intervenes only in case of danger.

[0031] With reference to Fig.1, the sound masking device 100 may include a human interface device 110, a communication device 120, a sensing device 130, a seat controller 140, and a controller 150, which may be connected via an intra-vehicle or inter-vehicle network. The inter-vehicle network may be implemented as a Controller Area Network (CAN), a Media Oriented Systems Transport (MOST) network, a Local Interconnect Network (LIN), an Ethernet, X-by-Wire (Flexray), and / or the like.

[0032] The human interface device 110 may be a device that enables interaction between the sound masking device 100 and a user (e.g., a driver or a passenger). The human interface device 110 may include an input device (e.g., a keyboard, a touchpad, a microphone, a touchscreen, and / or the like) for generating data according to a user's operation, an output device (e.g., a display, a speaker, a vibration generator, and / or the like) for outputting information according to an operation of the sound masking device 100, and / or the like. Such a human interface device 110 may be implemented as an audio, video, navigation (AVN) terminal, an in-vehicle infotainment terminal, a telematics terminal, a portable speaker, and / or the like.

[0033] The human interface device 110 may include a function on / off button capable of turning a sleep therapy function on or off. The human interface device 110 may also include an on / off button capable of turning a sound masking function on or off. The function on / off buttons may be implemented as hardware buttons and / or software buttons.

[0034] The communication device 120 may enable communication between the sound masking device 100 and an external electronic device (e.g., a server, an electronic control unit (ECU), a user device, a smartphone, or the like). The communication device 120 may include a wireless communication circuit (e.g., a cellular communication circuit, a wireless fidelity (Wi-Fi) communication circuit, a short-range wireless communication circuit, and / or a global navigation satellite system (GNSS) communication circuit) and / or a wired communication circuit (e.g., a local area network (LAN) communication circuit and / or a power line communication circuit). The communication device 120 may receive a masking sound source transmitted from the external electronic device.

[0035] The sensing device 130 may measure image information and biometric information of a passenger in the vehicle using a camera and / or a biometric signal measuring device (e.g., an electroencephalogram (EEG) measuring device or an electrocardiogram (ECG) measuring device). The biometric information may include EEG, heart rate, and / or the like.

[0036] The detection device 130 can measure interior noise of the vehicle using a microphone. At least one microphone can be installed in the vehicle. For example, the microphones can be installed in a dashboard or the periphery of an interior light on the rear seat.

[0037] The sensing device 130 may obtain driving information using sensors, an electronic control unit, and / or the like mounted on the vehicle. The sensors may include a wheel speed sensor, an inertial measurement unit (IMU), an image sensor, radio detection and ranging (RADAR), light detection and ranging (LIDAR), a steering angle sensor, and / or the like. The driving information may include vehicle speed, road curvature, lane departure or not, a steering angle, and / or the like.

[0038] The seat controller 140 may control a plurality of vibrators installed in the vehicle seat. When a sleep therapy function is enabled, the seat controller 140 may control the plurality of vibrators based on a predetermined vibration frequency, a predetermined vibration pattern, a predetermined vibration waveform, and / or the like. In other words, the seat controller 140 may control the plurality of vibrators to generate seat vibrations.

[0039] The controller 150 may control the overall operation of the sound masking device 100. The controller 150 may include a processor 151 and a memory 152. The processor 151 may be implemented as at least one of an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a programmable logic device (PLD), a field-programmable gate array (FPGA), a central processing unit (CPU), a microcontroller, or a microprocessor, or a combination thereof. The memory 152 may be a non-volatile storage medium that stores instructions executed by the processor 151.Memory 152 may be implemented using at least one of storage media, such as flash memory, a hard disk, a solid-state disk (SSD), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), programmable ROM (PROM), electrically erasable programmable ROM (EEPROM), or erasable programmable ROM (EPROM). Memory 152 may store a sound masking algorithm, sound masking control logic, and / or the like.

[0040] In response to receiving a command to enable a deep sleep therapy function from the human interface device 110, the controller 150 may execute the deep sleep therapy function. When the deep sleep therapy function is executed, the controller 150 may control the seat controller 140 to generate vibrations to guide a user to have a deep sleep on the seat. Further, the controller 150 may play a sleep guidance sound to output the sleep guidance sound externally through the human interface device 110.

[0041] The controller 150 may monitor a facial expression, sitting posture, and / or an EEG (or an EEG signal) of a passenger using the sensing device 130. The controller 150 may monitor a facial expression, sitting posture (or tossing and turning, or body movement), and an EEG pattern of the passenger using a camera and / or a biometric signal measuring device. The controller 150 may monitor a change in a body organ (e.g., eyes), for example, the passenger's gaze and / or blinking. The controller 150 may determine a sleep state as a sleep level if the passenger's blink duration is greater than or equal to, for example, 800 milliseconds (ms). The controller 150 may determine the sleep state as a sleep threshold level if the passenger's blink duration is greater than, for example, 400 ms and less than, for example, 800 ms.Furthermore, the controller 150 may determine the sleep state as a sleep disturbance level (or a sleep disturbance state) when the passenger's eye blink duration is less than or equal to, for example, 400 ms. The controller 150 may monitor a change in the passenger's sitting posture (e.g., the extent of behavior). If a periodic movement of the passenger is detected, the controller 150 may determine that the passenger is in normal sleep. If a rapid eye movement (REM) sleep behavior disturbance pattern (e.g., dream behavior) is detected, in which the passenger flinches and makes a large movement, the controller 150 may determine that the passenger is sleep-disturbed. The controller 150 may analyze a sleep cycle through EEG measurement. The controller 150 may determine normal sleep or sleep disturbance based on the result of the sleep cycle analysis.

[0042] The controller 150 may determine whether the passenger is disturbed during sleep based on the image information obtained from the camera and / or the biometric signal measured by the biometric signal measuring device.

[0043] If it is determined that the passenger is disturbed during sleep, the controller 150 may measure noise in the vehicle using the microphone. If it is determined that the passenger is not disturbed during sleep, the controller 150 may determine that the sleep state is normal sleep (or the normal sleep state).

[0044] The controller 150 may determine whether sound masking is necessary based on the magnitude of the noise measured by the microphone. The controller 150 may compare the magnitude of the measured noise to a predetermined reference value and determine whether sound masking is necessary based on the result of the comparison.

[0045] If it is determined that sound masking is necessary, the controller 150 can perform sound masking. The controller 150 can determine a masking sound (or masking sound source) based on the sleep state and / or the intended use (e.g., reducing noise between floors, relaxation, concentration on work, or the like). At least one of white noise, pink noise, or brown noise, or any combination thereof, can be used as the masking sound. White noise can be noise in electronic equipment generated by electron-free movement. White noise generally has a uniform frequency spectrum. White noise can be the sound of rain, the sound of waves, the sound of mountain temple bells, the sound of birds, or the like. Pink noise can be noise that has the same amount of energy at each octave.Pink noise can be used as a sound source for measuring and testing an acoustic property. Pink noise can be the sound of a forest, the sound of a stream, the sound of wind, the sound of grass bugs, or the like. Brown noise can be a sound in which a high-frequency range is completely removed from the white noise. As a result, brown noise can sound more pleasant in the lower register. Brown noise can be the distant sound of rushing water, the sound of thunder, or the like.

[0046] If it is determined that there is no need for sound masking, the controller 150 may determine the measured sounds as acceptable sounds. In other words, if it is determined that there is no need for sound masking, the controller 150 may determine that the measured sounds are acceptable.

[0047] Fig.2 is a drawing for describing a process for determining a sleep state according to embodiments of the present invention.

[0048] With reference to Fig. 2, the controller 150 of the sound masking device 100 of Fig. 1, measure an EEG signal (or EEG) using an EEG measuring device. The controller 150 may analyze a pattern of the measured EEG signal and may determine a sleep state of a user (e.g., a passenger, a driver, or the like) based on the pattern.

[0049] If the measured EEG signal is a theta wave, the controller 150 may determine the sleep state (or a sleep stage) as a threshold sleep stage (or a first sleep stage, or a sleep entry stage). The controller 150 may determine the sleep state as a sleep stage (or a second sleep stage, or a light sleep stage) if the measured EEG signal is a delta wave. The controller 150 may determine the sleep state as a deep sleep stage (or a third sleep stage) if the measured EEG signal is a beta wave.

[0050] Fig. 3 is a drawing for describing a process for determining a sleep level according to embodiments of the present invention.

[0051] With reference to Fig. 3, the controller 150 of the sound masking device 100 of Fig.1, the controller 150 may perform monitoring 300 of a passenger's body movement using a camera. For example, the controller 150 may analyze image information obtained from the camera. The controller 150 may detect tossing and turning of the passenger, a change in the passenger's seating posture, and / or the like based on the image information.

[0052] The controller 150 may perform monitoring 310 of a change in a body organ of the passenger using the camera. The controller 150 may detect a blink of the passenger's eyes, a change in the passenger's gaze, and / or the like from image information obtained from the camera.

[0053] The controller 150 may perform an analysis 320 of a biometric signal pattern using a biometric signal measuring device. The controller 150 may measure an EEG signal using an EEG measuring device and may analyze a pattern of the measured EEG signal.

[0054] The controller 150 may perform lane departure monitoring 330 using a lane departure warning system while the vehicle is traveling.

[0055] The controller 150 may determine (or recognize) a sleep level based on the result of monitoring the body movement of the body and / or the change of the body organ, the result of analyzing the biometric signal pattern, and / or the result of monitoring whether or not the vehicle is leaving the lane, or the like. The sleep level may be classified into, for example, three levels or four levels.

[0056] The controller 150 may apply a sleep induction method according to the sleep level.

[0057] When the sleep level is determined to be level 1, the controller 150 may continuously issue a notification 340 about the need for sleep using voice interaction technology through a display, a speaker, and / or the like.

[0058] If the sleep level is determined to be Level 2, the controller 150 may guide a driver to a rest area, sleep guard, and / or the like in conjunction with a navigation terminal. The controller 150 may also issue a warning 350 indicating that there is a possibility of drowsy driving.

[0059] When the sleep level is determined as level 3, the controller can generate 150 deep sleep vibrations 360 on the seat when the vehicle is turned off using sleep induction technology.

[0060] If the sleep stage is determined to be stage 4, the controller 150 may generate alarm vibrations 370 based on a frequency that comfortably awakens the driver and a seat vibration pattern. As an example, if the EEG is a beta wave and a gamma wave, the controller 150 may link and output wake-up music and vibrations. As another example, the controller 150 may output vibrations that stimulate in stage 5 sleep related to the sleep and deep sleep cycle. As another example, if the wake-up vibration stimulation frequency is 65 Hz to 85 Hz, the controller 150 may output a wake-up vibration stimulation pattern as a percussive vibration.

[0061] Fig. 4 is a drawing for describing a method for determining a sleep disorder according to embodiments of the present invention.

[0062] With reference to Fig. 4, the controller 150 of the masking device 100 can Fig.1 in a step S100 an EEG signal by means of the detection device 130 of Fig. 1. For example, the controller 150 may measure an EEG signal of a passenger using an EEG measuring device.

[0063] In step S110, the controller 150 may analyze a sleep cycle based on the measured EEG signal. The controller 150 may analyze the measured EEG signal. The controller 150 may determine a single sleep cycle (e.g., 90 minutes) consisting of rapid eye movement (REM) sleep and non-REM sleep based on the EEG signal.

[0064] If the analyzed sleep cycle is a normal sleep cycle (or a comfortable sleep cycle), the controller 150 may determine the sleep state as normal sleep in step S120. If the sleep cycle is 90 minutes, the controller 150 may determine that the sleep cycle is the normal sleep cycle.

[0065] If the analyzed sleep cycle is a sleepless cycle (or a sleepless cycle that does not result in deep sleep), the controller 150 may determine the sleep state as a sleep disturbance in step S130. For example, if the sleep cycle is 30 minutes, the controller 150 may determine that the sleep cycle is a sleepless cycle.

[0066] Fig. 5 is a drawing for describing a process for determining whether sound masking is required according to embodiments of the present invention.

[0067] In a step S200, the controller 150 of the sound masking device 100 may Fig. 1 a sleep disturbance by means of the detection device 130 of Fig.1. The controller 150 may analyze image information received from a camera and may detect whether a sleep disturbance is present based on the image information. For example, if a passenger's blink duration is less than or equal to a reference time (e.g., 400 ms) and / or if a REM sleep behavior disturbance pattern (e.g., tossing and turning) is detected, the controller 150 determines that the passenger is disturbed in sleep (i.e., in a sleep disturbance state).

[0068] If sleep disturbance is detected, the controller 150 may measure noise in a vehicle using a microphone in step S210. The controller 150 may measure a magnitude of noise that disturbs the passenger's sleep.

[0069] In step S220, the controller 150 may determine whether there is a need for sound masking based on the magnitude of the measured noises. The controller 150 may identify whether the magnitude of the measured noises is greater than or equal to a predetermined reference value (e.g., 66 decibels (dB)). If the magnitude of the measured noises is greater than or equal to the predetermined reference value, the controller 150 may determine that there is a need for sound masking. On the other hand, if the magnitude of the measured noises is less than the predetermined reference value, the controller 150 may determine that there is no need for sound masking.

[0070] If it is determined that sound masking is necessary, the controller 150 may perform sound masking in step S230. The controller 150 may output white noise or pink noise using a low-frequency specialized sound masking algorithm. The controller 150 may play random noise-based white noise during a sleep interval. The controller 150 may play pink noise to emphasize a mid-bass sound during a deep sleep interval. The played noise may be output through a speaker. The controller 150 may randomly play the masking sound that is unfamiliar to the brain and ears, thereby implementing a cocktail party effect. Further, the controller 150 may perform active sound masking in conjunction with sounds around a vehicle and an office.

[0071] If it is determined that there is no need for sound masking, the controller 150 may determine that noise in the vehicle is an acceptable level in step S240.

[0072] Fig. 6 is a drawing illustrating the result of analyzing a contribution of white noise according to embodiments of the present invention.

[0073] A sound masking device 100 of Fig. 1 can analyze a sleep quality according to white noise in a situation where a sleep state changes from a sleep threshold level to a sleep stage.

[0074] The sound masking device 100 can monitor a passenger's eye blinking using a camera. If the passenger's eye blink duration is greater than, for example, 400 ms and less than, for example, 800 ms, the controller 150 can determine the sleep state as the sleep threshold level. If the passenger's eye blink duration is greater than or equal to, for example, 800 ms, the controller 150 can determine the sleep state as the sleep level. If the eye blink duration is less than or equal to, for example, 400 ms, the controller 150 can determine the sleep state as a sleep disturbance level.

[0075] The controller 150 may monitor the number of times the passenger rolls and turns their body and a pattern in which the passenger rolls and turns their body using the camera. If the number of times the passenger rolls and turns their body is less than or equal to, for example, 2 times, and if the pattern in which the passenger rolls and turns their body is a periodic movement, the controller 150 may determine the sleep state as normal sleep. If the number of times the passenger rolls and turns their body is greater than or equal to, for example, 3 times, and if the pattern in which the passenger rolls and turns their body is a jerking REM sleep behavior disorder pattern, the controller 150 may determine the sleep state as a sleep disorder.

[0076] The controller 150 may monitor a biometric signal (e.g., an EEG signal) of the passenger using a biometric signal measuring device. The controller 150 may analyze a sleep cycle using the passenger's biometric signal. If the sleep cycle is a comfortable sleep cycle, the controller 150 may determine the sleep state as normal sleep. If the sleep cycle is a sleepless cycle that does not allow for deep sleep, the controller 150 may determine the sleep state as a sleep disorder.

[0077] If it is determined that the sleep state is sleep disturbance, the controller 150 may play and output a white noise sound source. A sound source such as the sound of waves, the sound of rain, or the sound of flowing water may be used as the white noise sound source. The controller 150 may randomly play white noise at intervals of a predetermined time (e.g., 10 minutes).

[0078] For example, the controller 150 may measure a time (or sleep delay or sleep latency) required to transition from the sleep threshold stage to the sleep stage to analyze sleep quality. It may be identified that the sleep delay is, for example, 6.5 min ± 1.8 before applying the white noise, but that the sleep delay decreases to, for example, 3.6 min ± 0.9 after applying the white noise. Accordingly, it may be identified that playing the white noise in the situation where the sleep state transitions from the sleep threshold stage to the sleep stage is effective in reducing the sleep delay.

[0079] Additionally or alternatively, the controller 150 may measure the number of awakenings (NWAK) (or the number of times the body tosses and turns) to analyze sleep quality. It may be identified that the NWAK is, for example, 3.0 ± 1.2 before applying the white noise, but that the NWAK decreases to, for example, 1.2 ± 0.6 after applying the white noise.

[0080] Thus, when playing the white noise in the situation where the sleep state changes from the sleep threshold stage to the sleep stage, because the time required to change from the sleep threshold stage to the sleep stage is reduced and / or because the number of times the passenger tosses and turns his body is also reduced, it can be seen that playing the white noise improves the sleep quality.

[0081] Fig.7 is a drawing illustrating the result of analyzing a pink noise contribution according to embodiments of the present invention.

[0082] If in a step S300 a sleep disturbance is detected in a situation where a sleep state changes from a sleep stage to a deep sleep stage, the controller 150 of the sound masking device 100 may Fig. 1 Measure noise in a vehicle using a microphone. For example, if the eye blink duration is less than or equal to a reference time (e.g., 400 ms) and / or if the pattern in which the passenger tosses and turns their body is a REM sleep behavior disturbance pattern, the controller 150 may determine that a passenger is disturbed during sleep. If it is determined that the passenger is disturbed during sleep, the controller 150 may measure noise that disturbs the passenger's sleep in the vehicle.

[0083] In step S310, the controller 150 may determine whether a magnitude of the measured noise is greater than or equal to a predetermined reference value. For example, the controller 150 may identify whether the magnitude of the measured noise is greater than or equal to 66 dB.

[0084] If the magnitude of the measured noise is greater than or equal to the predetermined reference value, the controller 150 may perform sound masking using pink noise in step S320. The controller 150 may reproduce and output the pink noise based on sound masking control logic.

[0085] In step S330, the controller 150 may analyze a contribution of pink noise while performing sound masking. The controller 150 may quantitatively analyze an effect of the pink noise on deep sleep in a sleep cycle to which the pink noise is applied.

[0086] For example, the controller 150 may analyze a restless time (TRL), a restless number (NRL), and / or a sleep depth (or deep sleep level or depth), depending on whether pink noise is applied, in the situation where the sleep state transitions from the sleep stage to the deep sleep stage. The sleep depth may be defined as a difference between a maximum value and a minimum value on a vertical axis (or a y-axis) of the sleep cycle.

[0087] The result of quantitatively analyzing the Time of Restless (TRL), the Number of Restless (NRL), and the depth of sleep depending on whether the pink noise is applied in the situation where the sleep state changes from the sleep stage to the deep sleep stage according to an embodiment is as shown in Table 1 below. Table 1 Before applying pink noise After applying pink noise TRL 120 min ± 60 40 min ± 20 NRL 10 Number ± 8 5 Number ± 3 depth 8 ± 4 16 ± 4

[0088] As shown in Table 1, the Time of Restless (TRL) can be reduced, the Number of Restless (NRL) can be reduced, and / or the depth of sleep can be increased when pink noise is applied in the situation where the sleep state changes from the sleep stage to the deep sleep stage. If it is determined that the magnitude of the measured noise is not greater than or equal to the predetermined reference value, the controller 150 can, in a step S340, Fig. 1 to generate seat vibrations based on a deep sleep vibration pattern.

[0089] Fig. 8 is a drawing for describing a process for applying a cocktail party effect according to embodiments of the present invention.

[0090] In a step S400, the controller 150 of the sound masking device 100 may Fig.1 Analyze image information obtained from a camera and can detect a state in which a passenger is disturbed in sleep (ie, in a sleep disorder) based on the image information.

[0091] If the sleep disturbance is detected, the controller 150 may measure noise in a vehicle in step S410. The controller 150 may measure noise using a microphone installed in the vehicle.

[0092] In step S420, the controller 150 may determine whether the magnitude of the measured noise is greater than or equal to a predetermined reference value. If the magnitude of the measured noise is greater than or equal to the predetermined reference value, the controller 150 may determine that sound masking is necessary. On the other hand, if the magnitude of the measured noise is not greater than or equal to the predetermined reference value, that is, if the magnitude of the measured noise is less than the predetermined reference value, the controller 150 may determine that sound masking is not necessary.

[0093] If it is identified that the magnitude of the measured noises is greater than or equal to the predetermined reference value, the controller 150 may perform sound masking in a step S340. The controller 150 may select a masking sound source (or a masking sound) based on a sleep state. When the sleep state transitions from a sleep threshold stage to a sleep stage, the controller 150 may select random noise-based white noise as the masking sound source. When the sleep state transitions from the sleep stage to a deep sleep stage, the controller 150 may select pink noise corrected and / or filtered with the same energy as the masking sound source. The controller 150 may play and output the selected masking sound source through a speaker.

[0094] The controller 150 can randomly play white noise (e.g., the sound of running water or the sound of people talking) and can perform passive sound masking. A cocktail party effect can be implemented through passive sound masking.

[0095] The controller 150 may perform active sound masking to serve as a blanket to mask noises in the vehicle by playing pink noise (e.g., the sound of incoming waves, the sound of falling raindrops, or the like).

[0096] If the magnitude of the measured noise is not greater than or equal to the predetermined reference value, the controller 150 may determine that the noise in the vehicle is acceptable in a step S440.

[0097] Fig. 9 is a drawing for describing a sound masking concept according to embodiments of the present invention.

[0098] Sound masking refers to a phenomenon in which one sound is drowned—that is, masked or compensated—by another sound. A distorted large sound refers to a masker, and a drowned small sound refers to something that is masked. At least one of white noise, pink noise, or brown noise, or any combination thereof, can be used as a masking sound source for sound masking.

[0099] The sound masking device 100 of Fig. 1 can play random noise-based white noise in a sleep interval and can play pink noise to emphasize a mid-depth sound in a deep sleep interval, using a sound masking algorithm specialized for a low frequency.

[0100] The sound masking device 100 can randomly reproduce a masking sound source that is unfamiliar to the brain and ears, thereby implementing a cocktail party effect.

[0101] Furthermore, the sound masking device 100 can perform active sound masking in connection with noises around a vehicle and an office.

[0102] Fig. 10 is a drawing for describing a sound masking algorithm according to embodiments of the present invention.

[0103] The sound masking algorithm can analyze spatial acoustic noises in a vehicle or parking lot environment and can adjust a sound based on the spatial acoustic noises. The sound masking algorithm can prevent a sound from being too large or too small using active sound control. The sound masking algorithm can variably implement sound masking specialized for a low frequency.

[0104] In a step S500, the controller 150 of the sound masking device 100 may Fig. 1 Measure noise in a vehicle and can perform a spectrum analysis of the measured noise.

[0105] In a step S510, the controller 150 may extract a perceived sound, if there is a masker, by means of the spectrum analysis.

[0106] In a step S520, the controller 150 may analyze a difference level between a sound pressure level of the extracted sound and a masking boundary line.

[0107] In step S530, the controller 150 may apply an active sound control formula based on the analyzed difference level. The active sound control formula ASC(n) may be represented as Equation 1 below. ASC(n)=noise(n)−mask(n)+margin

[0108] The controller 150 can set a maximum value (or maximum sound pressure level) and a minimum value (or minimum sound pressure level) such that the masking sound is not too large or too small using ASC(n). The controller 150 can reflect a margin to variably apply the masking boundary as the masking sound increases and decreases.

[0109] In step S540, the controller 150 may apply a filter based on a sleep level, REM sleep cycle information, or warning and / or emergency information to control the masking sound. The controller 150 may apply the filter as in Equation 2 below, thereby preventing the masking sound from changing rapidly. Sound(n)=Sound(n−1)+Filter×ASC(n)

[0110] The controller 150 can thus prevent the feeling of difference due to a rapid change in the sound pressure level of the masking sound.

[0111] The controller 150 can implement a cocktail party effect using the sound masking algorithm. The cocktail party effect results from the fact that party participants selectively focus on and receive conversations with an interlocutor, despite being in a room with loud ambient noise. Selectively accepting only information that is meaningful to oneself, regardless of the environment, is called "selective perception" or "selective attention." The cocktail party effect refers to a psychological phenomenon indicated by such selective perception or attention. The reason why the "cocktail party effect" occurs is that no matter how many different voices reach the ears, the human brain can only select and process one of them.

[0112] Fig.11 is a drawing for describing passive sound masking according to embodiments of the present invention.

[0113] Passive sound masking is a sound masking technology that reflects a cocktail party effect to randomly play a sound unfamiliar to the brain and ears. According to one embodiment of a sound masking algorithm of the sound masking technology, the sound masking algorithm can play random noise-based white noise during a sleep interval and can play pink noise to emphasize a medium-low sound during a deep sleep interval.

[0114] The sound masking algorithm can randomly play the masking sound to implement a deep sleep therapy solution using the masking sound, such as white noise or pink noise. For example, the sound masking algorithm can include a filter function to reduce sound variation and a random sound quality correction function.

[0115] Fig. 12 is a drawing for describing active sound masking according to embodiments of the present invention.

[0116] In a step S600, the sound masking device 100 may Fig. 1 perform a quantitative analysis for ambient noise in a specific space (e.g., a vehicle, an office, a classroom, or a campsite). For example, the sound masking device 100 may analyze a quantitative numerical value (e.g., a noise exposure index) for the ambient noise.

[0117] In step S610, the sound masking device 100 may perform a qualitative analysis for the ambient noise. For example, the sound masking device 100 may measure an EEG, which is a biometric signal, and analyze an EEG pattern.

[0118] In a step S620, the sound masking device 100 may perform active sound masking based on the result of performing the quantitative analysis for the ambient noise and / or the result of performing the qualitative analysis for the ambient noise.

[0119] Fig. 13 is a flowchart illustrating a sound masking method according to embodiments of the present invention.

[0120] In a step S700, the controller 150 of the sound masking device 100 may Fig.1 perform a deep sleep therapy function. The controller 150 may perform the deep sleep therapy function based on passenger input data received from a human interface device 110 of Fig. 1 can be received,

[0121] When the deep sleep therapy function is executed, the controller 150 may generate sleep vibrations on the seat and / or play a sleep guidance sound source in step S710. The controller 150 may control the seat controller 140 to generate vibrations with a vibration frequency and / or vibration pattern to guide a passenger to have deep sleep on the seat. Further, the controller 150 may play the sleep guidance sound source using a sound source player and may output the sleep guidance sound source through a speaker.

[0122] In a step S720, the controller 150 can detect a sleep level by means of the detection device 130 from Fig. 1. The controller 150 may measure a biometric signal using a biometric signal measuring device. The controller 150 may analyze a pattern of the measured biometric signal to determine a sleep stage. As one example, the controller 150 may measure an EEG signal using an EEG measuring device. The controller 150 may analyze a pattern of the measured EEG signal to determine a sleep stage. The sleep stage may be divided into a first sleep stage (or a borderline sleep stage), a second sleep stage (or a light sleep stage), and a third sleep stage (or a deep sleep stage).

[0123] In step S730, the controller 150 may monitor a change in a body organ of the passenger and a body movement of the passenger using the detection device 130. The controller 150 may obtain image information using a camera. The controller 150 analyzes the obtained image information to detect an eye blink duration of the passenger, a body movement pattern of the passenger, or a combination thereof.

[0124] In step S740, the controller 150 may determine whether a sleep state is a sleep disorder based on the change in a body organ of the passenger and the passenger's body movement. If the blink duration is less than or equal to a predetermined reference value (or a predetermined reference time) (e.g., 400 ms) and / or if the body movement pattern is a REM sleep behavior disorder pattern, the controller 150 may determine that the sleep state is a sleep disorder.

[0125] If it is determined that the sleep state is the sleep disturbance, the controller 150 may measure noise in a vehicle using a microphone in a step S750.

[0126] In step S760, the controller 150 may determine whether sound masking is necessary based on the measured noises. The controller 150 may compare a magnitude of the measured noises with a predetermined reference value. The controller 150 may determine that sound masking is necessary if the magnitude of the measured noises is greater than or equal to the predetermined reference value. If the magnitude of the measured noises is not greater than or equal to the predetermined reference value, the controller 150 may determine that sound masking is not necessary.

[0127] If it is determined that sound masking is necessary, the controller 150 may perform sound masking in step S770. The controller 150 may determine a masking sound based on the sleep level, sound magnitude, REM sleep cycle information, emergency information, and / or the like. The controller 150 may automatically adjust a sound using spatial acoustic sound analysis.

[0128] If it is determined that there is no need for sound masking, the controller 150 may determine that the noise in the vehicle is acceptable in step S780.

[0129] If the sleep state is not the sleep disturbance, the controller 150 may determine the sleep state of the passenger as normal sleep in a step S790.

[0130] Fig.14 is a block diagram illustrating a configuration of a sound masking system according to embodiments of the present invention.

[0131] With reference to Fig. 14, a sound masking system 400 may include a master terminal 410, a user terminal 420, and a smart speaker 430 connected via a wired and / or wireless communications network. Each of the master terminal 410, the user terminal 420, and the smart speaker 430 may include communications circuitry, a processor, and memory.

[0132] The master terminal 410 may be installed in a specific space (e.g., a vehicle, an office, or the like). The master terminal 410 may perform network management, individual speaker control in a network environment, monitoring of a spatial acoustic environment, or the like.

[0133] The master terminal 410 can analyze a user's sleep level using a biometric signal measuring device. The master terminal 410 can analyze a change in a user's body organ, a user's body movement pattern, and / or the like using a camera installed in the specific room, and can determine whether a sleep state is a sleep disorder.

[0134] When the sleep disturbance is detected, the master terminal 410 may transmit a control command to execute deep sleep therapy content to the user terminal 420. The master terminal 410 may transmit the user's sleep level information along with the control command.

[0135] The deep sleep therapy content may be pre-installed in the form of an application in the user terminal 420. The user terminal 420 may turn the deep sleep therapy content on or off based on the control command of the master terminal 410.

[0136] When the deep sleep therapy content is enabled, the user terminal 420 may measure sounds (or ambient sounds) in a spatial acoustic environment using a microphone 421. The user terminal 420 may select a masking sound source based on the user's sleep stage and the measured sounds. The user terminal 420 may transmit the selected masking sound source to the smart speaker 430.

[0137] The user terminal 420 may play and output the selected masking sound source through a sound output device 423. The sound output device 423 may include a function for detecting whether the smart speaker 430 is operating.

[0138] The smart speaker 430 may include a dedicated high-frequency tweeter 431, a hybrid-type woofer 432, a microphone 433, a small DC motor 434, a controller connector 435, an emotional LED 436, a battery 437, a Wi-Fi chip 438, and a Bluetooth chip 439.

[0139] The smart speaker 430 can receive the masking sound source transmitted from the user terminal 420 through the Wi-Fi chip 438 and / or the Bluetooth chip 439. The smart speaker 430 can reproduce and output the received masking sound source through the dedicated high-frequency tweeter 431 and / or the hybrid-type woofer 432.

[0140] The smart speaker 430 may be a portable speaker, such as a cup holder type smart speaker, a handle hanging type smart speaker, or the like.

[0141] The smart speaker 430 can measure ambient noise using the embedded microphone 433. When the user experience (UX)-based smart speaker 430 is used, a peer-to-peer masking sound source can be played near the user using the near-field microphone 433. Furthermore, a sound source obtained by synthesizing a natural sound with music can be used as a masking sound source to minimize the sense of difference.

[0142] As another example, the smart speaker 430 may analyze a type of measured sound using an artificial intelligence server (AI server) and may play a masking sound source optimized for the type of sound. The smart speaker 430 may transmit the received sound to the AI ​​server.

[0143] As another example, the smart speaker 430 may analyze a user experience using the AI ​​server and may play a masking sound source optimized for the user. The AI ​​server may provide the masking sound source.

[0144] An omnidirectional speaker may be embedded in the smart speaker 430 so that the smart speaker 430 maximizes a soundscape speaker's usability radius. Additionally or alternatively, an echo canceller may be embedded in the smart speaker 430 so that the smart speaker 430 prevents playback sound from being reintroduced into the microphone.

[0145] As another example, the smart speaker 430 may analyze a magnitude and frequency characteristic of sounds measured by the microphone 433. The smart speaker 430 may select and play a masking sound source that matches the analyzed result from among masking sound sources stored in a memory. The smart speaker 430 may adjust a level and timbre of the masking sound source in real time. A noise type analysis function and a user usability analysis function may additionally be applied to the smart speaker 430 in an active scheme.

[0146] Embodiments of the present invention may determine a sleep state of the user to guide the user to sleep, and may mask a sleep disturbance sound, thereby guiding the user to have a deep sleep.

[0147] Embodiments of the present invention may determine a sleep level and a sleep quality based on image information and / or biometric information and may play a masking sound based on the determined sleep level and / or the determined sleep quality, thereby guiding the user to sleep.

[0148] Although the present invention has been described above with reference to exemplary embodiments and the accompanying drawings, the present invention is not limited thereto. The embodiments of the present invention can be variously modified and changed by those skilled in the art to which the present invention pertains without departing from the spirit and scope of the present invention as claimed in the following claims. Therefore, embodiments of the present invention are provided for illustrative purposes only and are not intended to limit the technical essence of the present invention. The scope of the present invention should be construed based on the appended claims, and all technical ideas within the scope that are equivalent to the claims should be included in the scope of the present invention. 100 Sound masking device 110 Human Interface Device 120 communication device 130 Recording device 140 seat controllers 150 controllers 300 Monitoring a body movement 310 Monitoring a change in a body organ 320 Analysis of a biometric signal pattern 330 Monitoring lane departure or not 340 Level 1: Notification 350 Level 2: Warning 360 Level 3: Deep sleep vibrations 370 Level 4: Alarm vibrations 400 Sound Masking System 410 Master terminal 420 user terminal 421 Microphone 422 processor 423 Sound output device 430 smart speakers 431 dedicated high-frequency tweeter 432 hybrid type woofer 433 Microphone 434 small DC motor 435 Controller connector 436 emotional LEDs 437 Battery 438 Wi-Fi chip 439 Bluetooth chip

Claims

[1] Sound masking device comprising: a detection device configured to measure image information and biometric information of a passenger in a vehicle; and a controller connected to the detection device, the controller being configured to Determining a sleep state of the passenger based on the biometric information, Determine whether the passenger will be disturbed in the passenger's sleep state based on the image information, Measuring noise in the vehicle in response to determining that the passenger is disturbed during sleep, Determine whether there is a need for sound masking based on the measured noises, and Performing sound masking based on sleep state in response to determining that there is a need for sound masking. [2] The sound masking device of claim 1, wherein the controller is configured to: analyzing a pattern of an electroencephalogram (EEG) signal measured by an EEG measuring device; and Determining the passenger's sleep state based on the analyzed EEG signal pattern. [3] The sound masking device of claim 1, wherein the controller is configured to: Monitoring a change in a body organ of the passenger and a body movement of the passenger by analyzing the image information; and Determine whether the passenger is disturbed during sleep based on a change in a passenger's body organ and / or body movement pattern, or any combination thereof. [4] The sound masking device of claim 1, wherein the controller is configured to determine that the passenger is disturbed in sleep when an eye blink duration of the passenger is less than or equal to a predetermined reference time and / or a body movement pattern is a rapid eye movement (REM) sleep behavior disturbance pattern, or any combination thereof. [5] The sound masking device of claim 1, wherein the controller is configured to: Comparing a magnitude of the measured noise with a predetermined reference value; and Determine that sound masking is necessary when the magnitude of the measured noise is greater than or equal to the predetermined reference value. [6] The sound masking device of claim 1, wherein the controller is configured to: Selecting white noise as a masking sound source when the sleep state changes from a sleep threshold level to a sleep stage; and Play and output the selected white noise. [7] The sound masking device of claim 6, wherein the controller is configured to randomly play the selected white noise. [8] The sound masking device of claim 1, wherein the controller is configured to: Selecting pink noise as a masking sound source when the sleep state changes from a sleep stage to a deep sleep stage; and Play and output the selected pink noise. [9] The sound masking device of claim 8, wherein the controller is configured to control a magnitude of the pink noise based on a magnitude of the measured sounds. [10] The sound masking device according to claim 1, wherein the controller is configured to select and play a masking sound source based on a purpose of the sound masking. [11] Sound masking method comprising: Determining a sleep state of a passenger in a vehicle based on biometric information of the passenger, wherein the biometric information is measured by a detection device; Determining whether the passenger is disturbed during sleep based on image information of the passenger, the image information being obtained by the detecting device in the sleeping state of the passenger; Measuring noise in the vehicle in response to determining that the passenger is being disturbed during sleep; Determine whether there is a need for sound masking based on the measured noise; and Performing sound masking based on sleep state in response to determining that there is a need for sound masking. [12] The sound masking method according to claim 11, wherein determining the sleep state of the passenger comprises: analyzing a pattern of an EEG signal measured by an EEG measuring device; and Determining the passenger's sleep state based on the analyzed EEG signal pattern. [13] The sound masking method of claim 11, wherein determining whether the passenger is disturbed during sleep comprises: Monitoring a change in a body organ of the passenger and a body movement of the passenger by analyzing the image information; and Determine whether the passenger is disturbed during sleep based on a change in a passenger's body organ and / or body movement pattern, or any combination thereof. [14] The sound masking method of claim 11, wherein determining whether the passenger is disturbed during sleep comprises: Determining that the passenger is sleep-disturbed if an eye blink duration of the passenger is less than or equal to a predetermined reference time and / or a body movement pattern is a REM sleep behavior disturbance pattern, or any combination thereof. [15] The sound masking method of claim 11, wherein determining whether sound masking is necessary comprises: Comparing a magnitude of the measured noise with a predetermined reference value; and Determine that sound masking is necessary when the magnitude of the measured noise is greater than or equal to the predetermined reference value. [16] The sound masking method of claim 11, wherein performing the sound masking comprises: Selecting white noise as a masking sound source when the sleep state changes from a sleep threshold level to a sleep stage; and Play and output the selected white noise. [17] The sound masking method of claim 16, wherein reproducing and outputting the selected white noise comprises randomly reproducing the selected white noise. [18] The sound masking method of claim 11, wherein performing the sound masking comprises: Selecting pink noise as a masking sound source when the sleep state changes from a sleep stage to a deep sleep stage; and Play and output the selected pink noise. [19] The sound masking method of claim 18, wherein reproducing and outputting the selected pink noise comprises controlling a magnitude of the pink noise based on a magnitude of the measured sounds. [20] The sound masking method according to claim 11, wherein performing the sound masking comprises selecting and reproducing a masking sound source based on a purpose of the sound masking.

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