KR20210042221A - Massage chair providing healthcare service using medical data and operation thereor - Google Patents

Abstract

The present disclosure relates to a massage chair for collecting medical data from at least one device to provide a healthcare service, and an operation method for the massage chair. The operation method comprises the steps of: identifying user information; acquiring medical data including at least one of blood pressure information, activity information, blood sugar level information, body composition information, weight information, a stress index, sleep information, and electrocardiogram signal information corresponding to the identified user information; and determining health improvement information on the basis of the medical data.

Description

Massage chairs and chairs that provide health care services using medical data {MASSAGE CHAIR PROVIDING HEALTHCARE SERVICE USING MEDICAL DATA AND OPERATION THEREOR}

The present disclosure relates to a massage chair that collects medical data from at least one device to provide a health care service and a method of operating the massage chair.

In line with the recent trend of well-being and five days a week, they are investing a lot of time and money to improve their physical health, and people's awareness of health care, health maintenance, and health promotion is increasing, regardless of age group. In particular, many people not only receive expert diagnosis or advice from medical facilities such as hospitals for the purpose of early detection or prevention of diseases, but also manage, maintain or promote their own health by using non-medical facilities such as so-called sports clubs. Are working for you.

In addition, equipment used to maintain or promote one's own health and physical strength at home or in a gym, or to recover from fatigue or to relieve stress, for example, exercise equipment such as a treadmill or massage equipment, has been developed and is widely used in real life.

Massage is one of the medical adjuvant therapy that helps blood circulation and relieves fatigue by sweeping, kneading, pressing, pulling, tapping, or moving the body with hands or special devices. A device that performs massage by a mechanical device is called a massage machine, and various mechanical elements are used for an effective massage.

As such a massage device, a massage chair that allows a user to sit comfortably and receive a massage is mainly used, and such a massage chair consists of a seat, a back, armrest, and a leg massage part so that the user can sit comfortably and receive a massage. Each part is provided with a massage unit that performs massage while moving along the user's spine, buttocks, thighs, calves, and arms.

However, since the massage unit of the conventional massage chair does not receive various information related to the user's body from various external devices, there is a problem in that it cannot provide an optimal massage to the user.

A method of operating a massage chair including a processor and a memory according to the present disclosure includes the steps of identifying user information, blood pressure information corresponding to the identified user information, activity information, blood sugar level information, body composition information, weight information, stress index, And obtaining medical data including at least one of sleep information or electrocardiogram signal information, and determining health improvement information based on the medical data.

The determining of health improvement information of the method of operating the massage chair according to the present disclosure includes obtaining a normal range corresponding to each of a plurality of pieces of information included in the medical data from a memory, and a plurality of pieces of information included in the medical data and normal Comparing the ranges, acquiring abnormal information based on information not included in the normal range among a plurality of pieces of information included in the medical data, and outputting an alarm when the abnormal information indicates that there is an abnormality to the user And selecting a massage mode based on the abnormality information.

The obtaining of medical data of the method of operating the massage chair according to the present disclosure includes transmitting user information to a hospital server, transmitting medical data to the hospital server, and the user based on user information and medical data from the hospital server. The step of obtaining health status information, and determining the health improvement information includes determining health improvement information based on the health status information.

The determining of health improvement information in the method of operating the massage chair according to the present disclosure includes acquiring an abnormal part of the body part of the user based on the health state information, and the part corresponding to the abnormal part in the massage chair. It characterized in that it comprises the step of adjusting the temperature based on the health state information, and the step of selecting a massage mode based on the abnormal area.

The determining of health improvement information of the operating method of the massage chair according to the present disclosure includes obtaining a first machine learning model obtained by machine learning the correlation between the health state information and the past medical data before the health state information is generated. , Determining the predicted health state information by applying the obtained medical data to the first machine learning model, outputting the predicted health state information, generating health improvement information based on the predicted health state information, Past medical data and acquired medical data are characterized in that they include a personal health record (PHR).

The step of determining health improvement information of the operating method of the massage chair according to the present disclosure includes a massage mode selected by the user in the past and a massage mode selected by the user in the past with respect to past medical data before the user selects the massage mode. Obtaining a second machine learning model in which the correlation of the user's satisfaction information with respect to the machine is learned, and by applying medical data and a plurality of massage modes to the second machine learning model, the user's prediction for each of the plurality of massage modes And generating a satisfaction level and selecting a massage mode having the highest satisfaction among prediction satisfaction levels for each of the plurality of massage modes.

The massage chair according to the present disclosure includes a processor and a memory, and the processor identifies user information based on instructions stored in the memory, blood pressure information corresponding to the identified user information, activity information, blood sugar level information, body composition information, It characterized by performing the step of acquiring medical data including at least one of weight information, stress index, sleep information, or electrocardiogram signal information, and selecting a massage mode based on the medical data.

The processor of the massage chair according to the present disclosure obtains a normal range corresponding to each of a plurality of pieces of information included in the medical data from the memory based on a command stored in the memory, the plurality of pieces of information and the normal range included in the medical data. Comparing, obtaining abnormal information based on information not included in the normal range among a plurality of pieces of information included in the medical data, and outputting an alarm when the abnormal information indicates that there is an abnormality to the user And selecting a massage mode based on the abnormal information.

The processor of the massage chair according to the present disclosure transmits user information to a hospital server based on instructions stored in the memory, transmitting medical data to the hospital server, and health status information based on user information and medical data from the hospital server. It characterized in that performing the step of acquiring and selecting a massage mode based on the health state information.

The processor of the massage chair according to the present disclosure obtains an abnormal part of a user's body part based on health status information based on a command stored in a memory, and calculates a temperature of a part corresponding to the abnormal part in the massage chair. It characterized in that performing the step of adjusting based on health status information and the step of selecting a massage mode based on the abnormal area.

The processor of the massage chair according to the present disclosure obtains a first machine learning model obtained by machine learning the correlation between health status information and past medical data before the health status information is generated, based on instructions stored in the memory. Applying the generated medical data to the first machine learning model to determine predicted health status information, outputting predicted health status information, generating health improvement information based on the predicted health status information, and performing past medical treatment The data and the acquired medical data are characterized in that they include a personal health record (PHR).

The processor of the massage chair according to the present disclosure is based on an instruction stored in a memory,

A second machine learning model based on machine learning of the correlation between the user's satisfaction information on the massage mode selected by the user in the past with respect to the massage mode selected by the user in the past and the medical data before the user selected the massage mode in the past. The step of obtaining, applying medical data and a plurality of massage modes to a second machine learning model, generating a user's predicted satisfaction for each of the plurality of massage modes, and the highest satisfaction among prediction satisfaction for each of the plurality of massage modes It characterized in that performing the step of selecting a massage mode having a.

In addition, a program for implementing the method of operating the massage chair as described above may be recorded on a computer-readable recording medium.

1 is a view for explaining a massage chair according to an embodiment of the present disclosure.
2 is a diagram for describing a main frame according to an embodiment of the present disclosure.
3 is a view showing a massage chair according to an embodiment of the present disclosure.
4 is a diagram illustrating a method of operating a massage chair according to an embodiment of the present disclosure.
5 is a diagram illustrating an external device capable of communicating with the massage chair 100 according to an embodiment of the present disclosure.
6 is a flowchart illustrating a method of selecting a massage mode according to an embodiment of the present disclosure.
7 is a flowchart illustrating a method of obtaining medical data according to an embodiment of the present disclosure.
8 is a diagram illustrating machine learning of a massage chair according to an embodiment of the present disclosure.
9 is a diagram illustrating a data learning unit 610 and a massage chair 100 according to an embodiment of the present disclosure.
10 is a flowchart illustrating an operation of a massage chair according to an embodiment of the present disclosure.
11 is a diagram illustrating a data learning unit 610 and a massage chair 100 according to an embodiment of the present disclosure.
12 is a flowchart illustrating an operation of a massage chair according to an embodiment of the present disclosure.

Advantages and features of the disclosed embodiments, and a method of achieving them will become apparent with reference to the embodiments described below together with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below, but may be implemented in a variety of different forms, and only these embodiments make the present disclosure complete, and those skilled in the art to which the present disclosure pertains. It is provided only to fully inform the person of the scope of the invention.

The terms used in the present specification will be briefly described, and the disclosed embodiments will be described in detail.

Terms used in the present specification have selected general terms that are currently widely used as possible while considering functions in the present disclosure, but this may vary according to the intention or precedent of a technician engaged in a related field, the emergence of new technologies, and the like. In addition, in certain cases, there are terms arbitrarily selected by the applicant, and in this case, the meaning of the terms will be described in detail in the description of the corresponding invention. Therefore, the terms used in the present disclosure should be defined based on the meaning of the term and the contents of the present disclosure, not the name of a simple term.

In the present specification, expressions in the singular include plural expressions unless the context clearly specifies that they are in the singular. In addition, plural expressions include expressions in the singular, unless the context clearly specifies that they are plural.

When a part of the specification is said to "include" a certain component, it means that other components may be further included rather than excluding other components unless specifically stated to the contrary.

In addition, the term "unit" used in the specification refers to software or hardware components, and "unit" performs certain roles. However, "unit" is not meant to be limited to software or hardware. The “unit” may be configured to be in an addressable storage medium or may be configured to reproduce one or more processors. Thus, as an example, "unit" refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, procedures, Includes subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, database, data structures, tables, arrays and variables. The functions provided within the components and "units" may be combined into a smaller number of components and "units" or may be further separated into additional components and "units".

According to an embodiment of the present disclosure, the "unit" may be implemented with a processor and a memory. The term “processor” is to be interpreted broadly to include general purpose processors, central processing units (CPUs), microprocessors, digital signal processors (DSPs), controllers, microcontrollers, state machines, and the like. In some circumstances, “processor” may refer to an application specific application (ASIC), programmable logic device (PLD), field programmable gate array (FPGA), and the like. The term "processor" refers to a combination of processing devices, such as, for example, a combination of a DSP and a microprocessor, a combination of a plurality of microprocessors, a combination of one or more microprocessors in combination with a DSP core, or any other such configuration. You can also refer to it.

The term "memory" should be interpreted broadly to include any electronic component capable of storing electronic information. The term memory refers to random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), programmable read-only memory (PROM), erase-programmable read-only memory (EPROM), electrical May refer to various types of processor-readable media such as erasable PROM (EEPROM), flash memory, magnetic or optical data storage, registers, and the like. The memory is said to be in electronic communication with the processor if the processor can read information from and/or write information to the memory. The memory integrated in the processor is in electronic communication with the processor.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art may easily implement the embodiments. In the drawings, parts not related to the description are omitted in order to clearly describe the present disclosure.

1 is a view for explaining a massage chair according to an embodiment of the present disclosure.

The massage chair 100 according to an embodiment of the present disclosure forms an area for accommodating at least a part of the user's body, and a body massage unit 2100 that massages the user's body, and massages the user's leg. It may include a leg massage unit 2300.

The body massage unit 2100 may provide a massage to at least a part of a user's body. The body massage unit 2100 includes a massage module 2170 that provides a massage function to at least a part of a user's body, an audio output module 2160 for providing an audio output in an arbitrary form to the user, and a body massage unit 2100 It may include a main frame 2110 constituting the skeleton of the user and a user input unit 2180 for receiving an input of an arbitrary form from the user.

Components included in the above-described body massage unit 2100 are merely exemplary embodiments, and the body massage unit 2100 may include various configurations in addition to the above-described configuration.

In addition, the shape and structure of the massage chair 100 shown in FIG. 1 is only exemplary, and as long as it does not depart from the scope of rights defined by the claims of the present disclosure, various types of massage chair 100 are also disclosed herein. It can be included within the scope of the content.

The body massage unit 2100 may form an arbitrary type of space for accommodating a user. The body massage unit 2100 may have a space having a shape corresponding to the shape of the user's body. For example, as shown in FIG. 1, the body massage unit 2100 may be implemented in a seating type capable of accommodating a user's whole body or a part of the body.

A portion of the body massage unit 2100 in contact with the ground may include an arbitrary material for increasing the frictional force or an arbitrary member (eg, an anti-slip pad, etc.) for increasing the frictional force, and the massage chair 100 It may include a wheel to enhance the mobility of the.

At least a portion of the body massage unit 2100 may slide. For example, when the body massage unit 2100 starts a massage, at least a part of the body massage unit 2100 may slide forward. In addition, the body massage unit 2100 may be inclined rearward. As a result, the body massage unit 2100 may provide air massage in a state in which it is inclined backward.

According to an embodiment of the present disclosure, the massage chair 100 may include at least one air cell (not shown). The air cell may be located in the user's shoulder part, pelvis part, arm massage part, leg massage part 2300, and the like, but is not limited thereto and may be disposed in various parts of the massage chair 100.

The massage chair 100 may include an air supply unit, and the air supply unit may inflate the air cell by supplying air to the air cell. The air supply unit may be located inside the body massage unit 2100 and may be located at the leg massage unit 2300. In addition, the air supply unit may be located outside the massage chair 100.

The leg massage unit 2300 may provide a leg massage to a user. For example, the leg massage unit 2300 may include a calf massage unit that massages the user's calf and/or a foot massage unit that massages the user's foot.

The leg massage unit 2300 may be adjustable in length according to the user's body characteristics. For example, when a tall user uses the massage chair 100, the length of the leg massage unit 2300 needs to be lengthened because the length of the calf is long. In addition, when a user with a small height uses the massage chair 100, the leg massage unit 2300 needs to be shortened because the length of the calf is short. Accordingly, the leg massage unit 2300 may provide a leg massage customized to the user's height.

The massage module 2170 may be provided inside the body massage unit 2100 to provide an arbitrary type of mechanical stimulation to a user accommodated in the body massage unit 2100. As shown in FIG. 1, the massage module 2170 may move along the main frame 2110 provided inside the body massage part 2100.

For example, a rack gear may be provided on the main frame 2110 of the body massage unit 2100, and the massage module 2170 may move along the rack gear, while mechanically controlling various parts of the user's body. Can provide stimulation. The massage module 2170 may include a ball massage unit or a roller massage unit, but is not limited thereto.

The main frame 2110 constitutes a skeleton of the internal structure of the body massage unit 2100 and may be implemented with a metal material or a plastic material. For example, the main frame 2110 may be implemented with iron, alloy, steel, or the like, but is not limited thereto and may be implemented with various hard materials.

According to an embodiment of the present disclosure, the massage chair 100 may include an audio output module 2160. The audio output module 2160 may be provided in various locations. For example, the audio output module 2160 is an upper audio output unit disposed on the upper part of the seat in contact with the user, a front audio output unit attached to the front end of the left and right arm massage parts of the seat part, and/or attached to the rear end of the arm massage part It may include a plurality of output units such as a rear audio output unit and the like, but is not limited thereto. In this case, the audio output module 2160 may provide 3D sound such as 5.1 channels, but is not limited thereto.

According to an embodiment of the present disclosure, a user may control the massage chair 100 using the massage device control device 2200. The massage apparatus control device 2200 may be connected to the massage chair 100 through wired communication and/or wireless communication.

The massage device control device 2200 may include a remote controller, a cellular phone, a personal digital assistant (PDA), and the like, but is not limited thereto, and through wired or wireless communication with the massage chair 100 It may include a variety of connectable electronic devices.

2 is a diagram for explaining a main frame according to an embodiment of the present disclosure.

According to an embodiment of the present disclosure, the main frame 2110 may include an upper frame 2250 in which the massage module 2170 is provided and a base frame 2210 supporting the upper frame 2250.

A rack gear 2251 may be provided on at least a portion of the upper frame 2250. The rack gear 2251 is a member for guiding the upward movement of the body massage module 2170 and may include a plurality of valleys and a plurality of floors.

According to an embodiment of the present disclosure, the rack gear 2251 may be provided to face both sides of the upper frame 2250, and the body massage module 2170 may move along the rack gear 2251. .

For example, the body massage module 2170 may include a gear that meshes with the rack gear 2251, and by rotating the gear by an actuator provided in the body massage module 2170, the body massage module 2170 It can be moved upwards or downwards.

The rack gear 2251 may be implemented with a metal material or a plastic material. For example, the rack gear 2251 may be implemented with iron, steel, alloy, reinforced plastic, melamine resin, phenol resin, etc., but is not limited thereto.

The upper frame 2250 may be implemented in various shapes. For example, the upper frame 2250 may be classified into an S frame, an L frame, an S&L frame, and a double S&L frame according to the shape, but is not limited thereto.

The S frame refers to a frame in which at least a portion of the upper frame 2250 has a curved shape such as “S”. The L frame refers to a frame in which at least part of the upper frame 2250 has a curved shape like “L”, and the S&L frame includes both a curved shape like “S” and a curved shape like “L” The double S&L frame refers to a frame that includes a curved shape like “L” and a curved shape like “S” of two parts.

The base frame 2210 refers to a portion of the main frame 2110 that supports the upper frame 2250 and contacts the ground. The base frame 2210 may include a base upper frame 2211 and a base lower frame 2212.

The base upper frame 2211 may support the upper frame 2250, and the base lower frame 2212 may contact the ground. In addition, the upper base frame 2211 may be positioned in contact with the lower base frame 212.

According to an embodiment of the present disclosure, the upper base frame 2211 may move along the lower base frame 2212. For example, the base upper frame 2211 may slide forward or backward along the base lower frame 2212. In this case, the upper frame 2250 is connected to the base upper frame 2211 and may move according to the movement of the base upper frame 2211.

For example, when the base upper frame 2211 moves forward, the upper frame 2250 may also move forward, and when the base upper frame 2211 moves backward, the upper frame 2250 is also moved backward. You can move. For this reason, the sliding movement of the body massage unit 2100 may be allowed.

Specifically, in order to allow movement of the base upper frame 2211, a moving wheel may be provided below the base upper frame 2211. In addition, a guide member capable of guiding the moving wheel may be provided above the base lower frame 2212. The moving wheel provided in the base upper frame 2211 moves along the guide member provided in the base lower frame 2212, so that the base upper frame 2211 can be moved forward or backward.

According to another embodiment of the present disclosure, the massage chair 100 may not provide a sliding function, and in this case, the base frame 2210 may not be separated into upper and lower frames.

3 is a view showing a massage chair according to an embodiment of the present disclosure.

The massage chair 100 may include a processor 110 and a memory 120. The processor 110 may execute instructions stored in the memory 120.

The processor 110 may control the operation of the massage chair 100. The massage chair 100 may include one processor and may include a plurality of processors. When the massage chair 100 includes a plurality of processors, at least some of the plurality of processors may be located at physically spaced distances. In addition, the massage chair 100 is not limited thereto and may be implemented in various ways.

According to an embodiment of the present disclosure, the processor 110 may control the operation of the massage chair 100. For example, the massage chair 100 may include a plurality of actuators, and the massage chair 100 may control the operation of the massage chair 100 by controlling the operation of the plurality of actuators. For example, the massage chair 100 includes at least one of a massage module 2170 moving actuator, at least one actuator included in the massage module, a back angle actuator, a leg angle actuator, a foot massage actuator, a leg length adjustment actuator, and a sliding actuator. It may include, and the processor 110 may control the operation of the massage chair 100 by controlling them.

The massage module movement actuator is an actuator that enables the massage module 2170 to move up and down, and the massage module 2170 may move along the rack gear by the movement of the movement actuator of the massage module 2170.

The back angle actuator is an actuator that adjusts the angle of a portion of the massage chair 100 where the user's back abuts, and the conformal angle of the massage chair 100 may be adjusted by the operation of the conformal actuator.

The leg angle actuator is an actuator that adjusts the angle of the leg massage unit 2300 of the massage chair 100, and the angle between the leg massage unit 2300 and the body massage unit 2100 can be adjusted by the operation of the leg angle actuator. have.

The foot massage actuator refers to an actuator that operates the foot massage module included in the leg massage unit 2300. Using the foot massage actuator, the massage chair 100 may provide a foot massage to a user.

The massage module 2170 may include at least one actuator, and the processor 110 may provide various massage operations by operating at least one actuator. For example, the processor 110 may provide a tapping massage and a kneading massage by operating at least one actuator included in the massage module 2170, but is not limited thereto and may provide various massage operations.

The leg length adjustment actuator represents an actuator that adjusts the length of the leg massage unit 2300. For example, the processor 110 may adjust the length of the leg massage unit 2300 to suit the user by using the leg length adjustment actuator, and as a result, the user may receive a massage suitable for a body shape.

The sliding actuator enables the sliding operation of the massage chair 100. For example, by the operation of the sliding actuator, the horizontal base upper frame may move forward or backward, and as a result, the upper frame connected to the horizontal base upper frame may also move forward or backward.

The memory 120 may store various types of information related to the massage chair 100. For example, the memory 120 may include massage control information and personal authentication information, but is not limited thereto.

The memory 120 may be implemented through a non-volatile storage medium capable of continuously storing arbitrary data. For example, the memory 120 may include a storage device based on a flash memory and/or a battery-backup memory, as well as a disk, an optical disk and a magneto-optical storage device, but is not limited thereto. Does not.

The massage chair 100 may include a sensor unit. The sensor unit may acquire various information using at least one sensor. The sensor unit may be provided as a sensor using measuring means such as pressure, electric potential, and optics. For example, the sensor may include, but is not limited to, a pressure sensor, an infrared sensor, an LED sensor, and a touch sensor.

In addition, the sensor unit may include a biometric information acquisition sensor. The biometric information acquisition sensor may acquire fingerprint information, face information, voice information, iris information, weight information, electrocardiogram information, body composition information, and the like, but is not limited thereto and may include various biometric information.

According to another embodiment of the present disclosure, the massage chair 100 may detect a contact area and/or a contact location with a user through sensors. In addition, the massage chair 100 may provide a customized massage based on information obtained through sensors. In addition, the massage chair 100 may include a communication unit. The communication unit of the massage chair 100 may receive a signal to an external device. The processor 110 may obtain a result signal by processing the received signal. The communication unit may output a result signal to an external device.

The communication unit may communicate with a module inside the massage chair 100, an external massage device, and/or the user terminal 2200 through a network of any type. The communication unit may include a wired/wireless connection module for network access. As a wireless access technology, for example, wireless LAN (WLAN) (Wi-Fi), wireless broadband (Wibro), World Interoperability for Microwave Access (Wimax), and High Speed Downlink Packet Access (HSDPA) may be used. As a wired connection technology, for example, Digital Subscriber Line (XDSL), Fibers to the Home (FTTH), Power Line Communication (PLC), and the like may be used. In addition, the network connection unit may include a short range communication module and transmit and receive data to and from any device/terminal located in a short range. For example, as short range communication technology, Bluetooth, Radio Frequency Identification (RFID), infrared data association (IrDA), Ultra Wideband (UWB), ZigBee, etc. may be used. Not limited.

In addition, the massage chair 100 may further include an input unit or an output unit. The massage chair 100 may receive an input from a user using an input unit. In addition, the massage chair 100 may output the processing result of the processor 110 to an output unit.

Specifically, the input unit may receive a command related to operation control of the massage chair 100 from a user, and the input unit 2180 may be implemented in various forms. For example, the input unit 2180 may be provided in the body massage unit 2100 and may be provided in the leg massage unit 2300, but is not limited thereto.

The massage chair 100 may obtain various commands from a user through the input unit 2180. For example, the massage chair 100 includes selection of a massage module, selection of a massage type, selection of a massage intensity, selection of a massage time, selection of a massage site, selection of the position and motion of the body massage unit 2100, and massage. Arbitrary commands may be received for selection of power on-off of the chair 100, selection of whether or not to operate the heating function, selection related to sound source reproduction, and the like, but are not limited thereto.

The massage chair 100 may provide an interface for selecting a massage mode. For example, the input unit 2180 or the output unit may include the massage apparatus control device 2200. Medical massage lists of various modes related to body improvement may be listed through the massage apparatus control device 2200.

The medical massage mode may include at least one of a concentration mode, a meditation mode, a recovery mode, a stretching mode, a sleep mode, a vitality mode, a golf mode, a hip-up mode, a candidate mode, a zero gravity mode, and a growth mode.

According to another embodiment of the present disclosure, the input unit 2180 performs hot key type buttons and/or direction selection, cancellation, and input according to a preset user setting function or a self-preset function. It may be provided with a selection button for.

The input unit 2180 may be implemented as a keypad, a dome switch, a touch pad (positive pressure/electrostatic), a jog wheel, a jog switch, and the like, but is not limited thereto. In addition, the input unit 2180 may obtain a command through a user's speech based on a voice recognition technology.

According to an embodiment of the present disclosure, the output unit may include a display for displaying an operation state of the massage chair 100 or a current state of a user. In this case, the display is a liquid crystal display (LCD), a thin film transistor-liquid crystal display (TFT LCD), an organic light-emitting diode (OLED), and a flexible display. ) And at least one of a 3D display, but is not limited thereto.

The output unit may include an audio output module 2160. The audio output module 2160 may provide an arbitrary type of audio output to a user. For example, the audio output module 2160 may provide brain stimulation to the user by outputting a sound source and/or binaural beat optimized for a massage pattern provided from the massage chair 100 to the user. The audio output module 2160 may output sound signals received through a network (not shown) or stored in an internal/external storage medium (not shown). For example, the audio output module 2160 may output a sound source according to the control of the user terminal 2200 through a network connection (eg, Bluetooth connection, etc.) with the user terminal 2200. In addition, the audio output module 1600 may output an arbitrary type of sound signal generated in connection with the operation of the massage chair 100.

Those skilled in the art will appreciate that the present invention may be implemented in combination with other program modules and/or as a combination of hardware and software. For example, the present invention can be implemented by a computer-readable medium.

Computer-readable media can be any computer-readable media, including volatile and nonvolatile media, transitory and non-transitory media, removable and non-transitory media. Includes removable media. By way of example and not limitation, computer-readable media may include computer-readable storage media and computer-readable transmission media.

Computer-readable storage media include volatile and nonvolatile media, temporary and non-transitory media, removable and non-removable media implemented in any method or technology for storing information such as computer readable instructions, data structures, program modules or other data. Includes the medium. Computer-readable storage media include RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital video disk (DVD) or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage, or other magnetic storage. Devices, or any other medium that can be accessed by a computer and used to store desired information.

4 is a diagram illustrating a method of operating a massage chair according to an embodiment of the present disclosure.

The massage chair 100 may perform the step 210 of identifying user information. User information may include facial recognition information, user ID and password, voice information, fingerprint information, or iris information.

For example, when the user sits in the massage chair, the massage chair 100 may acquire an image of the user's face using the image acquisition unit. The massage chair 100 may extract facial recognition information from an image of a user's face. The facial recognition information may be feature points of an image of a user's face. The massage chair 100 may compare the extracted facial recognition information with the user's facial recognition information previously stored in the database of the memory 120. When the extracted facial recognition information matches the facial recognition information of a specific user in the database, the massage chair 100 may determine the user seated in the massage chair as a party user who can use the massage chair 100. When the extracted facial recognition information does not match the facial recognition information of a specific user in the database, the massage chair 100 may display on the output unit that the user is not a legitimate user. In addition, the massage chair 100 may guide a method for becoming a party user through the output unit.

Although only the user's facial recognition information has been described above, a similar process can be performed for the user ID and password, fingerprint information, or iris information. Therefore, redundant descriptions are omitted.

The massage chair 100 includes medical data including at least one of weight information, blood pressure information, activity information, blood sugar level information, body composition information, weight information, stress index, sleep information, or electrocardiogram signal information corresponding to the identified user information. The obtaining step 220 may be performed. The massage chair 100 may periodically acquire medical data. The period may be determined in advance, and may be changed according to the user's b setting.

When the user sits in the massage chair 100, the massage chair 100 may measure the user's weight using a weight sensor. The massage chair 100 may track the user's weight. However, the present invention is not limited thereto, and the weight information may be received from an external device. In addition, weight information can be directly input by the user.

The massage chair 100 may track the amount of change in the user's weight. The massage chair 100 may output a danger signal when the user's weight is excessively increased or decreased during a predetermined period.

The blood pressure information is information on the user's blood pressure, and the massage chair 100 may measure the blood pressure from the user's body part using a sensor. Also, blood pressure information may be received from an external device. Also, the blood pressure information can be directly input by the user.

The activity information is information indicating the amount of activity of the user. For example, the activity information may include information on the number of steps the user took per day. In addition, the activity information may include information on the type of exercise and the amount of exercise performed by the user. For example, the activity information may include information on the type of exercise such as swimming, walking, running, and cycling. In addition, the activity information may include information on a specific exercise time, distance, calories consumed, and the like. In addition, the activity information may include information related to a heart rate while the user is exercising. The massage chair 100 may receive activity information from an external device or a user.

The blood sugar level information is information indicating a user's blood sugar in a numerical value. The massage chair 100 may measure blood sugar level information by collecting a small amount of blood from the user's hand while the user is performing a massage. In addition, the massage chair 100 may receive blood sugar level information from an external device or input from a user.

The body composition information represents a user's moisture content, protein content, inorganic mass or body fat content as numerical information. The massage chair 100 may measure body composition information using a bioelectrical impedance analysis (BIA). The bioelectrical impedance method uses the principle that the resistance varies depending on the amount of water in the human body, and is a method of measuring body water by obtaining an impedance index generated by passing a minute alternating current through the human body. In addition, the massage chair 100 may receive body composition information from an external device or input from a user.

The stress index is information indicating whether the user's stress is severe or not. The massage chair 100 may perform a questionnaire survey to the user, measure a heart rate and select a stress index corresponding to the heart rate, or measure the stress index by collecting a small amount of blood. In addition, the massage chair 100 may receive a stress index from an external device or input from a user.

Sleep information includes information on various events that occur during the user's sleep. The massage chair 100 may determine the amount and quality of sleep based on sleep information. For example, the sleep information may include information on a sleep time, an elevation time, a wake-up time, a degree of turning during sleep, or a snoring time.

The massage chair 100 may obtain sleep information from the user when the user sleeps in the massage chair 100. For example, the massage chair 100 may obtain information on the sleeping time while the user receives a massage. In addition, the massage chair 100 may obtain information on whether the user snored while sleeping and information on the snoring time, using a microphone built in the massage chair 100. In addition, the massage chair 100 may acquire an electrocardiogram signal of the user using a sensor, and obtain whether the user is sleeping, an elevation time, a wake-up time, a REM sleep time, a shallow sleep time, and a wake-up time during sleep. In addition, the massage chair 100 may calculate sleep efficiency. In addition, the massage chair 100 may measure the amount of time the user turns while sleeping by using a sensor. The massage chair 100 may analyze the user's sleep information and provide information for improving the user's sleep efficiency. However, the present invention is not limited thereto, and the massage chair 100 may receive sleep information from an external device or may receive sleep information input from a user.

The electrocardiogram information is information showing an action current and action potential difference according to the contraction of the heart. ECG information can be represented by several ECG curves, usually using an ECG system. The massage chair 100 may acquire electrocardiogram information from a user's body using a sensor. However, the present invention is not limited thereto, and the massage chair 100 may receive ECG information from an external device or may receive sleep information from a user.

In addition to the information described above, the massage chair 100 may receive from an external device such as a blood color value, an electrolyte level, and a urine protein level. In addition, the massage chair 100 may acquire heart rate information. The massage chair 100 may acquire heart rate information from a user's body or may receive heart rate information from an external device. The heart rate information may be displayed as a waveform according to the time of the heart rate. The heart rate information may include information on whether the heart rate is regular.

The massage chair 100 may store the acquired medical data in the memory 120. The massage chair 100 may associate medical data with the identified user information.

The massage chair 100 may receive medical data from an external device by wire or wirelessly. To this end, the massage chair 100 may transmit medical data request information together with the identified user information to an external device. External devices can check whether the identified user information is authentic or not. When the identified user information is true user information, the external device may obtain medical data from the database of the external device based on the user information. The external device may transmit the acquired medical data to the massage chair 100. The massage chair 100 and an external device can protect personal information by allowing only true users to check their own medical data.

The massage chair 100 may acquire medical data using sensors included in the massage chair 100, but is not limited thereto. The massage chair 100 may receive medical data from an external device via wired or wireless using a communication unit. Referring to FIG. 5 to describe an external device capable of communicating with the massage chair 100.

5 is a diagram illustrating an external device capable of communicating with the massage chair 100 according to an embodiment of the present disclosure.

The external device may include a portable electronic device 310 such as an AI speaker, a tablet, or a smartphone. In addition, the external device may include a wearable device 320 such as a smart watch or a smart band. The external device may include a massage chair 330 other than the massage chair 100 currently being used by the user. The external device may include a hospital server 340. The external device may include a personal health record (PHR) server. In addition, the external device may include a cloud server 350. The external device may include a medical measuring device such as an electronic scale, a blood glucose meter, or a blood pressure meter.

Although some examples of external devices have been described in the present disclosure, it should be understood that all electronic devices capable of acquiring the user's biometric information can be included in the external devices.

The portable electronic device 310 may store user's medical data. The medical data may include information directly measured by the portable electronic device 310 or information received from other external devices.

The wearable device 320 may be a device that is in contact with a user's body. The wearable device 320 may measure the user's medical data using a sensor.

The other massage chair 330 may be a massage chair different from the massage chair 100 currently used by the user. When the user inputs user information into the massage chair 100, the massage chair 100 may determine whether there is a massage chair that the user has used in the past.

For example, the massage chair 100 may request information on the user's use of the massage chair from the server. The server may acquire information on the other massage chair 330 based on the user's usage history of the massage chair. The information on the other massage chair 330 may include information for accessing the other massage chair 330 in the network. The massage chair 100 may transmit a medical data request signal together with user information to the other massage chair 330. The other massage chair 330 may extract the user's medical data from the memory based on the user information and transmit it to the massage chair 100. The user does not need to go through a process of directly copying his or her data to the current massage chair 100. The user can cause the massage chair 100 to receive past usage details and medical data from another massage chair 330 by simply inputting user information into the massage chair 100.

The hospital server 340 may store information on a record of a user visiting a hospital and receiving treatment. The massage chair 100 may transmit a medical data request signal to the hospital server 340 together with user information. When the user information is genuine, the hospital server 340 may obtain medical data from the database based on the user information. In addition, the hospital server 340 may transmit the user's medical data to the massage chair 100.

Since the massage chair 100 may transmit medical data from the hospital server 340, it is possible to transmit not only the user's biometric information but also a diagnosis record by a medical professional. Therefore, it is possible to more accurately predict the user's state.

The hospital server 340 may include a personal health record (PHR) server. Terms similar to PHR include Electronic Medical Record (EMR) and Electronic Health Record (EHR). EMR is medical information created and utilized within a single medical institution. In addition, EHR refers to medical information that can be used by multiple medical institutions that comply with national standards for interoperability. EMR and personal medical information stored in EHR are important information that constitutes PHR. PHR refers to a paradigm shift in which each individual becomes his or her own health management subject in the existing medical institution-centered health management.

The user may agree to provide his or her PHR data to the massage chair 100. In addition, when the user provides his/her user information to the massage chair 100, the massage chair 100 may receive a personal medical record from the PHR server. When the massage chair 100 receives a personal medical record from the PHR server, the massage chair 100 can not only use diagnostic information of a medical professional, but also can use the user's past medical history comprehensively.

The cloud server 350 may refer to various types of servers that record user's medical data. The cloud server 350 may store various medical data of a user. The cloud server 350 may receive medical data from various devices and match it with user information. Also, the cloud server 350 may store matched medical data.

Referring back to FIG. 4, the massage chair 100 may perform an operation 230 of determining health improvement information based on medical data. The memory 120 of the massage chair 100 may store health improvement information corresponding to medical data. The massage chair 100 may obtain health improvement information corresponding to medical data from the memory 120. In addition, the massage chair 100 may obtain health improvement information from the server based on medical data using the communication unit.

The health improvement information may represent various pieces of information for improving the user's abnormal information. The health improvement information may include food information, exercise information, behavior information to be avoided, medicine information, information on equipment useful for maintaining health, or information on dietary supplements. For example, when the user has high blood pressure, the massage chair 100 outputs a message to the user to avoid fatty foods, to avoid salty foods, to reduce alcohol consumption, or to reduce weight as health improvement information. can do.

In addition, as health improvement information, the massage chair 100 may output a message inviting the user to periodically measure medical data. The massage chair 100 may determine whether the user's health is recovering or deteriorating by periodically tracking the user's medical data. When the massage chair 100 indicates that abnormal information of the user is deteriorating, the massage chair 100 may output a message proposing to the user to visit the hospital. The massage chair 100 may help the user to maintain health.

The health improvement information may include a massage mode. The massage mode may represent a combination of information on a massage sequence, a massage type, a massage time, a massage intensity, a massage position, a temperature of a massage chair, or a massage posture.

The massage position may refer to a body part of the user that the massage chair 100 massages. The massage chair 100 may determine a body part to be massaged based on medical data. The massage chair 100 may provide a massage to a user's body part by controlling the actuator in the corresponding part to move.

The massage type may represent a motion of the massage chair 100 tapping a user, a massaging motion, or a complex motion. The massage chair 100 may control the actuator to move based on information on the type of massage.

The massage time represents a time when the massage chair 100 provides a massage to a user. The massage chair 100 may determine a time to provide a massage to the user based on the information on the massage time.

The massage intensity represents the intensity of the massage chair 100 pressing, kneading, or tapping the user. The massage chair 100 may control the actuator to adjust the intensity of pressing, kneading, or tapping the user. The intensity of pressing, kneading, or tapping the user may vary depending on the body part.

When providing a massage to a user based on the temperature information of the massage chair of the massage chair 100, the temperature of the massage chair may be adjusted. The temperature of the massage chair 100 may vary depending on the body part. The massage chair 100 may lower or increase the temperature of the massage chair below room temperature. The massage chair 100 may cool or warm the body part of the user based on medical data.

The massage posture may represent a posture taken when the user sits in the massage chair 100 and receives a massage. The shape of the massage chair 100 may be changed by a driving unit or an actuator, and based on the shape of the massage chair, the user can be laid down, the user raised, the user's leg bent, or the user's leg extended. have.

The massage order represents the change over time in information about the massage intensity, massage position, temperature of the massage chair, or massage posture. The massage chair 100 may provide various massages according to time based on the massage order. For example, the user's leg may be intensively massaged during the first time, and the user's back may be intensively massaged during the second time.

6 is a flowchart illustrating a method of selecting a massage mode according to an embodiment of the present disclosure.

The massage chair 100 may determine health improvement information based on medical data. For example, the massage chair 100 may perform an operation 410 of obtaining a normal range corresponding to each of a plurality of pieces of information included in the medical data from the memory 120.

The massage chair 100 compares a plurality of pieces of information included in the medical data with a normal range, and obtains abnormal information based on information that is not included in the normal range among a plurality of pieces of information included in the medical data. You can do 420.

For example, the abnormal information may be obtained as a bitstream, which is a collection of bits. The length of the bitstream may be proportional to the number of information included in the medical data. When the medical data includes five such as blood pressure information, activity information, blood sugar level information, sleep information, and electrocardiogram signal information, the bitstream may include at least five bits. Also, the value of the bit may be '0' when the information is included in the normal range, and may be '1' when the information is not included in the normal range. However, the present invention is not limited thereto, and the bit value may be '1' when the information is included in the normal range, and '0' when the information is not included in the normal range.

In addition, the abnormality information may include an index of information included in the medical data and an abnormality flag. The index of information included in medical data may be expressed in a predetermined text or number. For example, the index of blood pressure information may be represented by "BP". Also, the flag value may be '0' when the information is included in the normal range, and may be '1' when the information is not included in the normal range. However, the present invention is not limited thereto, and the flag value may be '1' when the information is included in the normal range, and '0' when the information is not included in the normal range.

In addition, although it has been described above to determine whether individual data included in medical data is abnormal, it is not limited thereto. The massage chair 100 may apply various values included in medical data to a predetermined function. The massage chair 100 may compare a result value of a predetermined function with a threshold range. When the result value falls within the threshold range, the massage chair 100 may determine that the user's health status is healthy. However, when the result value is outside the threshold range, the massage chair 100 may determine that the user's health status is not healthy.

When the abnormality information indicates that the user has an abnormality, the massage chair 100 may perform an operation 430 of outputting an alarm. As already described, the massage chair 100 may include an output unit. The output unit may include an image output unit or a sound output unit. The massage chair 100 may output an alarm with light or sound. The massage chair 100 may perform step 440 of generating health improvement information based on the abnormal information. The memory 120 of the massage chair 100 may store health improvement information corresponding to abnormal information. The massage chair 100 may obtain health improvement information corresponding to the abnormal information from the memory 120. In addition, the massage chair 100 may obtain health improvement information from the server based on the abnormality information using the communication unit.

The health improvement information may represent various pieces of information for improving the user's abnormal information. The health improvement information may include food information, exercise information, behavior information to be avoided, medicine information, information on equipment useful for maintaining health, or information on dietary supplements. For example, when the user has high blood pressure, the massage chair 100 outputs a message to the user to avoid fatty foods, to avoid salty foods, to reduce alcohol consumption, or to reduce weight as health improvement information. can do.

In addition, as health improvement information, the massage chair 100 may output a message inviting the user to periodically measure medical data. The massage chair 100 may determine whether the user's health is recovering or deteriorating by periodically tracking the user's medical data. When the massage chair 100 indicates that abnormal information of the user is deteriorating, the massage chair 100 may output a message proposing to the user to visit the hospital. The massage chair 100 may help the user to maintain health.

The health improvement information may include a massage mode. For example, the activity information may indicate the number of steps the user took per day. The massage chair 100 may determine whether the number of steps of the user is greater than or equal to the threshold number of steps. The threshold number of steps may be the maximum number of steps per day recommended for the user. The massage chair 100 may determine that the user has too much activity when the user walks more than the threshold number of steps. The massage chair 100 may generate abnormal information indicating that the user has too much activity. The massage chair 100 may acquire a massage mode corresponding to the abnormal information from the memory 120. The massage mode may be a mode for intensively releasing the lumped muscles in the legs. The massage chair 100 may provide a massage to a user by moving an actuator based on the massage mode.

7 is a flowchart illustrating a method of obtaining medical data according to an embodiment of the present disclosure.

The massage chair 100 may perform a step 531 of transmitting user information to the hospital server 340. In addition, the massage chair 100 may perform an operation 532 of transmitting medical data to the hospital server 340.

The hospital server 340 may store medical data in a database in correspondence with user information. The hospital's medical professional may make a diagnosis based on the user's medical data stored in the hospital server 340. When the massage chair 100 does not transmit medical data to the hospital server 340, the medical professional is bound to make a diagnosis based on the information on the symptoms dictated by the user and the current state of the user. However, since the hospital server 340 may receive the user's past health status periodically acquired by the massage chair 100, a medical professional in the hospital can make a diagnosis based on a wider range of data.

The medical professional may input diagnosis result information for the user into the hospital server 340. The hospital server 340 may store diagnosis result information in a database corresponding to user information. The diagnosis result information may be health status information. The health status information may include the user's disease name, the user's location of the lesion, the time when the lesion was confirmed, the name of the confirmed hospital, whether the lesion is deteriorating, and a response of a medical professional to the lesion. In addition, the health status information may include a disease code of the Korean standard disease cause classification. The massage chair 100 may transmit a signal requesting health status information to the hospital server 340. The hospital server 340 may perform a step 533 of obtaining health status information corresponding to user information received from the massage chair 100. In addition, the massage chair 100 may perform an operation 534 of obtaining health status information based on user information and medical data from the hospital server 340.

The massage chair 100 may perform the step 535 of generating health improvement information based on the health state information. The memory 120 of the massage chair 100 may store health improvement information corresponding to the health state information. The massage chair 100 may obtain health improvement information corresponding to the health state information from the memory 120. In addition, the massage chair 100 may obtain health improvement information from the server based on the health state information using the communication unit. The health improvement information may include massage mode information, food information, exercise information, action information to be avoided, medicine information, information on equipment useful for maintaining health, or information on dietary supplements. In addition, the massage chair 100 may output health improvement information through an output unit.

More specifically, when the health status information indicates that there is an abnormality in the lower back, the massage chair 100 may display food that is good for the lower back, an exercise that improves the lower back, or a behavior that is not good for the lower back on the screen or output it as a sound. have. The user may view or hear health improvement information while receiving a massage in the massage chair 100. Therefore, the user can maintain health based on the information provided by the massage chair 100.

The massage chair 100 may perform a step of selecting a massage mode based on health status information. The massage chair 100 may provide a user with a massage mode reflecting the opinion of a medical professional based on health status information.

More specifically, when the health status information indicates that the user's waist is bad, the massage chair 100 may select a massage mode for massaging the user's waist.

In addition, the massage chair 100 may perform an operation of acquiring an abnormal part of the user's body part based on the health state information. The massage chair 100 may store in the memory 120 a table corresponding to the health state information and the abnormal part of the user. The massage chair 100 may acquire an abnormal part of the user's body part based on the health state information and the table.

The massage chair 100 may perform a step of adjusting the temperature of a portion of the massage chair corresponding to the abnormal portion based on health status information. When the health status information indicates that the user's body part is inflamed, the massage chair 100 may lower the temperature of the part corresponding to the body part to provide a cold compress to the user. In addition, when the health status information indicates that the user's body part has muscle pain, the massage chair 100 may increase the temperature of the part corresponding to the body part to provide a warm compress to the user's body part.

In addition, the massage chair 100 may select a massage mode based on the abnormal portion. For example, based on health status information, if it is determined that the user may feel pain when pressure is applied to an abnormal area, the massage chair 100 only adjusts the temperature of the corresponding area, and the corresponding body part is fixed so that it cannot move. Or you can gently massage the body part. In addition, the massage chair 100 may select a massage mode to improve the abnormal area. Specifically, when the health status information indicates a headache, the massage chair 100 may select a massage mode for improving the headache. The massage chair 100 may store information on a massage mode according to an abnormal body part in a memory.

However, it is not limited thereto. The massage chair 100 may perform the step of selecting a massage mode based on health status information without acquiring an abnormal part. The massage chair 100 may store information on a massage mode according to health status information in a memory. When the health state information is determined, the massage chair 100 may select a massage mode corresponding to the health state information. Since massage is provided to the user based on health status information, the massage chair 100 has an effect of alleviating the user's disease.

8 is a diagram illustrating machine learning of a massage chair according to an embodiment of the present disclosure.

Referring to FIG. 8, the massage chair 100 according to an embodiment may include at least one of a data learning unit 610 and a data recognition unit 620. As described above, the massage chair 100 may include a processor and a memory, and the data learning unit 610 or the data recognition unit 620 may be implemented by the processor 110 and the memory 120. In addition, the data learning unit 610 or the data recognition unit 620 may be implemented by a processor and memory designed for machine learning.

The data learning unit 610 may learn a machine learning model for performing a target task using the data set. The data learning unit 610 may receive label information related to a data set and a target task. The data learning unit 610 may acquire a machine learning model by performing machine learning on the relationship between the data set and the label information. The machine learning model acquired by the data learning unit 610 may be a model for generating label information using a data set.

The data recognition unit 620 may receive and store the machine learning model of the data learning unit 610. The data recognition unit 620 may output label information by applying a machine learning model to input data. In addition, the data recognition unit 620 may use input data, label information, and results output by the machine learning model to update the machine learning model.

At least one of the data learning unit 610 and the data recognition unit 620 may be manufactured in the form of at least one hardware chip and mounted on an electronic device. For example, at least one of the data learning unit 610 and the data recognition unit 620 may be manufactured in the form of a dedicated hardware chip for artificial intelligence (AI), or an existing general-purpose processor (eg, a CPU Alternatively, it may be manufactured as a part of an application processor) or a graphics dedicated processor (eg, a GPU) and mounted on various electronic devices previously described.

In addition, the data learning unit 610 and the data recognition unit 620 may be mounted on separate electronic devices, respectively. For example, one of the data learning unit 610 and the data recognition unit 620 may be included in the electronic device, and the other may be included in the server. In addition, the data learning unit 610 and the data recognition unit 620 may provide the machine learning model information built by the data learning unit 610 to the data recognition unit 620 through wired or wireless communication, or to recognize data. Data input to the unit 620 may be provided to the data learning unit 610 as additional learning data.

Meanwhile, at least one of the data learning unit 610 and the data recognition unit 620 may be implemented as a software module. When at least one of the data learning unit 610 and the data recognition unit 620 is implemented as a software module (or a program module including an instruction), the software module is a memory or a computer-readable ratio. It may be stored in a non-transitory computer readable media. Also, in this case, at least one software module may be provided by an operating system (OS) or may be provided by a predetermined application. Alternatively, some of the at least one software module may be provided by an operating system (OS), and the remaining part may be provided by a predetermined application.

The data learning unit 610 according to an embodiment of the present disclosure includes a data acquisition unit 611, a preprocessor 612, a training data selection unit 613, a model learning unit 614, and a model evaluation unit 615. Can include.

The data acquisition unit 611 may acquire data necessary for machine learning. Since a lot of data is required for learning, the data acquisition unit 611 may receive a data set including a plurality of data.

Label information may be assigned to each of a plurality of data. The label information may be information describing each of a plurality of pieces of data. The label information may be information to be derived by a target task. The label information may be obtained from a user input, a memory, or a result of a machine learning model. For example, if the target task is to predict health status information from medical data, the plurality of data will be a plurality of medical data, and the label information will be health status information corresponding to each of the plurality of medical data.

The preprocessor 612 may preprocess the acquired data so that the received data can be used for machine learning. The preprocessor 612 may process the acquired data set into a preset format so that the model learning unit 614 to be described later can use it.

The learning data selection unit 613 may select data necessary for learning from among the preprocessed data. The selected data may be provided to the model learning unit 614. The learning data selection unit 613 may select data necessary for learning from among preprocessed data according to a preset criterion. In addition, the learning data selection unit 613 may select data according to a preset criterion by learning by the model learning unit 614 to be described later.

The model learning unit 614 may learn a criterion regarding which label information is to be output based on the data set. Also, the model learning unit 614 may perform machine learning by using the data set and label information on the data set as training data. In addition, the model learning unit 614 may perform machine learning by additionally using the previously acquired machine learning model. In this case, the previously acquired machine learning model may be a pre-built model. For example, the machine learning model may be a model built in advance by receiving basic training data.

The machine learning model may be constructed in consideration of the application field of the learning model, the purpose of learning, or the computer performance of the device. The machine learning model may be, for example, a model based on a neural network. For example, models such as Deep Neural Network (DNN), Recurrent Neural Network (RNN), Long Short-Term Memory models (LSTM), BRDNN (Bidirectional Recurrent Deep Neural Network), and Convolutional Neural Networks (CNN) are used as machine learning models. However, it is not limited thereto.

According to various embodiments, when a plurality of pre-built machine learning models exist, the model learning unit 614 may determine a machine learning model having a high correlation between the input learning data and the basic learning data as a machine learning model to be trained. have. In this case, the basic learning data may be pre-classified by data type, and the machine learning model may be pre-built for each data type. For example, the basic training data may be pre-classified according to various criteria such as a place where the training data is generated, a time when the training data is generated, a size of the training data, a creator of the training data, and a type of an object in the training data.

In addition, the model learning unit 614 may train the machine learning model using, for example, a learning algorithm including error back-propagation or gradient descent.

In addition, the model learning unit 614 may learn the machine learning model through supervised learning using, for example, training data as an input value. In addition, the model learning unit 614, for example, by self-learning the type of data required for the target task without any guidance, unsupervised learning (unsupervised learning) to discover the criteria for the target task. Through this, a machine learning model can be obtained. In addition, the model learning unit 614 may learn the machine learning model through reinforcement learning using feedback on whether the result of the target task according to the learning is correct, for example.

In addition, when the machine learning model is trained, the model learning unit 614 may store the learned machine learning model. In this case, the model learning unit 614 may store the learned machine learning model in a memory of the electronic device including the data recognition unit 620. Alternatively, the model learning unit 614 may store the learned machine learning model in a memory of a server connected to the electronic device through a wired or wireless network.

The memory in which the learned machine learning model is stored may also store commands or data related to at least one other component of the electronic device, for example. In addition, the memory may store software and/or programs. The program may include, for example, a kernel, middleware, an application programming interface (API) and/or an application program (or "application").

The model evaluation unit 615 may input evaluation data to the machine learning model and, when a result output from the evaluation data does not satisfy a predetermined criterion, may cause the model learning unit 614 to learn again. In this case, the evaluation data may be preset data for evaluating the machine learning model.

For example, the model evaluation unit 615 does not satisfy a predetermined criterion when the number or ratio of evaluation data whose recognition result is not accurate among the results of the machine learning model learned on the evaluation data exceeds a preset threshold. It can be evaluated as For example, when a predetermined criterion is defined as a ratio of 2%, when the learned machine learning model outputs incorrect recognition results for more than 20 evaluation data out of a total of 1000 evaluation data, the model evaluation unit 615 learns. It can be evaluated that the machine learning model is not suitable.

On the other hand, when there are a plurality of learned machine learning models, the model evaluation unit 615 evaluates whether each learned machine learning model satisfies a predetermined criterion, and determines the model that satisfies the predetermined criterion as the final machine learning model. You can decide. In this case, when there are a plurality of models that satisfy a predetermined criterion, the model evaluation unit 615 may determine any one or a predetermined number of models previously set in the order of the highest evaluation scores as the final machine learning model.

Meanwhile, at least one of the data acquisition unit 611, the preprocessor 612, the training data selection unit 613, the model learning unit 614, and the model evaluation unit 615 in the data learning unit 610 is at least one It can be manufactured in the form of a hardware chip and mounted on an electronic device. For example, at least one of the data acquisition unit 611, the preprocessor 612, the training data selection unit 613, the model learning unit 614, and the model evaluation unit 615 is artificial intelligence (AI). It may be manufactured in the form of a dedicated hardware chip, or may be manufactured as a part of an existing general-purpose processor (eg, CPU or application processor) or a graphics dedicated processor (eg, GPU) and mounted on the aforementioned various electronic devices.

In addition, the data acquisition unit 611, the preprocessor 612, the training data selection unit 613, the model learning unit 614, and the model evaluation unit 615 may be mounted on one electronic device, or separate Each of the electronic devices may be mounted. For example, some of the data acquisition unit 611, the preprocessing unit 612, the training data selection unit 613, the model learning unit 614, and the model evaluation unit 615 are included in the electronic device, and the rest are Can be included in the server.

In addition, at least one of the data acquisition unit 611, the preprocessor 612, the training data selection unit 613, the model learning unit 614, and the model evaluation unit 615 may be implemented as a software module. At least one of the data acquisition unit 611, the preprocessor 612, the training data selection unit 613, the model learning unit 614, and the model evaluation unit 615 is a software module (or a program including an instruction) Module), the software module may be stored in a computer-readable non-transitory computer readable media. Also, in this case, at least one software module may be provided by an operating system (OS) or may be provided by a predetermined application. Alternatively, some of the at least one software module may be provided by an operating system (OS), and the remaining part may be provided by a predetermined application.

The data recognition unit 620 according to an embodiment of the present disclosure includes a data acquisition unit 621, a preprocessor 622, a recognition data selection unit 623, a recognition result providing unit 624, and a model update unit 625. It may include.

The data acquisition unit 621 may receive input data. The preprocessor 622 may preprocess the acquired input data so that the acquired input data can be used by the recognition data selection unit 623 or the recognition result providing unit 624.

The recognition data selection unit 623 may select necessary data from the preprocessed data. The selected data may be provided to the recognition result providing unit 624. The recognition data selection unit 623 may select some or all of the preprocessed data according to a preset criterion. In addition, the recognition data selection unit 623 may select data according to a preset criterion by learning by the model learning unit 614.

The recognition result providing unit 624 may obtain result data by applying the selected data to the machine learning model. The machine learning model may be a machine learning model generated by the model learning unit 614. The recognition result providing unit 624 may output result data.

The model update unit 625 may update the machine learning model based on an evaluation of the recognition result provided by the recognition result providing unit 624. For example, the model update unit 625 provides the recognition result provided by the recognition result providing unit 624 to the model learning unit 614, so that the model learning unit 614 can update the machine learning model. have.

Meanwhile, at least one of the data acquisition unit 621, the preprocessor 622, the recognition data selection unit 623, the recognition result providing unit 624, and the model update unit 625 in the data recognition unit 620 is at least It can be manufactured in the form of a single hardware chip and mounted on an electronic device. For example, at least one of the data acquisition unit 621, the preprocessor 622, the recognition data selection unit 623, the recognition result providing unit 624, and the model update unit 625 is artificial intelligence (AI). ) May be manufactured in the form of a dedicated hardware chip, or may be manufactured as a part of an existing general-purpose processor (eg, a CPU or application processor) or a graphics dedicated processor (eg, a GPU) and mounted on the aforementioned various electronic devices.

In addition, the data acquisition unit 621, the preprocessing unit 622, the recognition data selection unit 623, the recognition result providing unit 624 and the model update unit 625 may be mounted on one electronic device, or separately It may be mounted on each of the electronic devices. For example, some of the data acquisition unit 621, the preprocessor 622, the recognition data selection unit 623, the recognition result providing unit 624, and the model update unit 625 are included in the electronic device, and the rest Can be included in the server.

In addition, at least one of the data acquisition unit 621, the preprocessor 622, the recognition data selection unit 623, the recognition result providing unit 624, and the model update unit 625 may be implemented as a software module. At least one of the data acquisition unit 621, the preprocessor 622, the recognition data selection unit 623, the recognition result providing unit 624, and the model update unit 625 includes a software module (or instruction). Program module), the software module may be stored in a computer-readable non-transitory computer readable media. Also, in this case, at least one software module may be provided by an operating system (OS) or may be provided by a predetermined application. Alternatively, some of the at least one software module may be provided by an operating system (OS), and the remaining part may be provided by a predetermined application.

9 is a diagram illustrating a data learning unit 610 and a massage chair 100 according to an embodiment of the present disclosure. 10 is a flowchart illustrating the operation of the massage chair according to an embodiment of the present disclosure.

Referring to FIG. 9, the data learning unit 610 may be included in the massage chair 100. In addition, the data learning unit 610 may be a separate device outside the massage chair 100.

The data learning unit 610 may receive the health state information 710 and the past medical data 720 before the health state information 710 is generated. The health status information 710 may be information input by a medical professional to a hospital server after determining by looking at a patient's status. In addition, the past medical data 720 may be medical data of a patient generated before the medical professional determines the health status information 710. Past medical data may include blood pressure information, activity information, blood sugar level information, sleep information, electrocardiogram signal information, heart rate information, blood test information, or bacterial culture test information. In addition, past medical data may include a personal health record (PHR). The data learning unit 610 may receive consent for collecting a plurality of personal health records from a plurality of users.

The data learning unit 610 may generate the first machine learning model 730 by machine learning the correlation between the health state information 710 and the past medical data 720. The data learning unit 610 may transmit the first machine learning model 730 to the massage chair 100.

The massage chair 100 may perform a step 810 of acquiring a first machine learning model obtained by machine learning the correlation between the health state information 710 and the past medical data 720 before the health state information is generated. have. The machine learning model may be stored in the memory 120 of the massage chair 100.

The massage chair 100 may perform an operation 820 of determining predicted health status information 750 by applying the acquired medical data to the first machine learning model. The acquired medical data may be current medical data 740 for the current user. At least part of the current medical data 740 and the past medical data 720 may overlap, but are not the same. In addition, the current medical data 740 may include medical data after the health status information 710 is generated by a medical professional. In addition, the current medical data 740 may include a personal health record (PHR). In order to obtain the personal health record, the massage chair 100 may receive the user's consent for collecting the personal health record from the user.

For example, the massage chair 100 may periodically acquire ECG signal information of a user as medical data. The massage chair 100 may apply periodically accumulated user's ECG signal information to the first machine learning model. The first machine learning model may be a machine learning model for predicting heart abnormalities based on electrocardiogram information. The massage chair 100 may predict heart abnormalities using the first machine learning model. In addition, the massage chair 100 may acquire a probability of occurrence of an abnormality in the heart by using the first machine learning model. The massage chair 100 may determine health state information corresponding to the predicted heart abnormality.

In the above, the massage chair 100 has disclosed an embodiment in which a heart abnormality is detected by relying on machine learning, but is not limited thereto. The massage chair 100 may detect an irregular rhythm from accumulated user's electrocardiogram information or heart rate information, and predict a user's heart abnormality without a first machine learning model.

The massage chair 100 may perform an operation 830 of outputting the predicted health state information 750. The massage chair 100 may output the predicted health status information 750 as an image or sound based on an image output unit or a sound output unit.

The massage chair 100 may perform the step of generating health improvement information based on the predicted health state information. The memory 120 of the massage chair 100 may store health improvement information corresponding to the predicted health state information. The massage chair 100 may obtain health improvement information corresponding to the predicted health state information from the memory 120. In addition, the massage chair 100 may obtain health improvement information from the server based on the predicted health state information using the communication unit.

As described above, the health improvement information may represent various pieces of information for improving the user's abnormal information. The health improvement information may include food information, exercise information, behavior information to be avoided, medicine information, information on equipment useful for maintaining health, or information on dietary supplements. In addition, the massage chair 100 may output health improvement information through an output unit. For example, when the user has high blood pressure, the massage chair 100 outputs a message to the user to avoid fatty foods, to avoid salty foods, to reduce alcohol consumption, or to reduce weight as health improvement information. can do.

In addition, as health improvement information, the massage chair 100 may output a message inviting the user to periodically measure medical data. The massage chair 100 may determine whether the user's health is recovering or deteriorating by periodically tracking the user's medical data. When the massage chair 100 indicates that abnormal information of the user is deteriorating, the massage chair 100 may output a message proposing to the user to visit the hospital. The massage chair 100 may help the user to maintain health.

In addition, when the predicted health status information 750 indicates that there is an abnormality in the lower back, the massage chair 100 displays food that is good for the lower back, an exercise that improves the lower back, or an action that is bad for the lower back on the screen or outputs it as a sound. can do. The user can view or hear treatment information while receiving a massage in the massage chair 100. Therefore, the user can maintain health based on the information provided by the massage chair 100.

The health improvement information may include a massage mode. The massage chair 100 may perform an operation 840 of acquiring an abnormal part of the user's body part in the predicted health state information. The massage chair 100 may store, in the memory 120, a table corresponding to the predicted health status information and an abnormal part of the user. The massage chair 100 may acquire an abnormal part of the user's body part based on the predicted health state information and the table.

The massage chair 100 may perform step 850 of selecting a massage mode based on the abnormal part. For example, if it is determined that the user may feel pain when pressure is applied to an abnormal area based on the predicted health status information 750, the massage chair 100 may fix the corresponding body part so that it cannot move or fix the corresponding body part. I can massage weakly.

In addition, the massage chair 100 may select a massage mode to improve the abnormal area. Specifically, when the predicted health status information 750 indicates a headache, the massage chair 100 may select a massage mode for improving the headache. The massage chair 100 may store information on a massage mode according to an abnormal body part in a memory.

However, it is not limited thereto. The massage chair 100 may perform an operation of selecting a massage mode based on the predicted health status information 750 without acquiring an abnormal part. The massage chair 100 may store information on a massage mode according to the predicted health state information 750 in a memory. When the predicted health state information 750 is determined, the massage chair 100 may select a massage mode corresponding to the predicted health state information 750. Since the massage is provided to the user based on the predicted health status information, the massage chair 100 has an effect of alleviating the user's disease.

11 is a diagram illustrating a data learning unit 610 and a massage chair 100 according to an embodiment of the present disclosure. 12 is a flowchart illustrating an operation of a massage chair according to an embodiment of the present disclosure.

The data learning unit 610 may receive massage mode information 911 selected by the user, past medical data 912, and user satisfaction information 913. The massage chair 100 may collect massage mode information 911 selected by the user and user satisfaction information 913. The user's satisfaction level information may be information indicating the level of satisfaction with the massage after the user receives the massage. The massage chair 100 may transmit the massage mode information 911 selected by the user and the user satisfaction information 913 to the data learning unit 610. However, it is not limited thereto. The data learning unit 610 may receive not the massage mode information 911 selected by the user, but the automatically selected massage mode information and the user's satisfaction level after the massage.

The past medical data 912 may be medical data collected before the user selects the massage mode. In addition, the past medical data 912 may be medical data collected before the massage chair 100 selects a massage mode. Past medical data may include blood pressure information, activity information, blood sugar level information, sleep information, electrocardiogram signal information, heart rate information, blood test information, or bacterial culture test information. In addition, past medical data may include a personal health record (PHR). The data learning unit 610 may receive consent for collecting a plurality of personal health records from a plurality of users.

The data learning unit 610 may generate a second machine learning model 930 by machine learning the massage mode information 911 selected by the user, past medical data 912, and user satisfaction information 913. Specifically, the second machine learning model 930 includes information on the user's satisfaction with the massage mode selected by the user in the past with respect to the massage mode selected by the user in the past and the medical data before the user selected the massage mode It may be machine learning of the correlation. The data learning unit 610 may transmit the second machine learning model to the massage chair 100.

The massage chair 100 may perform a step 1010 of acquiring a second machine learning model subjected to machine learning. The second machine learning model 930 correlates the user's satisfaction information with the massage mode selected by the user in the past with respect to the massage mode selected by the user in the past and the medical data before the user selected the massage mode in the past. Can be indicated.

The massage chair 100 applies the medical data 942 and the plurality of massage modes 941 to the second machine learning model 930 to determine the predicted satisfaction 950 of the user for each of the plurality of massage modes 941. The generating step 1020 may be performed. The medical data may be current medical data 942 for the current user. At least part of the current medical data 942 and the past medical data 912 may overlap, but are not the same. In addition, the current medical data 942 may include medical data after the massage chair 100 receives the user satisfaction information 913. In addition, the current medical data 942 may include a personal health record (PHR). In order to obtain the personal health record, the massage chair 100 may receive the user's consent for collecting the personal health record from the user.

The massage chair 100 may perform an operation 1030 of selecting a massage mode having the highest satisfaction among prediction satisfaction 950 for each of the plurality of massage modes. Since the massage chair 100 provides the user with a massage mode that is predicted to have high user satisfaction, the user's satisfaction with the massage chair 100 can be increased.

So far, we have looked at various embodiments mainly. Those of ordinary skill in the art to which the present invention pertains will be able to understand that the present invention may be implemented in a modified form without departing from the essential characteristics of the present invention. Therefore, the disclosed embodiments should be considered from an illustrative point of view rather than a limiting point of view. The scope of the present invention is shown in the claims rather than the above description, and all differences within the scope equivalent thereto should be construed as being included in the present invention.

Meanwhile, the above-described embodiments of the present invention can be written as a program that can be executed on a computer, and can be implemented in a general-purpose digital computer that operates the program using a computer-readable recording medium. The computer-readable recording medium includes storage media such as magnetic storage media (eg, ROM, floppy disk, hard disk, etc.) and optical reading media (eg, CD-ROM, DVD, etc.).

Claims (12)

In the operating method of the massage chair including a processor and a memory,
Identifying user information;
Obtaining medical data including at least one of blood pressure information, activity information, blood sugar level information, body composition information, weight information, stress index, sleep information, and electrocardiogram signal information corresponding to the identified user information; And
And determining health improvement information based on the medical data.
The method of claim 1,
The step of determining the health improvement information,
Obtaining a normal range corresponding to each of a plurality of pieces of information included in the medical data from the memory;
Comparing a plurality of pieces of information included in the medical data with the normal range, and obtaining abnormal information based on information not included in the normal range among a plurality of pieces of information included in the medical data;
Outputting an alarm when the abnormality information indicates that there is an abnormality to the user; And
And generating health improvement information based on the abnormal information.
The method of claim 1,
Obtaining the medical data,
Transmitting the user information to a hospital server;
Transmitting the medical data to the hospital server; And
Including the step of obtaining health status information based on the user information and the medical data from the hospital server,
The step of determining the health improvement information,
And determining health improvement information based on the health state information.
The method of claim 3,
The step of determining the health improvement information,
Acquiring an abnormal part of the body part of the user based on the health state information;
Adjusting a temperature of a portion of the massage chair corresponding to the abnormal portion based on the health state information; And
And selecting a massage mode based on the abnormal portion.
The method of claim 1,
The step of determining the health improvement information,
Obtaining a first machine learning model obtained by machine learning a correlation between health status information and past medical data before the health status information is generated;
Determining predicted health status information by applying the obtained medical data to the first machine learning model;
Outputting the predicted health status information;
Generating health improvement information based on the predicted health state information,
The method of operating a massage chair, characterized in that the past medical data and the acquired medical data include a personal health record (PHR).
The method of claim 1,
The step of determining the health improvement information,
A second machine learning model in which the correlation between the user's satisfaction information on the massage mode selected by the user in the past with respect to the massage mode selected by the user in the past and the medical data before the user selected the massage mode in the past Obtaining a;
Applying the medical data and a plurality of massage modes to the second machine learning model to generate a predicted satisfaction level of a user for each of the plurality of massage modes; And
And selecting a massage mode having a highest satisfaction level among prediction satisfaction levels for each of the plurality of massage modes.
The massage chair includes a processor and memory,
The processor is based on the instruction stored in the memory
Identifying user information;
Obtaining medical data including at least one of blood pressure information, activity information, blood sugar level information, body composition information, weight information, stress index, sleep information, and electrocardiogram signal information corresponding to the identified user information; And
And determining health improvement information based on the medical data.
The method of claim 7,
The processor based on the instruction stored in the memory,
Obtaining a normal range corresponding to each of a plurality of pieces of information included in the medical data from the memory;
Comparing a plurality of pieces of information included in the medical data with the normal range, and obtaining abnormal information based on information not included in the normal range among a plurality of pieces of information included in the medical data;
Outputting an alarm when the abnormality information indicates that there is an abnormality to the user; And
A massage chair, characterized in that performing the step of selecting a massage mode based on the abnormal information.
The method of claim 7,
The processor based on the instruction stored in the memory,
Transmitting the user information to a hospital server;
Transmitting the medical data to the hospital server;
Obtaining health status information based on the user information and the medical data from the hospital server; And
A massage chair, characterized in that performing the step of determining health improvement information based on the health state information.
The method of claim 9,
The processor based on the instruction stored in the memory,
Acquiring an abnormal part of the body part of the user based on the health state information;
Adjusting a temperature of a portion of the massage chair corresponding to the abnormal portion based on the health state information; And
A massage chair, characterized in that performing the step of selecting a massage mode based on the abnormal portion.
The method of claim 7,
The processor based on the instruction stored in the memory,
Obtaining a first machine learning model obtained by machine learning a correlation between health status information and past medical data before the health status information is generated;
Determining predicted health status information by applying the obtained medical data to the first machine learning model;
Outputting the predicted health status information; And
Performing the step of generating health improvement information based on the predicted health state information,
The massage chair, characterized in that the past medical data and the acquired medical data include a personal health record (PHR).
The method of claim 7,
The processor based on the instruction stored in the memory,
A second machine learning model in which the correlation between the user's satisfaction information on the massage mode selected by the user in the past with respect to the massage mode selected by the user in the past and the medical data before the user selected the massage mode in the past Obtaining a;
Applying the medical data and a plurality of massage modes to the second machine learning model to generate a predicted satisfaction level of a user for each of the plurality of massage modes; And
And selecting a massage mode having the highest satisfaction among prediction satisfaction levels for each of the plurality of massage modes.

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