Low-frequency wave generation apparatus using muscle characteristic information

Abstract

The present invention relates to a low-frequency wave generation apparatus using muscle characteristic information. According to the present invention, the low-frequency wave generation apparatus includes: an input unit for receiving at least one piece of personal information among gender, age, body, and clinical information about a user and a part attached to a measurement module; a communication unit for receiving muscle characteristic information about a part measured by the measurement module attached to a part of the user's body; a training unit for training a low-frequency wave information model to derive low-frequency wave feature information using the plurality of pieces of personal information, the part attached to the measurement module, and the muscle characteristic information; a low-frequency wave generation unit for generating low-frequency waves by applying the personal information about the user, the attached part, and the muscle characteristic information about the measured part to the pre-trained low-frequency wave information model; and an irradiation unit for irradiating a part of the body of the user with the generated low-frequency waves.

Description

Low-frequency generation device using muscle characteristic information

[0001] The present invention relates to a low-frequency generation device using muscle characteristic information, and more specifically, to a low-frequency generation device using muscle characteristic information that receives muscle characteristic information by irradiating ultrasound to a part of a user's body, and generates and applies a low-frequency by considering the user's muscle characteristic information.

[0002] Electrical muscle stimulation (EMS) is a method of artificially inducing muscle contraction through electrical signals. It is used to aid recovery in patients who cannot move parts of the body or the whole body, to prevent secondary symptoms that may occur after exercise, and for muscle or nerve testing.

[0003] Using this type of electrical muscle stimulation therapy, hospitals are assisting patients' recovery through low-frequency stimulators.

[0004] However, low-frequency stimulators have limitations in that the intensity felt by each patient varies depending on the area and information about the user's muscles is not taken into account.

[0005] The technology underlying the present invention is disclosed in Korean Patent Publication No. 10-2012-0099925 (published on September 12, 2012).

[0006] Thus, according to the present invention, there is provided a low-frequency generating device using muscle characteristic information, which receives muscle characteristic information by irradiating ultrasound to a part of a user's body, and generates and applies low-frequency by considering the user's muscle characteristic information.

[0007] According to an embodiment of the present invention for achieving such a technical task, a low-frequency generation device using muscle characteristic information comprises: an input unit for receiving at least one personal information among a user's gender, age, body, and clinical information and an attachment site of a measurement module; a communication unit for receiving muscle characteristic information of a site measured by a measurement module attached to a body site of the user; a learning unit for learning a low-frequency information model to derive low-frequency feature information using a plurality of pieces of personal information, the attachment site of the measurement module, and the muscle characteristic information; a low-frequency generation unit for applying the user's personal information, the attachment site, and the muscle characteristic information of the measured site to a previously learned low-frequency information model to generate a low-frequency; and an irradiation unit for irradiating the generated low-frequency to a body site of the user.

[0008] The above muscle characteristic information may include at least one of the muscle thickness of the attachment site, the fat thickness of the muscle of the attachment site, and the quality of the muscle of the attachment site.

[0009] The above low-frequency characteristic information may include at least one of a low-frequency frequency, a low-frequency intensity, and a low-frequency waveform determined based on the user's personal information, attachment site, and muscle characteristic information.

[0010] The above measurement module can measure muscle characteristic information by using ultrasound to investigate a part of a user's body, receiving a plurality of reflected sounds, filtering the received reflected sounds and removing a contact-reflection signal to implement a reflected signal, and extracting at least one peak from the reflected signal.

[0011] The above low-frequency information model can set at least one of the low-frequency frequency, low-frequency intensity, and low-frequency waveform according to the user's personal information, attachment site, and muscle characteristic information of the measured muscle characteristic device.

[0012] The low-frequency generating unit may generate a low-frequency of the first mode when the ratio of the fat thickness and the muscle thickness of the muscle is lower than or equal to a first reference value or the quality of the muscle is higher than or equal to a first ratio, generate a low-frequency of the second mode when the ratio of the fat thickness and the muscle thickness of the muscle is higher than or equal to a first reference value and lower than or equal to a second reference value or the quality of the muscle is lower than the first ratio and higher than or equal to the second ratio, generate a low-frequency of the third mode when the ratio of the fat thickness and the muscle thickness of the muscle is higher than or equal to a second reference value or the quality of the muscle is lower than the second ratio and higher than or equal to the third ratio, and generate a low-frequency of the fourth mode when the ratio of the fat thickness and the muscle thickness of the muscle is higher than or equal to a third reference value or the quality of the muscle is lower than the third ratio.

[0013] The above first to fourth modes can be set by combining two or more of concentrated tapping, wave tapping, soft tapping, concentrated kneading, wave kneading, and soft kneading, each of which has a different low-frequency intensity, strength, and frequency set according to the muscle characteristic information.

[0014] In this way, according to the present invention, the optimal low frequency can be applied to the user by generating the low frequency while considering the user's personal information, muscle thickness, muscle fat thickness, and muscle quality.

[0015] Figure 1 is a configuration diagram of a low-frequency generation device using muscle characteristic information according to one embodiment of the present invention.

[0016] FIG. 2 is a diagram illustrating an example of generating a low frequency according to one embodiment of the present invention.

[0017] FIG. 3 is an exemplary diagram illustrating an example of measuring muscle characteristic information of a part of a user's body and investigating low frequencies according to one embodiment of the present invention.

[0018] Below, with reference to the attached drawings, embodiments of the present invention are described in detail so that those skilled in the art can easily implement them. However, the present invention may be implemented in various different forms and is not limited to the embodiments described herein. In addition, in the drawings, parts irrelevant to the description are omitted for clarity of description, and similar parts are designated with similar reference numerals throughout the specification.

[0019] Throughout the specification, whenever a part is said to "include" a component, this does not mean that it excludes other components, but rather that it may include other components, unless otherwise stated.

[0020] With reference to the attached drawings, an embodiment of the present invention is described in detail so that a person having ordinary skill in the art to which the present invention pertains can easily practice the present invention.

[0021] In the embodiment described below, a low-frequency generation device (100) using muscle characteristic information is specifically described as being connected to a measurement module (200) via wire or wirelessly. However, the present invention is not limited thereto.

[0022] Figure 1 is a configuration diagram of a low-frequency generation device using muscle characteristic information according to one embodiment of the present invention.

[0023] As illustrated in FIG. 1, a low-frequency generation device (100) using muscle characteristic information according to one embodiment of the present invention includes an input unit (110), a communication unit (120), a learning unit (130), a low-frequency generation unit (140), and an investigation unit (150).

[0024] First, the input unit (110) receives at least one piece of personal information from among the user's gender, age, body, and clinical information, and the attachment site of the measurement module (200). Here, the body is personal information including the user's height and weight, and the clinical information may include the user's medical history, pain site, etc.

[0025] Next, the communication unit (120) receives muscle characteristic information of a part measured by a measurement module (200) attached to a part of the user's body. Here, the muscle characteristic information includes at least one of the muscle thickness of the attachment part, the fat thickness of the muscle of the attachment part, and the quality of the muscle of the attachment part.

[0026] Here, the measurement module (200) uses ultrasound to investigate a part of the user's body, receives a plurality of reflected sounds, filters the received reflected sounds, removes a contact-reflection signal to implement a reflected signal, and extracts at least one peak from the reflected signal to measure muscle characteristic information. At this time, the peak is a case where the intensity of the reflected sound at a specific point in time is relatively greater than the intensity of the reflected sound at surrounding points in time, and the intensity of the reflected sound is directly proportional to the impedance difference of the material through which the ultrasound passes, and the impedance difference between the materials that make up the body is greatest at the boundary between muscle and fat. Using this, the measurement module (200) can identify the boundary between muscle and fat and measure muscle characteristic information including at least one of the thickness of the muscle at the attachment site, the thickness of the fat of the muscle at the attachment site, and the quality of the muscle at the attachment site.

[0027] Next, the learning unit (130) can train a low-frequency information model to derive low-frequency feature information using a plurality of pieces of personal information, the attachment site of the measurement module, and muscle characteristic information. At this time, the low-frequency feature information includes at least one of a low-frequency frequency, a low-frequency intensity, and a low-frequency waveform determined based on the user's personal information, the attachment site, and the muscle characteristic information.

[0028] Specifically, the learning unit (130) can train a low-frequency information model to derive optimized low-frequency feature information using a learning data set that matches a plurality of pieces of personal information, an attachment site of a measurement module, and muscle characteristic information, respectively.

[0029] Next, the low-frequency generation unit (140) applies the user's personal information, attachment site, and muscle characteristic information of the measured site to a pre-learned low-frequency information model to generate low-frequency signals. At this time, the attachment site and the measured site are the same body part.

[0030] Specifically, the low-frequency generating unit (140) can generate a low-frequency of the first mode when the ratio of the fat thickness of the muscle to the thickness of the muscle is lower than or equal to the first reference value or the quality of the muscle is higher than or equal to the first ratio, generate a low-frequency of the second mode when the ratio of the fat thickness of the muscle to the thickness of the muscle is higher than or equal to the first reference value and lower than or equal to the second reference value or the quality of the muscle is lower than the first ratio and higher than or equal to the second ratio, generate a low-frequency of the third mode when the ratio of the fat thickness of the muscle to the thickness of the muscle is higher than or equal to the second reference value or the quality of the muscle is lower than or equal to the third ratio, and generate a low-frequency of the fourth mode when the ratio of the fat thickness of the muscle to the thickness of the muscle is higher than or equal to the third reference value or the quality of the muscle is lower than the third ratio. At this time, the first to fourth modes are modes set by combining two or more of concentrated tapping, wave tapping, soft tapping, concentrated kneading, wave kneading, and soft kneading, each of which has a different low-frequency intensity, strength, and frequency according to muscle characteristic information.

[0031] FIG. 2 is a diagram illustrating an example of generating a low frequency according to one embodiment of the present invention.

[0032] As illustrated in FIG. 2, the low-frequency generating unit (140) can generate low-frequency in the first mode by sequentially providing four wave taps, three soft taps, four wave kneadings, and three soft taps at least once when the ratio of muscle fat thickness to muscle thickness is equal to or lower than the first reference value (0.3) or the quality of the muscle is equal to or higher than the first ratio (82%).

[0033] In addition, the low-frequency generating unit (140) can generate a low-frequency of the second mode that sequentially provides three wave taps, four soft kneadings, four wave kneadings, and three soft taps at least once when the ratio of muscle fat thickness to muscle thickness exceeds the first reference value (0.3) and is lower than or equal to the second reference value (0.48) or the quality of the muscle is lower than the first ratio (82%) and higher than or equal to the second ratio (64%).

[0034] In addition, the low-frequency generating unit (140) can generate low-frequency in a third mode that sequentially provides four concentrated taps, three concentrated kneadings, four concentrated taps, and three gentle kneadings at least once when the ratio of muscle fat thickness to muscle thickness exceeds the second reference value (0.48) and is lower than or equal to the third reference value (0.76) or the quality of the muscle is lower than the second ratio (64%) and higher than or equal to the third ratio (50%).

[0035] In addition, the low-frequency generating unit (140) can generate low-frequency in the fourth mode by sequentially providing four concentrated taps, two wave taps, four concentrated taps, and three concentrated kneadings at least once when the ratio of muscle fat thickness to muscle thickness exceeds the third reference value (0.76) and is lower than or equal to the fourth reference value (1) or the quality of the muscle is lower than the third ratio (64%).

[0036] Next, the investigation unit (150) irradiates the generated low frequency to a part of the user's body.

[0037] Specifically, the investigation unit (150) can investigate the low frequency generated by the low frequency generation unit (140) through a pad attached to a part of the user's body.

[0038] FIG. 3 is an exemplary diagram illustrating an example of measuring muscle characteristic information of a part of a user's body and investigating low frequencies according to one embodiment of the present invention.

[0039] As illustrated in FIG. 3, a low-frequency generating device (100) using muscle characteristic information receives muscle characteristic information measured through a measurement module (200), and generates low-frequency based on the received muscle characteristic information and the input user's personal information and information on the attachment site, and can irradiate the low-frequency to the user's attachment site.

[0040] In this way, according to an embodiment of the present invention, the optimal low frequency can be applied to the user by generating the low frequency while considering the user's personal information, muscle thickness, muscle fat thickness, and muscle quality.

[0041] While the present invention has been described with reference to the embodiments illustrated in the drawings, these are merely exemplary, and those skilled in the art will understand that various modifications and equivalent embodiments are possible. Therefore, the true technical protection scope of the present invention should be determined by the technical spirit of the following claims.

[0042] [Explanation of symbols]

[0043] 100: Low-frequency generation device using muscle characteristic information

[0044] 110: Input section

[0045] 120: Communications Department

[0046] 130: Learning Department

[0047] 140: Low frequency generator

[0048] 150: Investigation Department

[0049] 200: Measurement module

Claims

1. In a low-frequency generating device using muscle characteristic information, An input section for receiving at least one personal information of the user's gender, age, body, and clinical information and an attachment site of the measurement module; A communication unit that receives muscle characteristic information of a part measured by a measurement module attached to a body part of the user; A learning unit that learns a low-frequency information model to derive low-frequency feature information by using multiple pieces of personal information, attachment site of a measurement module, and muscle characteristic information; A low frequency generation unit that generates low frequencies by applying the user's personal information, attachment site, and muscle characteristic information of the measured site to a pre-learned low frequency information model; and A low-frequency generating device including an irradiation unit that irradiates the generated low-frequency waves to a part of the user's body.

2. In paragraph 1, The above muscle characteristic information is, A low-frequency generating device comprising at least one of the muscle thickness of the attachment site, the fat thickness of the muscle of the attachment site, and the muscle quality of the attachment site.

3. In paragraph 1, The above low frequency feature information is, A low-frequency generating device comprising at least one of a low-frequency frequency, a low-frequency intensity, and a low-frequency waveform determined based on the user's personal information, attachment site, and muscle characteristic information.

4. In paragraph 1, The above measurement module, A low-frequency generating device that uses ultrasound to probe a part of a user's body, receives a plurality of reflected sounds, filters the received reflected sounds, removes a contact-reflection signal to implement a reflected signal, and extracts at least one peak from the reflected signal to measure muscle characteristic information.

5. In paragraph 4, The above low frequency information model is, A low-frequency generating device that sets at least one of the low-frequency frequency, low-frequency intensity, and low-frequency waveform according to the user's personal information, attachment site, and muscle characteristic information of the above-mentioned measured muscle characteristic device.

6. In paragraph 2, The above low frequency generator is, When the ratio of the fat thickness and muscle thickness of the above muscle is lower than or equal to the first reference value or the quality of the above muscle is higher than or equal to the first ratio, a low frequency of the first mode is generated, When the ratio of the fat thickness and the muscle thickness of the above muscle exceeds the first reference value and is lower than or equal to the second reference value, or when the quality of the above muscle is lower than the first ratio and higher than or equal to the second ratio, a low frequency of the second mode is generated. When the ratio of the fat thickness and the muscle thickness of the above muscle exceeds the second reference value and is lower than or equal to the third reference value, or when the quality of the above muscle is lower than the second ratio and higher than or equal to the third ratio, a low frequency of the third mode is generated, A low-frequency generating device that generates low frequencies of the fourth mode when the ratio of the fat thickness to the muscle thickness of the above muscle exceeds the third reference value and is lower than or equal to the fourth reference value or when the quality of the above muscle is lower than the third ratio.

7. In paragraph 6, The above first to fourth modes are: A low-frequency generating device set by combining two or more of concentrated tapping, undulating tapping, soft tapping, concentrated kneading, undulating kneading, and soft kneading, each of which has a different intensity, volume, and frequency of low-frequency according to the above muscle characteristic information.

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