Massage chair body shape detection method system
By acquiring user identity and location information, the massage intensity is analyzed and determined, enabling personalized massage from the massage chair. This solves the problem of poor massage effect caused by differences in user physical condition and intensity, and improves the accuracy and effectiveness of the massage.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- FUJIAN WEILONG ELECTRONIC TECH CO LTD
- Filing Date
- 2023-09-26
- Publication Date
- 2026-06-09
AI Technical Summary
Existing massage chairs often fail to provide adequate massage due to differences in users' physical conditions and desired massage intensity.
By acquiring user identity information and multiple location information, the system analyzes and determines the massage intensity at different massage locations, and controls the massage components to perform personalized massage operations.
It improves the accuracy and effectiveness of massage chair massage, meeting the personalized needs of different users.
Smart Images
Figure CN117100544B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of automatic control, and in particular to a method and system for detecting human body shape in a massage chair. Background Technology
[0002] As people's health awareness increases, more and more people are choosing massage chairs to unblock meridians and relieve fatigue. To meet user needs, existing massage chairs use massage components such as robotic arms or massage balls to massage different parts of the body or acupoints, thus achieving a better massage effect.
[0003] The existing control method for massage chairs is to first uniformly set the corresponding parts or acupoints for each area, and when the massage component moves to a certain area, the corresponding massage mode is run according to the corresponding parts or acupoints of that area.
[0004] Regarding the aforementioned technologies, the inventors have discovered the following drawbacks: Firstly, due to differences in each user's physical condition and height, the massage location and acupoints may vary relative to the preset area. Secondly, because different people have different tolerances to massage pressure, applying a uniform pressure will not produce good results. Summary of the Invention
[0005] In order to improve the accuracy of positional massage in a massage chair and thus enhance the massage effect, this application provides a method and system for detecting human body shape in a massage chair.
[0006] Firstly, this application provides a method for detecting the human body shape of a massage chair, employing the following technical solution:
[0007] A method for detecting human body shape in a massage chair, comprising:
[0008] The system obtains the user's identity information while seated on a massage chair, as well as the user's current location information, including shoulder position, waist position, and hip position.
[0009] Based on user identity information and the correspondence between multiple user locations and massage intensity, the massage intensity at different massage locations is analyzed and determined.
[0010] Based on the user's multiple locations and the massage intensity at different massage points, the massage components are controlled to perform massage operations at the corresponding locations of the user.
[0011] Optionally, obtaining user identity information while seated on the massage chair includes:
[0012] Obtain the user's weight and height information while seated on the massage chair;
[0013] Based on the preset user information and the acquired user weight and height information, the system analyzes and determines the current range of the user's weight and identity, and then determines the user information. The preset user information includes the weight range and the user's identity information.
[0014] Optionally, the analysis and determination of massage intensity at different massage locations includes:
[0015] Analyze whether the user's identity information is determined by preset user information, as well as the obtained user weight and height information;
[0016] If so, the massage intensity at different massage locations will be determined based on the user's identity information and the correspondence between the user's multiple locations and the massage intensity.
[0017] If not, then based on the obtained user weight information, user height information, and preset user information, analyze the user information that is closest to the obtained user weight information and user height information, and use the analyzed closest user information and the correspondence between multiple user positions and massage intensity to analyze and determine the massage intensity at different massage positions.
[0018] Optionally, the analysis of user information that most closely matches the obtained user weight and height information is as follows:
[0019] Obtain the similarity between the weight value of the preset user and the weight value of the obtained user, and the similarity between the height value of the preset user and the height value of the obtained user;
[0020] Based on the influence ratio of different similarities, the similarity between the preset user's weight value and the obtained user's weight value, and the similarity between the preset user's height value and the obtained user's height value, analyze the effective similarity between each preset user and the obtained user's weight information and height information.
[0021] The user with the highest effective similarity is selected as the user whose weight and height information are closest to the obtained information.
[0022] Optionally, it also includes steps following the control of the massage component to perform a massage operation at the user's corresponding location, as follows:
[0023] The data sources for analyzing the massage intensity at different massage locations were included user identity information and the closest user information identified in the analysis.
[0024] If the data source is the closest user information identified through analysis, then analyze whether the user has adjusted their position within a preset time range after the massage;
[0025] If so, the corresponding location will be identified, and the massage intensity at that location will be reduced by one level.
[0026] Optionally, steps may also be included after the user has changed their location;
[0027] If not, further identify whether the user has signs of falling asleep;
[0028] If so, the massage intensity after the user falls asleep is determined by analyzing the user's identity information, the user's signs of falling asleep, and the correspondence between the user's multiple locations and the massage intensity.
[0029] The massage intensity will be adjusted to the intensity you would apply after you fall asleep.
[0030] Optional, whether the user shows signs of falling asleep includes:
[0031] It can determine whether the user's eyes are closed and whether there are any sounds indicating that the user is falling asleep.
[0032] If the user has their eyes closed and there are sounds of falling asleep, it is determined that the user has signs of falling asleep.
[0033] If the user is only in a closed-eye state, the massage components will be controlled to perform massage operations on the corresponding positions of the user based on multiple positions of the user and the massage intensity at different massage positions.
[0034] Optionally, it also includes a step that runs parallel to analyzing and determining the massage intensity at different massage locations based on user identity information and the correspondence between multiple user locations and massage intensity, as detailed below:
[0035] Determine if the user has just finished exercising within the specified time frame;
[0036] If so, based on the correspondence between user identity information and the user's preferred sports, the massage areas and intensities required for the corresponding sports, analyze the massage areas and intensities required by the user, and set the priority of the massage areas and intensities required by the user to be higher than the massage areas and intensities set in other scenarios.
[0037] Perform the massage according to the user's desired massage area and intensity.
[0038] Secondly, this application provides a human body shape detection system for a massage chair, which adopts the following technical solution:
[0039] A massage chair human body shape detection system includes a memory, a processor, and a program stored in the memory and executable on the processor. When the program is loaded and executed by the processor, it implements the massage chair human body shape detection method as described in the first aspect. Attached Figure Description
[0040] Figure 1 This is an overall flowchart of a massage chair human body shape detection method according to an embodiment of this application.
[0041] Figure 2 This is a schematic diagram illustrating the process of obtaining user identity information when the user is seated on a massage chair, according to an embodiment of this application.
[0042] Figure 3 This is a schematic diagram illustrating the process of analyzing and determining the massage intensity at different massage locations in an embodiment of this application.
[0043] Figure 4 This is a schematic diagram illustrating the process of analyzing user information, which is closest to the obtained user weight and height information in this application embodiment.
[0044] Figure 5 This is a flowchart illustrating the steps following the control of the massage component to perform a massage operation at the user's corresponding location, according to an embodiment of this application.
[0045] Figure 6 This is a flowchart illustrating the steps following whether the user has adjusted their location, as described in this application embodiment.
[0046] Figure 7 This is a flowchart illustrating whether a user has signs of falling asleep, according to an embodiment of this application.
[0047] Figure 8 This is a flowchart illustrating the steps of analyzing and determining the massage intensity at different massage locations in parallel, based on user identity information, the correspondence between multiple user locations and massage intensity. Detailed Implementation
[0048] The present application will be further described in detail below with reference to the accompanying drawings.
[0049] Reference Figure 1 The present application discloses a method for detecting human body shape in a massage chair, comprising:
[0050] Step S100: Obtain the user's identity information while seated on the massage chair, as well as the user's current multiple positions. These multiple position information include shoulder position, waist position, and hip position.
[0051] Among them, the user's identity information when sitting on the massage chair can be identified by fingerprint recognition or by body shape or weight.
[0052] The user's current location information can be obtained by installing sensors in the massage chair. Specifically, one or more sensors can be installed in the seat and backrest of the massage chair. These sensors can be pressure sensors, detecting the pressure exerted by the user on the seat and backrest, and then combining this information with human biomechanics to detect and acquire information about the shoulder, waist, and hip positions. Alternatively, these sensors can be position sensors, detecting the user's shoulder, waist, and hip positions to obtain relevant position information. There are various existing technologies for using sensors to detect relevant parts of the human body; this embodiment does not specifically limit these methods and will not elaborate further.
[0053] Step S200: Based on the user's identity information and the correspondence between multiple user locations and massage intensity, analyze and determine the massage intensity at different massage locations.
[0054] The analysis and determination of massage intensity at different massage locations are as follows: using user identity information and multiple user locations as query objects, the massage intensity at different massage locations is obtained by querying a pre-set database that stores the correspondence between user identity information, multiple user locations and massage intensity.
[0055] Step S300: Based on the user's multiple positions and the massage intensity at different massage positions, control the massage component to perform massage operations at the corresponding positions of the user.
[0056] exist Figure 1 In step S100, further consideration is given to how to effectively analyze the user's identity. Further analysis is required here; please refer to [link / reference needed]. Figure 2 The illustrated embodiments are described in detail.
[0057] Reference Figure 2 The acquisition of user identity information while seated on a massage chair includes:
[0058] Step S1a0: Obtain the user's weight and height information located on the massage chair.
[0059] Among them, the user's weight information on the massage chair can be analyzed and judged by detecting the pressure when the user sits on the massage chair using pressure sensors, and the user's height information on the massage chair can be obtained by detecting the user's silhouette on the massage chair.
[0060] Step S1b0: Based on the preset user information and the obtained user weight and height information, analyze and determine the current range of the user's weight and identity, and determine the user information. The preset user information includes the weight range and the user's identity information.
[0061] exist Figure 1 In step S200, the possibility of valid user identification is further considered. If user identification is not verified, how to effectively analyze and determine the massage intensity at different massage locations requires further analysis. See below for details. Figure 3 The illustrated embodiments are described in detail.
[0062] Reference Figure 3 The analysis and determination of massage intensity at different massage locations includes:
[0063] Step S210: Analyze whether the user identity information is determined by preset user information and the obtained user weight and height information. If yes, proceed to step S220; if no, proceed to step S230.
[0064] Step S220: Based on the user's identity information and the correspondence between multiple user locations and massage intensity, analyze and determine the massage intensity at different massage locations.
[0065] Step S230: Based on the acquired user weight information, user height information, and preset user information, analyze the user information that is closest to the acquired user weight information and user height information, and use the analyzed closest user information and the correspondence between multiple user positions and massage intensity to analyze and determine the massage intensity at different massage positions.
[0066] exist Figure 3 In step S230, it is necessary to further analyze the closest match between the acquired user weight information and user height information, as detailed in the following section. Figure 4 The illustrated embodiments are described in detail.
[0067] Reference Figure 4 The analysis of user information that most closely matches the obtained user weight and height information is as follows:
[0068] Step S231: Obtain the similarity between the preset user's weight value and the obtained user's weight value, and the similarity between the preset user's height value and the obtained user's height value.
[0069] For example, the similarity analysis between the preset user's weight value and the obtained user's weight value is as follows: Assuming the user's weight value is 90kg, the preset user weight value is 72KG or 112.5kG, and the similarity is 90% in both cases.
[0070] Step S232: Based on the influence ratio of different similarities, the similarity between the preset user's weight value and the obtained user's weight value, and the similarity between the preset user's height value and the obtained user's height value, analyze the effective similarity between each preset user and the obtained user's weight information and height information.
[0071] The effective similarity between each preset user and the acquired user weight and height information is calculated as follows: The influence ratio of the similarity is multiplied by the similarity between the preset user's weight value and the acquired user's weight value to obtain similarity 1. Then, the similarity between the preset user's height value and the acquired user's height value is multiplied by the influence ratio of the similarity to obtain similarity 2. The sum of similarity 1 and similarity 2 is the effective similarity between each preset user and the acquired user weight and height information.
[0072] Step S233: Select the user with the highest effective similarity as the user whose weight and height information are closest to the obtained information.
[0073] exist Figure 1 After step S300, the user's tolerance for massage intensity should also be considered. Further analysis is required at this point; please refer to [the relevant documentation]. Figure 5 The illustrated embodiments are described in detail.
[0074] Reference Figure 5 A method for detecting human body shape in a massage chair also includes a step following the control of the massage components to perform a massage operation at the corresponding position of the user, as follows:
[0075] Step SA00: Analyze the data sources for the massage intensity at different massage locations. The data sources include user identity information and the closest user information identified in the analysis.
[0076] Step SB00: If the data source is the closest user information determined by the analysis, then analyze whether the user has made any position adjustments within the preset time range after the massage.
[0077] Whether the user has adjusted their location can be detected by a relevant detection device, and the preset time can be set as needed, such as half an hour or one hour.
[0078] Step SC00: If yes, identify the corresponding location and reduce the massage intensity at the corresponding location by one level.
[0079] exist Figure 5 In step SB00, the possibility of the user falling asleep is further considered. If the user falls asleep, the massage intensity should be reduced. This requires further analysis; please refer to [the relevant documentation]. Figure 6 The illustrated embodiments are described in detail.
[0080] Reference Figure 6 It also includes steps following whether the user has changed their location;
[0081] Step SD00: If not, further identify whether the user has signs of falling asleep.
[0082] Reference Figure 7 Whether a user has signs of falling asleep includes:
[0083] Step SD10: Determine if the user's eyes are closed and if there are any sleep sounds.
[0084] Step SD20: If the user has their eyes closed and there are sounds of falling asleep, then it is determined that the user has signs of falling asleep.
[0085] Step SD30: If the user is only in a closed-eye state, the massage component is controlled to perform massage operations on the corresponding positions of the user based on multiple positions of the user and the massage intensity at different massage positions.
[0086] Step SE00: If yes, then based on the user's identity information, the user's signs of falling asleep, and the correspondence between multiple user positions and massage intensity, analyze and determine the massage intensity after the user falls asleep.
[0087] Step SF00: Adjust the current massage intensity to the intensity you would apply after the user falls asleep.
[0088] exist Figure 1 In step S300, considering that the user may have just finished exercising, the massage intensity, location, and location should be adjusted accordingly. See details below. Figure 8 The illustrated embodiments are described in detail.
[0089] Reference Figure 8 A method for detecting human body shape in a massage chair also includes a parallel step of analyzing and determining the massage intensity at different massage positions based on user identity information and the correspondence between multiple user positions and massage intensity, as detailed below:
[0090] Step Sa00: Determine if the user is within the time range of just finishing exercise.
[0091] Whether a user has just finished exercising can be further analyzed using sweat and heart rate data. For example, if the sweat level exceeds a certain range and the heart rate is higher than a certain frequency, it can be determined that the user has exercised. The time range can be set as needed, such as half an hour or one hour.
[0092] Step Sb00: If yes, then based on the correspondence between the user's identity information and the user's preferred movement, the massage area and intensity required for the corresponding movement, analyze the massage area and intensity required by the user, and set the priority of the massage area and intensity required by the user to be higher than the massage location and intensity set in other scenarios.
[0093] The analysis of the massage areas and intensity required by the user is as follows: The user's identity information, the user's preferred sports, and the massage areas required for the corresponding sports are used as common query objects. The user's desired massage areas and intensity are retrieved from a pre-set database that stores the correspondence between user identity information, the user's preferred sports, the massage areas required for the corresponding sports, and the intensity.
[0094] Step Sc00: Perform a massage operation according to the user's desired massage area and intensity.
[0095] Based on the same inventive concept, embodiments of the present invention provide a human body shape detection system for a massage chair, including a memory and a processor, wherein the memory stores information that can run on the processor to implement the following... Figures 1 to 8 The procedure for any method.
[0096] The embodiments described in this specific implementation are preferred embodiments of this application and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.
Claims
1. A human body shape detection system for a massage chair, characterized in that, include: The memory, the processor, and the program stored in the memory and executable on the processor specifically include: The system obtains the user's identity information while seated on a massage chair, as well as the user's current location information, including shoulder position, lower back position, and hip position. The acquisition of the user's identity information while seated on a massage chair includes: Obtain the user's weight and height information while seated on the massage chair; Based on the preset user information and the obtained user weight and height information, the system analyzes and determines the current range of the user's weight and identity, and determines the user information. The preset user information includes the weight range and the user's identity information. Based on user identity information and the correspondence between multiple user locations and massage intensity, the massage intensity at different massage locations is analyzed and determined. This analysis and determination of massage intensity at different massage locations includes: Analyze whether the user's identity information is determined by preset user information, as well as the obtained user weight and height information; If so, the massage intensity at different massage locations will be determined based on the user's identity information and the correspondence between the user's multiple locations and the massage intensity. If not, then based on the acquired user weight information, user height information, and preset user information, analyze the user information that is closest to the acquired user weight information and user height information. Using the analyzed closest user information and the correspondence between multiple user positions and massage intensity, analyze and determine the massage intensity at different massage positions. The analysis of the user information that is closest to the acquired user weight information and user height information is as follows: Obtain the similarity between the weight value of the preset user and the weight value of the obtained user, and the similarity between the height value of the preset user and the height value of the obtained user; Based on the influence ratio of different similarities, the similarity between the preset user's weight value and the obtained user's weight value, and the similarity between the preset user's height value and the obtained user's height value, analyze the effective similarity between each preset user and the obtained user's weight information and height information. Select the user with the highest effective similarity as the user whose weight and height information are closest to the obtained user information. Based on the user's multiple locations and the massage intensity at different massage locations, the massage components are controlled to perform massage operations at the corresponding locations of the user. Based on the user's corresponding location, the data source of the massage intensity at different massage locations is analyzed. The data source includes user identity information and the closest user information identified in the analysis. If the data source is the closest user information identified through analysis, then the system analyzes whether the user has changed position within a preset time range after the massage. If yes, the system identifies the corresponding position and reduces the massage intensity at that position by one level. If no, the system further identifies whether the user has signs of falling asleep. If yes, the system analyzes and determines the massage intensity after the user falls asleep based on the user's identity information, the user's signs of falling asleep, and the correspondence between multiple user positions and massage intensity. The system then adjusts the current massage intensity to the intensity after the user falls asleep. Among the signs that a user has fallen asleep are: It can determine whether the user's eyes are closed and whether there are any sounds indicating that the user is falling asleep. If the user has their eyes closed and there are sounds of falling asleep, it is determined that the user has signs of falling asleep. If the user is only in a closed-eye state, the massage components will be controlled to perform massage operations on the corresponding positions of the user based on multiple positions of the user and the massage intensity at different massage positions. The steps involved in analyzing and determining the parallel massage intensity at different massage locations based on user identity information and the correspondence between multiple user locations and massage intensity are as follows: Determine if the user has just finished exercising within the specified time frame; If so, based on the correspondence between user identity information and the user's preferred sports, the massage areas and intensities required for the corresponding sports, analyze the massage areas and intensities required by the user, and set the priority of the massage areas and intensities required by the user to be higher than the massage areas and intensities set in other scenarios. Perform the massage according to the user's desired massage area and intensity.