Plantar pressure detection system and method based on air pressure sensor and air bag

Abstract

The invention discloses a plantar pressure detection system and method based on an air pressure sensor and air sacs, the system is embedded into a sole, and the system comprises a sensing module used for sensing plantar pressure, obtaining pressure data and adjusting the air pressure in each air sac according to an adjusting instruction; the data processing module is used for receiving and preprocessing the pressure data to obtain plantar pressure information and generating a plantar pressure health report and the adjusting instruction; the wireless communication module is used for transmitting the plantar pressure health report to external equipment or a cloud end and transmitting user feedback to the data processing module; the real-time feedback module is used for providing abnormal pressure state feedback for the user when the abnormal pressure state is detected; and the power management module is used for providing power, monitoring the electric quantity state of the system in real time and controlling the power consumption of the plantar pressure detection system. Real-time, comfortable and high-precision plantar pressure monitoring is provided, and better user experience is provided.

Description

Technical Field

[0001] This application relates to the technical field of plantar pressure detection, and particularly to a plantar pressure detection system and method based on a pneumatic sensor and an airbag. Background Art

[0002] In the field of plantar health monitoring, plantar pressure detection technology has been widely applied in scenarios such as gait analysis, sports monitoring, and rehabilitation training. Accurately detecting the plantar pressure distribution can not only help prevent foot diseases, but also improve gait, enhance sports performance, and provide important data support in rehabilitation treatment. Traditional plantar pressure detection systems usually rely on rigid sensors, which have many limitations in practical applications. For example, the hard material properties of rigid sensors determine that they will affect the wearing comfort and even normal gait, especially for the elderly, patients with chronic diseases, or users in the rehabilitation period. Moreover, these sensors have insufficient measurement accuracy when facing complex and variable gaits and terrains.

[0003] In addition, the existing plantar pressure detection systems usually lack a real-time feedback and warning mechanism. When the plantar pressure distribution of the user is abnormal, it cannot provide a timely reminder in the initial stage of the abnormality, thus delaying the best time for early intervention. This lagging monitoring method obviously cannot meet the growing health management needs.

[0004] In view of this, there is an urgent need to provide a plantar pressure monitoring solution with high precision, real-time performance, and comfort. Summary of the Invention

[0005] Based on the above application requirements and technical background, in order to solve the technical problem that the prior art cannot simultaneously perform plantar pressure monitoring in real time, comfortably, and with high precision, this application adopts the following technical solutions:

[0006] In the first aspect of this application, a plantar pressure detection system based on a pneumatic sensor and an airbag is proposed. The system is embedded in the sole of the shoe and includes: a sensing module, a data processing module, a wireless communication module, a real-time feedback module, and a power management module.

[0007] The sensing module includes multiple independently operating airbags, multiple pneumatic sensors, an air pump, and multiple air valves, and is used to sense plantar pressure, obtain pressure data, synchronously transmit it to the data processing module, and adjust the air pressure inside each airbag according to an adjustment instruction.

[0008] The data processing module is connected to the pneumatic sensor and includes a preprocessing unit and an algorithm unit, and is used to receive and preprocess the pressure data to obtain plantar pressure information, generate a plantar pressure health report, and the adjustment instruction.

[0009] The wireless communication module is used to transmit the real-time plantar pressure information and the plantar pressure health report to an external device or the cloud, and transmit the user feedback input by the user from the external device or the cloud to the data processing module;

[0010] The real-time feedback module is used to provide feedback on the abnormal pressure state to the user when an abnormal pressure state is detected. The ways of the abnormal pressure state feedback include vibration, sound, or visual feedback;

[0011] The power management module is used to provide power, monitor the power state of the system in real time, and control the power consumption of the plantar pressure detection system.

[0012] Further, each of the airbags is respectively embedded in the key pressure-bearing areas in the sole. The key pressure-bearing areas correspond to the key force points on the sole, including the heel area, the forefoot area, the lateral foot area, and the metatarsal arch area.

[0013] Further, each airbag corresponds to one or more of the air pressure sensors; the sensing module further includes a weighing sensor; each time the plantar pressure information, the plantar pressure health report, and the adjustment instruction processed by the data processing module are stored as user historical data in the memory of the system or the cloud.

[0014] Further, the algorithm unit includes a first preset algorithm for generating a plantar pressure distribution map and a plantar pressure change trend, calculating key gait indexes, and extracting gait features; the gait indexes include the center of pressure, the center of gravity transfer trajectory, and the plantar contact area and contact time; the gait features include step length, walking speed, plantar landing manner, and gait symmetry.

[0015] Further, the algorithm unit further includes a second preset algorithm for identifying an abnormal pressure state;

[0016] The second preset algorithm is a machine learning algorithm;

[0017] The abnormal pressure state includes center of gravity offset, abnormal pressure distribution, gait instability, excessive internal and external rotation, or gait asymmetry, etc. The second preset algorithm identifies the plantar pressure information exceeding the abnormal pressure threshold as the abnormal pressure state;

[0018] The abnormal pressure threshold is adaptively and dynamically adjusted based on user historical data and the plantar pressure information.

[0019] Further, the algorithm unit further includes a third preset algorithm. Through the third preset algorithm, a personalized plantar pressure health report is generated based on the user's historical data, the results of the first preset algorithm, and the results of the second preset algorithm, and the plantar pressure health report is transmitted to an external device through the wireless communication module;

[0020] The plantar pressure health report includes the abnormal pressure state, the plantar pressure distribution map and the plantar pressure change trend, the gait index and gait characteristics, personalized health suggestions, and a long-term health trend analysis report.

[0021] Further, the algorithm unit further includes a fourth preset algorithm for generating the adjustment instruction and transmitting it to the sensing module, and adjusting the air pressure of the airbag based on the adjustment instruction through the air pump and the multiple air valves.

[0022] Further, the power management module adopts a low-power design and includes a battery pack, a power monitoring circuit, and an intelligent power controller.

[0023] A second aspect of the present application proposes a plantar pressure detection method based on a pressure sensor and an airbag. The method includes:

[0024] Sensing the plantar pressure through the sensing module, obtaining pressure data and synchronously transmitting it to the data processing module, and adjusting the air pressure inside each airbag according to the adjustment instruction. The sensing module includes multiple independently operating airbags, multiple pressure sensors, an air pump, and multiple air valves;

[0025] Receiving and preprocessing the pressure data by the data processing module to obtain plantar pressure information, generating a plantar pressure health report and the adjustment instruction. The data processing module is connected to the pressure sensor and includes a preprocessing unit and an algorithm unit;

[0026] Transmitting the real-time plantar pressure information and the plantar pressure health report to an external device or the cloud through the wireless communication module, and transmitting the user feedback input by the user from the external device or the cloud to the data processing module;

[0027] Providing an abnormal pressure state feedback to the user through the real-time feedback module when an abnormal pressure state is detected. The abnormal pressure state feedback methods include vibration, sound, or visual feedback;

[0028] Providing power through the power management module, monitoring the power state of the system in real time, and controlling the power consumption of the plantar pressure detection system.

[0029] Furthermore, each of the airbags is respectively embedded in the key pressure - receiving areas in the sole, and the key pressure - receiving areas correspond to the key force - bearing points on the sole, including the heel area, the forefoot area, the lateral foot area, and the metatarsal arch area.

[0030] Compared with the prior art, the beneficial effects of the present application are as follows:

[0031] The plantar pressure detection system and method based on a pressure sensor and an airbag provided by the present application ensure the adaptability and comfort of the system to the foot during use by embedding flexible airbags in the sole. Especially during long - term use, it avoids the problem of local pressure concentration that may be caused by rigid sensors, improving the user's wearing comfort. By sensing the air pressure change inside the airbag with a pressure sensor, it realizes high - precision monitoring of plantar pressure, more effectively responds to complex terrains and gait changes, and provides more stable and reliable measurement data. Through the combined design of the pressure sensor and the airbag, the system can provide higher precision and sensitivity than traditional rigid pressure sensors. Especially under complex gait conditions, it can still maintain stable measurement performance. By real - time monitoring the plantar pressure distribution and changes and performing algorithm analysis based on real - time data, it generates a plantar pressure distribution map, identifies gait characteristics and abnormal plantar pressure states, and provides instant feedback and warning functions (such as vibration, sound, or visual cues) and personalized health advice and rehabilitation guidance based on the user's own needs, meeting the user's requirements for real - time monitoring and personalized dynamic management of plantar health, thereby improving the performance and user experience of the plantar pressure detection system. The system not only provides real - time plantar pressure monitoring but also generates personalized analysis reports and health advice according to the user's gait characteristics, which is of practical significance for athletes, rehabilitation patients, and users of daily health management.

[0032] When the plantar pressure detection system and method based on a pressure sensor and an airbag provided by the present application are used in the field of rehabilitation training, it can assist in rehabilitation treatment by real - time monitoring the gait changes of patients, and can be applied to the gait monitoring of rehabilitation patients. By real - time tracking the pressure changes and gait characteristics, it helps rehabilitation therapists evaluate the patient's recovery progress and provide personalized training programs. When used in the field of sports monitoring, it can help athletes optimize their gait and reduce the risk of sports injuries. For athletes, the system can provide detailed gait analysis reports to help them optimize their running or walking postures and avoid sports injuries caused by poor gait. It can also be used in the field of health assessment to detect gait abnormalities, plantar pressure concentration problems, etc., and detect early health problems by analyzing gait abnormalities, such as unsteady gait in the elderly and the risk of foot ulcers in diabetic patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0034] Figure 1 Schematic diagram of the plantar pressure detection system based on a pressure sensor and an airbag provided by the present application;

[0035] Figure 2 Schematic flow chart of the plantar pressure detection method based on a pressure sensor and an airbag provided by the present application. Detailed implementation manners

[0036] The present application proposes a plantar pressure detection system and method based on a pressure sensor and an airbag. To describe the present application more specifically, the following will detail the technical solutions of the present application with reference to the drawings and specific embodiments. It should be understood that the specific implementation manners described herein are only used to explain the present application and are not used to limit the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present application.

[0037] The first aspect of the present application proposes a plantar pressure detection system based on a pressure sensor and an airbag. The system is embedded in the sole, and the schematic diagram is as Figure 1 shown. Specifically, it includes: a sensing module, a data processing module, a wireless communication module, a real-time feedback module, and a power management module;

[0038] The sensing module includes a plurality of independently operating airbags, a plurality of pressure sensors, an air pump, and a plurality of air valves. The airbags are used to sense the plantar pressure, the pressure sensors are used to detect the air pressure inside the airbags, obtain pressure data and synchronously transmit it to the data processing module, and the air pump and the plurality of air valves are used to adjust the air pressure inside each airbag according to the adjustment instruction;

[0039] Among them, the airbag is made of a flexible and highly elastic material, including silicone or polyurethane material. The flexible and highly elastic material has the characteristics of high elasticity, wear resistance and light weight. It can not only withstand repeated pressure, but also deform according to the shape of the user's sole and the change of plantar pressure, so as to better adapt to the shape and movement of the sole, ensure that the pressure applied to different areas of the sole can be accurately sensed through the deformation of the airbag, and maintain comfort and durability during long-term wear. Compared with traditional rigid pressure sensors, the flexible airbag conducts pressure through gas, is softer and more conformable to the foot, can achieve more uniform distribution and perception of the pressure change on the sole, and reduce the interference to the user's gait.

[0040] In one embodiment, each of the airbags is respectively embedded in the key pressure-bearing areas in the sole. The key pressure-bearing areas correspond to the key force-bearing points on the sole, including the heel area, the forefoot area, the lateral foot area and the metatarsal arch area.

[0041] Among them, the heel area is used to detect the pressure change of the heel. The heel is the area that bears the greatest pressure during gait and undertakes the main vertical load of the human body when standing and walking. Especially at the moment of landing, the pressure is concentrated and the impact force is large. Therefore, the airbag set in the heel area is larger and thicker, with high buffering and shock absorption performance, so as to reduce the impact force on the heel, protect the foot joints and spine, and accurately monitor the pressure change in this area;

[0042] The forefoot area is used to detect the pressure change of the forefoot. The forefoot provides thrust output when the user walks or runs. The force change is dynamic and complex, and it requires both support and flexibility. Therefore, the airbag set in the forefoot area is thinner, designed to be flat or strip-shaped, and set more flexibly, so as to provide accurate pressure perception and appropriate support force;

[0043] The lateral foot area is used to detect the pressure change of the lateral side of the sole. The lateral side of the foot mainly bears dynamic load during walking, especially during the foot transition stage from the heel to the forefoot when the foot exerts force. By analyzing the force on the lateral foot area, it can help analyze the balance of the user's gait and whether there are problems such as valgus or varus of the foot. The airbag set in the lateral foot area is designed to be slender, covering the outer edge area of the sole, and is consistent with the direction of the plantar force line, so as to provide stability and support force and avoid lateral turning or spraining;

[0044] The metatarsal arch area is used to detect the pressure changes of the foot arch. The metatarsal arch (i.e., the foot arch) is an important cushioning structure on the sole of the foot, which can help disperse pressure and maintain the stability of the foot. By analyzing the force on the metatarsal arch area, the health status of the foot arch can be reflected, which plays an important role in evaluating foot structure abnormalities or damage. Especially for users with flat feet or high arches, the airbag set in the metatarsal arch area is designed in an arch shape, matching the shape of the foot arch and covering the key support parts of the metatarsal arch, thus preventing the foot arch from collapsing due to long-term load.

[0045] Furthermore, the key pressure area also includes the toe area, which is used to detect the pressure changes of the toes. The pressure on the toes is relatively small during gait and plays an auxiliary support and balance role in the propulsion action. The airbag set in the toe area is a slender and flexible small structure, matching the toe morphology. The airbag structure is relatively thin, emphasizing high sensitivity to capture the subtle pressure changes in the toe area.

[0046] Among them, the size, thickness and shape of the airbag are adjustable and can be adjusted according to the key pressure area set and the actual application scenario to effectively balance the relationship between detection accuracy, functionality and user experience. For example, in the scenarios of sports or rehabilitation training, the sole of the foot will bear higher impact force and dynamic load, and at the same time, accurate pressure detection is required. The airbag is designed to be thicker to accommodate more gas, distribute the sole pressure more evenly, provide more comprehensive pressure sensing and better shock absorption effect; in the daily wearing scenario, users pay more attention to the lightness, comfort and appearance of the shoes, and the requirements are mainly focused on basic health monitoring. The airbag is designed to be thinner and lighter to ensure the comfort and beautiful appearance of wearing the shoes.

[0047] In practical applications, the airbag is arranged in combination with the sole shape and mechanical characteristics in this application, which can flexibly adapt to the sole structures of different users. When the user walks or stands, the pressure exerted on different areas of the sole causes the air pressure inside the airbag to change, so that the airbag can accurately reflect the corresponding sole pressure changes, not only improving the accuracy of sole pressure perception, but also improving the support and protection functions of the shoes for the sole.

[0048] In one embodiment, each airbag corresponds to one or more air pressure sensors, which are used to detect the air pressure change inside the airbag, convert the air pressure change into an electrical signal, obtain pressure data and synchronously transmit it to the data processing module for processing to ensure data consistency and time matching, so as to realize real-time monitoring of the pressure distribution in each area of the sole. Specifically, when each airbag is independently connected to an air pressure sensor, a plantar pressure monitoring unit for precise zonal monitoring is formed. When each airbag is connected to multiple air pressure sensors, multi-dimensional pressure data from the same area can be collected. The multiple air pressure sensors can be distributed in different directions and positions to enhance the monitoring coverage and sensitivity, capture dynamic pressure fluctuations and directional changes, and even if a certain sensor fails, the redundant design can still ensure the normal operation of the system.

[0049] Among them, the air pressure sensor is connected to the airbag through a flexible air pipe, so as to ensure that the air pressure change inside the airbag can be transmitted to the air pressure sensor in real time. Transmitting the plantar pressure to the air pressure sensor through the air pipe can absorb the deformation of the sole, effectively avoid the direct force on the air pressure sensor, and reduce the damage of the sensor caused by direct extrusion or impact.

[0050] In practical applications, whenever the user walks or stands, the pressure in different areas of the sole will cause the air pressure inside the airbag to change. The air pressure sensor can capture these subtle air pressure changes and convert these air pressure changes into electrical signals (that is, pressure data) for output. The intensity of the electrical signal is proportional to the air pressure change, reflecting the pressure exerted on each area of the sole, thus providing accurate data support for subsequent gait analysis.

[0051] Among them, the air pressure sensor has high sensitivity, high precision and high sampling frequency, and can detect the minute air pressure change inside the airbag in real time, so as to accurately capture the minute pressure change on the sole during the user's walking or movement, especially the minute pressure fluctuations when athletes are running fast. In one embodiment, the air pressure sensor adopts a miniaturized design with a sampling frequency as high as hundreds of Hertz, ensuring that the minute changes in each gait cycle can be captured without affecting the wearing comfort.

[0052] Among them, the material of the air pressure sensor is fatigue-resistant and high-temperature-resistant, and has a moisture-proof coating design to ensure that it can still maintain high sensitivity under repeated pressure (such as hundreds of times of pressure per minute during running) and complex environments (such as high temperature, humidity or strenuous exercise scenarios), ensure the continuous accuracy of the monitoring data, and prevent damage caused by external impact or moisture intrusion.

[0053] In one embodiment, the air pump and multiple air valves are used to adjust the air pressure inside the airbag according to the adjustment instruction, ensure that the airbag is within the standard working air pressure range, avoid measurement errors caused by too low or too high air pressure, and thus improve the detection accuracy.

[0054] Specifically, when the system starts, the airbag is at the initial air pressure. After the user wears the system and steps on the airbag, the air pressure inside the airbag rises. The pressure sensor collects pressure data. Since the airbag will slowly leak air, its initial air pressure will drop, resulting in deviations in multiple measurement results. At this time, the air pressure of the airbag is adjusted to the initial air pressure through the air pump and multiple air valves. Among them, each airbag is connected by an air pipe, enabling the gas to flow between multiple airbags. The air pump compresses or inhales air, and the air valves regulate the flow of gas between the air pump and the airbag, realizing the inflation or deflation of the airbag and dynamically adjusting the air pressure to ensure that each airbag is in the best working state (that is, the air pressure inside the airbag is the initial air pressure).

[0055] In one embodiment, the sensing module further includes a weighing sensor, and the pressure data further includes weight data. The weighing sensor is located below the airbag and is used to detect the weight distribution and changes in each area of the sole of the foot to obtain the weight data. The weighing sensor and the pressure sensor complement each other. After the weight data is combined with the output of the pressure sensor, it can provide more comprehensive pressure analysis data for the system, helping to more accurately analyze the pressure distribution in each area of the sole of the foot, thereby further realizing the accurate detection of the pressure distribution in each area of the sole of the foot.

[0056] Among them, the weighing sensor is sturdy and durable, can withstand the weight pressure of different users, and has high sensitivity and accuracy.

[0057] Furthermore, the airbag, pressure sensor, air pump, and air valves are set to be detachable, enabling users to perform maintenance, replacement, and functional upgrades. For example, when the airbag leaks due to wear or the performance of the air pump decreases, users can directly disassemble and replace them. Moreover, by increasing the number of airbags and air pipes, users can conveniently expand the multi-point monitoring ability.

[0058] The data processing module is connected to the pressure sensor and includes a preprocessing unit and an algorithm unit, which are used to receive and preprocess the pressure data to obtain plantar pressure information, generate a plantar pressure health report, and the adjustment instruction;

[0059] Furthermore, each time the plantar pressure information, plantar pressure health report, and the adjustment instruction processed by the data processing module are stored as the user's historical data in the system's memory or cloud.

[0060] Among them, the data processing module receives the pressure data in real time through a high-speed interface to ensure synchronous recording of the pressure changes in all plantar areas. The high-speed interface can ensure that the pressure data is transmitted to the data processing module within milliseconds, avoiding delays, and realizing real-time reception and analysis of data to respond to the user's dynamic gait and pressure changes.

[0061] In one embodiment, the preprocessing unit is configured to preprocess the received pressure data, and the preprocessing includes filtering, smoothing, denoising, and calibration.

[0062] Specifically, the preprocessing step of filtering is used to retain the useful frequency components in the data, remove unnecessary noise or interference signals, and ensure the accuracy of the data, including: low-pass filtering, Kalman filtering, and adaptive filtering;

[0063] Among them, the low-pass filtering is used to pass low-frequency signals and eliminate high-frequency noise. This is because in plantar pressure detection, the real pressure signal is mainly concentrated in the low-frequency band (such as the change of gait cycle), while the high-frequency components are mostly noise or interference. The threshold of the filter used for low-pass filtering can be adjusted according to the application scenario;

[0064] The Kalman filtering is used for removing dynamic noise in gait monitoring. Kalman filtering is a recursive filtering method that can combine current data and historical data to estimate the optimal solution of the current state. By dynamically adjusting the deviation between the predicted value and the actual observed value, it gradually approaches the real signal. It is applied to dynamic and complex scenarios, especially suitable for systems with certain randomness or process noise, such as the continuously changing pressure signal of the user in this application during irregular movements;

[0065] The adaptive filtering is used to adjust the filtering parameters in real time according to the data characteristics. The adaptive filter adjusts the parameters of the filter in real time to adapt to the dynamic changes of the signal and noise. This filtering method does not require pre-determining fixed filtering parameters, but dynamically adjusts according to the environment and data characteristics. It is applicable to complex or unpredictable environments, such as when the user walks on uneven ground or quickly switches between different activity modes, to ensure that the system can obtain clear signals in different gaits or motion states.

[0066] Specifically, the preprocessing step of smoothing is used to further eliminate the fine fluctuations in the data. By removing short-term random variations, a signal with better continuity is generated to ensure that the data can clearly reflect the gait characteristics of the user without being affected by short-term fluctuations, including moving average and exponential smoothing;

[0067] Among them, the moving average generates a smoother curve by calculating the average value of data points within a sliding window, which can quickly reduce data fluctuations and is applicable to static or medium-low frequency dynamic detection;

[0068] The exponential smoothing generates a gradually changing signal by weighting historical data with higher weights for recent data, with a faster response and can achieve real-time processing, and is applicable to scenarios where gait changes rapidly.

[0069] Specifically, the preprocessing step of denoising is used to further eliminate random noise in the data while retaining the true signal, ensuring that the data is smooth and reliable, and includes wavelet transform;

[0070] Among them, the wavelet transform decomposes the signal into sub-bands of different frequencies through wavelet decomposition, removes the high-frequency noise components and then reconstructs the signal. It is applicable to non-stationary signals, can retain more detailed features, and can achieve fine analysis of plantar pressure changes in dynamic detection.

[0071] Specifically, the calibration process is used to adjust the original signal output by the sensor to the true physical quantity value to eliminate sensor bias and system errors, ensuring that each sensor can maintain accuracy under different temperature, humidity, and pressure environments.

[0072] In one embodiment, the algorithm unit includes a first preset algorithm for generating a plantar pressure distribution map and a plantar pressure change trend, calculating key gait metrics, and extracting gait features;

[0073] First, the first preset algorithm summarizes the plantar pressure information of the key plantar pressure-bearing areas at each time point, thereby generating the plantar pressure distribution map and the plantar pressure change trend. The plantar pressure distribution map and the plantar pressure change trend visually display the force conditions and the change trend over time of different areas of the plantar surface when the user is walking or standing. By presenting the force and change conditions of the plantar pressure in the form of a chart, it can clearly show the pressure concentration areas, pressure offsets, pressure abnormal points, pressure symmetry of each area, and the pressure change trend on the plantar surface;

[0074] Specifically, by continuously collecting and analyzing pressure data through the first preset algorithm, the plantar pressure distribution map and the plantar pressure change trend are dynamically changing. Since the plantar pressure is not static but dynamically changes with the user's steps and movements, the dynamic plantar pressure distribution map and the plantar pressure change trend can show how the pressure transfers between different areas of the plantar surface when the user is walking or running, and further analyze the user's center of gravity change and foot force application conditions, helping to identify the balance and stability of the gait;

[0075] Secondly, the first preset algorithm calculates gait metrics through the plantar pressure distribution map and the plantar pressure change trend. The gait metrics include the center of pressure, the center of gravity transfer trajectory, as well as the plantar contact area and contact time, which helps to analyze the user's gait health status;

[0076] Specifically, the center of pressure is obtained by dynamically calculating the centroid position of the pressure distribution. The center of pressure is used to represent the average force application point on the sole of the foot, reflecting gait stability and the sole load distribution. The center of gravity transfer trajectory is obtained through trajectory generation and feature extraction. The center of gravity transfer trajectory describes how the center of gravity transfers from the heel to the forefoot during the gait cycle of the user, helping to analyze the gait characteristics of the user. The sole contact area and contact time are obtained by statistically counting the pressure areas and durations where the pressure exceeds a preset ground contact pressure threshold. The sole contact area and contact time are used to analyze the regional distribution of the sole contacting the ground and the gait rhythm.

[0077] Finally, the first preset algorithm also extracts gait characteristics through the sole pressure distribution map and the trend of sole pressure changes. The gait characteristics include step length, walking speed, sole landing manner, and gait symmetry.

[0078] Specifically, the step length refers to the horizontal distance between two consecutive landings of the same foot, reflecting the rhythm and movement efficiency of the gait. It is calculated by recording the difference in the horizontal coordinates of the center of pressure when the same foot (such as the right foot) touches the ground twice consecutively. The walking speed refers to the number of steps completed per unit time, directly reflecting the walking speed. It is calculated by recording the time interval between two consecutive ground contact events. By analyzing the sole pressure change cycle of the user, the step length and walking speed of each step can be calculated.

[0079] The sole landing manner describes the order and pattern of different regions of the sole contacting the ground during the gait cycle. By determining the order of pressure value changes in the key pressure-bearing regions of the sole, the sole landing manner can be determined, including heel strike, forefoot strike, or flat foot strike. For example, when the pressure in the heel region rises first and then the pressure in the forefoot region increases, it is a heel strike manner. When the pressure in the forefoot region increases first and then the pressure in the heel region rises, it is a forefoot strike manner. Different landing manners may correspond to different gait problems or health conditions.

[0080] Gait symmetry is used to analyze the pressure distribution and gait rhythm of the left and right feet, and to judge whether the user's gait is symmetric. By combining indicators such as the step lengths and contact times of the left and right feet during the gait cycle, the differences in the key gait parameters of the left and right feet are quantitatively calculated to evaluate the overall symmetry. High symmetry indicates good gait stability and coordinated movement, while low symmetry usually indicates health problems, such as uneven lower limb strength or foot injuries.

[0081] In one embodiment, the algorithm unit includes a second preset algorithm for identifying an abnormal pressure state, and the second preset algorithm is a machine learning algorithm. The abnormal pressure state includes center of gravity shift, abnormal pressure distribution, unsteady gait, excessive internal or external rotation, or gait asymmetry, etc. The second preset algorithm identifies the plantar pressure information exceeding the abnormal pressure threshold as an abnormal pressure state. When the system detects an abnormal gait of the user, it will remind the user through a feedback mechanism to prompt the user to adjust the posture or activity mode in time to prevent plantar health problems or further injuries caused by long-term abnormal gait.

[0082] Specifically, center of gravity shift means that the center of gravity of the human body is not evenly distributed in the support area of the sole, which may lead to a decrease in body stability and an increased risk of injury. The system can analyze the movement trajectory of the center of pressure during the user's walking. The trajectory should be evenly distributed near the mid-axis of the sole from the heel (initial contact) to the forefoot (push-off phase). By calculating the average distance of the center of pressure trajectory deviating from the mid-axis of the sole and the angle change with the ideal mid-axis of the sole through the gait metrics, if an abnormal shift of the center of gravity in the gait is detected and the distance and angle exceed the abnormal pressure threshold, it is determined as a center of gravity shift, which may be caused by unbalanced foot strength or unsteady gait.

[0083] Abnormal pressure distribution includes excessive or insufficient pressure. The plantar pressure should change dynamically during the gait cycle and show a reasonable distribution. If the pressure in some areas is too high, it may mean that the user has an abnormal gait or poor posture, indicating foot injuries or plantar structure problems such as plantar fasciitis and metatarsal fractures. If the pressure in some areas is too low or completely absent, especially after long-term activities, this may also mean that the user has an incorrect gait, posture or potential plantar health problems such as fallen arches or unsteady gait. When a certain area continuously bears high pressure exceeding the abnormal pressure threshold (common in abnormal gait or exertion), or when the instantaneous pressure borne by a certain area exceeds the abnormal pressure threshold (common in strenuous exercise or accidental force), the system will identify it as an abnormal pressure distribution.

[0084] Unsteady gait refers to the situation where the user shows poor balance, abnormal gait or unstable posture when walking. Through the gait metrics and gait characteristics, when the offset value exceeds the abnormal pressure threshold, the system can detect and identify the unstable rhythm or abnormal stride change of the gait, so as to identify whether the user has a problem of unsteady gait, which is particularly important in rehabilitation training or health monitoring of the elderly.

[0085] Overpronation refers to the excessive pressure on the inner side of the foot (big toe and arch) when the user walks, with relatively low pressure on the outer side of the sole. It is usually accompanied by a collapsed arch (i.e., flat feet) or muscle strength imbalance. Over-supination refers to the excessive pressure on the outer side of the foot (little toe and outer side of the heel) when the user walks, with insufficient pressure on the inner side of the sole. It is more common in patients with high arches or unstable ankles. By comparing the pressure distribution ratio between the inner and outer sides of the sole to determine whether it is balanced, or by analyzing the deviation of the center of gravity transfer trajectory in the gait indicators, the dynamic trend of in- and out-rotation can be evaluated. When the abnormal pressure threshold is exceeded, it is identified as an abnormal pressure state. If over-in- and out-rotation are detected, it may mean that the user has incorrect posture or asymmetric loading conditions;

[0086] Gait asymmetry refers to the situation where key parameters such as step length, step speed, contact time with the ground, and pressure distribution of the left and right feet are significantly different during the user's walking process. By comparing the plantar pressure information of each area of the left and right feet, when the deviation degree exceeds the abnormal pressure threshold, it is identified as an abnormal pressure state. Gait asymmetry may cause chronic arthritis, muscle strength imbalance, and compensatory pain, etc.

[0087] Among them, the abnormal pressure threshold can be custom-set and adaptively adjusted dynamically based on the user's historical data and the plantar pressure information to meet the personalized needs of different user groups, learn the user's daily activity patterns as the usage time increases, and adaptively adjust according to different user needs. The normal pressure ranges of athletes and the elderly are significantly different. The system custom-sets and learns the user's activity patterns and pressure data during subsequent use to dynamically adjust the threshold to ensure more personalized and accurate abnormal pressure detection.

[0088] For example, for athletes, the system initially appropriately increases the pressure threshold to adapt to greater plantar loads. When athletes are undergoing high-intensity training, the system also correspondingly increases the pressure threshold to avoid excessive feedback interference caused by frequent movements. For the elderly, the system initially sets a lower threshold to detect plantar health problems earlier. For rehabilitation patients, the system initially reduces the threshold to ensure that any slight abnormal pressure changes can be detected and fed back in a timely manner. Especially in the early rehabilitation stage, the plantar pressure distribution of patients may be unstable, and the system automatically increases the feedback sensitivity to help patients adjust their postures in a timely manner. As the gait and plantar health status of rehabilitation patients gradually change, this system can automatically track the rehabilitation progress of patients, gradually increase the pressure threshold, and adjust the parameters of pressure monitoring and feedback, enabling patients to gradually adapt to normal gait and activity intensity and helping patients recover faster and more safely. For users with gradually emerging abnormal pressure states, the system can provide early warnings for users through trend analysis, helping users take early actions to prevent the further deterioration of health problems. When users suddenly accelerate or change their gait, the system quickly adjusts the analysis model of pressure data to avoid false alarms caused by drastic gait changes.

[0089] In one embodiment, the algorithm unit further includes a third preset algorithm. Through the third preset algorithm, a personalized plantar pressure health report is generated based on user historical data, the results of the first preset algorithm, and the results of the second preset algorithm. The plantar pressure health report is transmitted to an external device through the wireless communication module. The plantar pressure health report includes the abnormal pressure state, the plantar pressure distribution map and the trend of plantar pressure changes, the gait metrics and gait characteristics, personalized health suggestions, and a long-term health trend analysis report.

[0090] Specifically, the personalized health suggestions give rehabilitation training suggestions, gait adjustment suggestions, or health warnings by deeply analyzing the detection results of abnormal pressure states. This function is particularly applicable to patients, athletes, or elderly groups that require long-term monitoring. For long-term users, the system can also track changes in health status and generate a long-term health trend analysis report to help users detect gait abnormalities or foot problems earlier.

[0091] In the rehabilitation training scenario, the system can monitor the gait changes of rehabilitation patients in real time, judge the rehabilitation progress, and adjust the training plan according to the actual situation. In the sports monitoring scenario, the system can be used for gait optimization of athletes, providing personalized training guidance for athletes by analyzing gait characteristics and reducing the risk of sports injuries.

[0092] In one embodiment, the algorithm unit further includes a fourth preset algorithm for generating an adjustment instruction and transmitting it to the sensing module.

[0093] Specifically, when the plantar pressure detection system is started, the data processing module will perform air pressure calibration to ensure that the initial air pressure of all airbags is within the standard range. By analyzing whether the plantar pressure information is within the preset standard range, when the air pressure of some of the airbags is lower or higher than the standard value, an adjustment instruction is generated, so that the sensing module inflates or deflates the air pressure in the airbag to ensure that the airbag is in an appropriate working state and avoid data errors caused by uneven air pressure in the airbag; during the operation of the plantar pressure detection system, that is, when the user is walking or exercising, the data processing module will continuously monitor the air pressure state of each airbag and generate an adjustment instruction according to the real-time pressure change trend to dynamically adjust the pressure in the airbag. When it is detected that the air pressure of the airbag fluctuates greatly due to long-term use or the influence of different gait pressures, the system will automatically adjust to keep the air pressure in the airbag stable and ensure that the system always maintains the best pressure monitoring state, especially when the user uses it for a long time or switches between different gaits.

[0094] In one embodiment, the first preset algorithm, the second preset algorithm, the third preset algorithm, and the fourth preset algorithm can all be adaptively adjusted by the user to adapt to the usage habits and gait characteristics of different users, which makes the system applicable not only to healthy people but also to users with special gait requirements such as rehabilitation patients and the elderly.

[0095] Furthermore, the system can identify the differences in pressure distribution under different activity states of the user. For example, the pressure distribution on the sole of the foot is different in different states such as standing, walking, and running. The system can adaptively adjust the parameters in the algorithm unit according to different activity states to ensure accurate analysis in various states.

[0096] The wireless communication module is connected to an external device or the cloud through a wireless communication protocol such as Bluetooth or Wi-Fi to ensure the stability and real-time nature of data transmission. By transmitting the real-time plantar pressure information and the plantar pressure health report to the external device or the cloud, it is convenient for the user to remotely monitor. By transmitting the user feedback input by the user from the external device or the cloud to the data processing module, personalized adjustment of the parameters in the algorithm unit by the user is realized;

[0097] Specifically, the user can view real-time plantar pressure distribution maps, plantar pressure change trends, gait metrics, gait characteristics, and abnormal pressure status information through the external device or the cloud. The user can review the user's historical data at any time for comparative analysis. Through the external device or the cloud, the user can further analyze the data and generate detailed health advice or training programs. For example, a rehabilitation therapist can adjust a patient's training plan based on a plantar pressure health report, and an athlete can optimize their gait and sports performance based on a plantar pressure health report.

[0098] Among them, the external device includes other smart devices such as smartphones and tablets. Wireless connection can not only achieve real-time data transmission but also facilitate data synchronization with a health management platform or a rehabilitation monitoring system, sharing the data with medical staff or rehabilitation trainers, realizing remote health monitoring and rehabilitation guidance. Medical staff can also monitor the plantar pressure changes of patients in real time and adjust the rehabilitation plan in a timely manner to ensure that patients train within a safe range.

[0099] The real-time feedback module is used to provide feedback on the abnormal pressure status to the user when an abnormal pressure status is detected. The ways of the abnormal pressure status feedback include vibration, sound, or visual feedback. This immediate feedback mechanism can effectively prevent potential injuries to the plantar surface. Especially during exercise, when the user's gait or posture deviates from the normal range, the system can intervene in a timely manner to avoid damage to the plantar health caused by long-term improper postures.

[0100] Furthermore, the user can customize on the external device or have a professional help set and adjust the ways, intensities, sensitivities, and frequencies of the abnormal pressure status feedback, and transmit them to the real-time feedback module through the wireless communication module. The real-time feedback module makes adjustments to meet the user's personal preferences or scenario requirements.

[0101] Among them, in terms of the feedback method, sound feedback is suitable for receiving voice guidance in a quiet environment. When choosing sound feedback, the user can adjust the feedback intensity according to the ambient noise level; visual feedback is suitable for occasions where the user is not sensitive to hearing or the vibration feedback is not obvious, such as reminding the user through the flashlight or screen prompt of the mobile phone.

[0102] In terms of the feedback intensity, it can be customized according to the severity of the pressure abnormality or the activity scenario. For example, when severe pressure is detected, the feedback intensity will increase to attract the user's attention. Vibration feedback is suitable for dynamic scenarios. For example, the user can choose a stronger vibration feedback during exercise and a relatively mild vibration prompt during daily walking.

[0103] In terms of feedback sensitivity and frequency, a relatively high sensitivity can be set during rehabilitation training so that a prompt can be received even when there is a slight pressure abnormality. During daily activities, the user may wish to reduce the feedback sensitivity and frequency and only receive a reminder when there is a severe pressure abnormality. During high-intensity training, athletes hope to set a lower sensitivity to avoid frequent prompts.

[0104] Specifically, the vibration feedback is realized by a vibration motor embedded in the shoe. When the system detects an abnormal pressure state, it triggers vibration to remind the user to immediately adjust the gait or posture. The sound feedback is realized by an external device. When an abnormal pressure is detected, the system sends a signal to the external device through wireless connection, and the external device gives a sound feedback to remind the user to pay attention to the pressure abnormality. The visual prompt is realized by the external device, such as a flashing light or a screen alarm, to remind the user to make adjustments.

[0105] The power management module adopts a low-power design, including a battery pack, a power monitoring circuit, and an intelligent power controller. The battery pack is used to provide power. The power monitoring circuit is used to monitor the power state of the system in real time. The intelligent power controller is used to control the power consumption of the plantar pressure detection system and extend the battery life of the plantar pressure detection system.

[0106] Specifically, through the power monitoring circuit, when the battery power is lower than the set threshold, that is, when the power is insufficient, the system will give a low-power warning in advance to prompt the user to charge and ensure the continuity of the system operation.

[0107] The intelligent power controller automatically adjusts the power consumption according to the working state of the system. The working state of the system includes a standby state (when the user does not move for a long time) and an action state (when the user starts walking or exercising). The power management module enters the low-power mode in the standby state of the system. The sensing module, the data processing module, the wireless communication module, and the real-time feedback module will all enter the preset low-power mode to reduce energy consumption. Among them, the air pressure sensor will reduce the acquisition frequency and reduce the power consumption to ensure that the system can operate continuously for a long time. The power management module resumes the normal working mode in the action state of the system, and the system will resume high-frequency acquisition and processing to ensure the real-time nature of gait analysis. Through the low-power design, it is ensured that this application has low energy consumption characteristics during long-term operation, so as to extend the battery life and thus extend the battery life of the plantar pressure detection system to meet the continuous monitoring needs of users.

[0108] The second aspect of this application proposes a plantar pressure detection method based on an air pressure sensor and an airbag. The flow chart of the method is as Figure 2 shown, and it specifically includes:

[0109] The sensing module senses the plantar pressure, obtains pressure data and synchronously transmits it to the data processing module, and adjusts the air pressure inside each of the airbags according to an adjustment instruction. The sensing module includes a plurality of independently operating airbags, a plurality of air pressure sensors, an air pump, and a plurality of air valves;

[0110] The data processing module receives and preprocesses the pressure data to obtain plantar pressure information, generates a plantar pressure health report and the adjustment instruction. The data processing module is connected to the air pressure sensors and includes a preprocessing unit and an algorithm unit;

[0111] The wireless communication module transmits the real-time plantar pressure information and the plantar pressure health report to an external device or the cloud, and transmits the user feedback input by the user from the external device or the cloud to the data processing module;

[0112] The real-time feedback module provides an abnormal pressure state feedback to the user when an abnormal pressure state is detected. The ways of the abnormal pressure state feedback include vibration, sound or visual feedback;

[0113] The power management module provides power, monitors the power state of the system in real time, and controls the power consumption of the plantar pressure detection system.

[0114] Among them, each of the airbags is respectively embedded in a key pressure-bearing area in the sole. The key pressure-bearing area corresponds to the key force-bearing points on the sole, including the heel area, the forefoot area, the outer foot area, and the metatarsal arch area.

[0115] The above are only the preferred embodiments of the present application and are not used to limit the present application. Those skilled in the art should be able to realize that according to the basic method principles provided by the present application and in combination with the actual situation, there can be many examples. Without sufficient creative labor, they should all be within the protection scope of the present application.

[0116] In the description of this specification, the description referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0117] It should also be noted that in this specification, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or apparatus comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or apparatus.

Claims

1. A plantar pressure detection system based on an air pressure sensor and an airbag, characterized in that: The system is embedded in the sole, and includes: a sensor module, a data processing module, a wireless communication module, a real-time feedback module and a power management module. The sensing module includes a plurality of independently working air bags, a plurality of air pressure sensors, an air pump and a plurality of air valves, and is used to sense the pressure of the sole of the foot, obtain the pressure data and transmit it synchronously to the data processing module, and adjust the air pressure inside each of the air bags according to the adjustment instructions; The data processing module is connected to the air pressure sensor, and includes a preprocessing unit and an algorithm unit, which are used to receive and preprocess the pressure data to obtain plantar pressure information, generate a plantar pressure health report and the adjustment instruction; The wireless communication module is used to transmit the real-time plantar pressure information and the plantar pressure health report to an external device or a cloud, and transmit the user feedback input by the user from the external device or the cloud to the data processing module; The real-time feedback module is used to provide abnormal pressure state feedback to the user when an abnormal pressure state is detected, and the abnormal pressure state feedback includes vibration, sound or visual feedback; The power management module is used to provide power, monitor the power status of the system in real time, and control the power consumption of the plantar pressure detection system.

2. The plantar pressure detection system based on air pressure sensor and airbag according to claim 1 is characterized in that: Each of the airbags corresponds to a key pressure area embedded in the sole, and the key pressure areas correspond to key force points on the sole of the foot, including the heel area, the forefoot area, the lateral area of ​​the foot and the plantar arch area.

3. The plantar pressure detection system based on air pressure sensor and airbag according to claim 1, characterized in that: Each of the airbags corresponds to one or more of the air pressure sensors; the sensing module also includes a weighing sensor; each time the data processing module processes the plantar pressure information, plantar pressure health report and adjustment instructions, they are stored in the system's memory or in the cloud as user historical data.

4. The plantar pressure detection system based on air pressure sensor and airbag according to claim 1, characterized in that: The algorithm unit includes a first preset algorithm, which is used to generate a plantar pressure distribution map and a plantar pressure change trend, calculate key gait indicators, and extract gait characteristics; the gait indicators include the pressure center, the center of gravity transfer trajectory, and the plantar contact area and contact time; the gait characteristics include stride, step speed, plantar landing method and gait symmetry.

5. The plantar pressure detection system based on air pressure sensor and airbag according to claim 4, characterized in that: The algorithm unit further includes a second preset algorithm for identifying an abnormal pressure state; The second preset algorithm is a machine learning algorithm; The abnormal pressure state includes center of gravity shift, abnormal pressure distribution, unstable gait, excessive internal and external rotation or asymmetric gait, and the second preset algorithm identifies the plantar pressure information exceeding the abnormal pressure threshold as the abnormal pressure state; The abnormal pressure threshold is adaptively and dynamically adjusted based on the user's historical data and the plantar pressure information.

6. The plantar pressure detection system based on air pressure sensor and airbag according to claim 5, characterized in that: The algorithm unit further includes a third preset algorithm, through which a personalized plantar pressure health report is generated based on user historical data, a result of the first preset algorithm and a result of the second preset algorithm, and the plantar pressure health report is transmitted to an external device through the wireless communication module; The plantar pressure health report includes the abnormal pressure state, the plantar pressure distribution diagram and the plantar pressure change trend, the gait index and gait characteristics, personalized health advice, and a long-term health trend analysis report.

7. A plantar pressure detection system based on an air pressure sensor and an airbag according to claim 1, characterized in that: The algorithm unit also includes a fourth preset algorithm for generating the adjustment instruction and transmitting it to the sensor module, and adjusting the air pressure of the airbag based on the adjustment instruction through the air pump and the multiple air valves.

8. The plantar pressure detection system based on air pressure sensor and airbag according to claim 1, characterized in that: The power management module adopts a low-power design and includes a battery pack, a power monitoring circuit and an intelligent power controller.

9. A method for detecting plantar pressure based on an air pressure sensor and an airbag, characterized in that: The method comprises: The sensing module senses the pressure of the sole of the foot, obtains the pressure data and transmits it synchronously to the data processing module, and adjusts the air pressure inside each airbag according to the adjustment instruction, wherein the sensing module includes a plurality of independently working airbags, a plurality of air pressure sensors, an air pump and a plurality of air valves; The pressure data is received and preprocessed by the data processing module to obtain plantar pressure information, and a plantar pressure health report and the adjustment instruction are generated. The data processing module is connected to the air pressure sensor and includes a preprocessing unit and an algorithm unit; The real-time plantar pressure information and the plantar pressure health report are transmitted to an external device or a cloud through a wireless communication module, and the user feedback input by the user from the external device or the cloud is transmitted to the data processing module; Providing abnormal pressure state feedback to the user through the real-time feedback module when an abnormal pressure state is detected, wherein the abnormal pressure state feedback includes vibration, sound or visual feedback; The power management module provides power, monitors the power status of the system in real time, and controls the power consumption of the plantar pressure detection system.

10. A method for detecting plantar pressure based on an air pressure sensor and an airbag according to claim 9, characterized in that: Each of the airbags corresponds to a key pressure area embedded in the sole, and the key pressure areas correspond to key force points on the sole of the foot, including the heel area, the forefoot area, the lateral area of ​​the foot and the plantar arch area.

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