CN120036766A - Plantar pressure detection system and plantar pressure detection method based on air pressure sensor and air bag - Google Patents

Abstract

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

Description

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

Technical Field

The application relates to the technical field of plantar pressure detection, in particular to a plantar pressure detection system and method based on an air pressure sensor and an air bag.

Background

In the field of plantar health monitoring, plantar pressure detection technology is widely applied to gait analysis, movement monitoring, rehabilitation training and other scenes, and accurate detection of plantar pressure distribution can not only help prevent foot diseases, but also improve gait and promote movement performance, and provides important data support in rehabilitation therapy. Conventional plantar pressure detection systems generally rely on rigid sensors, which have many limitations in practical applications, for example, the hard material properties of the rigid sensors determine that they can affect wearing comfort and even normal gait, especially for elderly, chronically ill patients or users in convalescence, and that these sensors have inadequate measurement accuracy in the face of complex and varied gait and terrain.

In addition, the plantar pressure detection system in the prior art generally lacks a real-time feedback and early warning mechanism, when the plantar pressure distribution of a user is abnormal, a prompt can not be provided in an abnormal initial stage, so that the optimal opportunity for early intervention is delayed, and the delayed monitoring mode obviously cannot meet the increasing health management requirements.

In view of this, there is a need to provide a plantar pressure monitoring scheme that combines high accuracy, real-time and comfort.

Disclosure of Invention

Based on the application requirements and the technical background, in order to solve the technical problem that the plantar pressure monitoring cannot be simultaneously carried out in real time, comfortably and with high precision in the prior art, the application adopts the following technical scheme:

The first aspect of the application provides a plantar pressure detection system based on an air pressure sensor and an air bag, which is embedded into a sole and comprises a sensing module, a data processing module, a wireless communication module, a real-time feedback module and a power management module,

The sensing module comprises 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 for sensing plantar pressure, obtaining pressure data, synchronously transmitting the pressure data to the data processing module and adjusting the air pressure inside each air bag according to an adjusting instruction;

The data processing module is connected with the air pressure sensor and comprises a preprocessing unit and an algorithm unit, and is used for receiving and preprocessing the pressure data to obtain plantar pressure information and generating plantar pressure health reports and the adjusting instructions;

The wireless communication module is used for transmitting the real-time plantar pressure information and the plantar pressure health report to external equipment or a cloud end, and transmitting user feedback input by a user from the external equipment or the cloud end to the data processing module;

The real-time feedback module is used for providing abnormal pressure state feedback to a user when an abnormal pressure state is detected, and the mode of the abnormal pressure state feedback comprises vibration, sound or visual feedback;

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.

Further, each bladder corresponds to a critical compression area embedded in the sole, which corresponds to a critical plantar compression point, including a heel area, a forefoot area, a lateral plantar area, and a plantar arch area, respectively.

Further, each air bag corresponds to one or more air pressure sensors, the sensing module further comprises a weighing sensor, and the plantar pressure information, the plantar pressure health report and the adjusting instruction which are obtained through processing by the data processing module every time are stored in a memory or a cloud of the system as user historical data.

Further, the algorithm unit comprises a first preset algorithm, is used for generating a plantar pressure distribution map and a plantar pressure change trend, calculating key gait indexes and extracting gait characteristics, wherein the gait indexes comprise a pressure center, a gravity center transfer track, plantar touchdown area and touchdown time, and the gait characteristics comprise stride, pace, plantar touchdown mode and gait symmetry.

Further, the algorithm unit further comprises a second preset algorithm for identifying an abnormal pressure state;

The second preset algorithm is a machine learning algorithm;

The abnormal pressure state comprises gravity center deviation, abnormal pressure distribution, gait instability, excessive supination or gait asymmetry and the like, and the second preset algorithm identifies the plantar pressure information exceeding the abnormal pressure threshold value as the abnormal pressure state;

The abnormal pressure threshold is adaptively dynamically adjusted based on user history data and the plantar pressure information.

Further, the algorithm unit further comprises a third preset algorithm, wherein the third preset algorithm is used for generating a personalized plantar pressure health report based on the user history data, the result of the first preset algorithm and the result of the second preset algorithm, and the plantar pressure health report is transmitted to external equipment through the wireless communication module;

The plantar pressure health report includes the abnormal pressure state, the plantar pressure distribution map and plantar pressure change trend, the gait indicators and gait characteristics, personalized health advice, and long-term health trend analysis report.

Further, the algorithm unit further comprises a fourth preset algorithm for generating the adjusting instruction and transmitting the adjusting instruction to the sensing module, and the air pressure of the air bag is adjusted based on the adjusting instruction through the air pump and the air valves.

Further, the power management module adopts a low-power design and comprises a battery pack, an electric quantity monitoring circuit and an intelligent power controller.

The second aspect of the application provides a plantar pressure detection method based on a barometric sensor and an air bag, the method comprising:

sensing plantar pressure through a sensing module, obtaining pressure data, synchronously transmitting the pressure data to the data processing module, and adjusting air pressure inside each air bag according to an adjusting instruction, wherein the sensing module comprises a plurality of independently working air bags, a plurality of air pressure sensors, an air pump and a plurality of air valves;

The data processing module is used for receiving and preprocessing the pressure data to obtain plantar pressure information and generating plantar pressure health reports and the adjusting instructions, and is connected with the air pressure sensor and comprises a preprocessing unit and an algorithm unit;

Transmitting the real-time plantar pressure information and the plantar pressure health report to external equipment or a cloud end through a wireless communication module, and transmitting user feedback input by a user from the external equipment or the cloud end to the data processing module;

providing abnormal pressure state feedback to a user when an abnormal pressure state is detected through a real-time feedback module, wherein the mode of abnormal pressure state feedback comprises vibration, sound or visual feedback;

and providing power through a power management module, monitoring the electric quantity state of the system in real time, and controlling the power consumption of the plantar pressure detection system.

Further, each bladder corresponds to a critical compression area embedded in the sole, which corresponds to a critical plantar compression point, including a heel area, a forefoot area, a lateral foot area, and a plantar arch area.

Compared with the prior art, the application has the beneficial effects that:

The plantar pressure detection system and the plantar pressure detection method based on the air pressure sensor and the air bag, provided by the application, ensure the adaptability and comfortableness of the system to the foot in the use process by embedding the flexible air bag into the sole, especially avoid the problem of local pressure centralization possibly caused by the rigid sensor in long-time use, improve the wearing comfortableness of users, realize high-precision monitoring of plantar pressure by sensing the air pressure change in the air bag through the air pressure sensor, more effectively cope with complex topography and gait change, provide more stable and reliable measurement data, provide higher precision and sensitivity than the traditional rigid pressure sensor through the combined design of the air pressure sensor and the air bag, and especially maintain stable measurement performance under complex conditions, and provide instant feedback and early warning functions (such as vibration, sound or visual prompt) and health care guidance based on the self requirements of users by monitoring the plantar pressure distribution and change in real time and carrying out algorithm analysis based on real-time data, so as to generate plantar pressure distribution map, identify plantar pressure characteristics and abnormal plantar pressure state, and provide real-time health care and health care instruction for users, and provide the user with the health care system and the user with the special performance and the health management requirements. .

The plantar pressure detection system and the plantar pressure detection method based on the air pressure sensor and the air bag can be used for monitoring gait changes of patients in real time in the rehabilitation training field, assisting rehabilitation therapy, can be applied to gait monitoring of rehabilitation patients, can help rehabilitation therapists to evaluate the recovery progress of the patients by tracking the pressure changes and the gait characteristics in real time, and provide a personalized training scheme, can help athletes to optimize the gait and reduce the risk of sports injury when used in the sports monitoring field, can provide detailed gait analysis reports for athletes, can help the athletes to optimize running or walking postures and avoid sports injury caused by bad gait, can also be used for detecting gait abnormality, plantar pressure concentration problems and the like in the health evaluation field, and can detect early health problems such as aged gait instability, diabetic foot ulcer risks and the like by analyzing gait abnormality.

Drawings

In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic diagram of a plantar pressure detection system based on an air pressure sensor and an air bag provided by the application;

fig. 2 is a schematic flow chart diagram of a sole pressure detection method based on an air pressure sensor and an air bag.

Detailed Description

The present application provides a plantar pressure detection system and a plantar pressure detection method based on an air pressure sensor and an air bag, and in order to more specifically describe the present application, the following detailed description is given with reference to the accompanying drawings and specific examples, and it should be understood that the specific embodiments described herein are merely for explaining the present application and are not limiting the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

The first aspect of the application provides a plantar pressure detection system based on an air pressure sensor and an air bag, wherein the system is embedded into a sole, and a schematic diagram is shown in fig. 1, and the plantar pressure detection system specifically comprises a sensing module, a data processing module, a wireless communication module, a real-time feedback module and a power management module;

The sensing module comprises a plurality of independently working air bags, a plurality of air pressure sensors, an air pump and a plurality of air valves, wherein the air bags are used for sensing the pressure of the sole of a foot, the air pressure sensors are used for detecting the air pressure in the air bags, obtaining pressure data and synchronously transmitting the pressure data to the data processing module, and the air pump and the air valves are used for adjusting the air pressure in each air bag according to an adjusting instruction;

The flexible high-elasticity material has the characteristics of high elasticity, wear resistance and portability, can bear repeated pressure effects, can deform according to the sole shape of a user and the received sole pressure change, can better adapt to the shape and movement of the sole, ensures that the pressure applied by different areas of the sole can be accurately perceived through the deformation of the air bag, and simultaneously keeps comfort and durability in long-time wearing. Compared with the traditional rigid pressure sensor, the air bag of the flexible structure is softer and is attached to the foot through gas conduction pressure, so that the pressure change of the sole can be distributed and perceived more uniformly, and the interference to the gait of a user is reduced.

In one embodiment, each bladder corresponds to a critical compression area embedded in the sole that corresponds to a critical plantar compression point, including a heel area, a forefoot area, a lateral plantar area, and a plantar arch area, respectively.

The heel area is used for detecting pressure change of the heel, the heel is an area bearing the maximum pressure in gait, the main vertical load of a human body is borne when the human body stands and walks, particularly, the pressure is concentrated and the impact force is larger at the moment of landing, so that the air bag arranged in the heel area is larger and thicker, has high buffering and shock absorbing performance, reduces the impact force born by the heel, protects joints and vertebrae of the foot, and accurately monitors the pressure change of the area;

The front plantar region is used for detecting pressure change of the front sole, the front plantar region provides thrust output when a user walks or runs, the stress change is dynamic and complex, and support and flexibility are needed, so that the air bags arranged in the front plantar region are thinner, are designed to be flat or strip-shaped, are arranged more flexibly, and provide accurate pressure sensing and moderate supporting force;

The outer foot region is used for detecting pressure change of the outer foot side, the outer foot side mainly bears dynamic load in the walking process, particularly in the foot transition stage of foot force from heel to forefoot, the balance of gait of a user and whether the problem of eversion or varus of the foot is solved by analyzing the stress of the outer foot region, and the air bag arranged in the outer foot region is designed to be of an elongated shape, covers the outer foot edge region and is consistent with the trend of the sole force line, so that stability and supporting force are provided, and rollover or sprain is avoided;

The plantar arch area is used for detecting pressure change of the foot arch, the plantar arch (namely the foot arch) is an important buffer structure of the foot sole, the plantar arch can help disperse pressure and maintain stability of the foot, the health state of the foot arch can be reflected through analyzing the stress of the plantar arch area, the plantar arch area has an important effect on evaluating structural abnormality or damage of the foot, particularly for flat feet or high-arch users, an air bag arranged in the plantar arch area is designed to be arched and matched with the shape of the foot arch, and a key supporting part of the plantar arch is covered, so that the foot arch collapse caused by long-time load is prevented.

Further, the key compression area further comprises a toe area for detecting the pressure change of the toe, the toe has smaller pressure in gait, the auxiliary support and balance function in the propulsion action are achieved, the air bag arranged in the toe area is of a slender and flexible small structure, the air bag is matched with the toe in shape, the air bag is thinner, and the high sensitivity is emphasized, so that the slight pressure change of the toe area is captured.

The size, thickness and shape of the air bag are adjustable, and can be adjusted according to the set key compression area and the actual application scene so as to effectively balance the relation among detection precision, functionality and user experience. For example, in sports or rehabilitation training scenarios, the sole of the foot can bear higher impact force and dynamic load, and meanwhile accurate pressure detection is required, the air bag is designed to be thicker and more solid to contain more gas and distribute sole pressure more uniformly, so that more comprehensive pressure sensing and better buffering and damping effects are provided, in daily wearing scenarios, users pay more attention to the portability, comfort and appearance of shoes, the requirement is mainly focused on basic health monitoring, and the air bag is designed to be lighter and thinner, so that the wearing comfort and the appearance of the shoes are ensured to be attractive.

In practical application, the air bags are arranged by combining the sole shape and the mechanical characteristics, so that the sole structure of different users can be flexibly adapted, when the users walk or stand, the pressure applied by different areas of the sole causes the air pressure change in the air bags, so that the air bags can accurately reflect the corresponding sole pressure change, the accuracy of sole pressure sensing is improved, and the sole support and protection functions of the shoes are improved.

In one embodiment, each air bag corresponds to one or more air pressure sensors, and is used for detecting air pressure changes in the air bags, converting the air pressure changes into electric signals, obtaining pressure data, synchronously transmitting the pressure data to the data processing module for processing, and ensuring consistency and time matching of the data, so that real-time monitoring of pressure distribution of each area of the sole is realized. Specifically, when each air bag is independently connected with one air pressure sensor, a sole pressure monitoring unit for accurate partition monitoring is formed, when each air bag is connected with a plurality of air pressure sensors, multidimensional pressure data from the same area can be collected, the plurality of air pressure sensors can be distributed in different directions and positions, the coverage range and the sensitivity of monitoring are enhanced, dynamic pressure fluctuation and directional change are captured, and even if one sensor fails, the redundant design can ensure that the system functions are normal.

The air pressure sensor is connected with the air bag through a flexible air pipe, so that the air pressure change in the air bag can be transmitted to the air pressure sensor in real time. The sole pressure is transmitted to the air pressure sensor through the air pipe, so that the deformation of the sole can be absorbed, the direct stress of the air pressure sensor is effectively avoided, and the damage of the sensor caused by direct extrusion or impact is reduced.

In practical application, each time a user walks or stands, the pressure in different areas of the sole can cause the air pressure in the air bag to change, the air pressure sensor can capture the slight change of the air pressure and convert the air pressure change into an electric signal (namely pressure data) to be output, the electric signal strength is in direct proportion to the air pressure change, and the pressure applied by each area of the sole is reflected, so that accurate data support is provided for subsequent gait analysis.

The air pressure sensor has high sensitivity, high precision and high sampling frequency, and can detect tiny air pressure change in the air bag in real time, so that tiny change of plantar pressure of a user in the walking or movement process is accurately captured, and particularly tiny pressure fluctuation of an athlete in the rapid running process is accurately captured. In one embodiment, the barometric sensor is of a miniaturized design with a sampling frequency of up to several hundred hertz, ensuring that small changes per gait cycle can be captured without affecting wear comfort.

The material of the air pressure sensor is anti-fatigue and high-temperature resistant, has a moisture-proof coating design, ensures that the material can still keep high sensitivity under repeated pressure bearing (such as hundreds of pressure bearing per minute when running) and complex environments (such as high-temperature, humid or severe sports scenes), ensures continuous and accurate monitoring data, and prevents damage caused by external impact or moisture invasion.

In one embodiment, the air pump and the air valves are used for adjusting the air pressure in the air bag according to the adjusting instruction, so that the air bag is ensured to be in a standard working air pressure range, measurement errors caused by too low or too high air pressure are avoided, and therefore the detection precision is improved.

Specifically, when the system is started, the air bag is under initial air pressure, after the system is worn by a user, the air bag is stepped on, the air pressure inside the air bag rises, the air pressure sensor acquires pressure data, and as the air bag slowly leaks air, the initial air pressure of the air bag drops, so that deviation occurs in a plurality of measurement results, and at the moment, the air pressure of the air bag is regulated to the initial air pressure through the air pump and the air valves. The air bags are connected through air pipes, so that air between the air bags can flow, the air pump compresses or sucks air, the air valve regulates the air flow between the air pump and the air bags, the air bags are inflated or deflated, the air pressure is dynamically regulated, and each air bag is ensured to be in an optimal working state (namely, the air pressure in the air bags is initial air pressure).

In one embodiment, the sensing module further comprises a weighing sensor, the pressure data further comprises weight data, the weighing sensor is located below the air bag and used for detecting weight distribution and change of each sole region, and the weight data are obtained. The weighing sensor and the air pressure sensor are mutually complemented, and after the weight data are combined with the output of the air pressure sensor, more comprehensive pressure analysis data can be provided for the system, so that the pressure distribution of each region of the sole can be accurately analyzed, and the accurate detection of the pressure distribution of each region of the sole can be further realized.

The weighing sensor is firm and durable, can bear the weight pressure of different users, and has high sensitivity and accuracy.

Further, the air bag, the air pressure sensor, the air pump and the air valve are arranged to be detachable, and a user maintains, replaces and upgrades functions, for example, when the air bag leaks air due to abrasion, or the performance of the air pump is reduced, the user can directly detach and replace the air bag, and the user can conveniently expand the multi-point monitoring capability by increasing the number of the air bags and the air pipes.

The data processing module is connected with the air pressure sensor and comprises a preprocessing unit and an algorithm unit, and is used for receiving and preprocessing the pressure data to obtain plantar pressure information and generating plantar pressure health reports and the adjusting instructions;

further, each time the plantar pressure information, the plantar pressure health report and the adjustment instruction obtained by processing by the data processing module are stored in a memory or a cloud of the system as the user history data.

The data processing module receives the pressure data in real time through the high-speed interface, and ensures that the pressure changes of all plantar regions are synchronously recorded. The high speed interface ensures that pressure data is transmitted to the data processing module in millisecond-scale time, avoids delays, and enables data to be received and analyzed in real time in response to dynamic gait and pressure changes of the user.

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

Specifically, the preprocessing step of filtering is used for reserving useful frequency components in the data, removing unnecessary noise or interference signals, and ensuring the accuracy of the data, and comprises low-pass filtering, kalman filtering and adaptive filtering;

The low-pass filtering is used for eliminating high-frequency noise through low-frequency signals, because in plantar pressure detection, a real pressure signal is mainly concentrated in a low frequency band (such as the change of a gait cycle), high-frequency components are mostly noise or interference, and the threshold value of a filter used for the low-pass filtering can be adjusted according to application scenes;

The Kalman filtering is used for removing dynamic noise in gait monitoring, is a recursive filtering method, can estimate the optimal solution of the current state by combining current data and historical data, gradually approximates real signals by dynamically adjusting the deviation between a predicted value and an actual observed value, is applied to dynamic and complex scenes, and is particularly suitable for systems with certain randomness or process noise, such as pressure signals with continuous change of irregular movement of users;

The self-adaptive filtering is used for adjusting filtering parameters in real time according to data characteristics, the self-adaptive filter adapts to dynamic changes of signals and noise by adjusting the parameters of the filter in real time, the filtering method does not need to determine fixed filtering parameters in advance, and the self-adaptive filtering is dynamically adjusted according to environment and data characteristics, and is suitable for complex or unpredictable environments, such as users walking on uneven ground or switching different active modes rapidly, and clear signals can be obtained by the system under different gait or motion states.

Specifically, the smoothing preprocessing step is used for further eliminating fine fluctuation in the data, and generating a signal with better continuity by removing short-term random variation, so that the data can be ensured to clearly reflect gait characteristics of a user without being influenced by short-term fluctuation, including moving average and exponential smoothing;

the moving average generates a more stable curve by calculating the average value of data points in a sliding window, can realize rapid reduction of data fluctuation, and is suitable for static or medium-low frequency dynamic detection;

The exponential smoothing is used for weighting historical data, the weight of recent data is higher, a gradually-changing signal is generated, response is quicker, real-time processing can be realized, and the method is suitable for scenes with quicker gait change.

Specifically, the denoising preprocessing step is used for further eliminating random noise in the data, and meanwhile, preserving real signals to ensure smoothness and reliability of the data, including wavelet transformation;

The wavelet transformation decomposes the signal into sub-bands with different frequencies through wavelet decomposition, and rebuilds the signal after removing high-frequency noise components, so that the method is suitable for non-stationary signals, can retain more detail characteristics, and can realize fine analysis on plantar pressure change in dynamic detection.

Specifically, the calibration process is used to adjust the raw signals output by the sensors to actual physical values so as to eliminate sensor deviation and systematic errors, and ensure that each sensor can maintain accuracy under different temperature, humidity and pressure environments.

In one embodiment, the algorithm unit includes a first preset algorithm for generating a plantar pressure distribution map and a plantar pressure variation trend, calculating a key gait index, and extracting gait characteristics;

first, the first preset algorithm sums up the plantar pressure information of the plantar critical pressure areas at various time points, thereby generating the plantar pressure distribution map and the plantar pressure variation trend. The sole pressure distribution diagram and the sole pressure change trend visually show stress conditions of different areas of the sole and the change trend with time when a user walks or stands in a visual mode, and the stress and change conditions of the sole pressure are shown in a graph form, so that the pressure concentration area, the pressure deviation, the pressure abnormal points, the pressure symmetry of each area and the pressure change trend of the sole can be clearly shown;

Specifically, the pressure data is continuously collected and analyzed by a first preset algorithm, and the plantar pressure distribution map and the plantar pressure variation trend are dynamically varied. The sole pressure is not static but is dynamically changed along with the steps and movements of the user, so that the dynamic sole pressure distribution map and the sole pressure change trend can show how the pressure is transferred between different sole areas when the user walks or runs, further the gravity center change and the foot force condition of the user are analyzed, and the balance and stability of gait are helped to be identified;

Secondly, the first preset algorithm calculates gait indexes through the plantar pressure distribution diagram and the plantar pressure change trend, wherein the gait indexes comprise a pressure center, a gravity center transfer track, plantar touchdown area and touchdown time, and the gait indexes are helpful for analyzing gait health conditions of users;

The method comprises the steps of obtaining a center of gravity through dynamic calculation of the position of the center of gravity of pressure distribution, obtaining the center of pressure, wherein the center of pressure is used for representing average stress points of soles and reflecting gait stability and plantar load distribution conditions, obtaining a center of gravity transfer track through track generation and feature extraction, describing how a user transfers the center of gravity from heel to front plantar in a gait cycle, helping to analyze gait features of the user, obtaining plantar touchdown area and touchdown time through counting pressure areas and duration time when the pressure exceeds a preset grounding pressure threshold, and analyzing plantar touchdown area distribution and gait rhythm of the plantar touchdown area and the plantar touchdown time.

Finally, the first preset algorithm also extracts gait features including stride, pace, plantar strike pattern and gait symmetry through the plantar pressure distribution map and plantar pressure variation trend.

Specifically, the stride is the horizontal distance between two consecutive landings of the same side foot, reflects the rhythmicity and the movement efficiency of gait, is obtained by recording the calculation of the horizontal coordinate difference of the pressure center when the same side foot (such as the right foot) touches the ground twice, the pace speed is the number of steps completed in unit time, directly reflects the walking speed, is obtained by recording the calculation of the time interval of the two consecutive touchdown events, and can calculate the stride and the pace speed of each step by analyzing the plantar pressure change period of the user;

Plantar grounding patterns are sequences and modes for describing the contact of different areas of the sole with the ground in the gait cycle, and are determined by the sequence of pressure value changes of key stressed areas of the sole, and comprise heel grounding, front plantar grounding or full foot grounding. For example, the heel area pressure is increased first, then the front plantar area pressure is increased again, which is the heel strike mode, the front plantar area pressure is increased first, then the heel area pressure is increased again, which is the front plantar strike mode, and different strike modes may correspond to different gait problems or health conditions;

Gait symmetry is used for analyzing the pressure distribution and gait rhythm of the left and right feet, judging whether the gait of a user is symmetrical, quantitatively calculating the difference of key gait parameters of the left and right feet by combining the indexes such as the stride of the left and right feet, the ground contact time and the like in the gait cycle, evaluating the overall symmetry, wherein high symmetry indicates good gait stability, coordinated movement and low symmetry generally indicates health problems such as unbalanced lower limb strength or foot injury.

In one embodiment, the algorithm unit includes a second preset algorithm for identifying an abnormal pressure state, the second preset algorithm being a machine learning algorithm. The abnormal pressure state comprises gravity center deviation, abnormal pressure distribution, gait instability, excessive internal and external rotation or gait asymmetry and the like, the second preset algorithm identifies the plantar pressure information exceeding the abnormal pressure threshold as the abnormal pressure state, and when the system detects that the gait of the user is abnormal, the system can remind the user through a feedback mechanism so as to remind the user to adjust the posture or the activity mode in time and prevent plantar health problems or further damage caused by long-term bad gait.

Specifically, the center of gravity shift refers to that the center of gravity of the human body is not uniformly distributed in the supporting area of the sole of the foot, which may result in a decrease in body stability and an increase in risk of injury. The system can analyze the movement track of the pressure center in the walking process of a user, the track is uniformly distributed near the central axis of the sole from the heel (initial contact) to the front plantar (push-away stage), the average distance of the pressure center track from the central axis of the sole and the change of the included angle between the pressure center track and the ideal central axis of the sole are calculated through the gait index, if abnormal shift of the center of gravity in the gait is detected, the distance and the included angle exceed abnormal pressure threshold values, the gravity center shift is judged, and the gravity center shift is possibly caused by unbalanced foot strength or unstable gait;

Abnormal pressure distribution includes excessive or insufficient pressure, plantar pressure should dynamically change during the gait cycle and exhibit reasonable distribution, if the pressure in certain areas is excessive, it may mean that the user has abnormal gait or bad posture, indicating foot injury or plantar structural problems such as plantar fasciitis, metatarsal fractures, if the pressure in certain areas is too small or not at all, especially after prolonged activity, it may also mean that the user has incorrect gait, posture or potential plantar health problems such as arch collapse or gait instability. When a certain area continuously bears high pressure exceeding an abnormal pressure threshold (usually in bad gait or force), or when the instantaneous pressure borne by a certain area exceeds the abnormal pressure threshold (usually in intense exercise or unexpected force), the system can recognize the pressure as abnormal pressure distribution;

Gait instability refers to a situation where a user exhibits poor balance, abnormal gait, or unstable posture while walking. Through the gait index and the gait characteristics, when the deviation value exceeds the abnormal pressure threshold, the system can detect and identify the abnormal rhythm or abnormal stride change of the gait, so that whether the user has the problem of unstable gait or not is identified, which is particularly important in rehabilitation training or old people health monitoring;

Over pronation refers to the fact that the inside of the foot (big toe and arch) is subjected to excessive pressure while the user walks, the outside pressure of the sole is lower, usually accompanied by collapse of the arch (i.e., flat foot) or uneven muscle strength, over supination refers to the fact that the outside of the foot (little toe and outside of heel) is subjected to excessive pressure while the user walks, and the inside pressure of the sole is insufficient, mostly seen in patients with high arches or unstable ankle joints. Judging whether the pressure distribution ratio of the inner side and the outer side of the sole is balanced or analyzing the deviation of the gravity center transfer track in the gait index, evaluating the trend of the internal and external rotation states, and identifying the state as an abnormal pressure state when the trend exceeds an abnormal pressure threshold value, wherein if excessive internal and external rotation is found, the situation that the posture of a user is incorrect or asymmetric load exists can be indicated;

The gait asymmetry refers to the situation that key parameters such as stride, pace, bottoming time, pressure distribution and the like of the left foot and the right foot are obviously different in the walking process of a user, and the user can identify an abnormal pressure state by comparing plantar pressure information of each region of the plantar of the left foot and the right foot when the deviation degree exceeds an abnormal pressure threshold value. Gait asymmetry may cause chronic arthritis, unbalanced muscle strength, and compensatory pain, etc.

The abnormal pressure threshold can be set in a self-defined mode, and is self-adaptively and dynamically adjusted based on user historical data and the plantar pressure information so as to meet personalized requirements of different user groups, learn daily activity modes of users along with the increase of the use time, and self-adaptively adjust according to different user requirements. The normal pressure range of the athlete is obviously different from the normal pressure range of the old, and the system learns the activity mode and the pressure data of the user in the subsequent use process by self-defining setting, and dynamically adjusts the threshold value so as to ensure that abnormal pressure detection is more personalized and accurate.

For example, for athletes, the system initially increases the pressure threshold appropriately to accommodate the greater plantar load, while for athletes performing high-intensity training, the system also increases the pressure threshold accordingly to avoid excessive feedback interference due to frequent exercise, for elderly people, the system initially sets a lower threshold to detect plantar health problems earlier, while for rehabilitation patients, the system initially decreases the threshold to ensure that any slight abnormal pressure changes can be detected and fed back in time, especially in early rehabilitation stages, plantar pressure distribution of the patient may be unstable, the system automatically increases the sensitivity of feedback to help the patient adjust posture in time, the system can automatically track the rehabilitation progress of the patient gradually to increase the pressure threshold as the gait and plantar health conditions of the rehabilitation patient gradually change, adjust the pressure monitoring and feedback parameters, so that the patient can gradually adapt to normal gait and activity intensity to help the patient recover faster and more safely, while for users gradually developing abnormal pressure states, the system can provide early warning for the user through trend analysis to help the user to take early action to prevent health problems further, and when the user suddenly accelerates or changes in gait, the system can rapidly adjust the gait data model to avoid rapid changes.

In one embodiment, the algorithm unit further comprises a third preset algorithm by which a personalized plantar pressure health report is generated based on user history data, results of the first preset algorithm and 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 comprising the abnormal pressure state, the plantar pressure distribution map and plantar pressure change trend, the gait index and gait feature, the personalized health advice, and a long-term health trend analysis report.

Specifically, the personalized health advice gives rehabilitation training advice, gait adjustment advice or health early warning by deeply analyzing the abnormal pressure state detection result. The function is particularly suitable for patients, athletes or elderly people needing long-term monitoring, and for users with long-term use, the system can also track the change of health state, generate long-term health trend analysis reports and help users to find gait abnormalities or foot problems early.

In the sports monitoring scene, the system can be used for optimizing the gait of athletes, and provides personalized training guidance for the athletes by analyzing gait characteristics so as to reduce sports injury risks.

In one embodiment, the algorithm unit further comprises a fourth preset algorithm for generating and transmitting the adjustment command to the sensing module.

Specifically, when the plantar pressure detection system is started, the data processing module carries out air pressure calibration to ensure that the initial air pressure of all air bags is in a standard range, by analyzing whether the plantar pressure information is in the preset standard range or not, when the air pressure of some air bags is lower than or higher than the standard value, an adjusting instruction is generated, so that the sensing module inflates or deflates the air pressure in the air bags to ensure that the air bags are in a proper working state, and data errors caused by the uneven air pressure of the air bags are avoided.

In one embodiment, the first preset algorithm, the second preset algorithm, the third preset algorithm and the fourth preset algorithm can be used for adaptively adjusting parameters by users, so that the system is suitable for healthy people and users with special requirements on gait of rehabilitation patients, old people and the like.

Further, the system is able to identify pressure distribution differences in 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, and the system can adaptively adjust parameters in the algorithm unit according to different activity states, so that accurate analysis can be realized in various states.

The wireless communication module is connected with external equipment or cloud end through a Bluetooth or Wi-Fi wireless communication protocol mode to ensure stability and instantaneity of data transmission, and the real-time plantar pressure information and the plantar pressure health report are transmitted to the external equipment or cloud end so as to facilitate remote monitoring of a user;

Specifically, the user can view the real-time information such as the plantar pressure distribution map, the plantar pressure change trend, the gait index, the gait characteristic, the abnormal pressure state and the like through the external device or the cloud, and can review the historical data of the user at any time to perform comparison analysis. Through the external device or cloud, the user can further analyze the data and generate detailed health advice or training programs, e.g., a rehabilitation therapist can adjust the training program of the patient according to the plantar pressure health report, and the athlete can optimize gait and athletic performance according to the plantar pressure health report.

The external equipment comprises other intelligent equipment such as a smart phone, a tablet personal computer and the like. The wireless connection can realize real-time transmission of data, can also conveniently synchronize the data with a health management platform or a rehabilitation monitoring system, shares the data with medical staff or a rehabilitation trainer, realizes remote health monitoring and rehabilitation guidance, can also monitor plantar pressure change of a patient in real time, timely adjusts a rehabilitation plan, and ensures that the patient trains in a safe range.

The real-time feedback module is used for providing abnormal pressure state feedback for a user when the abnormal pressure state is detected, the abnormal pressure state feedback mode comprises vibration, sound or visual feedback, the instant feedback mechanism can effectively prevent potential injury of the sole, particularly in the movement process, when the gait or posture of the user deviates from the normal range, the system can intervene in time, and injury of the long-time bad posture to the health of the sole is avoided;

Further, the user can customize or be helped by a professional to set and adjust the mode, intensity, sensitivity and frequency of the abnormal pressure state feedback on the external device, and the abnormal pressure state feedback is transmitted to the real-time feedback module through the wireless communication module, and the real-time feedback module is adjusted to meet personal preference or scene requirements of the user.

In the feedback mode, the voice feedback is suitable for receiving voice guidance in a quiet environment, when the voice feedback is selected, a user can adjust the feedback intensity according to the noise degree of the environment, and the visual feedback is suitable for occasions with insensitive hearing or unobvious vibration feedback, for example, the user is reminded through a flashlight or a screen prompt of a mobile phone.

Regarding the intensity of feedback, the user-defined setting may be performed according to the severity of the pressure abnormality or the activity scene, for example, when the severe pressure is detected, the feedback intensity may be increased to attract the user's attention. Vibration feedback is applicable to dynamic scenarios, e.g. a user selects a stronger vibration feedback during exercise and a lighter vibration cue during daily walking.

In terms of feedback sensitivity and frequency, a higher sensitivity can be set during rehabilitation training so that prompts can be received when slight pressure is abnormal, a user may wish to reduce the feedback sensitivity and frequency in daily activities and only receive prompts when severe pressure is abnormal, and a lower sensitivity is set during high-intensity training so as to avoid frequent prompts.

The system is characterized in that the vibration feedback is realized through a vibration motor embedded in the shoe, the system triggers vibration when an abnormal pressure state is detected to remind a user to adjust gait or posture immediately, the sound feedback is realized through external equipment, when the abnormal pressure is detected, the system sends a signal to the external equipment through wireless connection, the external equipment sends out the sound feedback to remind the user of the abnormal pressure, and the visual prompt is realized through the external equipment, such as flashing light or a screen alarm, to remind the user to adjust.

The power management module adopts a low-power consumption design and comprises a battery pack, an electric quantity monitoring circuit and an intelligent power supply controller, wherein the battery pack is used for providing electric power, the electric quantity monitoring circuit is used for monitoring the electric quantity state of the system in real time, and the intelligent power supply controller is used for controlling the power consumption of the plantar pressure detection system and prolonging the endurance time of the plantar pressure detection system;

Specifically, through the electric quantity monitoring circuit, when the electric quantity of the battery is lower than a set threshold value, namely, the electric quantity is insufficient, the system gives a low electric quantity warning in advance to prompt a user to charge, so that the continuity of system operation is ensured;

The intelligent power supply controller is used for automatically adjusting power consumption according to the working state of the system, the working state of the system comprises a standby state (when a user does not move for a long time) and a moving state (when the user starts walking or moving), the power supply management module enters a low power consumption 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 all enter a preset low power consumption mode to reduce energy consumption, the air pressure sensor can reduce acquisition frequency, reduce electric quantity consumption and ensure that the system can continuously run for a long time, and the power supply management module resumes the normal working mode in the moving state of the system, and the system resumes high-frequency acquisition and processing to ensure the real-time performance of gait analysis. Through the low-power consumption design, the application has the characteristic of low energy consumption when working for a long time, so as to prolong the service life of a battery, further prolong the endurance time of the plantar pressure detection system and adapt to the continuous monitoring requirement of a user.

The second aspect of the present application proposes a plantar pressure detection method based on an air pressure sensor and an air bag, the flow chart of the method is shown in fig. 2, and the method specifically includes:

sensing plantar pressure through a sensing module, obtaining pressure data, synchronously transmitting the pressure data to the data processing module, and adjusting air pressure inside each air bag according to an adjusting instruction, wherein the sensing module comprises a plurality of independently working air bags, a plurality of air pressure sensors, an air pump and a plurality of air valves;

The data processing module is used for receiving and preprocessing the pressure data to obtain plantar pressure information and generating plantar pressure health reports and the adjusting instructions, and is connected with the air pressure sensor and comprises a preprocessing unit and an algorithm unit;

Transmitting the real-time plantar pressure information and the plantar pressure health report to external equipment or a cloud end through a wireless communication module, and transmitting user feedback input by a user from the external equipment or the cloud end to the data processing module;

providing abnormal pressure state feedback to a user when an abnormal pressure state is detected through a real-time feedback module, wherein the mode of abnormal pressure state feedback comprises vibration, sound or visual feedback;

and providing power through a power management module, monitoring the electric quantity state of the system in real time, and controlling the power consumption of the plantar pressure detection system.

Wherein each air bag corresponds to a key compression area embedded in the sole, the key compression areas correspond to key stress points of the sole, and the key compression areas comprise a heel area, a front plantar area, a foot outer area and a plantar arch area.

The above description is only of a preferred embodiment of the present application and is not intended to limit the present application, and it should be appreciated by those skilled in the art that many examples of the basic method principles provided in accordance with the present application may exist without performing enough inventive labor.

In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms are not necessarily for the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.

It should also be noted that in this specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

Claims (10)

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 of a shoe, and comprises: a sensing 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 sensors and airbags 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, including the heel area, forefoot area, lateral foot area and plantar arch area. 3. 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 one or more of the air pressure sensors; the sensing module also includes a weighing sensor; the plantar pressure information, plantar pressure health report and adjustment instructions obtained by the data processing module each time are stored as user historical data in the system's memory or cloud. 4. According to claim 1, the plantar pressure detection system based on air pressure sensor and airbag is characterized in that the algorithm unit includes a first preset algorithm for generating a plantar pressure distribution diagram and a plantar pressure change trend, calculating key gait indicators, and extracting gait characteristics; the gait indicators include pressure center, center of gravity transfer trajectory, and plantar contact area and contact time; the gait characteristics include stride, walking speed, plantar landing method and gait symmetry. 5. The plantar pressure detection system based on an air pressure sensor and an airbag according to claim 4, characterized in that the algorithm unit further comprises 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 the air pressure sensor and the airbag according to claim 5, characterized in that the algorithm unit further comprises a third preset algorithm, through which a personalized plantar pressure health report is generated based on user historical data, the result of the first preset algorithm and the 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 sensing 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 is characterized in that the power management module adopts a low-power design, including 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, including the heel area, the forefoot area, the lateral area of the foot, and the plantar arch area.