WO2018188577A1 - 依压力侦测结果定制化产品的方法 - Google Patents

依压力侦测结果定制化产品的方法 Download PDF

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Publication number
WO2018188577A1
WO2018188577A1 PCT/CN2018/082454 CN2018082454W WO2018188577A1 WO 2018188577 A1 WO2018188577 A1 WO 2018188577A1 CN 2018082454 W CN2018082454 W CN 2018082454W WO 2018188577 A1 WO2018188577 A1 WO 2018188577A1
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Prior art keywords
data
foot
insole
physiological condition
user
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PCT/CN2018/082454
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English (en)
French (fr)
Inventor
陆一平
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清远广硕技研服务有限公司
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Application filed by 清远广硕技研服务有限公司 filed Critical 清远广硕技研服务有限公司
Priority to EP18784647.2A priority Critical patent/EP3611639A1/en
Priority to US16/500,433 priority patent/US20200202406A1/en
Publication of WO2018188577A1 publication Critical patent/WO2018188577A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
    • G01L1/00—Measuring force or stress, in general
    • G01L1/14—Measuring force or stress, in general by measuring variations in capacitance or inductance of electrical elements, e.g. by measuring variations of frequency of electrical oscillators
    • G01L1/142—Measuring force or stress, in general by measuring variations in capacitance or inductance of electrical elements, e.g. by measuring variations of frequency of electrical oscillators using capacitors
    • G01L1/146—Measuring force or stress, in general by measuring variations in capacitance or inductance of electrical elements, e.g. by measuring variations of frequency of electrical oscillators using capacitors for measuring force distributions, e.g. using force arrays
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/17—Mechanical parametric or variational design
    • A—HUMAN NECESSITIES
    • A43—FOOTWEAR
    • A43B—CHARACTERISTIC FEATURES OF FOOTWEAR; PARTS OF FOOTWEAR
    • A43B3/00—Footwear characterised by the shape or the use
    • A43B3/34—Footwear characterised by the shape or the use with electrical or electronic arrangements
    • A43B3/44—Footwear characterised by the shape or the use with electrical or electronic arrangements with sensors, e.g. for detecting contact or position
    • A—HUMAN NECESSITIES
    • A43—FOOTWEAR
    • A43B—CHARACTERISTIC FEATURES OF FOOTWEAR; PARTS OF FOOTWEAR
    • A43B3/00—Footwear characterised by the shape or the use
    • A43B3/34—Footwear characterised by the shape or the use with electrical or electronic arrangements
    • A43B3/48—Footwear characterised by the shape or the use with electrical or electronic arrangements with transmitting devices, e.g. GSM or Wi-Fi®
    • A—HUMAN NECESSITIES
    • A43—FOOTWEAR
    • A43D—MACHINES, TOOLS, EQUIPMENT OR METHODS FOR MANUFACTURING OR REPAIRING FOOTWEAR
    • A43D1/00—Foot or last measuring devices; Measuring devices for shoe parts
    • A43D1/02—Foot-measuring devices
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
    • A61B5/0022—Monitoring a patient using a global network, e.g. telephone networks, internet
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/1036—Measuring load distribution, e.g. podologic studies
    • A61B5/1038—Measuring plantar pressure during gait
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802—Sensor mounted on worn items
    • A61B5/6804—Garments; Clothes
    • A61B5/6807—Footwear
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7253—Details of waveform analysis characterised by using transforms
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7253—Details of waveform analysis characterised by using transforms
    • A61B5/7257—Details of waveform analysis characterised by using transforms using Fourier transforms
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
    • A63B24/0062—Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
    • G01L1/00—Measuring force or stress, in general
    • G01L1/14—Measuring force or stress, in general by measuring variations in capacitance or inductance of electrical elements, e.g. by measuring variations of frequency of electrical oscillators
    • G01L1/142—Measuring force or stress, in general by measuring variations in capacitance or inductance of electrical elements, e.g. by measuring variations of frequency of electrical oscillators using capacitors
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0621—Item configuration or customization
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/12—Cloth

Definitions

  • the present invention relates to a method of customizing a product; in particular, the present invention relates to a method of customizing a product based on insoles pressure detection results.
  • the insole set in the shoe not only provides the traditional cushion function, but also provides different functions such as heightening and shock absorption through thickness and material design.
  • the present invention provides a method for customizing an insole product based on the detection result of the condition of the foot, so as to effectively solve the above problems encountered in the prior art.
  • the method includes: the computing chip of the capacitive pressure detecting insole receives a plurality of capacitance changes from the plurality of capacitive sensing nodes and obtains a pressure corresponding to the plurality of detecting positions of the foot according to the plurality of capacitance changes Data, to determine the motion physiological condition data of the user's foot; obtain the exercise physiological condition data from the computing chip via the data reading device, and transmit it to the cloud database or the remote computing device via the network; determine the correction from the exercise physiological condition data Data is suggested and a corresponding foot orthotic insole model is generated based on the corrected recommendation data; and a corresponding foot insole is fabricated and provided in accordance with the foot orthotic insole model.
  • the step of determining the physiological condition data further includes: when the capacitive pressure detecting insole is subjected to a pressure applied by a user's foot, respectively sensing the corresponding through the plurality of capacitive sensing nodes A plurality of capacitance changes at a plurality of detection locations of the foot.
  • the computing chip includes a receiving unit and a value converting unit
  • the step of obtaining pressure data corresponding to the plurality of detecting positions of the foot according to the plurality of capacitance changes further comprises: receiving, by the receiving unit M original detection data, wherein M is a positive integer; and the value conversion unit performs a numerical conversion process on the M original detection data, and K numerically transformed data has been generated, where K is a positive integer and K is smaller than M, causing the data amount of the K value-converted data to be smaller than the data amount of the M original detected data.
  • the method further includes: performing, by the numerical conversion unit, the numerical conversion process on the M original detected data by using a numerical conversion mechanism.
  • the numerical conversion mechanism is a Fourier transform mechanism or a Laplace transform mechanism.
  • the method further includes: outputting the K values converted data to the network; and connecting to the cloud database or the mobile communication device through the network.
  • the method further comprises: determining the motion physiological condition data of the user's foot based on the K numerically converted data, and transmitting the exercise physiological condition data to the network.
  • the computing chip is a Bluetooth chip embedded in the capacitive pressure detecting insole
  • the step of the data reading device acquiring the motion physiological condition data from the computing chip further comprises: when the position of the computing chip is adjacent to the data reading When the device is taken, the computing chip and the data reading device are communicably connected to each other by a Bluetooth communication protocol.
  • the step of determining the correction suggestion data from the exercise physiological condition data further comprises: comparing the exercise physiological condition data with a normal foot average; and analyzing the exercise physiological condition data and the normal foot average according to the comparison result. The difference in values and the generation of correctional recommendations data.
  • the method further comprises: determining, from the motion physiological condition data, a distribution shape of the user's foot applying a pressure channel to the insole, and comparing the normal to the normal foot average.
  • the data reading device comprises an apparatus of the Internet of Things, Bluetooth, or wireless network.
  • FIG. 1 is a schematic view showing the capacitive pressure detecting insole 2 of the present invention disposed in the shoe 1.
  • FIG. 2 is a schematic diagram of a capacitive pressure sensing insole 2 of the present invention having a plurality of capacitive sensing nodes N.
  • FIG. 3 is a plurality of capacitive sensing nodes N in the capacitive pressure sensing insole 2 of the present invention located below the thermoplastic polyester elastomer (TPEE) layer TP and the computing chip CH is embedded in the capacitive pressure detecting insole 2 schematic diagram.
  • TPEE thermoplastic polyester elastomer
  • the computing chip CH receives the plurality of capacitive sensing nodes N1, N2, N3, ... respectively sensed corresponding to the foot FT
  • a plurality of schematic representations of the plurality of capacitance changes of the detected positions P1, P2, P3, . . . and connected to the cloud database DB or the mobile communication device MB via the network NET.
  • Fig. 5 is a schematic view showing that the condenser yarn L1 and the conductive yarn L2 are twisted together.
  • Figure 6 is a functional block diagram of a data processing apparatus of the present invention.
  • Figure 7 is an embodiment of the user while in motion.
  • FIG. 8 is a flow chart of a method of customizing a product of the present invention.
  • CT1 ⁇ CTK data after numerical conversion
  • N, N1 to N3, N1 to NM Capacitive sensing nodes
  • a particular embodiment of the invention is a data processing apparatus.
  • the data processing device may be a microprocessor, a Bluetooth chip, or an Internet of Things chip, and may be embedded in a capacitive pressure detecting insole, but not limited thereto.
  • the data processing device receives the M original detection data
  • the data processing device performs a numerical conversion process on the M original detection data to generate K numerically converted data, wherein M and K are both positive integers and K is smaller than M, the amount of data of the K values after conversion is less than the amount of data of the M original detected data, so as to reduce the amount of data.
  • the M raw detecting data received by the data processing device may be sensed by the M capacitive sensing nodes of the capacitive pressure detecting insole.
  • the measured M capacitance changes, and the M capacitance changes respectively correspond to M detection positions of the user's foot.
  • FIG. 1 and FIG. 2 show that the capacitive pressure detecting insole 2 is disposed in the shoe 1
  • FIG. 2 illustrates the capacitive pressure detecting insole 2 having a plurality of capacitive sensing nodes N .
  • FIG. 3 is a schematic diagram of the pressure applied by the capacitive pressure detecting insole 2 to the user's foot
  • FIG. 4 is the capacitive pressure detecting insole 2 received by the user's foot FT. Schematic diagram of the applied pressure.
  • the capacitive pressure detecting insole 2 includes a thermoplastic polyester elastomer (TPEE) layer TP, a plurality of capacitive sensing nodes N, and an arithmetic chip CH.
  • the plurality of capacitive sensing nodes N are located below the thermoplastic polyester elastomer layer TP and the computing chip CH is embedded in the capacitive pressure detecting insole 2 .
  • the capacitive pressure detecting insole 2 can be formed by coupling the condenser yarn L1 and the conductive yarn L2 to each other under the thermoplastic polyester elastomer layer TP, and the plurality of capacitive feelings
  • the measuring node N can be located where the capacitive yarn L1 and the conductive yarn L2 are interdigitated, but not limited thereto.
  • the surface of the condenser yarn L1 is formed by forming two electrified coatings and forming a capacitor when there is a charge distribution between the two electrified coating layers.
  • the capacitive pressure sensing insole 2 has not been subjected to the pressure exerted by the user's foot FT, the charge distribution between the two charged coatings is denser, that is, the charge density is higher; when the capacitive pressure detecting insole 2 When subjected to the pressure exerted by the user's foot FT, the capacitive yarn L1 is crushed by the pressure, resulting in a more dispersed charge distribution between the two electrified coatings, in two chargeable coatings.
  • the plurality of capacitive sensing nodes N1, N2, N3, ... of the insole 2 are detected due to the capacitive pressure.
  • the positions respectively correspond to the plurality of detecting positions P1, P2, P3, ... of the foot FT. Therefore, the plurality of capacitive sensing nodes N1, N2, N3, ... of the capacitive pressure detecting insole 2 correspondingly sense correspondingly
  • the plurality of capacitance changes of the plurality of detection positions P1, P2, P3, . . . of the foot FT transmit the capacitance change amount to the operation chip CH.
  • the computing chip CH includes at least a receiving unit 50, a numerical value converting unit 52, and an output unit 54.
  • the value conversion unit 52 is coupled between the receiving unit 50 and the output unit 54.
  • the receiving unit 50 receives M capacitance change amounts CS1 to CSM from the M capacitive sensing nodes N1 to NM, respectively, the receiving unit 50 transmits the M capacitance change amounts CS1 to CSM to the numerical value converting unit 52, and the values are
  • the converting unit 52 performs a numerical conversion process on the M capacitance changing amounts CS1 to CSM by using a numerical conversion mechanism to generate K numerically converted data CT1 to CTK, wherein M and K are both positive integers and K is smaller than M, resulting in a numerical value.
  • the data amount of the K numerically converted data generated by the converting unit 52 is smaller than the data amount of the M capacitive changing amounts received by the numerical converting unit 52, so as to achieve the effect of reducing the amount of data.
  • the numerical conversion mechanism adopted by the numerical conversion unit 52 may be a Fourier transform mechanism or a Laplace transform mechanism, but is not limited thereto. Next, the Fourier transform and Laplace transform will be explained separately:
  • Fourier transform is a linear integral transform, which is often used in the fields of physics and engineering to convert signals between time domain (or spatial domain) and frequency domain.
  • time domain or spatial domain
  • frequency domain For example, in signal processing, a typical use of Fourier transform is to decompose a signal into an amplitude component and a frequency component. Since the basic idea was first proposed systematically by the French scholar Joseph Fourier, it was named after his name to commemorate.
  • Laplace transform is a linear integral transform commonly used in applied mathematics to convert a function with an exponent real number (greater than or equal to 0) into a function with a complex argument. Because French astronomer and mathematician Pierre-Simon Laplace first used it in the study of probability theory, it was named after his name to commemorate.
  • Laplace transforms are related to Fourier transforms, but the difference between them is that Fourier transforms represent a function or signal as the superposition of many chords, while Laplace transforms represent a function as many matrices. The superposition.
  • Laplace transforms are often used to analyze linear time-invariant systems and convert between time and frequency domains, where both input and output are functions of time in the time domain ( The unit is in seconds, and the input and output in the frequency domain are functions of the complex angular frequency (in radians/second).
  • the numerical value conversion unit 52 receives 1000 capacitance change amounts CS1 to CS1000 corresponding to 1000 detection positions P1 to P1000 of the foot FT, respectively, and the numerical value conversion unit 52 can pass
  • the Fourier transform mechanism or the Laplace transform mechanism performs a sampling process on 1000 capacitance change amounts CS1 to CS1000, and samples a capacitance change amount every 10 detection positions to generate 100 value converted data CT1 to CT100 (ie, K is 100). Since the number of data processed by the above numerical conversion is only 1/10 of the original number, the total amount of data can be effectively reduced, so that the computing chip CH has the ability to store and process the program.
  • the computing chip CH can also reduce the amount of data by screening. For example, when the computing chip CH receives 1000 capacitance change amounts CS1 to CS1000 corresponding to 1000 detection positions P1 to P1000 of the foot FT (that is, M is 1000), the operation chip CH can compare 1000 Capacitance change amount CS1 ⁇ CS1000 and a preset value. If only 200 capacitors in the 1000 capacitor change amount CS1 ⁇ CS1000 are larger than the preset value, the other 800 capacitors are relatively small, which should be negligible. The CH will generate the numerically converted data CT1 to CT200 (that is, K is 200) based on the 200 capacitance changes greater than the preset value.
  • the advantage of this method is that the amount of data can be effectively reduced, and the amount of the unretained capacitance changes is relatively small, and the pressure distribution of the detected position of the corresponding foot FT does not change significantly. Therefore, it can be ignored, and it will not affect the subsequent judgment of the physiological information or data of the foot.
  • the operation chip CH can store the K numerically converted data CT1 to CTK or analyze the user's foot based on the K numerically converted data CT1 to CTK analysis. Department of exercise physiological information or data.
  • the data after the value conversion may be inversely converted into the original detection data, and then the data processing, or the lookup table is used.
  • the raw data corresponding to the data CT1 to CTK after the K numerical value conversion There is no specific limitation on the raw data corresponding to the data CT1 to CTK after the K numerical value conversion.
  • the amount of capacitance change of the computing chip CH can be transmitted to the cloud database DB and/or the remote computing device RD via other means. Specifically, in the present embodiment, the computing chip CH can wait until the data reading device R is close to transmit the data of the capacitance change amount to the cloud database DB or the remote computing device RD via the network NET.
  • the computing chip CH can be connected to the cloud database DB through the network NET, and can press the pressures of the plurality of detecting positions P1, P2, P3, ... corresponding to the foot FT. Data such as data and/or motion physiology information of the user's foot FT is uploaded to the cloud database DB for reference in subsequent applications.
  • the user can perform a movement from a position A and move to position B with the data reading device R.
  • the data reading device R can be an Internet of Things (IoT) device connected to the network NET. It is assumed that the movement performed by the user between position A and position B is "running".
  • the data reading device R can automatically receive from the computing chip CH. The data of the amount of change in capacitance with respect to the "running" motion generated between the position A and the position B (that is, data such as the motion physiological condition information of the foot FT between the position A and the position B) is obtained.
  • the insole operator can obtain the motion physiological condition information or data of the user's foot FT through the cloud database DB and determine the user's foot problem according to the data, for example, the insole manufacturer can The user's exercise physiological condition information or data is obtained from the cloud database DB via the network by the remote computing device RD.
  • the insole operator can reconstruct or simulate the condition of the user's foot during exercise, and determine whether the user's foot deviates from the normal state and whether correction is needed. Insole.
  • the insole manufacturer can refer to the average normal foot pressure shape and other data, and determine whether the user's foot physiological state information or data is normal or deviated from normal data. For example, assuming that the user's ankle has an external oblique or flat foot problem, the motion physiological condition information of the foot generated during exercise or the foot pressing shape of the data may deviate from the normal shape. In this case, the insole manufacturer can customize the customized insole for the user and set it in the shoe. When the user walks and moves for a period of time with a shoe with a customized correction insole, The user's foot problems should be significantly improved.
  • the user can also operate an application (APP) of his mobile communication device (for example, a smart phone) MB to connect to the computing chip CH or the cloud database DB through the network NET, so as to grasp the foot about the user A itself at any time.
  • APP application
  • Information or data on the physiology of FT Information or data on the physiology of FT.
  • FIG. 8 is a flowchart of a method for customizing a product according to the present invention.
  • the method for customizing a product according to the present invention may include the following steps:
  • Step S10 The computing chip receives a plurality of capacitance changes from the plurality of capacitive sensing nodes and obtains pressure data corresponding to the plurality of detecting positions of the foot according to the plurality of capacitance changes to determine the motion of the user's foot. Physiological status data.
  • the customization method of the present invention uses at least one capacitive pressure sensing insole that can be placed in the shoe and that includes an operational chip and a plurality of capacitive sensing nodes.
  • the computing chip CH can be embedded in the capacitive pressure detecting insole 2.
  • the user's foot FT will press on the capacitive pressure detecting insole 2.
  • FIGS. 4 and 5 when the foot FT is pressed against the capacitive sensing node N of the capacitance detecting insole 2, the capacitive sensing node N that is stepped on is different from the capacitive sensing node that is not stepped on. capacitance.
  • the computing chip CH receives a plurality of capacitance changes, and obtains pressure data corresponding to a plurality of detection positions of the foot according to the capacitance variation.
  • Step S12 The motion physiological condition data is obtained from the computing chip via the data reading device, and transmitted to the cloud database or the remote computing device via the network.
  • the data reading device R can be an Internet of Things (IOT) device or other device that can be connected to the computing chip CH and receive motion physiological condition data.
  • the data reading device R may have the function of Bluetooth or WiFi wireless communication; but is not limited thereto, in other embodiments, the data reading device R may also be connected to and received by the computing chip CH via a wired manner.
  • Sports physiological status data After receiving the exercise physiological condition data, the data reading device R can transmit the exercise physiological condition data to the cloud database DB and/or the remote computing device RD via the network NET.
  • Step S14 determining the foot correction suggestion data from the exercise physiological condition data, and generating a corresponding foot corrected insole model according to the corrected suggestion data.
  • the remote computing device RD can connect to the cloud database DB via the network NET and check whether there is new athletic physiological condition data.
  • the remote calculation device RD can compare the exercise physiological condition data with the aforementioned average value of the normal foot to determine whether the exercise physiological condition data is normal or abnormal data.
  • the remote computing device RD may analyze the abnormal portion of the data and generate the foot correction suggestion data.
  • Step S16 generating a corrective insole model based on the foot correction suggestion data and manufacturing a corresponding foot insole for providing to the user.
  • the remote computing device RD can generate a corresponding orthotic insole model based on the foot correction suggestion data, which is used to simulate where the foot needs to be corrected or needs to be adjusted to facilitate the production of a corresponding orthotic insole.
  • the customized insole can be customized for use by the user by creating the orthotic insole.
  • the method for customizing the product according to the pressure detection result of the invention enables the insole maker to obtain the following data of a plurality of different people: the foot data generated by the user's foot pressing the insole during exercise; The average normal foot pressure shape and pressure channel.
  • the insole manufacturer can refer to the average normal foot pressure shape and other data, and determine whether the user's foot physiological state information or data is normal or deviated from normal data, and customize the product according to the data.

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Abstract

一种依压力侦测结果定制化产品的方法，其中：运算芯片自多个电容感应节点接收多个电容变化量并根据多个电容变化量得到对应于足部的多个侦测位置的压力数据，以研判出使用者的足部的运动生理状况数据（S10）；经由数据读取装置从运算芯片取得运动生理状况数据，并经由网络传送至云端数据库或远端计算装置（S12）；从运动生理状况数据判断矫正建议数据，并根据矫正建议数据产生对应的足部矫正鞋垫模型（S14）；根据足部矫正鞋垫模型制造并提供对应的足部鞋垫，并将其提供给使用者（S16）。

Description

依压力侦测结果定制化产品的方法 技术领域
本发明是关于一种定制化产品的方法；具体而言，本发明是关于一种依据鞋垫压力侦测结果定制化产品的方法。
背景技术
随着科技不断的演进，设置于鞋子内的鞋垫除了提供传统的垫子功能外，还可通过厚度及材料上的不同设计提供给使用者增高、减震等不同功能。
然而，由于每个使用者的脚底的压力点分布情形均不尽相同，若采用目前市面上大量生产的鞋垫设置于鞋子内，并无法满足每个使用者的实际需求，导致许多使用者穿着鞋子走路或运动时感到不舒适，亦无法针对每个使用者的足部问题进行相对应的矫正，使得使用者的足部问题无法获得改善，甚至还会更加恶化。
发明的公开
有鉴于此，本发明提出一种依据足部状况的侦测结果可定制化鞋垫产品的方法，以有效解决现有技术所遭遇到的上述种种问题。
根据本发明的一具体实施例为一种鞋垫定制化的方法。于此实施例中，此方法包含：电容压力侦测鞋垫的运算芯片自多个电容感应节点接收多个电容变化量并根据多个电容变化量得到对应于足部的多个侦测位置的压力数据，以研判出使用者的足部的运动生理状况数据；经由数据读取装置从运算芯片取得运动生理状况数据，并经由网络传送至云端数据库或远端计算装置；从运动生理状况数据判断矫正建议数据，并根据矫正建议数据产生对应的足部矫正鞋垫模型；以及根据足部矫正鞋垫模型制造并提供对应的足部鞋垫。
于一实施例中，该研判运动生理状况数据的步骤进一步包含：当该电容 压力侦测鞋垫受到一使用者的一足部所施加的一压力时，通过该多个电容感测节点分别感测对应于该足部的多个侦测位置的多个电容变化量。
于一实施例中，该运算芯片包含一接收单元及一数值转换单元，该根据多个电容变化量得到对应于足部的多个侦测位置的压力数据的步骤进一步包含：以该接收单元接收M个原始侦测数据，其中M为正整数；以及以该数值转换单元对该M个原始侦测数据进行一数值转换程序，已产生K个数值转换后数据，其中K为正整数且K小于M，致使该K个数值转换后数据的数据量小于该M个原始侦测数据的数据量。
于一实施例中，进一步包含：以该数值转换单元采用一数值转换机制对该M个原始侦测数据进行该数值转换程序。
于一实施例中，该数值转换机制是为一傅立叶转换(Fourier transform)机制或一拉普拉斯转换(Laplace transform)机制。
于一实施例中，进一步包含：将该K个数值转换后数据输出至该网络；以及通过该网络连接至该云端数据库或该移动通信装置。
于一实施例中，进一步包含：根据该K个数值转换后数据研判出使用者的足部的该运动生理状况数据，并且传送该运动生理状况数据至该网络。
于一实施例中，运算芯片是为嵌于该电容压力侦测鞋垫内的一蓝牙芯片，该数据读取装置从运算芯片取得运动生理状况数据的步骤进一步包含：当运算芯片的位置邻近数据读取装置时，运算芯片及数据读取装置以蓝牙的通信协议互相进行通信连接。
于一实施例中，从运动生理状况数据判断矫正建议数据的步骤进一步包含：将运动生理状况数据与一个正常足部平均值做比对；根据比对结果分析运动生理状况数据及正常足部平均值的差异，并产生矫正建议数据。
于一实施例中，进一步包含：从运动生理状况数据中判断出使用者的足部对鞋垫施压力道的分布形状，并将其与正常足部平均值做比对。
于一实施例中，数据读取装置包含物联网、蓝牙、无线网络的装置。
附图的简要说明
在附图中，标号的最左边的数字标识该附图首次出现的顺序。在说明及附图的不同情况下，使用相同的图标表示为相同的元件。
图1为本发明的电容压力侦测鞋垫2设置于鞋子1内的示意图。
图2为本发明的电容压力侦测鞋垫2具有多个电容感测节点N的示意图。
图3为示本发明的电容压力侦测鞋垫2中的多个电容感测节点N是位于热塑性聚酯弹性体(TPEE)层TP下方并且运算芯片CH是嵌于电容压力侦测鞋垫2内的示意图。
图4为当电容压力侦测鞋垫2受到使用者的足部FT所施加的压力时，运算芯片CH接收该多个电容感测节点N1,N2,N3,…分别感测到对应于足部FT的多个侦测位置P1,P2,P3,…的多个电容变化量并可通过网络NET与云端数据库DB或移动通信装置MB连结的示意图。
图5为电容纱线L1与导电纱线L2彼此捻合在一起的示意图。
图6为本发明的数据处理装置的功能方块图。
图7为使用者在运动时的一个实施例。
图8为本发明的定制化产品的方法的流程图。
主要元件符号说明：
1：鞋子
2：电容压力侦测鞋垫
50：接收单元
52：数值转换单元
54：输出单元
CS、CS1～CSM：电容变化量
CT1～CTK：数值转换后数据
N、N1～N3、N1～NM：电容感测节点
TP：热塑性聚酯弹性体层
CH：运算芯片
FT：足部
P1～P3：侦测位置
NET：网络
DB：云端数据库
MB：移动通信装置
R：数据读取装置
RD：远端计算装置
L1：电容纱线
L2：导电纱线
S10～S16：步骤
实现本发明的最佳方式
根据本发明的一具体实施例为一种数据处理装置。于此实施例中，数据处理装置可以是一微处理器、一蓝牙芯片或一物联网芯片，并可嵌设于一电容压力侦测鞋垫内，但不以此为限。当数据处理装置接收到M个原始侦测数据时，数据处理装置会对M个原始侦测数据进行一数值转换程序以产生K个数值转换后数据，其中M与K均为正整数且K小于M，致使K个数值转换后数据的数据量会小于M个原始侦测数据的数据量，以达到减少数据量的功效。
假设数据处理装置是嵌设于电容压力侦测鞋垫内的一运算芯片，则数据处理装置所接收到的M个原始侦测数据可以是电容压力侦测鞋垫的M个电容感测节点所分别感测到的M个电容变化量，并且该M个电容变化量分别对应于使用者的足部的M个侦测位置。请参照图1及图2，图1为电容压力侦测鞋垫2设置于鞋子1内，而图2为电容压力侦测鞋垫2具有多个电容感测节点N。
接着，请参照图3及图4，图3为电容压力侦测鞋垫2尚未受到使用者的足部所施加的压力的示意图；图4为电容压力侦测鞋垫2受到使用者的足部FT所施加的压力的示意图。
如图3及图4所示，电容压力侦测鞋垫2包含热塑性聚酯弹性体(TPEE)层TP、多个电容感测节点N及运算芯片CH。其中，该多个电容感测节点N是位于热塑性聚酯弹性体层TP下方并且运算芯片CH系嵌于电容压力侦测鞋垫2内。
于实际应用中，如图5所示，电容压力侦测鞋垫2可采用电容纱线L1与导电纱线L2彼此捻合于热塑性聚酯弹性体层TP的下方而成，并且该多个电容感测节点N可位于电容纱线L1与导电纱线L2彼此交错处，但不以此为限。
需说明的是，电容纱线L1的表面是形成两个有可带电涂层，并且在两个可带电涂层之间有电荷分布时而形成一电容。当电容压力侦测鞋垫2尚未受到使用者的足部FT所施加的压力时，位于两个有可带电涂层之间的电荷分布较为密集，亦即电荷密度较高；当电容压力侦测鞋垫2受到使用者的足部FT所施加的压力时，电容纱线L1会被压力压扁而导致位于两个有可带电涂层之间的电荷分布变得较为分散，在两个可带电涂层之间的距离不变的情况下由于电荷密度变小而造成其电容值的变化，并由位于电容纱线L1与导电纱线L2交错处的多个电容感测节点N分别感测到多个电容变化量。
举例而言，如图4所示，当使用者的足部FT踩在电容压力侦测鞋垫2上时，由于电容压力侦测鞋垫2的多个电容感测节点N1,N2,N3,…的位置分别对应于足部FT的多个侦测位置P1,P2,P3,…，因此，电容压力侦测鞋垫2的多个电容感测节点N1,N2,N3,…会相对应地感测对应于足部FT的多个侦测位置P1,P2,P3,…的多个电容变化量并将电容变化量传送至运算芯片CH。
请参照图6，运算芯片CH至少包含有接收单元50、数值转换单元52及输出单元54。其中，数值转换单元52是耦接于接收单元50与输出单元54之间。当接收单元50从M个电容感测节点N1～NM分别接收到M个电 容变化量CS1～CSM时，接收单元50会将M个电容变化量CS1～CSM传送至数值转换单元52，并由数值转换单元52采用一数值转换机制对M个电容变化量CS1～CSM进行一数值转换程序，以产生K个数值转换后数据CT1～CTK，其中M与K均为正整数且K小于M，致使数值转换单元52所产生的K个数值转换后数据的数据量会小于数值转换单元52所接收的M个电容变化量的数据量，以达到减少数据量的功效。
需说明的是，数值转换单元52所采用的数值转换机制可以是傅立叶转换(Fourier transform)机制或拉普拉斯转换(Laplace transform)机制，但不以此为限。接下来，将分别就傅立叶转换与拉普拉斯转换进行说明：
傅立叶转换是一种线性的积分转换，常应用于物理学与工程学等领域，用以将信号在时域(或空域)与频域之间进行转换。举例而言，在信号处理中，傅立叶转换的典型用途是将信号分解成振幅分量与频率分量。由于其基本思想是由法国学者约瑟夫傅立叶首先有系统地提出，故以其名字来命名以示纪念。
拉普拉斯转换是应用数学中常用的一种线性的积分转换，用以将一个有引数实数(大于或等于0)的函数转换为一个引数为复数的函数。由于是法国天文学家暨数学家皮埃尔-西蒙·拉普拉斯在机率论的研究中首先使用，故以其名字来命名以示纪念。
拉普拉斯转换与傅立叶转换有关，但两者不同之处在于：傅立叶转换是将一个函数或信号表示为许多弦波的迭加，而拉普拉斯转换则是将一个函数表示为许多矩阵的迭加。在物理学及工程学中，拉普拉斯转换常被用来分析线性非时变系统并可进行时域与频域之间的转换，其中在时域中输入及输出均为时间的函数(单位为秒)，而在频域中输入及输出则均为复变角频率的函数(单位为弧度/秒)。
举例而言，假设M为1000，亦即数值转换单元52是接收到分别对应于足部FT的1000个侦测位置P1～P1000的1000个电容变化量CS1～CS1000，数值转换单元52即可通过傅立叶转换机制或拉普拉斯转换机制对1000个电 容变化量CS1～CS1000进行一取样程序，每隔10个侦测位置取样一电容变化量以产生100个数值转换后数据CT1～CT100(亦即K为100)。由于经上述数值转换处理后的数据数量仅为原来的1/10，故可有效减少总数据量，使得运算芯片CH有能力进行储存与处理的程序。
除此之外，运算芯片CH亦可通过筛选的方式来减少数据量。举例而言，当运算芯片CH接收到分别对应于足部FT的1000个侦测位置P1～P1000的1000个电容变化量CS1～CS1000时(亦即M为1000)，运算芯片CH可比较1000个电容变化量CS1～CS1000与一预设值，若1000个电容变化量CS1～CS1000当中仅有200个电容变化量大于预设值，代表其他800个电容变化量相当小应可忽略不计，运算芯片CH即会根据这200个大于预设值的电容变化量产生数值转换后数据CT1～CT200(亦即K为200)。
需说明的是，此一作法的优点在于能够有效减少数据量，并且该些未被保留的电容变化量相当小，代表其相对应的足部FT的侦测位置的压力分布并无明显的变化，故可忽略不计，亦不会影响到后续对于足部的运动生理状况资讯或数据的判断。
当数值转换单元52产生K个数值转换后数据CT1～CTK后，运算芯片CH可储存K个数值转换后数据CT1～CTK或根据K个数值转换后数据CT1～CTK分析研判出关于使用者的足部的运动生理状况资讯或数据。
需说明的是，当数值转换单元52产生数值转换后数据后，于后续的应用程序中可先将数值转换后数据进行逆转换还原为原始侦测数据后再进行数据处理，或是利用查找表比对出K个数值转换后数据CT1～CTK所分别对应的原始数据为何，并无特定的限制。
如图7所示，在另一个实施例中，运算芯片CH的电容变化量可经由其他装置传输至云端数据库DB及/或远端计算装置RD。具体而言，在本实施例中，运算芯片CH可等到靠近一个数据读取装置R时再将电容变化量的数据经由网络NET传送至云端数据库DB或远端计算装置RD。于实际应用中，如图4至7所示，运算芯片CH可通过网络NET连线至云端数据库DB，并 可将对应于足部FT的多个侦测位置P1,P2,P3,…的压力数据及/或使用者的足部FT的运动生理状况资讯等数据上传至云端数据库DB，以供后续进行其他应用时的参考。
举例而言，使用者可从一个位置A进行一项运动并移动至具有数据读取装置R的位置B。在本实施例中，数据读取装置R可为一种与网络NET连接的物联网(Internet of Things，IoT)装置。假设使用者在位置A及位置B间所进行的运动是“跑步”，在一实施例中，当使用者靠近位置B的数据读取装置R时，数据读取装置R可自动从运算芯片CH取得位置A至位置B间所产生相对于“跑步”运动的电容变化量的数据(亦即，位置A至位置B间的足部FT的运动生理状况资讯等数据)。
在一个实施例中，如图7所示，鞋垫业者可通过云端数据库DB得到使用者的足部FT的运动生理状况资讯或数据并据以研判出使用者的足部问题，例如，鞋垫业者可通过远端计算装置RD经由网络从云端数据库DB取得使用者的运动生理状况资讯或数据。
根据鞋垫业者所取得的足部FT的运动生理状况资讯或数据，鞋垫业者可重建或模拟使用者的足部在运动时的状况，并且判断使用者的足部是否偏离正常状态，并且是否需要矫正的鞋垫。
具体而言，在运动时，实际上使用者的足部会对鞋垫施压，因此经过统计多个不同人的足部数据，可取得平均正常足部施压形状及施压力道。鞋垫业者可参考此平均正常足部施压形状等数据，并判断使用者的足部的运动生理状况资讯或数据是否为正常或偏离正常的数据。例如，假设使用者的脚踝有外斜倾或有平底脚的问题，在运动时所产生的足部的运动生理状况资讯或数据的足部施压形状会偏离正常的形状。在此情况下，鞋垫业者即可替使用者量身订做定制化的矫正用鞋垫，并且设置于鞋子内，当使用者穿着设有定制化的矫正用鞋垫的鞋子走路及运动一段时间后，使用者的足部问题应能获得明显的改善。
此外，使用者亦可操作其移动通信装置(例如智慧型手机)MB的应用程 序(APP)通过网络NET连线至运算芯片CH或云端数据库DB，由以随时掌握关于使用者A本身的足部FT的运动生理状况资讯或数据。
请参照图8，图8为本发明定制化产品的方法的流程图，根据本发明的定制化产品的方法，可包含下列步骤：
步骤S10：运算芯片自多个电容感测节点接收多个电容变化量并根据多个电容变化量得到对应于足部的多个侦测位置的压力数据，以研判出使用者的足部的运动生理状况数据。
具体而言，本发明的定制化方法会使用到至少一个电容压力侦测鞋垫，此鞋垫可设置于鞋子里，并且会包含一个运算芯片及多个电容感应节点。如图2至5所示，运算芯片CH可以嵌入式的设置于电容压力侦测鞋垫2中。当使用者穿上鞋子并且开始走动时，使用者的足部FT会压在电容压力侦测鞋垫2上。如图4及5所示，当足部FT压在电容侦测鞋垫2的电容感应节点N上时，相对于未被踩到的电容感应节点，被踩到的电容感应节点N会产生不同的电容。运算芯片CH会接收到多个电容变化量，并根据此电容变化量得到对应于足部的多个侦测位置的压力数据。
步骤S12：经由数据读取装置从运算芯片取得运动生理状况数据，并经由网络传送至云端数据库或远端计算装置。如图3至6所示，数据读取装置R可为物联网(Internet of Things，IOT)的装置或其他可与运算芯片CH连接并接收运动生理状况数据的装置。在一实施例中，数据读取装置R可具有蓝牙或WiFi无线通信的功能；但不限于此，在其他实施例中，数据读取装置R亦可经由有线的方式与运算芯片CH连接并且接收运动生理状况数据。在接收到运动生理状况数据后，数据读取装置R可经由网络NET将运动生理状况数据传送至云端数据库DB及/或远端计算装置RD。
步骤S14：从运动生理状况数据判断足部矫正建议数据，并根据矫正建议数据产生对应的足部矫正鞋垫模型。在本实施例中，若远端计算装置RD没有收到运动生理状况数据，远端计算装置RD可经由网络NET与云端数据库DB连接并且检查是否有新的运动生理状况数据。在此情况下，远端计 算装置RD可将运动生理状况数据与前述的正常足部的平均值比对来判断运动生理状况数据是否为正常或不正常的数据。当远端计算装置RD判断运动生理状况数据为不正常的数据时，远端计算装置RD可针对数据不正常的部分进行分析并且产生足部矫正建议数据。
步骤S16：根据足部矫正建议数据产生矫正鞋垫模型，并制造对应的足部鞋垫以提供给使用者。具体而言，远端计算装置RD根据足部矫正建议数据可产生对应的矫正鞋垫模型，此模型是用于模拟足部需要矫正或需要调整姿态的地方以方便可生产对应的矫正鞋垫。在本实施例中，通过产生此矫正鞋垫，可定制化鞋垫给使用者使用。
由以上较佳具体实施例的详述，是希望能更加清楚描述本发明的特征与精神，而并非以上述所公开的较佳具体实施例来对本发明的范畴加以限制。相反地，其目的是希望能涵盖各种改变及具相等性的安排于本发明权利要求的范畴内。
工业应用性
本发明的依压力侦测结果定制化产品的方法，可使鞋垫制作者获取到多个不同人的如下数据：在运动时，使用者的足部对鞋垫施压产生的足部数据；可取得平均正常足部施压形状及施压力道。鞋垫业者可参考此平均正常足部施压形状等数据，并判断使用者的足部的运动生理状况信息或数据是否为正常或偏离正常的数据，并依据数据定制化产品。

Claims (11)

  1. 一种依压力侦测结果定制化产品的方法，其特征在于：
    由一个电容压力侦测鞋垫的运算芯片自多个电容感应节点接收多个电容变化量，并根据所述多个电容变化量得到对应于使用者的足部的多个侦测位置的压力数据，以研判出所述足部的运动生理状况数据；
    经由一个数据读取装置从所述运算芯片取得所述运动生理状况数据，并经由网络传送至一个云端数据库或远端计算装置；
    从所述运动生理状况数据判断矫正建议数据，并根据所述矫正建议数据产生对应的足部矫正鞋垫模型；以及
    根据所述足部矫正鞋垫模型制造并提供对应的足部鞋垫。
  2. 如权利要求1所述依压力侦测结果定制化产品的方法，其特征在于，所述研判运动生理状况数据的步骤进一步包含：
    当所述电容压力侦测鞋垫受到所述使用者的足部所施加的一压力时，通过所述多个电容感测节点分别感测对应于所述足部的多个侦测位置的所述多个电容变化量。
  3. 如权利要求2所述依压力侦测结果定制化产品的方法，其特征在于，所述运算芯片包含一接收单元及一数值转换单元，所述根据多个电容变化量得到对应于所述使用者的足部的多个侦测位置的压力数据的步骤进一步包含：
    以所述接收单元接收M个原始侦测数据，其中M为正整数；以及
    以所述数值转换单元对所述M个原始侦测数据进行一数值转换程序，产生K个数值转换后数据，其中K为正整数且K小于M，致使所述K个数值转换后数据的数据量小于所述M个原始侦测数据的数据量。
  4. 如权利要求3所述依压力侦测结果定制化产品的方法，其特征在于，进一步包含：
    以所述数值转换单元采用一数值转换机制对所述M个原始侦测数据进行所述数值转换程序。
  5. 如权利要求4所述依压力侦测结果定制化产品的方法，其特征在于，该数值转换机制是为一傅立叶转换机制或一拉普拉斯转换机制。
  6. 如权利要求3所述依压力侦测结果定制化产品的方法，其特征在于，进一步包含：
    将所述K个数值转换后数据输出至所述网络；以及
    通过所述网络连接至所述云端数据库或所述远端计算装置。
  7. 如权利要求3所述依压力侦测结果定制化产品的方法，其特征在于，进一步包含：
    根据所述K个数值转换后数据研判出所述使用者的足部的所述运动生理状况数据，并且传送所述运动生理状况数据至所述网络。
  8. 如权利要求1所述依压力侦测结果定制化产品的方法，其特征在于，所述运算芯片是为嵌于所述电容压力侦测鞋垫内的一蓝牙芯片，所述数据读取装置从所述运算芯片取得所述运动生理状况数据的步骤进一步包含：
    当所述运算芯片的位置邻近所述数据读取装置时，所述运算芯片及所述数据读取装置以蓝牙的通信协议互相进行通信连接。
  9. 如权利要求1所述依压力侦测结果定制化产品的方法，其特征在于，从所述运动生理状况数据判断所述矫正建议数据的步骤进一步包含：
    将所述运动生理状况数据与一个正常足部平均值做比对；
    根据比对结果分析所述运动生理状况数据及所述正常足部平均值的差异，并产生所述矫正建议数据。
  10. 如权利要求9所述依压力侦测结果定制化产品的方法，其特征在于，进一步包含：
    从所述运动生理状况数据中判断出所述使用者的足部对所述鞋垫施压力道的分布形状，并将其与所述正常足部平均值做比对。
  11. 如权利要求1所述依压力侦测结果定制化产品的方法，其特征在于，所述数据读取装置包含物联网、蓝牙、无线网络的装置。
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