WO2018161861A1 - 数据处理装置及数据量减少方法 - Google Patents

数据处理装置及数据量减少方法 Download PDF

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Publication number
WO2018161861A1
WO2018161861A1 PCT/CN2018/077912 CN2018077912W WO2018161861A1 WO 2018161861 A1 WO2018161861 A1 WO 2018161861A1 CN 2018077912 W CN2018077912 W CN 2018077912W WO 2018161861 A1 WO2018161861 A1 WO 2018161861A1
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Prior art keywords
data
capacitive
reduction method
original
amount
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PCT/CN2018/077912
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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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Priority to EP18763838.2A priority Critical patent/EP3594816A4/en
Priority to US16/492,212 priority patent/US20200046288A1/en
Publication of WO2018161861A1 publication Critical patent/WO2018161861A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
    • G06F11/3013—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system is an embedded system, i.e. a combination of hardware and software dedicated to perform a certain function in mobile devices, printers, automotive or aircraft systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
    • G06F11/3072—Monitoring arrangements determined by the means or processing involved in reporting the monitored data where the reporting involves data filtering, e.g. pattern matching, time or event triggered, adaptive or policy-based reporting
    • G06F11/3082—Monitoring arrangements determined by the means or processing involved in reporting the monitored data where the reporting involves data filtering, e.g. pattern matching, time or event triggered, adaptive or policy-based reporting the data filtering being achieved by aggregating or compressing the monitored data
    • A—HUMAN NECESSITIES
    • A43—FOOTWEAR
    • A43B—CHARACTERISTIC FEATURES OF FOOTWEAR; PARTS OF FOOTWEAR
    • A43B17/00—Insoles for insertion, e.g. footbeds or inlays, for attachment to the shoe after the upper has been joined
    • 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
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3089—Monitoring arrangements determined by the means or processing involved in sensing the monitored data, e.g. interfaces, connectors, sensors, probes, agents
    • G06F11/3093—Configuration details thereof, e.g. installation, enabling, spatial arrangement of the probes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/041—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
    • G06F3/0416—Control or interface arrangements specially adapted for digitisers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/041—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
    • G06F3/044—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means by capacitive means
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/041—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
    • G06F3/044—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means by capacitive means
    • G06F3/0447—Position sensing using the local deformation of sensor cells

Definitions

  • the present invention relates to reducing the amount of data, and more particularly to a data processing apparatus and a data amount reduction method.
  • data processing devices such as microprocessors or computing chips
  • microprocessors or computing chips are designed to be smaller and smaller, while relatively There is also a limit to the amount of data that can be stored and processed.
  • portable devices and wearable devices are often provided with a plurality of detection units respectively.
  • the detection is performed, and the detected original detection data is transmitted to a data processing device (such as a microprocessor or an arithmetic chip).
  • the present invention provides a data processing apparatus and a data amount reduction method to effectively solve the above various problems encountered in the prior art.
  • a particular embodiment of the invention is a data processing apparatus.
  • the data processing apparatus includes a receiving unit and a numerical converting unit.
  • the receiving unit is configured to receive M original detected data, where M is a positive integer.
  • the numerical conversion unit is coupled to the receiving unit for performing a numerical conversion process on the M original detected data to generate K numerically transformed data, wherein K is a positive integer and K is less than M, so that the K values are converted.
  • the amount of data is smaller than the amount of data of the M original detected data to achieve the effect of reducing the amount of data.
  • the numerical conversion unit performs a 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 data processing device is a Bluetooth chip or an Internet of Thing (IoT) chip and can be connected to a cloud database or a mobile communication device via a network.
  • IoT Internet of Thing
  • the value conversion unit further compares the M original detection data with a preset value, and generates the K pieces according to the K original detection data that are greater than the preset value in the M original detection data. Data after numerical conversion.
  • the M raw detection data is a M capacitance change amount respectively sensed by the M capacitive sensing nodes of a capacitive pressure detecting insole, and the M capacitance change amounts respectively correspond to a foot portion M detection positions.
  • the M capacitive sensing nodes of the capacitive pressure sensing insole are located where the capacitive yarn and the conductive yarn are interdigitated with each other, and the surface of the capacitive yarn is formed with two chargeable coatings.
  • Another embodiment of the present invention is a data amount reduction method, comprising the steps of: (a) providing M original detection data, wherein M is a positive integer; and (b) detecting the M original detection data. Performing a numerical conversion process to generate K numerically transformed data; wherein K is a positive integer and K is less than M, such that the data amount of the K value converted data is smaller than the data amount of the M original detected data.
  • step (b) is to perform the numerical conversion process on the M original detected data by using a numerical conversion mechanism.
  • the data volume reduction method as described above further includes the steps of: outputting the K numerically converted data to a network; and connecting a cloud database or a mobile communication device through the network.
  • the data volume reduction method as described above further includes the steps of: comparing the M original detection data with a preset value, and based on the K original detections of the M original detection data that are greater than the preset value
  • the measured data produces the K numerically transformed data.
  • the M original detection data is a M capacitance change amount respectively sensed by the M capacitive sensing nodes of a capacitance pressure detecting insole, and the M capacitances
  • the amount of change corresponds to the M detection positions of one foot respectively.
  • the data processing apparatus and the data amount reduction method according to the present invention adopt a numerical conversion mechanism such as Fourier transform or Laplacian conversion or a screening mechanism that compares with a preset value to receive the received signal.
  • the huge amount of data is processed to greatly reduce the amount of data, so that the data processing device can store and process the numerically converted data in an instant, so that the prior art cannot be stored and processed due to excessive data volume.
  • 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 schematic diagram of 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 embedded in the capacitive pressure detecting insole 2 .
  • 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.
  • FIG. 7 is a flow chart of the method for reducing the amount of data of the present invention applied to a capacitive pressure detecting insole.
  • N, N1 to N3, N1 to NM Capacitive sensing nodes
  • CT1 ⁇ CTK data after numerical conversion
  • 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 forms two electrified coatings and forms a capacitance 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 change amounts of the plurality of detection positions P1, P2, P3, . . . of the foot FT transmit the capacitance change amount CS to the operation chip CH.
  • the computing chip CH can also be connected to the network NET and can be connected to the cloud database DB or the mobile communication device MB via the network NET.
  • 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 show his mind.
  • 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 a superposition of many sine waves, while Laplace transforms represent a function as many matrices. Superimposed. In physics and engineering, 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 on the physiological information 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 sports physiological information.
  • 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 computing chip CH can also be connected to the network NET through the output unit 54 and output K values converted data CT1 to CTK to the network NET.
  • the computing chip CH can be connected to the cloud database DB through the network NET, and the pressure distribution information and/or the user corresponding to the plurality of detecting positions P1, P2, P3, ... of the foot FT can be The sports physiology information and other data of the foot FT are uploaded to the cloud database DB for reference for subsequent application.
  • the insole manufacturer can obtain the sports physiology information of the user A's foot FT through the cloud database DB and judge the user A's foot problem. Then, the insole manufacturer can customize the customized insole for the user A and set it in the shoe. When the user A wears a shoe with a customized correction insole and walks for a period of time, The user's foot problems should be significantly improved.
  • the user A 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
  • Another embodiment of the present invention is a data amount reduction method, which may include the steps of: providing M original detection data, wherein M is a positive integer; and performing a numerical conversion procedure on the M original detection data. To generate K value-converted data; wherein K is a positive integer and K is less than M, such that the data amount of the K-value converted data is smaller than the data amount of the M original detected data.
  • FIG. 7 is a flowchart of a method for reducing data amount applied to a capacitive pressure detecting insole according to the present invention. As shown in Figure 7, the method can include the following steps:
  • Step S10 When the capacitance pressure detecting insole is subjected to the pressure applied by the user's foot, the capacitor yarn formed on the surface with two electrified coatings is crushed by pressure to cause charge dispersion, and the two electrified coatings are applied. In the case where the distance between the layers is constant, the capacitance changes due to the decrease in the charge density.
  • Step S12 The capacitive pressure detecting insole senses a plurality of capacitance changes corresponding to the plurality of detecting positions of the foot through the plurality of capacitive sensing nodes.
  • Step S14 The computing chip receives a plurality of capacitance changes from the plurality of capacitive sensing nodes and reduces the data amount by the screening conversion mechanism, and then determines the motion physiological condition information of the user's foot.
  • the computing chip can use a numerical conversion program such as Fourier transform or Laplacian conversion, or perform screening by comparing with a preset value to achieve the effect of reducing the amount of data, but not limited thereto.
  • a numerical conversion program such as Fourier transform or Laplacian conversion
  • Step S16 The computing chip can upload the motion physiological condition information of the user's foot to the cloud database through the network.
  • Step S18 The user can operate the mobile communication device to connect to the computing chip or the cloud database through the network to obtain the motion physiological condition information of the user's foot.
  • the data volume reduction method of the present invention is to create pressure on a plurality of grid points on the insole by pressure sensing the yarn.
  • these sensing points sense the pressure on the footpad as a function of time, and then record the pressure as a function of time as a sample.
  • the present invention provides useful information about the crawlable on the insole including at least the following items:
  • Peak Frequency in the third point is an integer multiple of another Peak Frequency, the lowest frequency is called Base Frequency.
  • the other integer multiple of Frequency is the general frequency for Base Frequency, which is used to determine the approximate waveform of each period of motion.
  • A (basic frequency, amplitude); (first overclocking multiple, amplitude); (second overclocking multiple, amplitude)...
  • part A is the reference data and belongs to the data model of the correct motion posture.
  • the part of B is the offset generated by 10 error modes that deviate from the standard pose. Assuming that for a large number of 10,000 measurement points, 500 measurement points are offset from the standard pose, the following analysis can be performed for these 500 points:
  • the Point(N) deviation is the ratio of the length of this offset vector to the length of the standard offset vector, which can represent the magnitude of the offset (proportional).
  • the total amount of data (that is, the IoT memory capacity) can be about 120 KB, and does not require a large amount of memory space, so the data amount M can be greatly simplified, and the operation and memory space can be saved.
  • the present invention can also make 100 grid lines in the lateral and longitudinal directions of the insole. 25 measuring connectors are respectively arranged on the end points of each grid line (400 endpoints) to couple the voltage signal sensors.
  • the data processing apparatus and the data amount reduction method according to the present invention adopt a numerical conversion mechanism such as Fourier transform or Laplacian conversion or a screening mechanism that compares with a preset value to receive the received signal.
  • the huge amount of data is processed to greatly reduce the amount of data, so that the data processing device can store and process the numerically converted data in an instant, so that the prior art cannot be stored and processed due to excessive data volume.
  • the data processing apparatus and the data amount reduction method of the present invention use a numerical conversion mechanism such as Fourier transform or Laplacian conversion or a filtering mechanism that compares with a preset value to process the huge amount of data received.
  • the amount of data is greatly reduced, so that the data processing device can store and process the numerically converted data in an instant, so that the disadvantages of the prior art that the data volume is too large to be stored and processed can be effectively avoided.

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Abstract

一种数据处理装置及数据量减少方法。数据处理装置包含一接收单元及一数值转换单元。接收单元用以接收M个原始侦测数据，其中M为正整数。数值转换单元耦接接收单元，用以对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K为正整数且K小于M，致使K个数值转换后数据的数据量小于M个原始侦测数据的数据量，以达到减少数据量的功效。

Description

数据处理装置及数据量减少方法 技术领域
本发明是与减少数据量有关，尤其是关于一种数据处理装置及数据量减少方法。
背景技术
随着数据处理技术不断的演进，为了能够应用于各种可携式装置与穿戴式装置上，数据处理装置(例如微处理器或运算芯片)的体积设计得愈来愈小，而相对地其能够储存与处理的数据量也有一定的限度。
由于目前许多的可携式装置与穿戴式装置均提供各种不同的侦测功能，为了能够达到更准确的侦测结果，可携式装置与穿戴式装置往往设置有相当多的侦测单元分别进行侦测，并将侦测到的原始侦测数据均传送至数据处理装置(例如微处理器或运算芯片)。
然而，由于侦测单元的数量过多并且每个侦测单元均会有侦测到的数据资料要传送至数据处理装置，导致数据处理装置所接收到的数据资料量相当庞大，远超过数据处理装置所能储存与处理的上限，使得数据处理装置无法完成储存与数据处理的程序。
发明的公开
有鉴于此，本发明提出一种数据处理装置及数据量减少方法，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数据处理装置。于此实施例中，数据处理装置包含一接收单元及一数值转换单元。接收单元用以接收M个原始侦测数据，其中M为正整数。数值转换单元耦接接收单元，用以对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K为正整数且K小于M，致使K个数值转换后数据的数据量小于M个原始侦测 数据的数据量，以达到减少数据量的功效。
于一实施例中，数值转换单元是采用一数值转换机制对该M个原始侦测数据进行数值转换程序。
于一实施例中，数值转换机制是一傅立叶转换(Fourier transform)机制或一拉普拉斯转换(Laplace transform)机制。
于一实施例中，数据处理装置是一蓝牙芯片或一物联网(Internet of Thing,IoT)芯片并可通过一网络连结一云端数据库或一移动通信装置。
于一实施例中，数值转换单元还比较该M个原始侦测数据与一预设值，并根据该M个原始侦测数据中的大于预设值的K个原始侦测数据产生该K个数值转换后数据。
于一实施例中，M个原始侦测数据是一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一足部的M个侦测位置。
于一实施例中，电容压力侦测鞋垫的该M个电容感测节点是位于电容纱线与导电纱线彼此交错处，并且电容纱线的表面形成有两个可带电涂层。
根据本发明的另一具体实施例为一种数据量减少方法，包含下列步骤：(a)提供M个原始侦测数据，其中M为正整数；以及(b)对该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，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。
如前所述的数据量减少方法，其中，步骤(b)是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。
如前所述的数据量减少方法，其中，该数值转换机制是一傅立叶转换机制或一拉普拉斯转换机制。
如前所述的数据量减少方法，进一步包含下列步骤：将该K个数值转换后数据输出至一网络；以及通过该网络连结一云端数据库或一移动通信装置。
如前所述的数据量减少方法，进一步包含下列步骤：比较该M个原始侦测数据与一预设值，并根据该M个原始侦测数据中的大于该预设值的K个原始侦测数据产生该K个数值转换后数据。
如前所述的数据量减少方法，其中，该M个原始侦测数据是一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一足部的M个侦测位置。
如前所述的数据量减少方法，其中，该电容压力侦测鞋垫的该M个电容感测节点是位于电容纱线与导电纱线彼此交错处，并且该电容纱线的表面形成有两个可带电涂层。
相较于现有技术，根据本发明的数据处理装置及数据量减少方法是采用傅立叶转换或拉普拉斯转换等数值转换机制或是通过与预设值进行比较的筛选机制来对接收到的庞大数据量进行处理，由以大幅减少其数据量，以使得数据处理装置能够储存并即时处理经数值转换后的数据，故能有效避免现有技术中由于数据量过大而无法储存与数据处理的缺点。
关于本发明的优点与精神可以通过以下的发明详述及附图得到进一步的了解。
附图的简要说明
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为本发明的数据量减少方法应用于电容压力侦测鞋垫的流程图。
主要元件符号说明：
1：鞋子
2：电容压力侦测鞋垫
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
CS、CS1～CSM：电容变化量
CT1～CTK：数值转换后数据
50：接收单元
52：数值转换单元
54：输出单元
L1：电容纱线
L2：导电纱线
S10～S18：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是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CS传送至运算芯片CH。运算芯片CH亦可连线至网络NET并可通过网络NET连结至云端数据库DB或移动通信装置MB。
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叠加，而拉普拉斯转换则是将一个函数表示为许多矩阵的叠加。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。
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。
于实际应用中，如图6所示，运算芯片CH亦可通过输出单元54连线至网络NET并将K个数值转换后数据CT1～CTK输出至网络NET。如图4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,…的压力分布资讯及/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，鞋垫业者可通过云端数据库DB得到使用者A的足部FT的运动生理状况资讯并据以研判出使用者A的足部问题。接着，鞋垫业者即可替使用者A量身订做客制化的矫正用鞋垫并设置于鞋子内，当使用者A穿着设有客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A亦可操作其移动通信装置(例如智能型手机)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。
根据本发明的另一具体实施例为一种数据量减少方法，可包含下列步骤：提供M个原始侦测数据，其中M为正整数；以及对该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，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。
请参照图7，图7为本发明的数据量减少方法应用于电容压力侦测鞋垫的流程图。如图7所示，该方法可包含下列步骤：
步骤S10：当电容压力侦测鞋垫受到使用者的足部所施加的压力时，表面形成有两个可带电涂层的电容纱线被压力压扁而导致电荷分散，在该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电容改变。
步骤S12：电容压力侦测鞋垫通过多个电容感测节点分别感测对应于足部的多个侦测位置的多个电容变化量。
步骤S14：运算芯片自多个电容感测节点接收多个电容变化量并通过筛选转换机制缩减数据量后研判出使用者的足部的运动生理状况资讯。
需说明的是，运算芯片可采用例如傅立叶转换或拉普拉斯转换等数值转换程序，或是通过与预设值比较的方式进行筛选来达到缩减数据量的功效，但不以此为限。
步骤S16：运算芯片可通过网络将使用者的足部的运动生理状况资讯上传至云端数据库。
步骤S18：使用者可操作移动通信装置通过网络连线至运算芯片或云端数据库，以取得使用者的足部的运动生理状况资讯。
于一实施例中，本发明的数据量减少方法是通过压力感测纱线在鞋垫上建立多个网格点上的压力。当消费者在运动的过程中，这些感测点会感测到足垫上的压力相对于时间的函数，然后以取样的方式去记录压力对时间的函数曲线。
假设鞋垫上有10,000个不同的压力感测点，每个感测点为每0.1秒取样一次并连续取样8小时，则鞋垫上在8小时内取样得到的压力量测值共有10,000x 10x 60x 60x 8＝2,880,000,000，亦即28亿8,000万笔数据。这数量表面上看起来相当惊人，但实际上可通过秩序化的模型去加以大幅简化，并以简单的模型记录下来。
于此实施例中，本发明提出关于鞋垫上可抓取的有用资讯至少包括下列 几项：
(1)可设定站立/坐下、慢走/快走、慢跑/快跑、下坡/平地/上坡/畸形地面等四个模式。于每个模式中，当使用者在学习的初期，也就是第一阶段模型，分别把数据的查找表分成2,2,2,4等四个选项值，并据以产生出32种不同的模式(Patterns)。
(2)针对标准的动作(也就是标准的脚型，标准的动作，标准的身高体重＜体型＞)去测试这32种模式约30秒左右的取样。也就是说每个取样大约耗费10,000x 10x 30＝3,000,000(亦即300万笔的取样数据)。整体而言，所有32个模式可以建立出来约9,600万笔的取样数据。
(3)将每个300万点的数据中的每一个点的300个取样点去进行10,000次快速傅立叶分析(FFT)，以找出两组重要的数值(A,F)：
F:Peak Frequency(找出DB值最高，前三大不同Base Frequency的频率)
A:Amplitude of Peak Frequency(找出对应这些频率的振幅DB数值)
(4)若上述第三点中的Peak Frequency是另一个Peak Frequency的整数倍时，则该最低频率即称为Base Frequency。其他整数倍的Frequency则为针对Base Frequency的泛频率，用以决定每一个周期运动的大致波型。
(5)至今为止总共取得6组数据，分成3个主要频率，每组数据各有以下2组数据：
甲、(基础频率，振幅)；(第一泛频倍数，振幅)；(第二泛频倍数，振幅)…
乙、针对32种组合式的运动模式，分别订出约10种指标型的运动模式并测出压力对时间波形后，做出快速傅立叶分析(FFT)与上述甲数据中的波形进行比较，以计算出32组各10种指标型运动模式的转换后频率与振幅差异。
Delta[(基础频率，振幅)；(第一泛频倍数，振幅)；(第二泛频倍数，振幅)…]
(6)于上述第5点中的数据中，甲的部份是参考数据，属于正确运动姿态的数据模型。而乙的部份则是10种偏离标准姿态的错误模式所产生出来的偏移量。假设针对10,000个量测点中，有500个量测点大量偏移标准姿态的数值，则可针对这500个点进行下列分析：
甲、找出32个模式中是哪几个模式在这500个点上面是最明显偏离标准值的。选出其中最多到主要的三个模式。
Point(N)偏离1＝模式M1(Delta F,Delta A,Delta F1,Delta A1,….)
Point(N)偏离2＝模式M2(Delta F,Delta A,Delta F1,Delta A1,….)
Point(N)偏离3＝模式M3(Delta F,Delta A,Delta F1,Delta A1,….)
需说明的是，上述之所以可判断出是哪个模式的偏离，是因为当初建立的标准错误模式偏离Delta的数值偏移向量与目前这个数据所算出来的偏移向量均朝向相同的方向。而Point(N)偏离则是这个偏移向量长度与标准偏移向量长度的比值，可代表偏移程度的大小(成正比)。
乙、在每一段30秒的时间之内，纪录最多3个泛频，3个模式(偏离)中的各两笔数据。所以每30秒钟内，最多有500个点要记录到最多6笔数据。所以是每30秒钟3,000笔数据。
丙、将500个异常点分成最多10个区域，分别在各区域之内找出特定模式下，偏离程度最高的点。这样最多也只会有10个点的数据被记录下来。因此每30秒钟记录下来的数据最多只有60笔。
丁、8个小时内有2x 60x 8＝960个30秒的时间段，所以8小时的运动纪录在这10,000个量测点上，最多可产生60x 960x 2＝115,200Bytes的数据。因此，总数据量(也就是IoT记忆体容量)只需约120KB即可，不需占用大量记忆体空间，故可大幅简化数据量M，有效节省运算及记忆体空间。
(7)为了简化量测点数据搜集的复杂度，本发明亦可在鞋垫的横向与纵向各制作100条网格线。每一条网格线的端点(共400个端点)上分别架设25条量测接头，以耦接电压信号感测器。
相较于现有技术，根据本发明的数据处理装置及数据量减少方法是采用傅立叶转换或拉普拉斯转换等数值转换机制或是通过与预设值进行比较的筛选机制来对接收到的庞大数据量进行处理，由以大幅减少其数据量，以使得数据处理装置能够储存并即时处理经数值转换后的数据，故能有效避免现有技术中由于数据量过大而无法储存与数据处理的缺点。
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所欲申请的专利范围的范畴内。
工业应用性
本发明的数据处理装置及数据量减少方法是采用傅立叶转换或拉普拉斯转换等数值转换机制或是通过与预设值进行比较的筛选机制来对接收到的庞大数据量进行处理，由以大幅减少其数据量，以使得数据处理装置能够储存并即时处理经数值转换后的数据，故能有效避免现有技术中由于数据量过大而无法储存与数据处理的缺点。

Claims (14)

  1. 一种数据处理装置，包含：
    一接收单元，用以接收M个原始侦测数据，其中M为正整数；以及
    一数值转换单元，耦接该接收单元，用以对该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。
  2. 如权利要求1所述的数据处理装置，其特征在于，该数值转换单元是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。
  3. 如权利要求2所述的数据处理装置，其特征在于，该数值转换机制是一傅立叶转换机制或一拉普拉斯转换机制。
  4. 如权利要求1所述的数据处理装置，其特征在于，一蓝牙芯片或一物联网芯片并可通过一网络连结一云端数据库或一移动通信装置。
  5. 如权利要求1所述的数据处理装置，其特征在于，该数值转换单元还比较该M个原始侦测数据与一预设值，并根据该M个原始侦测数据中的大于该预设值的K个原始侦测数据产生该K个数值转换后数据。
  6. 如权利要求1所述的数据处理装置，其特征在于，该M个原始侦测数据是一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一足部的M个侦测位置。
  7. 如权利要求6所述的数据处理装置，其特征在于，该电容压力侦测鞋垫的该M个电容感测节点是位于电容纱线与导电纱线彼此交错处，并且该电容纱线的表面形成有两个可带电涂层。
  8. 一种数据量减少方法，包含下列步骤：
    (a)提供M个原始侦测数据，其中M为正整数；以及
    (b)对该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，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。
  9. 如权利要求8所述的数据量减少方法，其特征在于，步骤(b)是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。
  10. 如权利要求9所述的数据量减少方法，其特征在于，该数值转换机制是一傅立叶转换机制或一拉普拉斯转换机制。
  11. 如权利要求8所述的数据量减少方法，进一步包含下列步骤：
    将该K个数值转换后数据输出至一网络；以及
    通过该网络连结一云端数据库或一移动通信装置。
  12. 如权利要求8所述的数据量减少方法，进一步包含下列步骤：
    比较该M个原始侦测数据与一预设值，并根据该M个原始侦测数据中的大于该预设值的K个原始侦测数据产生该K个数值转换后数据。
  13. 如权利要求8所述的数据量减少方法，其特征在于，该M个原始侦测数据是一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一足部的M个侦测位置。
  14. 如权利要求12所述的数据量减少方法，其特征在于，该电容压力侦测鞋垫的该M个电容感测节点是位于电容纱线与导电纱线彼此交错处，并且该电容纱线的表面形成有两个可带电涂层。
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