WO2018086321A1 - 一种计步方法及装置 - Google Patents

一种计步方法及装置 Download PDF

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Publication number
WO2018086321A1
WO2018086321A1 PCT/CN2017/082933 CN2017082933W WO2018086321A1 WO 2018086321 A1 WO2018086321 A1 WO 2018086321A1 CN 2017082933 W CN2017082933 W CN 2017082933W WO 2018086321 A1 WO2018086321 A1 WO 2018086321A1
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WIPO (PCT)
Prior art keywords
limb
information
counting
wearing
period
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PCT/CN2017/082933
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English (en)
French (fr)
Inventor
廖衡
孙毅
黄雪妍
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华为技术有限公司
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Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Publication of WO2018086321A1 publication Critical patent/WO2018086321A1/zh
Priority to US16/172,341 priority Critical patent/US20190063949A1/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C22/00—Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
    • G01C22/006—Pedometers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
    • G06F1/16—Constructional details or arrangements
    • G06F1/1613—Constructional details or arrangements for portable computers
    • G06F1/163—Wearable computers, e.g. on a belt
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/20—Movements or behaviour, e.g. gesture recognition
    • G06V40/23—Recognition of whole body movements, e.g. for sport training
    • G06V40/25—Recognition of walking or running movements, e.g. gait recognition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/12—Classification; Matching

Definitions

  • the present application relates to the field of communications technologies, and in particular, to a step counting method and apparatus.
  • a pedometer is used to monitor daily exercise progress, and people's walking steps, walking distance, and the like are calculated.
  • the pedometer currently used on the market is mainly an acceleration sensor or a gyroscope.
  • the pedometer is set in the collection wearable device, directly worn on the body or integrated into the user's clothes or accessories, by collecting the vibration time domain of the wearing limb.
  • the number of walking steps is calculated by the period, amplitude, acceleration or waveform information of the frequency domain.
  • the vibration signal collected by the pedometer is not necessarily caused by the user's walking, it may be due to other reasons, such as arm movement caused by brushing, arm movement caused by typing on the keyboard, or small amplitude of the leg.
  • the vibration signals caused by these non-walking are not judged, and these cases are counted, resulting in inaccurate step counting.
  • an embodiment of the present invention provides a step counting method, the method comprising: the step counting device collecting information of a wearing limb, wherein the wearing limb information is used to characterize a user's wearing of the limb of the step counting device Characteristic information; the pedometer device determines a limb type of the pedometer device according to the wearing limb information, the limb type includes a dominant limb or a non-dominant limb; and the pedometer device collects and wears the pedometer device The step information of the limb in a step counting period, wherein the step information is information for calculating the number of steps; wherein the collecting of the step information can be performed simultaneously with the collecting of the information of the wearing limb And the step counting device searches for the step reference standard reference information corresponding to the limb of the step counting device in the step counting period in the corresponding relationship between the limb type and the step standard reference information; wherein the limb body
  • the correspondence between the type and the step reference standard reference information may be pre-learned or pre
  • the test information is obtained by processing the different step information collected by the plurality of users using the dominant limb or the non-dominant limb wearing the pedometer device and being in the walking state; specifically, the step counting standard reference information may be Pre-processing may be performed by pre-processing different pre-processing information collected by the plurality of users using the dominant limb or the non-dominant limb wearing the pedometer device and being in the walking state, and the pre-processing may include using a statistical method or machine learning.
  • the step counting device determines, according to the step counting information and the found step counting standard reference information, whether the user is in a walking state during the counting step; the step counting device is Determining that the user is in the week of the week During the period of walking, the number of steps is calculated according to the step information.
  • the pedometer device determines the limb type of the wearing limb according to the collected wearing limb information, and collects the reference standard reference information corresponding to the limb of the pedometer device. Wearing the step information of the limb of the pedometer device to determine whether the user is in a walking state during the step counting period, because the limb type of the wearing limb is distinguished, and the corresponding step is set for different limb types. Standard reference information, thus reducing step counting errors and improving step accuracy.
  • the pedometer device determines that the user is in a non-walking state during the current step period and discards the pedometer information.
  • the method further comprises: the step counting device accumulating the calculated number of steps to the previous step counting period of the counting step period The total number of steps accumulated at the end; after the step counting device discards the step information, the method further includes: the step counting device accumulating the total number of steps accumulated at the end of the previous counting period of the counting step period The total number of steps accumulated at the end of this counting step.
  • the step counting device adds the calculated number of steps to the total number of steps accumulated at the end of the previous counting period of the counting step, or the previous counting period of the counting step period.
  • the total number of steps accumulated at the end is used as the total number of steps accumulated at the end of the counting step, which improves the step counting accuracy of the pedometer.
  • the step reference standard reference information includes a parameter threshold corresponding to each of the at least one setting parameter; wherein the setting parameter may be a probability that the wearing limb is in a walking state and the wearing limb The difference in probability of being in a non-walking state, or the vibration frequency of the wearing limb, or the amplitude of vibration of the wearing limb.
  • Determining, by the step counting device, whether the user is in a walking state during the counting step according to the step counting information and the found step counting standard reference information comprising: determining, by the step counting device, the step information At least one parameter value of the set parameter; if the determined parameter value of the at least one set parameter exceeds the parameter threshold of the corresponding set parameter, determining that the user is in a walking state during the counting step period, otherwise determining the user It is in a non-walking state during this counting step.
  • different parameter thresholds are set according to different setting parameters, and whether the user is in a walking state is determined by the set parameter threshold, and the step counting precision of the pedometer device is improved.
  • the pedometer device is in a corresponding relationship between the limb type and the filtering mode, wherein the correspondence between the limb type and the filtering mode may be pre-learned or preset.
  • the corresponding filtering relationship is determined according to the determined limb type, and the step information is filtered, thereby further improving the step counting precision of the step counting device.
  • an embodiment of the present invention provides a step counting method, the method comprising: the step counting device collecting information of the wearing limb, wherein the wearing limb information is used to represent a correlation of a limb worn by the user wearing the pedometer device Characteristic information; the pedometer device determines a limb type of the pedometer device according to the wearing limb information, the limb type includes a dominant limb or a non-dominant limb; and the pedometer device collects and wears the pedometer device The step information of the limb in a counting period, wherein the step information is information for calculating the number of steps; wherein the step counting device is in a correspondence between the limb type and the filtering method, wherein Corresponding relationship between the limb type and the filtering method is pre-learned or preset, and the filter corresponding to the limb wearing the pedometer device in the present step counting period is searched.
  • the step counting device performs filtering processing on the step information using a determined filtering manner to determine filtered step information; the step counting device determines the user according to the filtered step information Whether it is in a walking state in the current counting period; the counting device determines that the user is in a walking state during the counting step, and calculates the number of steps according to the step information.
  • the pedometer device determines the limb type of the wearing limb according to the collected wearing limb information, determines a corresponding filtering manner according to the limb type, and determines according to the filtered step information. Whether the user is in the walking state during the counting cycle, because the limb type of the wearing limb is distinguished, and the corresponding filtering mode is set for different limb types, the step counting error is reduced, and the step counting precision is improved.
  • the pedometer device determines that the user is in a non-walking state during the current step period and discards the pedometer information.
  • an embodiment of the present invention provides a pedometer device, the device comprising: an acquisition module, configured to collect information of a wearing limb, wherein the wearing limb information is used to represent a limb of a user wearing the pedometer device Corresponding feature information; a processing module, configured to determine a limb type of the pedometer device according to the wearing limb information, the limb type includes a dominant limb or a non-dominant limb; the collecting module is further configured to collect and wear The step information of the limb of the step counting device in a step counting period, wherein the step counting information is information for calculating the number of steps; the searching module is configured to refer to the reference information in the limb type and the stepping standard In the corresponding relationship, the step reference standard reference information corresponding to the limb wearing the pedometer device in the current step counting period is searched; wherein the step reference standard reference information corresponding to a dominant limb or a non-dominant limb is separately for multiple users Using the different step information
  • the pedometer device determines the limb type of the wearing limb according to the collected wearing limb information, and collects the reference standard reference information corresponding to the limb of the pedometer device. Wearing the step information of the limb of the pedometer device to determine whether the user is in a walking state during the step counting period, because the limb type of the wearing limb is distinguished, and the corresponding step is set for different limb types. Standard reference information, thus reducing step counting errors and improving step accuracy.
  • the determining module is further configured to: add the calculated number of steps to the end of the previous step period of the step step The total number of steps accumulated in the time; after the determining module discards the step information, the determining module further uses: the determining module to accumulate the total number of steps accumulated at the end of the previous counting period of the counting step period The total number of steps accumulated at the end of the step cycle.
  • the step reference standard reference information includes a parameter threshold corresponding to each of the at least one setting parameter; the step counting device determines the location according to the step information and the found step reference standard reference information. Whether the user is in the walking state during the counting step, the step counting device determines the parameter value of the at least one setting parameter of the step counting information; if the determined parameter value of the at least one setting parameter exceeds the corresponding value Setting a parameter threshold of the parameter determines that the user is in a walking state during the counting step period, otherwise determining that the user is in a non-walking state during the counting step period.
  • the at least one setting parameter includes: a difference between a probability that the wearing limb is in a walking state and a probability that the wearing limb is in a non-walking state; in one possible design, the The at least one setting parameter further includes: a vibration frequency of the wearing limb, or a vibration amplitude of the wearing limb.
  • the searching module is further configured to: in a correspondence between the limb type and the filtering mode, search for a filtering method corresponding to a limb wearing the pedometer device in the counting step period, wherein Corresponding relationship between the limb type and the filtering mode is pre-learned or preset; the processing module determines, according to the step information and the found step reference standard reference information, whether the user is in the current step period Before being in the walking state, the method is further configured to: perform filtering processing on the step information by using a determined filtering manner.
  • an embodiment of the present invention provides a pedometer device, the device comprising: an acquisition module, configured to collect information of a wearing limb, wherein the wearing limb information is used to represent a limb of a user wearing the pedometer device Corresponding feature information; a processing module, configured to determine a limb type of the pedometer device according to the wearing limb information, the limb type includes a dominant limb or a non-dominant limb; the collecting module is further configured to collect and wear The step information of the limb of the step counting device in a step counting period, wherein the step counting information is information for calculating the number of steps; and the searching module is configured to correspond to the relationship between the limb type and the filtering method And searching for a filtering method corresponding to the limb of the step counting device in the step of the step counting, wherein the correspondence between the limb type and the filtering mode is pre-learned or preset; the processing module is further configured to: Performing a filtering process on the step information using
  • the pedometer device determines the limb type of the wearing limb according to the collected wearing limb information, determines a corresponding filtering manner according to the limb type, and determines according to the filtered step information. Whether the user is in the walking state during the counting cycle, because the limb type of the wearing limb is distinguished, and the corresponding filtering mode is set for different limb types, the step counting error is reduced, and the step counting precision is improved.
  • an embodiment of the present invention provides a pedometer device, including:
  • a processor for storing a software program, the processor for reading a software program stored in the memory, implementing the first aspect, any one of the possible aspects of the first aspect, the second aspect or the Any of a number of possible designs in either aspect.
  • an embodiment of the present invention provides a computer readable storage medium, comprising instructions, when executed on a computer, causing a computer to perform the first aspect, any one of the possible aspects of the first aspect, the second aspect or the Any of a number of possible designs in either aspect.
  • the pedometer device determines the limb type of the wearing limb according to the collected wearing limb information, and collects the reference standard reference information corresponding to the limb of the pedometer device. Wearing the step information of the limb of the pedometer device to determine whether the user is in a walking state during the step counting period, because the limb type of the wearing limb is distinguished, and the corresponding step is set for different limb types. Standard reference information, thus reducing step counting errors and improving step accuracy.
  • FIG. 1 is a schematic flowchart of a step counting method according to an embodiment of the present invention.
  • FIG. 2 is a schematic flowchart of another step counting method according to an embodiment of the present invention.
  • FIG. 3 is a schematic structural diagram of a step counting device according to an embodiment of the present invention.
  • FIG. 4 is a schematic structural diagram of another step counting device according to an embodiment of the present invention.
  • FIG. 5 is a schematic structural diagram of hardware of a pedometer device according to an embodiment of the present invention.
  • the user uses a pedometer to monitor the daily exercise progress and calculate the number of walking steps. Since the pacing device is different in position to be worn, the collected vibration signal is not necessarily caused by the user's walking. The existing pedometer method does not distinguish the wearing position of the pedometer device from the collected vibration signal, thereby causing the measurement. The steps are not accurate.
  • the step counting device judges the collected step information according to different limb types, improves the step counting precision, and reduces the step counting error.
  • the embodiment of the invention provides a step counting method. As shown in FIG. 1 , the method includes the following process:
  • the pedometer device collects information about the wearing limb, wherein the wearing limb information is used to characterize relevant feature information of the limb worn by the user wearing the pedometer device.
  • the step counting device may be a wearable device, such as a smart watch, a smart bracelet, or the like, or may be a portable device, such as a smart phone.
  • the step counting device may be a system including a wearable device, a mobile smart device with the wearable device, or a network cloud server or the like directly or indirectly connected to the wearable device.
  • the pedometer device determines a limb type of the pedometer device according to the wearing limb information, and the limb type includes a dominant limb or a non-dominant limb.
  • the dominant limb is the limb most commonly used by the wearer
  • the non-dominant limb is other limbs of the wearer's limb other than the dominant limb, such as a hand, foot, finger or other limb.
  • the wearer's common hand is the left hand
  • the wearer's dominant limb is the left hand
  • the non-dominant limb is the right hand
  • the wearer's dominant limb is the right hand and the non-dominant limb is the left hand
  • the frequency of use of dominant and non-dominant limbs is different. After the accumulation of time, there will be different manifestations.
  • the differences include: the dominant limb is thicker than the non-dominant limb, because the dominant limb is rougher than the non-dominant limb, and the skin surface of the dominant limb is more than non-dominant.
  • the skin surface of the limb is thicker, resulting in the pH of the user's dominant limb is significantly higher than the pH of the non-dominant limb; according to the skin conductivity principle, the skin conductivity of the user's dominant hand and the skin conductivity of the non-dominant hand are statistically significant.
  • the difference is that the variance of the skin conductivity signal of the dominant hand and the skin conductivity signal of the non-dominant hand is less than or equal to 0.05; or the body temperature of the dominant limb is higher than that of the non-dominant limb, and the blood oxygen concentration of the dominant limb is higher than that of the non-dominant limb
  • the dominant limb is different from the non-dominant limb by the photoplethysmographic signal.
  • the information of the dominant limb is collected by the pedometer device during the wearing process, and a large number of repeated collected data are counted to obtain parameter information corresponding to the dominant limb or the non-dominant limb.
  • At least one of body temperature, blood oxygen, chemical pH information or other information is collected, and the parameter information corresponding to the dominant limb or the non-dominant limb obtained in advance is used to determine the wearing of the limb.
  • Types of. the variance of the skin conductivity signal of the scientific research leader and the skin conductivity signal of the non-dominant hand is less than or equal to 0.05, and a threshold value for distinguishing the dominant and non-dominant limb conductivity signals may be set, and the conductive signal of the wearing limb may be collected. And if the signal of the conductivity signal is greater than the conductivity signal threshold, determining that the pedometer device is worn on the dominant limb.
  • the pedometer device collects step information of a limb wearing the pedometer device in a step counting period, wherein the step counting information is information used to calculate the number of steps.
  • the step information may include: a time domain or a frequency domain vibration week of the limb in various directions Period, vibration amplitude, waveform information, vibration acceleration information in all directions, etc.
  • calculating the number of steps of the step counting object by using the step counting information includes collecting vibration directions of various directions of the wearing limb, for example, X, Y, and Z directions, and generating a waveform diagram that changes with time.
  • the number of steps is calculated from the number of waveforms in the waveform graph.
  • the concept of frequency threshold or frequency interval can also be introduced. Waveforms within the frequency interval or within the threshold range are counted into the number of waveforms, otherwise they are not counted in the number of waveforms.
  • the pedometer device searches, in a correspondence relationship between the limb type and the step reference standard reference information, the step reference standard reference information corresponding to the limb wearing the pedometer device in the step counting period; wherein
  • the correspondence between the limb type and the step reference standard reference information may be pre-learned or pre-set, and the step reference standard reference information corresponding to a dominant limb or non-dominant limb is to use the dominant limb or the non-dominant limb to wear the step for each user separately.
  • the different step information collected by the device and in the walking state is obtained.
  • the step reference standard reference information may be obtained by pre-processing different step information collected by the plurality of users using the dominant limb or the non-dominant limb wearing the pedometer device and being in a walking state.
  • the pre-processing may include using a statistical method, or a machine learning method, or an empirical value setting method.
  • the pedometer device determines, according to the step counting information and the found step counting standard reference information, whether the user is in a walking state during the counting step period.
  • the step counting standard reference information includes a parameter threshold corresponding to the at least one setting parameter respectively; the step counting device determines, according to the step counting information and the found step counting standard reference information, that the user is in the present Whether the step counting device determines the parameter value of the at least one setting parameter of the step counting information; if the determined parameter value of the at least one setting parameter exceeds the corresponding setting parameter
  • the parameter threshold determines that the user is in a walking state during the counting step period, otherwise it is determined that the user is in a non-walking state during the counting step period.
  • the at least one setting parameter comprises: a difference between a probability that the wearing limb is in a walking state and a probability that the wearing limb is in a non-walking state; a vibration frequency of the wearing limb, or the wearing limb The amplitude of the vibration.
  • Example 1 Using the step information to calculate the probability that the user is in a walking state and the probability that the user is in a non-walking state, and if it is determined that the step counting device is worn on the user's dominant limb, the probability of the user being in a walking state The difference between the probability that the step object is in the non-walking state is greater than the first threshold, and the user is determined to be in the walking state; the difference between the probability that the user is in the walking state and the probability that the stepping object is in the non-walking state is less than or equal to the first threshold.
  • Determining that the user is in a walking state if it is determined that the pedometer device is worn on the non-dominant limb of the user, the difference between the probability that the user is in the walking state and the probability that the stepping object is in the non-walking state is greater than the second threshold, and determining that the user is in the walking state; The difference between the probability that the user is in the walking state and the probability that the stepping object is in the non-walking state is less than or equal to the second threshold, and the user is determined to be in the walking state, wherein the first threshold is greater than the second threshold.
  • the probability for being in the walking state is calculated by the walking state probability function
  • the probability for the non-walking state is calculated by the non-walking state probability function.
  • the step function or the non-counter function is calculated by using a linear function, a forward function, or an inverse function, and is not limited by the embodiment of the present invention.
  • Example 2 If it is determined that the pedometer device is worn on the main limb of the user, the vibration frequency or vibration amplitude of the collected wearing limb is greater than the third threshold, then the user is determined to be in a walking state; if it is determined that the pedometer device is worn by the user On the non-dominant limb, if the vibration frequency or the vibration amplitude of the collected wearing limb is greater than the fourth threshold, it is determined that the user is in a walking state, wherein the third threshold is greater than the fourth threshold.
  • the pedometer device determines that the user is in a walking state during the counting step period, and calculates the number of steps according to the step counting information.
  • the step counting device discards the step information in determining that the user is in a non-walking state in the current counting period.
  • the pedometer device determines the limb type of the wearing limb according to the collected wearing limb information, and collects the reference standard reference information corresponding to the limb of the pedometer device. Wearing the step information of the limb of the pedometer device to determine whether the user is in a walking state during the step counting period, because the limb type of the wearing limb is distinguished, and the corresponding step is set for different limb types. Standard reference information, thus reducing step counting errors and improving step accuracy.
  • the step counting device further comprises: adding, by the step counting device, the calculated number of steps to the step of the step step. In the total number of steps accumulated at the end of a counting period;
  • the step counting device After the step counting device discards the step counting information in step S16, the step counting device further includes the total number of steps accumulated at the end of the previous counting period of the counting step period as the end of the counting step period. The total number of steps accumulated.
  • the pedometer device searches for a filtering method corresponding to a limb wearing the pedometer device in the step counting period in a corresponding relationship between the limb type and the filtering mode, where Corresponding relationship between the limb type and the filtering mode is pre-learned or preset; the step counting device determines whether the user is in the current step counting period according to the step counting information and the found step counting standard reference information.
  • the method further includes: the step counting device performing filtering processing on the step information by using a determined filtering manner.
  • Another embodiment of the present invention provides a step counting method. As shown in FIG. 2, the method includes the following process:
  • the pedometer device collects information about the wearing limb, wherein the wearing limb information is used to represent relevant feature information of the limb of the user wearing the pedometer device.
  • the pedometer device determines a limb type of the pedometer device according to the wearing limb information, and the limb type includes a dominant limb or a non-dominant limb.
  • the pedometer device collects pedometer information of a limb wearing the pedometer device in a pedometer period, wherein the pedometer information is information used to calculate the number of steps.
  • the pedometer device searches for a filtering manner corresponding to a limb wearing the pedometer device in the counting step period in a correspondence between the limb type and the filtering method.
  • the correspondence between the limb type and the filtering mode is pre-learned or preset.
  • the first filter is matched; if it is determined that the pedometer device is worn on the non-dominant limb of the user, the second filter is matched, wherein the first filter
  • the filter and the second filter use different filtering parameters.
  • the first filter has a stronger filtering effect than the second filter, and can filter more interference signals or noise, and uses a weaker second filter for filtering the non-dominant limb wearer's step signal to avoid Errors filter out more walking signals.
  • the filter may be a high pass filter, a low pass filter, a band pass filter, or an FFT filter for converting step information from a time domain to a frequency domain signal.
  • the filter parameters of the filter include a filter lower limit of the high pass filter, a filter upper limit of the low pass filter, a filter upper limit or a filter lower limit of the band pass filter, or a filter upper limit, a lower limit or a sampling frequency of the FFT filter, etc., Not limited.
  • the step counting device performs filtering processing on the step information by using a determined filtering manner, and determines the filtered step information.
  • the pedometer device determines, according to the filtered step information, whether the user is in a walking state during the counting step period.
  • a periodic signal of the filtered step information includes a rising and falling interval
  • the periodic signal is counted as a walking step
  • the filtered step information is a maximum value and a minimum value of the periodic signal If the difference between the absolute values is greater than the fifth threshold, the periodic signal is counted as a walking step; if the proportion of the rising interval and the falling interval of one periodic signal of the filtered step information is close, the periodic signal is Count as a walking step.
  • the pedometer device determines that the user is in a walking state during the counting step period, and calculates the number of steps according to the step counting information.
  • the step counting device discards the step information in determining that the user is in a non-walking state in the current counting period.
  • the pedometer device determines the limb type of the wearing limb according to the collected wearing limb information, determines a corresponding filtering manner according to the limb type, and determines according to the filtered step information. Whether the user is in the walking state during the counting cycle, because the limb type of the wearing limb is distinguished, and the corresponding filtering mode is set for different limb types, the step counting error is reduced, and the step counting precision is improved.
  • a pedometer device 30 according to an embodiment of the present invention, as shown in FIG. 3, includes:
  • the collecting module 31 is configured to collect information about the wearing limb, wherein the wearing limb information is used to represent relevant feature information of the limb of the user wearing the pedometer.
  • the processing module 32 is configured to determine a limb type of the step counting device according to the wearing limb information, the limb type including a dominant limb or a non-dominant limb.
  • the collecting module 31 is further configured to collect step counting information of a limb wearing the pedometer device in a step counting period, wherein the step counting information is information used to calculate the number of steps.
  • the searching module 33 is configured to search, in a correspondence between the limb type and the step reference standard reference information, the step reference standard reference information corresponding to the limb wearing the step counting device in the current step counting period; wherein, the corresponding one is dominant
  • the step reference standard reference information of the limb or the non-dominant limb is obtained by pre-processing the different step information collected by the plurality of users using the dominant limb or the non-dominant limb wearing the pedometer device and being in the walking state.
  • the determining module 34 determines, according to the step counting information and the found step counting standard reference information, whether the user is in a walking state during the counting step period.
  • the determining module 34 is further configured to: when determining that the user is in a walking state during the counting step period, calculate the number of steps according to the step counting information.
  • the pedometer device determines the limb type of the wearing limb according to the collected wearing limb information, and collects the reference standard reference information corresponding to the limb of the pedometer device. Wearing the step information of the limb of the pedometer device to determine whether the user is in a walking state during the step counting period, because the limb type of the wearing limb is distinguished, and the corresponding step is set for different limb types. Standard reference information, thus reducing step counting errors and improving step accuracy.
  • the determining module is further configured to: add the calculated step number to the total accumulated at the end of the previous counting period of the counting step period.
  • the determining module further uses the total number of steps accumulated at the end of the previous counting period of the counting step period as the end of the counting step period. The total number of steps accumulated.
  • the step counting standard reference information includes a parameter threshold corresponding to each of the at least one setting parameter;
  • the step counting device determines, according to the step counting information and the found step counting standard reference information, whether the user is in a walking state during the counting step period, and the step counting device determines at least one of the step counting information Setting a parameter value of the parameter; if the determined parameter value of the at least one setting parameter exceeds the parameter threshold of the corresponding setting parameter, determining that the user is in a walking state during the counting step period, otherwise determining that the user is in the present It is in a non-walking state during the counting period.
  • the at least one setting parameter includes: a difference between a probability that the wearing limb is in a walking state and a probability that the wearing limb is in a non-walking state;
  • the at least one setting parameter further includes: a vibration frequency of the wearing limb, or a vibration amplitude of the wearing limb.
  • the searching module searches for a filtering manner corresponding to a limb wearing the pedometer device in the counting step period, wherein the limb type and the filtering manner Corresponding relationship is pre-learned or preset; the processing module determines, according to the step information and the found step reference standard reference information, whether the user is in a walking state in the current step period, and is further configured to: Filter processing is performed on the step information using a determined filtering method.
  • a pedometer device 40 according to an embodiment of the present invention, as shown in FIG. 4, includes:
  • the collecting module 41 is configured to collect information about the wearing limb, wherein the wearing limb information is used to represent relevant feature information of the limb of the user wearing the pedometer.
  • the processing module 42 is configured to determine a limb type of the pedometer device according to the wearing limb information, the limb type including a dominant limb or a non-dominant limb.
  • the collecting module 41 is further configured to collect step counting information of a limb wearing the step counting device in a step counting period, wherein the step counting information is information used to calculate the number of steps.
  • the searching module 43 is configured to search, in a correspondence relationship between the limb type and the filtering mode, a filtering manner corresponding to a limb wearing the pedometer device in the counting step period; wherein the limb type corresponds to a filtering manner Relationships are pre-learned or pre-set.
  • the processing module 42 is further configured to perform filtering processing on the step information by using a determined filtering manner to determine the filtered step information.
  • the determining module 44 is configured to determine, according to the filtered step information, whether the user is in a walking state during the counting step.
  • the determining module 44 is further configured to: when the step counting device determines that the user is in a walking state during the counting step period, calculate the number of steps according to the step counting information.
  • the pedometer device determines the limb type of the wearing limb according to the collected wearing limb information, determines a corresponding filtering manner according to the limb type, and determines according to the filtered step information. Whether the user is in the walking state during the counting cycle, because the limb type of the wearing limb is distinguished, and the corresponding filtering mode is set for different limb types, the step counting error is reduced, and the step counting precision is improved.
  • the embodiment of the present invention provides a pedometer device 500, as shown in FIG. 5, including a processor 510, a memory 520 connected to the processor, and a display 540 connected to the bus 530 for displaying the number of steps.
  • the memory 520 and the processor 510 are connected to each other through a bus 530, wherein:
  • a memory 520 configured to store program code executed by the processor
  • the processor 510 is configured to execute the program code stored by the memory, and perform any of the step counting methods provided in the foregoing embodiments, for example, perform the following process:
  • the wearing limb information is used to characterize relevant feature information of a limb worn by the user wearing the pedometer device; determining a limb type of wearing the pedometer device according to the wearing limb information, The limb type includes a dominant limb or a non-dominant limb; collecting step information of a limb wearing the pedometer device in a step counting period, wherein the step information is information for calculating a step number;
  • the step reference standard reference information corresponding to the limb wearing the pedometer device in the current step period is searched; wherein the correspondence between the limb type and the step reference standard reference information It is pre-learned or pre-set, and the step reference standard reference information corresponding to a dominant limb or non-dominant limb is that the plurality of users respectively use the dominant limb or the non-dominant limb to wear the pedometer device and are collected in the walking state.
  • step information is pre-processed; according to the step information and the found step reference standard reference letter , It is determined whether the user is in the walking state in the present cycle of counting steps; upon determining that the user is in the walking state in the present cycle count step, the number of steps is calculated based on the information of the pedometer.
  • embodiments of the present invention can be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the invention can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.
  • computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

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Abstract

一种计步方法及装置，用于解决现有技术中计步精度低的问题。计步装置采集佩戴肢体的信息，并根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体；计步装置采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，在所述肢体类型与计步标准参考信息的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的计步标准参考信息，根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态；在确定所述用户在本计步周期内处于走路状态时，则根据所述计步信息计算步数。采用上述方案，减小计步误差，提高了计步精度。

Description

一种计步方法及装置
本申请要求在2016年11月11日提交中国专利局、申请号为201610998245.7、发明名称为“一种计步方法及装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及通信技术领域，尤其涉及一种计步方法及装置。
背景技术
随着社会的发展，人们对健身投入了越来越多的关注，为了科学健身，通常使用一些计量工具，来计算运动量。例如，采用计步器对日常锻炼进度监控，计算人们的步行步数，步行距离等。目前市场上使用的计步器主要为加速度传感器或者陀螺仪，将计步器设置在采集可穿戴设备中，直接穿在身上或者整合到用户的衣服或配件中，通过采集佩戴肢体的振动时域或频域的周期、幅度、加速度或波形信息计算步行步数。由于计步器采集到的振动信号并非一定由用户行走造成的，还可能由于其他原因，比如：刷牙时造成的手臂运动，使用键盘打字时造成的手臂运动或者小幅度抖动腿部等。现有的计步方法中并没有针对这些非行走造成的振动信号进行判断，将这些情况都进行了计步，造成计步不准确。
综上，减小计步误差，提高计步精度是目前需要解决的问题。
发明内容
本发明的目的是提供一种计步方法及装置，以解决现有技术中计步精度低的问题。
第一方面，本发明实施例提出了一种计步方法，该方法包括:计步装置采集佩戴肢体的信息，其中，所述佩戴肢体信息用于表征用户佩戴所述计步装置的肢体的相关特征信息；所述计步装置根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体；所述计步装置采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，其中，所述计步信息为用于计算步数的信息；其中，所述计步信息的采集可以与所述佩戴肢体的信息的采集同时进行；所述计步装置在所述肢体类型与计步标准参考信息的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的计步标准参考信息；其中，所述肢体类型与计步标准参考信息的对应关系可以是预先学习或预先设置的，对应一个主导肢体或者非主导肢体的计步标准参考信息为对多个用户分别使用该主导肢体或者非主导肢体佩戴计步装置、且处于走路状态下采集到的不同计步信息进行处理得到的；具体的，所述计步标准参考信息可以为预先对多个用户分别使用该主导肢体或者非主导肢体佩戴计步装置、且处于走路状态下采集到的不同计步信息进行预先处理得到的，所述预先处理可以包括使用统计方法,或者机器学习方法,或者经验值设置方法；所述计步装置根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态；所述计步装置在确定所述用户在本计步周 期内处于走路状态，则根据所述计步信息计算步数。
本发明实施例中，所述计步装置根据采集到的佩戴肢体信息，确定出所述佩戴肢体的肢体类型，根据确定出佩戴所述计步装置的肢体对应的计步标准参考信息与采集到的佩戴所述计步装置的肢体的计步信息，确定出用户在计步周期内是否处于走路状态，由于对佩戴肢体的肢体类型进行了区分，并对不同的肢体类型设置了对应的计步标准参考信息，因此减小了计步误差，提高计步精度。
在一种可能的设计中，所述计步装置在确定所述用户在本计步周期内处于非走路状态，丢弃所述计步信息。
在一种可能的设计中，所述计步装置根据所述计步信息计算步数之后，还包括：所述计步装置将计算得到的步数累加到本计步周期的上一计步周期结束时累加的总步数中；所述计步装置丢弃所述计步信息之后，还包括：所述计步装置将本计步周期的上一计步周期结束时累加的总步数，作为本计步周期结束时累加的总步数。
本发明实施例中，所述计步装置将计算得到的步数累加到本计步周期的上一计步周期结束时累加的总步数中，或者将本计步周期的上一计步周期结束时累加的总步数，作为本计步周期结束时累加的总步数，提高了所述计步装置的计步精度。
在一种可能的设计中，所述计步标准参考信息包括至少一个设定参数分别对应的参数阈值；其中，所述设定参数可以为所述佩戴肢体处于走路状态的概率与所述佩戴肢体处于非走路状态的概率的差值、或者所述佩戴肢体的振动频率、或所述佩戴肢体的振动幅度。
所述计步装置根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态，包括：所述计步装置确定所述计步信息的至少一个设定参数的参数值；若确定的至少一个设定参数的参数值均超过对应设定参数的参数阈值，则确定所述用户在本计步周期内处于走路状态，否则确定所述用户在本计步周期内处于非走路状态。
本发明实施例中，根据不同的设定参数设置不同的参数阈值，通过设定的参数阈值判断所述用户是否处于走路状态，提高了所述计步装置的计步精度。
在一种可能的设计中，还包括：所述计步装置在所述肢体类型与滤波方式的对应关系中，其中，所述肢体类型与滤波方式的对应关系可以是预先学习或预先设置的，查找在本计步周期内佩戴所述计步装置的肢体对应的滤波方式；所述计步装置根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态之前，还包括：所述计步装置使用确定的滤波方式对所述计步信息执行滤波处理。
本发明实施例中，根据确定的肢体类型确定对应的滤波关系，对计步信息进行滤波，进一步的提高了所述计步装置的计步精度。
第二方面，本发明实施例提出了一种计步方法，该方法包括:计步装置采集佩戴肢体的信息，其中，所述佩戴肢体信息用于表征用户佩戴所述计步装置的肢体的相关特征信息；所述计步装置根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体；所述计步装置采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，其中，所述计步信息为用于计算步数的信息；所述计步装置在所述肢体类型与滤波方式的对应关系中，其中，所述肢体类型与滤波方式的对应关系是预先学习或预先设置的，查找在本计步周期内佩戴所述计步装置的肢体对应的滤波方 式；所述计步装置使用确定的滤波方式对所述计步信息执行滤波处理，确定出滤波后的计步信息；所述计步装置根据所述滤波后的计步信息，确定所述用户在本计步周期内是否处于走路状态；所述计步装置在确定所述用户在本计步周期内处于走路状态，则根据所述计步信息计算步数。
本发明实施例中，所述计步装置根据采集到的佩戴肢体信息，确定出所述佩戴肢体的肢体类型，根据所述肢体类型确定出对应的滤波方式，根据滤波后的计步信息，确定出用户在计步周期内是否处于走路状态，由于对佩戴肢体的肢体类型进行了区分，并对不同的肢体类型设置了对应的滤波方式，因此减小了计步误差，提高计步精度。
在一种可能的设计中，所述计步装置在确定所述用户在本计步周期内处于非走路状态，丢弃所述计步信息。
第三方面，本发明实施例提出了一种计步装置，该装置包括:采集模块，用于采集佩戴肢体的信息，其中，所述佩戴肢体信息用于表征用户佩戴所述计步装置的肢体的相关特征信息；处理模块，用于根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体；所述采集模块还用于，采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，其中，所述计步信息为用于计算步数的信息；查找模块，用于在所述肢体类型与计步标准参考信息的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的计步标准参考信息；其中，对应一个主导肢体或者非主导肢体的计步标准参考信息为对多个用户分别使用该主导肢体或者非主导肢体佩戴计步装置、且处于走路状态下采集到的不同计步信息进行处理得到的；确定模块，根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态；所述确定模块还用于，用于在确定所述用户在本计步周期内处于走路状态，则根据所述计步信息计算步数。
本发明实施例中，所述计步装置根据采集到的佩戴肢体信息，确定出所述佩戴肢体的肢体类型，根据确定出佩戴所述计步装置的肢体对应的计步标准参考信息与采集到的佩戴所述计步装置的肢体的计步信息，确定出用户在计步周期内是否处于走路状态，由于对佩戴肢体的肢体类型进行了区分，并对不同的肢体类型设置了对应的计步标准参考信息，因此减小了计步误差，提高计步精度。
在一种可能的设计中，所述确定模块根据所述计步信息计算步数之后，所述确定模块还用于：将计算得到的步数累加到本计步周期的上一计步周期结束时累加的总步数中；所述确定模块丢弃所述计步信息之后，还用于：所述确定模块将本计步周期的上一计步周期结束时累加的总步数，作为本计步周期结束时累加的总步数。
在一种可能的设计中，所述计步标准参考信息包括至少一个设定参数分别对应的参数阈值；所述计步装置根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态，包括：所述计步装置确定所述计步信息的至少一个设定参数的参数值；若确定的至少一个设定参数的参数值均超过对应设定参数的参数阈值，则确定所述用户在本计步周期内处于走路状态，否则确定所述用户在本计步周期内处于非走路状态。
在一种可能的设计中，所述至少一个设定参数包括：所述佩戴肢体处于走路状态的概率与所述佩戴肢体处于非走路状态的概率的差值；在一种可能的设计中，所述至少一个设定参数还包括：所述佩戴肢体的振动频率、或所述佩戴肢体的振动幅度。
在一种可能的设计中，所述查找模块还用于：在所述肢体类型与滤波方式的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的滤波方式，其中，所述肢体类型与滤波方式的对应关系是预先学习或预先设置的；所述处理模块根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态之前，还用于：使用确定的滤波方式对所述计步信息执行滤波处理。
第四方面，本发明实施例提出了一种计步装置，该装置包括:采集模块，用于采集佩戴肢体的信息，其中，所述佩戴肢体信息用于表征用户佩戴所述计步装置的肢体的相关特征信息；处理模块，用于根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体；所述采集模块还用于，采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，其中，所述计步信息为用于计算步数的信息；查找模块，用于在所述肢体类型与滤波方式的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的滤波方式，其中，所述肢体类型与滤波方式的对应关系是预先学习或预先设置的；所述处理模块还用于，使用确定的滤波方式对所述计步信息执行滤波处理，确定出滤波后的计步信息；确定模块，所述计步装置根据所述滤波后的计步信息，确定所述用户在本计步周期内是否处于走路状态；所述确定模块还用于，所述计步装置在确定所述用户在本计步周期内处于走路状态，则根据所述计步信息计算步数。
本发明实施例中，所述计步装置根据采集到的佩戴肢体信息，确定出所述佩戴肢体的肢体类型，根据所述肢体类型确定出对应的滤波方式，根据滤波后的计步信息，确定出用户在计步周期内是否处于走路状态，由于对佩戴肢体的肢体类型进行了区分，并对不同的肢体类型设置了对应的滤波方式，因此减小了计步误差，提高计步精度。
第五方面，本发明实施例提出一种计步装置，其特征在于，包括：
处理器和存储器；所述存储器用于存储软件程序，所述处理器用于读取所述存储器中存储的软件程序，实现第一方面、第一方面任意一种可能的设计、第二方面或第二方面任意一种可能的设计中的任一项。
第六方面，本发明实施例提出一种计算机可读存储介质，包括指令，当其在计算机上运行时，使得计算机执行第一方面、第一方面任意一种可能的设计、第二方面或第二方面任意一种可能的设计中的任一项。
本发明实施例中，所述计步装置根据采集到的佩戴肢体信息，确定出所述佩戴肢体的肢体类型，根据确定出佩戴所述计步装置的肢体对应的计步标准参考信息与采集到的佩戴所述计步装置的肢体的计步信息，确定出用户在计步周期内是否处于走路状态，由于对佩戴肢体的肢体类型进行了区分，并对不同的肢体类型设置了对应的计步标准参考信息，因此减小了计步误差，提高计步精度。
附图说明
图1为本发明实施例提供的一种计步方法的流程示意图；
图2为本发明实施例提供的另一种计步方法的流程示意图；
图3为本发明实施例提供的一种计步装置的结构示意图；
图4为本发明实施例提供的另一种计步装置的结构示意图；
图5为本发明实施例提供的一种计步装置的硬件结构示意图。
具体实施方式
下面结合说明书附图对本发明实施例作进一步详细描述。应当理解，此处所描述的实施例仅用于说明和解释本发明，并不用于限定本发明。
用户采用计步装置对日常锻炼进度监控，计算步行步数。由于计步装置由于佩戴的位置不同，采集到的振动信号并非一定由用户行走造成的，现有的计步方法中并没有区分计步装置的佩戴位置对采集到的振动信号进行判断，造成计步不准确。本发明实施例中，计步装置根据不同的肢体类型，对采集到的计步信息进行判断，提高了计步精度，减小了计步误差。
本发明实施例提供了一种计步方法，如图1所示，该方法包括以下过程：
S11、计步装置采集佩戴肢体的信息，其中，所述佩戴肢体信息用于表征用户佩戴所述计步装置的肢体的相关特征信息。
可选的，所述计步装置可以为可穿戴设备，比如智能手表、智能手环等，也可以是可携带的设备，比如智能手机等。
可选的，所述计步装置可以为一个系统，该系统包括可穿戴设备、与所述可穿戴设备移动智能设备，或与所述可穿戴设备直接或间接连接的网络云服务器等。
S12、所述计步装置根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体。
具体的，主导肢体为佩戴者最常使用的肢体，非主导肢体为所述佩戴者肢体中除所述主导肢体之外的其他肢体，例如，手、脚、手指或其他肢体。假设佩戴者的常用手为左手，则佩戴者的主导肢体为左手，非主导肢体为右手，或者若佩戴者的常用手为右手，则佩戴者的主导肢体为右手，非主导肢体为左手；由于主导肢体和非主导肢体的使用频率不同，日积月累之后会呈现差异性的表现，差异包括：主导肢体比非主导肢体更粗，由于主导肢体较非主导肢体粗糙，且主导肢体的皮肤表层比非主导肢体的皮肤表层更厚，导致用户的主导肢体的酸碱度明显高于非主导肢体的酸碱度；根据皮肤导电性原理，用户的主导手的皮肤导电性和非主导手的皮肤导电性具有统计性的显著差别，即主导手的皮肤导电性信号和非主导手的皮肤导电性信号的方差小于或者等于0.05；或者主导肢体比非主导肢体的体温更高、主导肢体比非主导肢体的血氧浓度更高、主导肢体比非主导肢体的光电脉搏波信号不同主导肢体和非主导肢体的信息，通过计步装置在佩戴过程中采集，并将大量重复的采集数据进行统计，得到主导肢体或非主导肢体对应的参数信息。
本发明实施例中，采集佩戴肢体信息，包括体温、血氧、化学酸碱度信息或其他信息中的至少一项，利用预先获得的主导肢体或非主导肢体分别对应的参数信息，判断出佩戴肢体的类型。举例说明：基于科学研究主导手的皮肤导电性信号和非主导手的皮肤导电性信号的方差小于或者等于0.05，可设置区分主导和非主导肢体导电性信号的阈值，采集佩戴肢体的导电性信号，若导电性信号的信号大于所述导电性信号阈值，则判断计步装置佩戴于主导肢体上。
S13、所述计步装置采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，其中，所述计步信息为用于计算步数的信息。
可选的，所述计步信息中可以包括：佩戴肢体的在各个方向的时域或频域的振动周 期、振动幅度、波形信息、各个方向振动加速度信息等。
举例说明，采用计步信息计算所述计步对象的步数包括，采集佩戴肢体各个方向，例如，X,Y,Z方向的振动幅度，生成随时间变化的波形图。通过波形图的波形数量计算步数。在计算波形图波形数量时，还可引入频率阈值或频率区间的概念，在频率区间范围内、或阈值范围内的波形被计入波形数量，否则不被计入波形数量。
S14、所述计步装置在所述肢体类型与计步标准参考信息的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的计步标准参考信息；其中，所述肢体类型与计步标准参考信息对应关系可以是预先学习或预先设置的，对应一个主导肢体或者非主导肢体的计步标准参考信息为对多个用户分别使用该主导肢体或者非主导肢体佩戴计步装置、且处于走路状态下采集到的不同计步信息进行得到的。
具体的，所述计步标准参考信息可以为预先对多个用户分别使用该主导肢体或者非主导肢体佩戴计步装置、且处于走路状态下采集到的不同计步信息进行预先处理得到的，所述预先处理可以包括使用统计方法,或者机器学习方法,或者经验值设置方法。
S15、所述计步装置根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态。
可选的，所述计步标准参考信息包括至少一个设定参数分别对应的参数阈值；所述计步装置根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态，包括：所述计步装置确定所述计步信息的至少一个设定参数的参数值；若确定的至少一个设定参数的参数值均超过对应设定参数的参数阈值，则确定所述用户在本计步周期内处于走路状态，否则确定所述用户在本计步周期内处于非走路状态。
可选的，所述至少一个设定参数包括：所述佩戴肢体处于走路状态的概率与所述佩戴肢体处于非走路状态的概率的差值；所述佩戴肢体的振动频率、或所述佩戴肢体的振动幅度。
举例说明：例一、采用所述记步信息计算用户处于走路状态的概率和用户处于非走路状态的概率，若判断出计步装置佩戴于用户的主导肢体上，用户处于走路状态的概率与计步对象处于非走路状态的概率的差值大于第一阈值，判断用户处于走路状态；用户处于走路状态的概率与计步对象处于非走路状态的概率的差值小于或等于所述第一阈值，判断用户处于走路状态；若判断出计步装置佩戴于用户的非主导肢体，用户处于走路状态的概率与计步对象处于非走路状态的概率的差值大于第二阈值，判断用户位于走路状态；用户处于走路状态的概率与计步对象处于非走路状态的概率的差值小于或等于所述第二阈值，判断用户位于走路状态，其中，所述第一阈值大于所述第二阈值。
其中，用于处于走路状态的概率是通过走路状态概率函数计算的，用于处于非走路状态的概率是通过非走路状态概率函数计算的。计步函数或非计步函数使用计步信息中包括的至少一项，采用线性函数、正向函数、或反向函数进行计算得到，本发明实施例对其不做限定。
例二、若判断出计步装置佩戴于用户的主导肢体上，采集的佩戴肢体的振动频率、或振动幅度大于第三阈值，则判断用户处于走路状态；若判断出计步装置佩戴于用户的非主导肢体上，采集的佩戴肢体的振动频率、或振动幅度大于第四阈值，则判断用户处于走路状态，其中，所述第三阈值大于第四阈值。
S16、所述计步装置在确定所述用户在本计步周期内处于走路状态，则根据所述计步信息计算步数。
可选的，所述计步装置在确定所述用户在本计步周期内处于非走路状态，丢弃所述计步信息。
本发明实施例中，所述计步装置根据采集到的佩戴肢体信息，确定出所述佩戴肢体的肢体类型，根据确定出佩戴所述计步装置的肢体对应的计步标准参考信息与采集到的佩戴所述计步装置的肢体的计步信息，确定出用户在计步周期内是否处于走路状态，由于对佩戴肢体的肢体类型进行了区分，并对不同的肢体类型设置了对应的计步标准参考信息，因此减小了计步误差，提高计步精度。
在一种可能的实现方式中，在步骤S16所述计步装置根据所述计步信息计算步数之后，还包括：所述计步装置将计算得到的步数累加到本计步周期的上一计步周期结束时累加的总步数中；
在步骤S16所述计步装置丢弃所述计步信息之后，还包括：所述计步装置将本计步周期的上一计步周期结束时累加的总步数，作为本计步周期结束时累加的总步数。
在一种可能的实现方式中，所述计步装置在所述肢体类型与滤波方式的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的滤波方式，其中，所述肢体类型与滤波方式的对应关系是预先学习或预先设置的；所述计步装置根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态之前，还包括：所述计步装置使用确定的滤波方式对所述计步信息执行滤波处理。
本发明实施例提供了另一种计步方法，如图2所示，该方法包括以下过程：
S21、计步装置采集佩戴肢体的信息，其中，所述佩戴肢体信息用于表征用户佩戴所述计步装置的肢体的相关特征信息。
S22、所述计步装置根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体。
S23、所述计步装置采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，其中，所述计步信息为用于计算步数的信息。
S24、所述计步装置在所述肢体类型与滤波方式的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的滤波方式。
可选的，所述肢体类型与滤波方式的对应关系是预先学习或预先设置的。
具体的，若判断出计步装置佩戴于用户的主导肢体上，匹配第一滤波器；若判断出计步装置佩戴于用户的非主导肢体上，匹配第二滤波器，其中，所述第一滤波器和第二滤波器使用不同的滤波参数。所述第一滤波器的滤波效果强于所述第二滤波器，能够过滤更多的干扰信号或者噪声，对于非主导肢体佩戴者的计步信号使用更弱的第二滤波器进行滤波，避免错误过滤掉更多的走路信号。本发明实施例中，所述滤波器可以是高通滤波器、低通滤波器、带通滤波器、或FFT滤波器，用于将计步信息从时域转换为频域信号。滤波器的滤波参数包括高通滤波器的滤波下限、低通滤波器的滤波上限、带通滤波器的滤波上限或滤波下限、或FFT滤波器的滤波上限、下限或者采样频率等，本发明对其不做限定。
S25、所述计步装置使用确定的滤波方式对所述计步信息执行滤波处理，确定出滤波后的计步信息。
S26、所述计步装置根据所述滤波后的计步信息，确定所述用户在本计步周期内是否处于走路状态。
具体的，若滤波后的计步信息的一个周期信号包括上升和下降区间，则将所述周期信号计为一个走路步数；若滤波后的计步信息的一个周期信号的最大值和最小值绝对值的差值大于第五阈值，则将所述周期信号计为一个走路步数；若滤波后的计步信息的一个周期信号的上升区间和下降区间的比重接近，则将所述周期信号计为一个走路步数。
S27、所述计步装置在确定所述用户在本计步周期内处于走路状态，则根据所述计步信息计算步数。
可选的，所述计步装置在确定所述用户在本计步周期内处于非走路状态，丢弃所述计步信息。
本发明实施例中，所述计步装置根据采集到的佩戴肢体信息，确定出所述佩戴肢体的肢体类型，根据所述肢体类型确定出对应的滤波方式，根据滤波后的计步信息，确定出用户在计步周期内是否处于走路状态，由于对佩戴肢体的肢体类型进行了区分，并对不同的肢体类型设置了对应的滤波方式，因此减小了计步误差，提高计步精度。
基于同一发明构思，本发明实施例提供的一种计步装置30，如图3所示，该装置包括：
采集模块31，用于采集佩戴肢体的信息，其中，所述佩戴肢体信息用于表征用户佩戴所述计步装置的肢体的相关特征信息。
处理模块32，用于根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体。
所述采集模块31还用于，采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，其中，所述计步信息为用于计算步数的信息。
查找模块33，用于在所述肢体类型与计步标准参考信息的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的计步标准参考信息；其中，对应一个主导肢体或者非主导肢体的计步标准参考信息为预先对多个用户分别使用该主导肢体或者非主导肢体佩戴计步装置、且处于走路状态下采集到的不同计步信息进行预先处理得到的。
确定模块34，根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态。
所述确定模块34还用于，用于在确定所述用户在本计步周期内处于走路状态，则根据所述计步信息计算步数。
本发明实施例中，所述计步装置根据采集到的佩戴肢体信息，确定出所述佩戴肢体的肢体类型，根据确定出佩戴所述计步装置的肢体对应的计步标准参考信息与采集到的佩戴所述计步装置的肢体的计步信息，确定出用户在计步周期内是否处于走路状态，由于对佩戴肢体的肢体类型进行了区分，并对不同的肢体类型设置了对应的计步标准参考信息，因此减小了计步误差，提高计步精度。
可选的，所述确定模块根据所述计步信息计算步数之后，所述确定模块还用于：将计算得到的步数累加到本计步周期的上一计步周期结束时累加的总步数中；所述确定模块丢弃所述计步信息之后，还用于：所述确定模块将本计步周期的上一计步周期结束时累加的总步数，作为本计步周期结束时累加的总步数。
可选的，所述计步标准参考信息包括至少一个设定参数分别对应的参数阈值；所述 计步装置根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态，包括：所述计步装置确定所述计步信息的至少一个设定参数的参数值；若确定的至少一个设定参数的参数值均超过对应设定参数的参数阈值，则确定所述用户在本计步周期内处于走路状态，否则确定所述用户在本计步周期内处于非走路状态。
可选的，所述至少一个设定参数包括：所述佩戴肢体处于走路状态的概率与所述佩戴肢体处于非走路状态的概率的差值；
可选的，所述至少一个设定参数还包括：所述佩戴肢体的振动频率、或所述佩戴肢体的振动幅度。
可选的，所述查找模块在所述肢体类型与滤波方式的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的滤波方式，其中，所述肢体类型与滤波方式的对应关系预先学习或预先设置的；所述处理模块根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态之前，还用于：使用确定的滤波方式对所述计步信息执行滤波处理。
基于同一发明构思，本发明实施例提供的一种计步装置40，如图4所示，该装置包括：
采集模块41，用于采集佩戴肢体的信息，其中，所述佩戴肢体信息用于表征用户佩戴所述计步装置的肢体的相关特征信息。
处理模块42，用于根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体。
所述采集模块41还用于，采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，其中，所述计步信息为用于计算步数的信息。
查找模块43，用于在所述肢体类型与滤波方式的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的滤波方式；其中，所述肢体类型与滤波方式的对应关系是预先学习或预先设置的。
所述处理模块42还用于，使用确定的滤波方式对所述计步信息执行滤波处理，确定出滤波后的计步信息。
确定模块44，所述计步装置根据所述滤波后的计步信息，确定所述用户在本计步周期内是否处于走路状态。
所述确定模块44还用于，所述计步装置在确定所述用户在本计步周期内处于走路状态，则根据所述计步信息计算步数。
本发明实施例中，所述计步装置根据采集到的佩戴肢体信息，确定出所述佩戴肢体的肢体类型，根据所述肢体类型确定出对应的滤波方式，根据滤波后的计步信息，确定出用户在计步周期内是否处于走路状态，由于对佩戴肢体的肢体类型进行了区分，并对不同的肢体类型设置了对应的滤波方式，因此减小了计步误差，提高计步精度。
下面结合优选的硬件结构，对本发明实施例提供的装置的结构、处理方式进行说明。
本发明实施例提出一种计步装置500，如图5所示，包括处理器510、与该处理器连接的存储器520，以及与所述总线530连接的用于显示步数的显示器540，所述存储器520和所述处理器510分别通过总线530相互连接，其中：
存储器520，用于存储所述处理器所执行的程序代码；
处理器510，用于用于执行所述存储器所存储的程序代码，执行上述实施例提供的任一计步方法,例如执行下列过程：
采集佩戴肢体的信息，其中，所述佩戴肢体信息用于表征用户佩戴所述计步装置的肢体的相关特征信息；根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体；采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，其中，所述计步信息为用于计算步数的信息；在所述肢体类型与计步标准参考信息的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的计步标准参考信息；其中，所述肢体类型与计步标准参考信息的对应关系是预先学习或预先设置的，对应一个主导肢体或者非主导肢体的计步标准参考信息为预先对多个用户分别使用该主导肢体或者非主导肢体佩戴计步装置、且处于走路状态下采集到的不同计步信息进行预先处理得到的；根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态；在确定所述用户在本计步周期内处于走路状态，则根据所述计步信息计算步数。
本领域内的技术人员应明白，本发明的实施例可提供为方法、系统、或计算机程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
尽管已描述了本发明的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例作出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本发明范围的所有变更和修改。
显然，本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的精神和范围。这样，倘若本发明的这些修改和变型属于本发明权利要求及其等同技术的范围之内，则本发明也意图包含这些改动和变型在内。

Claims (16)

  1. 一种计步方法，其特征在于，该方法包括:
    计步装置采集佩戴肢体的信息，其中，所述佩戴肢体信息用于表征用户佩戴所述计步装置的肢体的相关特征信息；
    所述计步装置根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体；
    所述计步装置采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，其中，所述计步信息为用于计算步数的信息；
    所述计步装置在所述肢体类型与计步标准参考信息的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的计步标准参考信息；其中，对应一个主导肢体或者非主导肢体的计步标准参考信息为对多个用户分别使用该主导肢体或者非主导肢体佩戴计步装置、且处于走路状态下采集到的不同计步信息进行处理得到的；
    所述计步装置根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态；
    所述计步装置在确定所述用户在本计步周期内处于走路状态，则根据所述计步信息计算步数。
  2. 如权利要求1所述的方法，其特征在于，所述计步装置根据所述计步信息计算步数之后，还包括：
    所述计步装置将计算得到的步数累加到本计步周期的上一计步周期结束时累加的总步数中；
    所述计步装置丢弃所述计步信息之后，还包括：
    所述计步装置将本计步周期的上一计步周期结束时累加的总步数，作为本计步周期结束时累加的总步数。
  3. 如权利要求1所述的方法，其特征在于，所述计步标准参考信息包括至少一个设定参数分别对应的参数阈值；
    所述计步装置根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态，包括：
    所述计步装置确定所述计步信息的至少一个设定参数的参数值；
    若确定的至少一个设定参数的参数值均超过对应设定参数的参数阈值，则确定所述用户在本计步周期内处于走路状态，否则确定所述用户在本计步周期内处于非走路状态。
  4. 如权利要求3所述的方法，其特征在于，所述至少一个设定参数包括：
    所述佩戴肢体处于走路状态的概率与所述佩戴肢体处于非走路状态的概率的差值。
  5. 如权利要求3所述的方法，其特征在于，所述至少一个设定参数还包括：
    所述佩戴肢体的振动频率、或所述佩戴肢体的振动幅度。
  6. 如权利要求1～5中任一项所述的方法，其特征在于，还包括：
    所述计步装置在所述肢体类型与滤波方式的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的滤波方式；
    所述计步装置根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本 计步周期内是否处于走路状态之前，还包括：
    所述计步装置使用确定的滤波方式对所述计步信息执行滤波处理。
  7. 一种计步方法，其特征在于，该方法包括:
    计步装置采集佩戴肢体的信息，其中，所述佩戴肢体信息用于表征用户佩戴所述计步装置的肢体的相关特征信息；
    所述计步装置根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体；
    所述计步装置采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，其中，所述计步信息为用于计算步数的信息；
    所述计步装置在所述肢体类型与滤波方式的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的滤波方式；
    所述计步装置使用确定的滤波方式对所述计步信息执行滤波处理，确定出滤波后的计步信息；
    所述计步装置根据所述滤波后的计步信息，确定所述用户在本计步周期内是否处于走路状态；
    所述计步装置在确定所述用户在本计步周期内处于走路状态，则根据所述计步信息计算步数。
  8. 一种计步装置，其特征在于，该装置包括:
    采集模块，用于采集佩戴肢体的信息，其中，所述佩戴肢体信息用于表征用户佩戴所述计步装置的肢体的相关特征信息；
    处理模块，用于根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体；
    所述采集模块还用于，采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，其中，所述计步信息为用于计算步数的信息；
    查找模块，用于在所述肢体类型与计步标准参考信息的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的计步标准参考信息；其中，对应一个主导肢体或者非主导肢体的计步标准参考信息为对多个用户分别使用该主导肢体或者非主导肢体佩戴计步装置、且处于走路状态下采集到的不同计步信息进行处理得到的；
    确定模块，根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态；
    所述确定模块还用于，用于在确定所述用户在本计步周期内处于走路状态，则根据所述计步信息计算步数。
  9. 如权利要求8所述的装置，其特征在于，所述确定模块根据所述计步信息计算步数之后，所述确定模块还用于：将计算得到的步数累加到本计步周期的上一计步周期结束时累加的总步数中；
    所述确定模块丢弃所述计步信息之后，还用于：
    所述确定模块将本计步周期的上一计步周期结束时累加的总步数，作为本计步周期结束时累加的总步数。
  10. 如权利要求8所述的装置，其特征在于，所述计步标准参考信息包括至少一个设定参数分别对应的参数阈值；
    所述计步装置根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态，包括：
    所述计步装置确定所述计步信息的至少一个设定参数的参数值；
    若确定的至少一个设定参数的参数值均超过对应设定参数的参数阈值，则确定所述用户在本计步周期内处于走路状态，否则确定所述用户在本计步周期内处于非走路状态。
  11. 如权利要求10所述的装置，其特征在于，所述至少一个设定参数包括：
    所述佩戴肢体处于走路状态的概率与所述佩戴肢体处于非走路状态的概率的差值。
  12. 如权利要求10所述的装置，其特征在于，所述至少一个设定参数还包括：
    所述佩戴肢体的振动频率、或所述佩戴肢体的振动幅度。
  13. 如权利要求8～12中任一项所述的装置，其特征在于，所述查找模块还用于：在所述肢体类型与滤波方式的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的滤波方式；
    所述处理模块根据所述计步信息和查找到的计步标准参考信息，确定所述用户在本计步周期内是否处于走路状态之前，还用于：使用确定的滤波方式对所述计步信息执行滤波处理。
  14. 一种计步装置，其特征在于，该装置包括:
    采集模块，用于采集佩戴肢体的信息，其中，所述佩戴肢体信息用于表征用户佩戴所述计步装置的肢体的相关特征信息；
    处理模块，用于根据所述佩戴肢体信息，确定佩戴所述计步装置的肢体类型，所述肢体类型包括主导肢体或者非主导肢体；
    所述采集模块还用于，采集佩戴所述计步装置的肢体在一个计步周期内的计步信息，其中，所述计步信息为用于计算步数的信息；
    查找模块，用于在所述肢体类型与滤波方式的对应关系中，查找在本计步周期内佩戴所述计步装置的肢体对应的滤波方式；
    所述处理模块还用于，使用确定的滤波方式对所述计步信息执行滤波处理，确定出滤波后的计步信息；
    确定模块，所述计步装置根据所述滤波后的计步信息，确定所述用户在本计步周期内是否处于走路状态；
    所述确定模块还用于，所述计步装置在确定所述用户在本计步周期内处于走路状态，则根据所述计步信息计算步数。
  15. 一种计步装置，其特征在于，包括：
    处理器和存储器；所述存储器用于存储软件程序，所述处理器用于读取所述存储器中存储的软件程序，实现权利要求1至7任意项所述的方法。
  16. 一种计算机可读存储介质，其特征在于，包括指令，当其在计算机上运行时，使得计算机执行如权利要求1至7任意一项所述的方法。
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