CN113679380A - Gait monitoring method, device, equipment and storage medium - Google Patents
Gait monitoring method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of motion monitoring, and discloses a gait monitoring method, a gait monitoring device, gait monitoring equipment and a storage medium, wherein the method comprises the following steps: acquiring gait perception information of a monitored user in a preset time period, carrying out phase recognition and standardization processing on the gait perception information, acquiring standard gait information under different dynamic phases, matching a corresponding target gait monitoring mode based on the standard gait information, and carrying out gait monitoring on the monitored user according to the target gait monitoring mode. The gait monitoring method comprises the steps of carrying out phase recognition and standardization processing on gait perception information of a monitored user in a preset time period to obtain standard gait information under different dynamic phases so as to improve sampling efficiency and sampling precision of the gait information, matching a corresponding target gait monitoring mode based on the standard gait information, and carrying out gait monitoring on the monitored user according to the target gait monitoring mode so as to improve monitoring efficiency and stability of gait monitoring and realize accurate monitoring on human gait quickly and stably.
Description
Technical Field
The invention relates to the technical field of motion monitoring, in particular to a gait monitoring method, a gait monitoring device, gait monitoring equipment and a storage medium.
Background
The gait is an important index reflecting the human health, the human health degree can be known according to the gait, and further, whether the human body has dyskinesia, whether the skeleton is malformed, whether the muscle is healthy and the like can be judged. In order to obtain more abundant gait information, although the prior art has developed researches on human gait from different aspects and made corresponding contributions, the prior art still has a number of defects in gait information acquisition and monitoring, such as low gait information sampling rate, low acquisition precision, complex acquired signal processing, poor gait monitoring effect and the like, so that how to rapidly and stably accurately monitor human gait becomes an urgent problem to be solved.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a gait monitoring method, a gait monitoring device, gait monitoring equipment and a storage medium, and aims to solve the technical problem of how to rapidly and stably accurately monitor human gait.
To achieve the above object, the present invention provides a gait monitoring method, which includes the steps of:
acquiring gait perception information of a monitored user within a preset time period;
carrying out phase identification on the gait perception information to obtain target gait information under different dynamic phases;
carrying out standardization processing on the target gait information to obtain standard gait information under different dynamic phases;
and matching a corresponding target gait monitoring mode based on the standard gait information, and carrying out gait monitoring on the monitored user according to the target gait monitoring mode.
Optionally, the gait perception information includes toe perception information, phalanx perception information, midfoot perception information, and heel perception information;
correspondingly, the step of obtaining the gait perception information of the monitored user within the preset time period comprises the following steps:
carrying out region division on a foot sensing region contacted by a monitored user to obtain a toe sensing region, a phalanx sensing region, a middle foot sensing region and a heel sensing region;
the toe perception information corresponding to the toe perception area, the phalange perception information corresponding to the phalange perception area, the midfoot perception information corresponding to the midfoot perception area and the heel perception information corresponding to the heel perception area within a preset time period are obtained respectively.
Optionally, the toe sensing information comprises toe pressure information, the phalange sensing information comprises phalange pressure information, the midfoot sensing information comprises midfoot pressure information, and the heel sensing information comprises heel pressure information;
correspondingly, the toe sensing area is provided with a first film type force-sensitive sensor for acquiring the toe pressure information, the phalange sensing area is provided with a second film type force-sensitive sensor for acquiring the phalange pressure information, the midfoot sensing area is provided with a third film type force-sensitive sensor for acquiring the midfoot pressure information, and the heel sensing area is provided with a fourth film type force-sensitive sensor for acquiring the heel pressure information;
correspondingly, the step of respectively obtaining the toe perception information corresponding to the toe perception area, the phalange perception information corresponding to the phalange perception area, the midfoot perception information corresponding to the midfoot perception area, and the heel perception information corresponding to the heel perception area within a preset time period includes:
acquiring the toe pressure information corresponding to the toe sensing area within a preset time period through the first thin film type force-sensitive sensor of the toe sensing area;
acquiring the phalange pressure information corresponding to the phalange sensing area within the preset time period through the second thin film type force-sensitive sensor of the phalange sensing area;
acquiring the pressure information of the middle foot corresponding to the middle foot sensing area within the preset time period through the third film type force-sensitive sensor of the middle foot sensing area;
and acquiring the heel pressure information corresponding to the heel sensing area in the preset time period through the fourth film type force-sensitive sensor of the heel sensing area.
Optionally, the step of performing phase identification on the gait awareness information to obtain target gait information in different phase states includes:
acquiring user attribute data of the monitored user, and matching a corresponding gait standard model according to the user attribute data;
determining a gait perception interval of the monitored user under different dynamic phases according to the gait standard model;
and carrying out phase identification on the gait perception information according to the gait perception interval so as to obtain target gait information under different dynamic phases.
Optionally, the step of normalizing the target gait information to obtain standard gait information in different gait phases includes:
acquiring user attribute data of the monitored user, and matching a corresponding gait standard model according to the user attribute data;
determining standard perception information under different dynamic phases according to the gait standard model;
and carrying out standardization processing on the target gait information according to the standard perception information so as to obtain the standard gait information under different dynamic phases.
Optionally, before the step of obtaining the user attribute data of the monitored user and matching the corresponding gait standard model according to the user attribute data, the method includes:
acquiring sample attribute data and sample gait data of different users;
carrying out gait calibration on the sample gait data to obtain calibration gait data of different users in different dynamic phases;
and training a preset classification model according to the sample attribute data and the calibration gait data to obtain gait standard models under different user attribute data.
Optionally, the step of matching a corresponding target gait monitoring mode based on the standard gait information and performing gait monitoring on the monitored user according to the target gait monitoring mode includes:
matching a corresponding target gait monitoring mode based on the standard gait information;
carrying out gait monitoring on the monitored user according to the target gait monitoring mode to obtain a gait monitoring result;
and generating a corresponding gait monitoring report based on the gait monitoring result, and outputting the gait monitoring report.
In addition, to achieve the above object, the present invention also provides a gait monitoring device, including:
the gait perception module is used for acquiring the gait perception information of the monitored user within a preset time period;
the phase recognition module is used for carrying out phase recognition on the gait perception information so as to obtain target gait information under different dynamic phases;
the information standardization module is used for carrying out standardization processing on the target gait information so as to obtain standard gait information under different dynamic phases;
and the gait monitoring module is used for matching a corresponding target gait monitoring mode based on the standard gait information and carrying out gait monitoring on the monitored user according to the target gait monitoring mode.
In addition, to achieve the above object, the present invention also proposes a gait monitoring device, which includes: a memory, a processor, and a gait monitoring program stored on the memory and executable on the processor, the gait monitoring program being configured to implement the steps of the gait monitoring method as described above.
Furthermore, to achieve the above object, the present invention further provides a storage medium having a gait monitoring program stored thereon, which, when executed by a processor, implements the steps of the gait monitoring method as described above.
The method comprises the steps of acquiring gait perception information of a monitored user within a preset time period, carrying out phase recognition on the gait perception information to obtain target gait information under different dynamic phases, carrying out standardization processing on the target gait information to obtain standard gait information under different dynamic phases, matching a corresponding target gait monitoring mode based on the standard gait information, and carrying out gait monitoring on the monitored user according to the target gait monitoring mode. Compared with the defects of low gait information sampling rate and poor gait monitoring effect caused by the complex connection and conversion problem among the monitoring devices in the prior art, which are caused by the configuration of a plurality of monitoring devices, the invention carries out phase recognition and standardization processing on the gait perception information of the monitored user in the preset time period to obtain the standard gait information under different phases, improves the sampling efficiency and the sampling precision of the gait information, also improves the monitoring efficiency of carrying out gait monitoring based on the obtained gait information, and then matches a corresponding target gait monitoring mode based on the standard gait information to carry out gait monitoring on the monitored user according to the target gait monitoring mode, improves the monitoring efficiency and the monitoring stability, and also realizes the rapid and stable accurate monitoring on human gait.
Drawings
Fig. 1 is a schematic structural diagram of a gait monitoring device of a hardware operating environment according to an embodiment of the invention;
FIG. 2 is a schematic flow chart of a first embodiment of a gait monitoring method according to the invention;
FIG. 3 is a schematic layout of a foot sensing area according to a first embodiment of the gait monitoring method of the invention;
FIG. 4 is a schematic flow chart of a gait monitoring method according to a second embodiment of the invention;
FIG. 5 is a schematic view of a foot sensing region layout according to a second embodiment of the gait monitoring method of the invention;
fig. 6 is a block diagram of a gait monitoring device according to a first embodiment of the invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a gait monitoring device in a hardware operating environment according to an embodiment of the invention.
As shown in fig. 1, the gait monitoring device may comprise: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the gait monitoring device and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
As shown in fig. 1, the memory 1005, which is a storage medium, may include therein an operating system, a data storage module, a network communication module, a user interface module, and a gait monitoring program.
In the gait monitoring device shown in fig. 1, the network interface 1004 is primarily used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 of the gait monitoring device of the invention can be arranged in the gait monitoring device, and the gait monitoring device calls the gait monitoring program stored in the memory 1005 through the processor 1001 and executes the gait monitoring method provided by the embodiment of the invention.
An embodiment of the present invention provides a gait monitoring method, and referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of the gait monitoring method of the present invention.
In this embodiment, the gait monitoring method includes the following steps:
step S10: acquiring gait perception information of a monitored user within a preset time period;
it is easy to understand that the executing main body of the embodiment is the above gait monitoring device, wherein the gait perception information can be understood as pressure change information, heat radiation change information and the like borne by the area contacted by the sole of the monitored user, the gait perception information of the monitored user can be reflected through the pressure change information, the heat radiation change information and the like, the gait perception information includes but is not limited to toe perception information, phalanx perception information, midfoot perception information and heel perception information, the toe perception information includes toe pressure information, toe heat radiation information and the like, wherein the toe pressure information can be understood as pressure information borne by a toe perception area in the foot perception area contacted by the monitored user; phalanx perception information includes phalanx pressure information, phalanx heat radiation information etc, and wherein, phalanx pressure information can be understood as the pressure information that the phalanx perception area among the foot perception area that is contacted by the monitored user bore, well foot perception information includes well foot pressure information, well foot heat radiation information etc, and wherein, well foot pressure information can be understood as the pressure information that well foot perception area among the foot perception area that is contacted by the monitored user bore, heel perception information includes heel pressure information, heel heat radiation information etc. wherein, heel pressure information can be understood as the pressure information that the heel perception area in the foot perception area that is contacted by the monitored user bore.
In concrete realization, can carry out regional division to the foot perception region that monitored user contacted, obtain toe perception region, phalange perception region, well foot perception region and heel perception region, obtain respectively again in the preset time quantum toe perception region corresponds toe perception information toe perception region corresponds phalange perception information well foot perception region corresponds well foot perception information and the heel perception region corresponds the heel perception information. The preset time period can be set according to actual requirements, such as 1 minute, 5 minutes, 15 minutes, and the like, which is not limited in this embodiment.
Referring to fig. 3, fig. 3 is a schematic layout view of a foot sensing area according to a first embodiment of the gait monitoring method of the invention.
In fig. 3, the foot sensing area is divided into a toe sensing area, a phalange sensing area, a middle foot sensing area and a heel sensing area, wherein the toe sensing area is provided with a toe monitoring unit 101, the phalange sensing area is provided with a phalange monitoring unit 102, the middle foot sensing area is provided with a middle foot monitoring unit 103, the heel sensing area is provided with a heel monitoring unit 104, wherein the toe monitoring unit 101, the phalange monitoring unit 102, the middle foot monitoring unit 103 and the heel monitoring unit 104 all include a film type Force Sensitive Resistor (FSR), that is, the toe monitoring unit 101, the phalange monitoring unit 102, the middle foot monitoring unit 103 and the heel monitoring unit 104 can obtain corresponding pressure signals through the included film type Force Sensitive resistors, wherein the number of the film type Force Sensitive resistors can be set according to the areas corresponding to different areas of the sole, in this embodiment, the collection difficulty of the toe region of the sole is greater than that of other regions of the sole, and the collection efficiency is lower, so as to improve the collection stability and the collection efficiency of the pressure signal corresponding to the toe region of the monitored user, the toe monitoring unit 101 may be attached to the thin film signal amplifier (it may be understood that the toe monitoring unit 101 includes the thin film signal amplifier), so as to reduce the signal collection difficulty of the toe region of the monitored user, and accordingly, improve the collection stability and the collection efficiency of the pressure signal corresponding to the toe region.
In a specific implementation, in order to improve the acquisition precision of gait perception information, the foot perception area contacted by a monitored user can be acquired in a partitioned manner, wherein the toe monitoring unit 101 can be used for acquiring a toe pressure signal of the toe perception area of the monitored user; the phalange monitoring unit 102, configured to obtain a phalange pressure signal of a phalange sensing area of the monitored user; the midfoot monitoring unit 103 is configured to obtain a midfoot pressure signal of a midfoot sensing area of the monitored user; the heel monitoring unit 104 may be configured to obtain a heel pressure signal of a heel sensing area of the monitored user.
Step S20: carrying out phase identification on the gait perception information to obtain target gait information under different dynamic phases;
it should be noted that, before performing phase identification according to the obtained gait perception information of the monitored user, user attribute data of the monitored user may be obtained, and a corresponding gait standard model may be matched according to the user attribute data, where the user attribute data may be understood as data used to represent attribute characteristics of the user, such as age, gender, height, weight, and the like.
In a specific implementation, in order to obtain the gait standard models under different user attribute data, sample attribute data and sample gait data of different users may be obtained first, and then the sample attribute data is subjected to cluster analysis to obtain sample gait data under different user categories, and a specific classification standard may be set according to actual requirements, for example, the belonging age class (i.e., an age interval, for example, 3 years old is used as a delivery value of the age interval, in a specific implementation, different intervals may also be divided for the adult class and the immature class, for example, an interval is divided for each 1 year old of the immature class and an interval is divided for each 5 years old of the immature class), a gender, a height class of the belonging body, a weight class of the belonging body, whether the adult class is in a pregnancy stage, and the like, which is not limited in this embodiment. Further, gait calibration is performed on the sample gait data of the different user categories to obtain calibration gait data of the different user categories in different dynamic phases, where the calibration gait data includes, but is not limited to, gait sensing intervals and standard sensing information, where the gait sensing intervals can be understood as pressure intervals corresponding to the different user categories in different dynamic phases, for example, a pressure interval corresponding to the X-type user in the initial stage of touchdown is [ a, b ], a pressure interval corresponding to the load-bearing stage is [ c, d ], a pressure interval corresponding to the stable stage of touchdown is [ e, f ], a pressure interval corresponding to the late stage of touchdown is [ g, h ], a pressure interval corresponding to the early stage of suspension is [ i, j ], and a pressure interval corresponding to the suspended stage is [ m, n ]. The standard perception information can be understood as pressure standards corresponding to different user types in different phase positions, for example, the pressure standard corresponding to the X-type user in the initial touchdown period is A, the pressure standard corresponding to the bearing period is B, the pressure standard corresponding to the touchdown stabilization period is C, the pressure standard corresponding to the final touchdown period is D, the pressure standard corresponding to the suspension period is E, and the pressure standard corresponding to the suspension period is F. And then, training a preset classification model according to the sample attribute data and the calibration gait data to obtain gait standard models under different user categories. The preset classification model can be understood as a classifier, and in specific implementation, the sample attribute data can be used as a model input feature, and the calibration gait data can be used as a model output feature to train the classifier so as to obtain gait standard models in different user categories. The specific training mode can be set according to actual requirements, so as to improve the model precision of the gait standard model, which is not limited in the embodiment.
Further, after acquiring gait standard models corresponding to different user categories, determining the user category of the monitored user according to user attribute data of the monitored user, searching the gait standard model corresponding to the user category, then determining a gait perception interval of the monitored user in an asynchronous phase according to the gait standard model, and performing phase recognition on gait perception information according to the gait perception interval to acquire target gait information in the asynchronous phase, wherein the target gait information can be understood as the gait perception information classified according to the gait phase. If the monitored user belongs to the X-class user, the pressure interval corresponding to the X-class user in the initial touchdown stage is [ a, b ], the pressure interval corresponding to the bearing period is [ c, d ], the pressure interval corresponding to the stable touchdown stage is [ e, f ], the pressure interval corresponding to the final touchdown stage is [ g, h ], the pressure interval corresponding to the suspension early stage is [ i, j ], the pressure interval corresponding to the suspension stage is [ m, n ], the gait perception information is subjected to phase recognition by the pressure interval, and target gait information under different phase positions is obtained.
Step S30: carrying out standardization processing on the target gait information to obtain standard gait information under different dynamic phases;
it is easy to understand that before the target gait information is standardized, user attribute data of the monitored user may be acquired, the user category to which the monitored user belongs may be determined according to the user attribute data of the monitored user, a gait standard model corresponding to the user category may be searched, then standard perception information in different dynamic phases may be determined according to the gait standard model, and the target gait information may be standardized according to the standard perception information to obtain standard gait information in different dynamic phases, where the standard gait information may be understood as information representing a deviation from the standard perception information. For example, the monitored user belongs to a class X user, the pressure standard corresponding to the class X user in the initial touchdown stage is a, the pressure standard corresponding to the load-bearing stage is B, the pressure standard corresponding to the stable touchdown stage is C, the pressure standard corresponding to the final touchdown stage is D, the pressure standard corresponding to the early suspension stage is E, the pressure standard corresponding to the suspension stage is F, and the standard gait information may be: at the initial stage of touchdown: a- α, load bearing period: b + β, touchdown stabilization period: c- γ, end of touchdown: d + δ, flying prophase: e + epsilon, dangling phase: f-zeta.
Step S40: matching a corresponding target gait monitoring mode based on the standard gait information, and carrying out gait monitoring on the monitored user according to the target gait monitoring mode
It should be noted that, after obtaining the standard gait information, the corresponding target gait monitoring mode may be matched based on the standard gait information, in a specific implementation, the corresponding target gait monitoring mode may be matched in a preset gait monitoring mode library based on the sum of absolute values of various deviations between the standard gait information and the standard sensing information, the preset gait monitoring mode library stores various gait monitoring modes, if the sum of the absolute values of the deviations is smaller than a first preset threshold, a first-level (weak) monitoring mode is selected, if the deviation is greater than or equal to the first preset threshold and smaller than a second preset threshold, a second-level (normal) monitoring mode is selected, and if the deviation is greater than or equal to a third preset threshold, a third-level (strong) monitoring mode is selected, wherein the first preset threshold, the second preset threshold and the third preset threshold may all be set according to actual requirements, this implementation is not so limited. And then, carrying out gait monitoring on the monitored user according to the matched target gait monitoring mode to obtain a gait monitoring result, generating a corresponding gait monitoring report based on the gait monitoring result, and outputting the gait monitoring report.
In the embodiment, gait awareness information of a monitored user in a preset time period is acquired, phase recognition is performed on the gait awareness information to acquire target gait information in different dynamic phases, the target gait information is subjected to standardization processing to acquire standard gait information in different dynamic phases, a corresponding target gait monitoring mode is matched based on the standard gait information, and gait monitoring is performed on the monitored user according to the target gait monitoring mode. Compared with the defects of low sampling rate of gait information and poor gait monitoring effect caused by complex connection and conversion among monitoring devices in the prior art, which are caused by the fact that a plurality of monitoring devices are equipped, in the embodiment, the gait perception information of the monitored user in the preset time period is subjected to phase recognition and standardized processing to obtain the standard gait information under different dynamic phases, so that the sampling efficiency and the sampling precision of the gait information are improved, the monitoring efficiency of gait monitoring based on the obtained gait information is also improved, and then the corresponding target gait monitoring mode is matched based on the standard gait information to monitor the gait of the monitored user according to the target gait monitoring mode, so that the monitoring efficiency and the monitoring stability are improved, and the purpose of accurately monitoring the human gait is also realized quickly and stably.
Referring to fig. 4, fig. 4 is a flowchart illustrating a gait monitoring method according to a second embodiment of the invention.
Based on the first embodiment described above, in the present embodiment, the step S10 includes:
step S101: carrying out region division on a foot sensing region contacted by a monitored user to obtain a toe sensing region, a phalanx sensing region, a middle foot sensing region and a heel sensing region;
step S102: and respectively acquiring toe sensing information corresponding to the toe sensing area, phalange sensing information corresponding to the phalange sensing area, midfoot sensing information corresponding to the midfoot sensing area and heel sensing information corresponding to the heel sensing area in a preset time period.
It is easily understood that can carry out regional division to the foot perception region that monitored user contacted, obtain toe perception region, phalanx perception region, middle foot perception region and heel perception region, acquire respectively in the preset time quantum again toe perception region corresponds toe perception information toe perception region corresponds phalanx perception information middle foot perception region corresponds middle foot perception information and heel perception region corresponds heel perception information. The preset time period can be set according to actual requirements, such as 1 minute, 5 minutes, 15 minutes, and the like, which is not limited in this embodiment.
It should be noted that the toe sensing information includes toe pressure information, the phalange sensing information includes phalange pressure information, the midfoot sensing information includes midfoot pressure information, and the heel sensing information includes heel pressure information; correspondingly, the toe perception area is provided with a first film type force-sensitive sensor (namely a force-sensitive resistor) for acquiring toe pressure information, the phalange perception area is provided with a second film type force-sensitive sensor for acquiring the phalange pressure information, the middle foot perception area is provided with a third film type force-sensitive sensor for acquiring the middle foot pressure information, and the heel perception area is provided with a fourth film type force-sensitive sensor for acquiring the heel pressure information. Correspondingly, the toe pressure information corresponding to the toe sensing area in a preset time period can be acquired through the first thin film type force-sensitive sensor of the toe sensing area; acquiring the phalange pressure information corresponding to the phalange sensing area within the preset time period through the second thin film type force-sensitive sensor of the phalange sensing area; acquiring the pressure information of the middle foot corresponding to the middle foot sensing area within the preset time period through the third film type force-sensitive sensor of the middle foot sensing area; and acquiring the heel pressure information corresponding to the heel sensing area in the preset time period through the fourth film type force-sensitive sensor of the heel sensing area.
Referring to fig. 5, fig. 5 is a schematic view of a foot sensing area layout according to a second embodiment of the gait monitoring method of the invention.
In fig. 5, in order to further improve the acquisition accuracy of the toe pressure signals in the gait monitoring, the toe pressure signals may include a first toe pressure signal, a second toe pressure signal, a third toe pressure signal, a fourth toe pressure signal and a fifth toe pressure signal;
accordingly, the toe sensing area is provided with a foot big toe pressure sensor 1011, a foot two toe pressure sensor 1012, a foot three toe pressure sensor 1013, a foot four toe pressure sensor 1014 and a foot little toe pressure sensor 1015, in the specific implementation, since the toe area of the sole is more difficult and less efficient to collect than other areas of the sole, in order to improve the collection stability and the collection efficiency of the pressure signal corresponding to the toe area of the monitored user, the foot big toe pressure sensor 1011, the foot two toe pressure sensor 1012, the foot three toe pressure sensor 1013, the foot four toe pressure sensor 1014 and the foot little toe pressure sensor 1015 are all adhered to the thin film type signal amplifier (it can be understood that the foot big toe pressure sensor 1011, the foot two toe pressure sensor 1012, the foot three toe pressure sensor 1013, the foot four toe pressure sensor 1014 and the foot little toe pressure sensor 1015 all include thin film type signal amplifiers), the signal acquisition difficulty of the toe area of the monitored user is reduced, and accordingly, the acquisition stability and the acquisition efficiency of the pressure signal corresponding to the toe area are improved.
Wherein the foot big toe pressure sensor 1011 is configured to obtain the first foot toe pressure signal at the foot big toe of the monitored user; the second toe pressure sensor 1012, configured to acquire the second toe pressure signal at the second toe of the monitored user; said toe pressure sensor 1013 to acquire said third toe pressure signal at the toe of said monitored user; said four-toe pressure sensor 1014 for acquiring said fourth toe pressure signal at the four toes of said monitored user's foot; the foot little toe pressure sensor 1015 is configured to acquire the fifth toe pressure signal at the foot little toe of the monitored user.
In this embodiment, the pressure signals corresponding to the toe sensing area of the monitored user are acquired in five-toe subarea, so as to obtain a first toe pressure signal at the big toe position, a second toe pressure signal at the second toe position, a third toe pressure signal at the third toe position, a fourth toe pressure signal at the fourth toe position, and a fifth toe pressure signal at the little toe position of the monitored user, so as to further improve the accuracy of acquiring the toe pressure signals in gait monitoring.
In another implementation, in order to save economic expenditure while ensuring acquisition accuracy of toe pressure signals in gait monitoring, the toe pressure signals may include a first-zone toe pressure signal, a second-zone toe pressure signal and a third-zone toe pressure signal;
correspondingly, the toe sensing area is provided with a first area pressure sensor, a second area pressure sensor and a third area pressure sensor, in the specific implementation, as the toe area of the sole is more difficult to collect and has lower collection efficiency compared with other areas of the sole, in order to improve the collection stability and the collection efficiency of the pressure signals corresponding to the toe area of the monitored user, the first area pressure sensor, the second area pressure sensor and the third area pressure sensor can be adhered to a film type signal amplifier (it can be understood that the first area pressure sensor, the second area pressure sensor and the third area pressure sensor all comprise film type signal amplifiers) so as to reduce the signal collection difficulty of the toe area of the monitored user, and correspondingly, the collection stability and the collection efficiency of the pressure signals corresponding to the toe area are also improved;
the first-zone pressure sensor is used for acquiring the first-zone toe pressure signal at the position of the big toe of the monitored user; the second-area pressure sensor is used for acquiring the second-area toe pressure signals at the positions of the two toes and the three toes of the foot of the monitored user; the three-region pressure sensor is used for acquiring the three-region toe pressure signals at the four toes and the little toe of the foot of the monitored user.
In another implementation manner of this embodiment, a three-region acquisition is performed on a pressure signal corresponding to a toe sensing region of a monitored user based on sense of mass, so as to obtain a first-region toe pressure signal at a toe of a foot of the monitored user, a second-region toe pressure signal at a second toe and a third toe pressure signal at a third toe of the foot, and a three-region toe pressure signal at a fourth toe and a little toe of the foot, so that while the acquisition accuracy of the toe pressure signal in gait monitoring is ensured, the number of sensors in the toe region is reduced to reduce economic expenditure, and the development cost is reduced.
In fig. 5, in order to further improve the acquisition accuracy of the phalange pressure signals in gait monitoring, the phalange pressure signals may include a first phalange pressure signal, a second phalange pressure signal, a third phalange pressure signal, a fourth phalange pressure signal, and a fifth phalange pressure signal;
accordingly, the phalange sensing area is provided with a first phalange pressure sensor 1021, a second phalange pressure sensor 1022, a third phalange pressure sensor 1023, a fourth phalange pressure sensor 1024, and a fifth phalange pressure sensor 1025;
wherein the first phalange pressure sensor 1021 is configured to acquire the first phalange pressure signal at a first phalange of the monitored user; the second phalange pressure sensor 1022 for acquiring the second phalange pressure signal at a second phalange of the monitored user; the third toe bone pressure sensor 1023 for acquiring the third toe bone pressure signal at the third toe bone of the monitored user; the fourth phalange pressure sensor 1024 for acquiring the fourth phalange pressure signal at a fourth phalange of the monitored user; the fifth phalange pressure sensor 1025 for acquiring the fifth phalange pressure signal at a fifth phalange of the monitored user.
In this embodiment, the pressure signal corresponding to the phalange sensing area of the monitored user is collected in five-toe subareas, so as to obtain a first phalange pressure signal at the first phalange of the monitored user, a second phalange pressure signal at the second phalange, a third phalange pressure signal at the third phalange, a fourth phalange pressure signal at the fourth phalange, and a fifth phalange pressure signal at the fifth phalange, thereby further improving the collection accuracy of the phalange pressure signal in gait monitoring.
In another implementation, in order to save economic expenditure while guaranteeing acquisition accuracy of a phalange pressure signal in gait monitoring, the phalange pressure signal may include a first phalange pressure signal, a second phalange pressure signal, a three phalange pressure signal, and a four phalange pressure signal;
correspondingly, the phalange sensing area is provided with a first-area phalange pressure sensor, a second-area phalange pressure sensor, a third-area phalange pressure sensor and a fourth-area phalange pressure sensor;
wherein the first phalange pressure sensor is configured to acquire the first phalange pressure signal at the first phalange of the monitored user; the second phalange pressure sensor for acquiring the second phalange pressure signal at a second phalange of the monitored user; the three-region phalange pressure sensor for acquiring the three-region phalange pressure signals at the third and fourth phalanges of the monitored user; the four-region phalange pressure sensor is used for acquiring the four-region phalange pressure signal at the fifth phalange of the monitored user.
In another implementation manner of this embodiment, a pressure signal corresponding to a phalange sensing area of a monitored user is subjected to four-region acquisition based on a pressure correlation degree, so as to obtain a phalange pressure signal of a first region at a first phalange of the monitored user, a phalange pressure signal of a second region at a second phalange, a phalange pressure signal of a third region at a third phalange and a fourth phalange, and a phalange pressure signal of a fifth region at a fifth phalange, so that while acquisition accuracy of the phalange pressure signal in gait monitoring is guaranteed, the number of sensors in the phalange area is reduced to reduce economic expenditure, and development cost is reduced.
In fig. 5, to further improve the accuracy of the acquisition of the midfoot pressure signal in gait monitoring, the midfoot pressure signal may include a medial midfoot pressure signal and a lateral midfoot pressure signal;
correspondingly, the midfoot sensing area is provided with a midfoot medial pressure sensor 1031 and a midfoot lateral pressure sensor 1032;
wherein the medial foot pressure sensor 1031 is configured to obtain the medial foot pressure signal of the medial foot region of the monitored user; the lateral midfoot pressure sensor 1032 is configured to obtain the lateral midfoot pressure signal for the lateral midfoot region of the monitored user.
In this embodiment, the medial-lateral subarea acquisition is performed on the pressure signal corresponding to the medial-foot sensing area of the monitored user, so as to obtain the medial-foot pressure signal of the medial-foot area and the lateral-foot pressure signal of the lateral-foot area of the monitored user, thereby further improving the acquisition accuracy of the medial-foot pressure signal in gait monitoring.
Accordingly, the step S20 includes:
step S201: and carrying out phase identification on the toe perception information, the phalange perception information, the midfoot perception information and the heel perception information to obtain target gait information under different dynamic phases.
It is easy to understand that after obtaining the toe sensing information, the phalange sensing information, the midfoot sensing information and the heel sensing information, phase recognition can be performed based on a change rule of the toe sensing information in a preset time period, a change rule of the phalange sensing information in the preset time period, a change rule of the midfoot sensing information in the preset time period and a change rule of the heel sensing information in the preset time period, or the toe sensing information, the phalange sensing information, the midfoot sensing information and the heel sensing information corresponding to each moment can be compared with the toe sensing information, the phalange sensing information, the midfoot sensing information and the heel sensing information corresponding to a previous moment to obtain a sensing comparison result, phase recognition can be performed based on the sensing comparison result, and in a specific implementation, phase recognition can be performed in combination with the gait standard models corresponding to different user categories in the first embodiment of the gait monitoring device of the present invention, for example, after the user category to which the monitored user belongs is determined according to the user attribute data, the gait standard model corresponding to the user category is searched, then the gait sensing interval of the monitored user in the different dynamic phases is determined according to the gait standard model, and phase recognition is performed through the gait sensing interval and the sensing comparison result so as to obtain target gait information in the different dynamic phases, wherein the target gait information can be understood as the sensing comparison result of the gait sensing information classified according to the gait phases.
In this embodiment, carry out regional division to the foot perception region that monitored user contacted, obtain toe perception region, phalanx perception region, middle foot perception region and heel perception region, acquire respectively again in the preset time quantum toe perception information that the toe perception region corresponds, phalanx perception information that the phalanx perception region corresponds, middle foot perception information that the middle foot perception region corresponds and heel perception information that the heel perception region corresponds. Compared with the prior art that only the sole of the monitored user is roughly divided, the accuracy of the collected toe sensing information corresponding to the toe sensing area, the phalange sensing information corresponding to the phalange sensing area, the middle-foot sensing information corresponding to the middle-foot sensing area and the heel sensing information corresponding to the heel sensing area is improved by accurately collecting the sole of the monitored user in a partitioning manner, the sampling efficiency is also improved, in addition, compared with the prior art that a plurality of sensors are equipped to collect gait information, the embodiment obtains the toe pressure information corresponding to the toe sensing area in a preset time period through the first film type force sensitive sensor of the toe sensing area, and obtains the phalange pressure information corresponding to the phalange sensing area in the preset time period through the second film type force sensitive sensor of the phalange sensing area, the third film type force-sensitive sensor of the middle foot sensing area acquires the middle foot pressure information corresponding to the middle foot sensing area in the preset time period, and the fourth film type force-sensitive sensor of the heel sensing area acquires the heel pressure information corresponding to the heel sensing area in the preset time period, so that the information acquisition process is simplified, the information acquisition difficulty is reduced, the information acquisition stability and speed are improved, and therefore, the follow-up gait monitoring process based on the acquired pressure information in different areas is facilitated, and the gait of a human body is rapidly and stably accurately monitored.
Furthermore, an embodiment of the present invention further provides a storage medium, in which a gait monitoring program is stored, and the gait monitoring program, when executed by a processor, implements the steps of the gait monitoring method as described above.
Referring to fig. 6, fig. 6 is a block diagram of a gait monitoring device according to a first embodiment of the invention.
As shown in fig. 6, a gait monitoring device according to an embodiment of the invention includes:
the gait perception module 10 is used for acquiring gait perception information of a monitored user within a preset time period;
the phase recognition module 20 is configured to perform phase recognition on the gait perception information to obtain target gait information in different dynamic phases;
the information standardization module 30 is used for standardizing the target gait information to obtain standard gait information under different dynamic phases;
and the gait monitoring module 40 is used for matching a corresponding target gait monitoring mode based on the standard gait information and carrying out gait monitoring on the monitored user according to the target gait monitoring mode.
In the embodiment, gait awareness information of a monitored user in a preset time period is acquired, phase recognition is performed on the gait awareness information to acquire target gait information in different dynamic phases, the target gait information is subjected to standardization processing to acquire standard gait information in different dynamic phases, a corresponding target gait monitoring mode is matched based on the standard gait information, and gait monitoring is performed on the monitored user according to the target gait monitoring mode. Compared with the defects of low sampling rate of gait information and poor gait monitoring effect caused by complex connection and conversion among monitoring devices in the prior art, which are caused by the fact that a plurality of monitoring devices are equipped, in the embodiment, the gait perception information of the monitored user in the preset time period is subjected to phase recognition and standardized processing to obtain the standard gait information under different dynamic phases, so that the sampling efficiency and the sampling precision of the gait information are improved, the monitoring efficiency of gait monitoring based on the obtained gait information is also improved, and then the corresponding target gait monitoring mode is matched based on the standard gait information to monitor the gait of the monitored user according to the target gait monitoring mode, so that the monitoring efficiency and the monitoring stability are improved, and the purpose of accurately monitoring the human gait is also realized quickly and stably.
Based on the above-mentioned first embodiment of the gait monitoring device of the invention, a second embodiment of the gait monitoring device of the invention is proposed.
In this embodiment, the gait perception information includes toe perception information, phalanx perception information, midfoot perception information, and heel perception information;
correspondingly, the gait perception module 10 is further configured to perform area division on a foot perception area contacted by the monitored user to obtain a toe perception area, a phalanx perception area, a midfoot perception area and a heel perception area;
the gait perception module 10 is further configured to obtain the toe perception information corresponding to the toe perception area, the phalange perception information corresponding to the phalange perception area, the midfoot perception information corresponding to the midfoot perception area, and the heel perception information corresponding to the heel perception area within a preset time period, respectively.
Optionally, the toe sensing information comprises toe pressure information, the phalange sensing information comprises phalange pressure information, the midfoot sensing information comprises midfoot pressure information, and the heel sensing information comprises heel pressure information;
correspondingly, the toe sensing area is provided with a first film type force-sensitive sensor for acquiring the toe pressure information, the phalange sensing area is provided with a second film type force-sensitive sensor for acquiring the phalange pressure information, the midfoot sensing area is provided with a third film type force-sensitive sensor for acquiring the midfoot pressure information, and the heel sensing area is provided with a fourth film type force-sensitive sensor for acquiring the heel pressure information;
correspondingly, the gait perception module 10 is further configured to obtain the toe pressure information corresponding to the toe perception area within a preset time period through the first thin film type force sensor of the toe perception area;
the gait perception module 10 is further configured to acquire the phalange pressure information corresponding to the phalange perception area within the preset time period through the second thin film type force-sensitive sensor of the phalange perception area;
the gait perception module 10 is further configured to obtain, by the third thin film type force-sensitive sensor in the midfoot perception region, the midfoot pressure information corresponding to the midfoot perception region within the preset time period;
the gait perception module 10 is further configured to obtain the heel pressure information corresponding to the heel perception area within the preset time period through the fourth thin film type force sensor of the heel perception area.
Optionally, the phase identification module 20 is further configured to acquire user attribute data of the monitored user, and match a corresponding gait standard model according to the user attribute data;
the phase identification module 20 is further configured to determine, according to the gait standard model, a gait sensing interval of the monitored user in an asynchronous phase;
the phase recognition module 20 is further configured to perform phase recognition on the gait perception information according to the gait perception interval to obtain target gait information in different dynamic phases.
Optionally, the information standardization module 30 is further configured to obtain user attribute data of the monitored user, and match a corresponding gait standard model according to the user attribute data;
the information standardization module 30 is further configured to determine standard perception information in different gait phases according to the gait standard model;
the information standardization module 30 is further configured to standardize the target gait information according to the standard perception information to obtain standard gait information in different dynamic phases.
Optionally, the gait monitoring device further comprises:
the model building module is used for acquiring sample attribute data and sample gait data of different users;
the model building module is also used for carrying out gait calibration on the sample gait data so as to obtain calibration gait data of different users in different dynamic phases;
the model building module is further used for training a preset classification model according to the sample attribute data and the calibration gait data to obtain gait standard models under different user attribute data.
Optionally, the gait monitoring module 40 is further configured to match a corresponding target gait monitoring mode based on the standard gait information;
the gait monitoring module 40 is further configured to perform gait monitoring on the monitored user according to the target gait monitoring mode to obtain a gait monitoring result;
the gait monitoring module 40 is further configured to generate a corresponding gait monitoring report based on the gait monitoring result, and output the gait monitoring report.
Other embodiments or specific implementations of the gait monitoring device of the invention can refer to the above method embodiments, and are not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., a rom/ram, a magnetic disk, an optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A gait monitoring method, characterized in that it comprises the steps of:
acquiring gait perception information of a monitored user within a preset time period;
carrying out phase identification on the gait perception information to obtain target gait information under different dynamic phases;
carrying out standardization processing on the target gait information to obtain standard gait information under different dynamic phases;
and matching a corresponding target gait monitoring mode based on the standard gait information, and carrying out gait monitoring on the monitored user according to the target gait monitoring mode.
2. A gait monitoring method according to claim 1, characterized in that the gait awareness information includes toe awareness information, phalange awareness information, midfoot awareness information and heel awareness information;
correspondingly, the step of obtaining the gait perception information of the monitored user within the preset time period comprises the following steps:
carrying out region division on a foot sensing region contacted by a monitored user to obtain a toe sensing region, a phalanx sensing region, a middle foot sensing region and a heel sensing region;
the toe perception information corresponding to the toe perception area, the phalange perception information corresponding to the phalange perception area, the midfoot perception information corresponding to the midfoot perception area and the heel perception information corresponding to the heel perception area within a preset time period are obtained respectively.
3. A gait monitoring method according to claim 2, characterized in that the toe sensing information includes toe pressure information, the phalanx sensing information includes phalanx pressure information, the midfoot sensing information includes midfoot pressure information, the heel sensing information includes heel pressure information;
correspondingly, the toe sensing area is provided with a first film type force-sensitive sensor for acquiring the toe pressure information, the phalange sensing area is provided with a second film type force-sensitive sensor for acquiring the phalange pressure information, the midfoot sensing area is provided with a third film type force-sensitive sensor for acquiring the midfoot pressure information, and the heel sensing area is provided with a fourth film type force-sensitive sensor for acquiring the heel pressure information;
correspondingly, the step of respectively obtaining the toe perception information corresponding to the toe perception area, the phalange perception information corresponding to the phalange perception area, the midfoot perception information corresponding to the midfoot perception area, and the heel perception information corresponding to the heel perception area within a preset time period includes:
acquiring the toe pressure information corresponding to the toe sensing area within a preset time period through the first thin film type force-sensitive sensor of the toe sensing area;
acquiring the phalange pressure information corresponding to the phalange sensing area within the preset time period through the second thin film type force-sensitive sensor of the phalange sensing area;
acquiring the pressure information of the middle foot corresponding to the middle foot sensing area within the preset time period through the third film type force-sensitive sensor of the middle foot sensing area;
and acquiring the heel pressure information corresponding to the heel sensing area in the preset time period through the fourth film type force-sensitive sensor of the heel sensing area.
4. A gait monitoring method according to claim 1, wherein the step of phase identifying the gait awareness information to obtain target gait information in out-of-phase phases comprises:
acquiring user attribute data of the monitored user, and matching a corresponding gait standard model according to the user attribute data;
determining a gait perception interval of the monitored user under different dynamic phases according to the gait standard model;
and carrying out phase identification on the gait perception information according to the gait perception interval so as to obtain target gait information under different dynamic phases.
5. A gait monitoring method according to claim 1, wherein the step of normalising the target gait information to obtain standard gait information in out-of-phase phases comprises:
acquiring user attribute data of the monitored user, and matching a corresponding gait standard model according to the user attribute data;
determining standard perception information under different dynamic phases according to the gait standard model;
and carrying out standardization processing on the target gait information according to the standard perception information so as to obtain the standard gait information under different dynamic phases.
6. A gait monitoring method according to any of claims 4 to 5, characterized in that the step of obtaining user attribute data of the monitored user and matching a corresponding gait standard model in dependence on said user attribute data is preceded by the steps of:
acquiring sample attribute data and sample gait data of different users;
carrying out gait calibration on the sample gait data to obtain calibration gait data of different users in different dynamic phases;
and training a preset classification model according to the sample attribute data and the calibration gait data to obtain gait standard models under different user attribute data.
7. A gait monitoring method according to claim 1, characterized in that the step of matching a corresponding target gait monitoring pattern based on the standard gait information and performing gait monitoring of the monitored user according to the target gait monitoring pattern comprises:
matching a corresponding target gait monitoring mode based on the standard gait information;
carrying out gait monitoring on the monitored user according to the target gait monitoring mode to obtain a gait monitoring result;
and generating a corresponding gait monitoring report based on the gait monitoring result, and outputting the gait monitoring report.
8. A gait monitoring device, characterized in that it comprises:
the gait perception module is used for acquiring the gait perception information of the monitored user within a preset time period;
the phase recognition module is used for carrying out phase recognition on the gait perception information so as to obtain target gait information under different dynamic phases;
the information standardization module is used for carrying out standardization processing on the target gait information so as to obtain standard gait information under different dynamic phases;
and the gait monitoring module is used for matching a corresponding target gait monitoring mode based on the standard gait information and carrying out gait monitoring on the monitored user according to the target gait monitoring mode.
9. A gait monitoring device, characterized in that the device comprises: a memory, a processor, and a gait monitoring program stored on the memory and executable on the processor, the gait monitoring program being configured to implement the steps of the gait monitoring method of any of claims 1 to 7.
10. A storage medium having a gait monitoring program stored thereon, which when executed by a processor implements the steps of the gait monitoring method according to any one of claims 1 to 7.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117421605A (en) * | 2023-10-27 | 2024-01-19 | 绍兴清研微科技有限公司 | Gait recognition method and system based on block chain technology |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110152726A1 (en) * | 2009-12-18 | 2011-06-23 | Paul Edward Cuddihy | System and method for monitoring the gait characteristics of a group of individuals |
| CN106166071A (en) * | 2016-07-04 | 2016-11-30 | 中国科学院计算技术研究所 | The acquisition method of a kind of gait parameter and equipment |
| CN109770911A (en) * | 2019-01-21 | 2019-05-21 | 北京诺亦腾科技有限公司 | A kind of gait analysis method, device and storage medium |
| CN110916679A (en) * | 2019-12-31 | 2020-03-27 | 复旦大学 | Human body lower limb pose gait detection device and method |
| WO2021084427A1 (en) * | 2019-10-28 | 2021-05-06 | Scuola Superiore Di Studi Universitari E Di Perfezionamento Sant'anna | Method for optimising the arrangement of pressure sensors and device obtained by this method |
-
2021
- 2021-08-31 CN CN202111017543.0A patent/CN113679380B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110152726A1 (en) * | 2009-12-18 | 2011-06-23 | Paul Edward Cuddihy | System and method for monitoring the gait characteristics of a group of individuals |
| CN106166071A (en) * | 2016-07-04 | 2016-11-30 | 中国科学院计算技术研究所 | The acquisition method of a kind of gait parameter and equipment |
| CN109770911A (en) * | 2019-01-21 | 2019-05-21 | 北京诺亦腾科技有限公司 | A kind of gait analysis method, device and storage medium |
| WO2021084427A1 (en) * | 2019-10-28 | 2021-05-06 | Scuola Superiore Di Studi Universitari E Di Perfezionamento Sant'anna | Method for optimising the arrangement of pressure sensors and device obtained by this method |
| CN110916679A (en) * | 2019-12-31 | 2020-03-27 | 复旦大学 | Human body lower limb pose gait detection device and method |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117421605A (en) * | 2023-10-27 | 2024-01-19 | 绍兴清研微科技有限公司 | Gait recognition method and system based on block chain technology |
| CN117421605B (en) * | 2023-10-27 | 2024-04-30 | 绍兴清研微科技有限公司 | Gait recognition method and system based on block chain technology |
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