CN110786862B - Gait cycle identification method based on torque and angle feedback fusion - Google Patents
Gait cycle identification method based on torque and angle feedback fusion Download PDFInfo
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- 230000005021 gait Effects 0.000 title claims abstract description 47
- 238000000034 method Methods 0.000 title claims abstract description 21
- 230000004927 fusion Effects 0.000 title claims abstract description 8
- 210000002414 leg Anatomy 0.000 claims abstract description 32
- 238000005452 bending Methods 0.000 claims abstract description 20
- 210000000629 knee joint Anatomy 0.000 claims abstract description 17
- 210000002683 foot Anatomy 0.000 claims description 20
- 210000000544 articulatio talocruralis Anatomy 0.000 claims description 3
- 150000001875 compounds Chemical class 0.000 claims description 3
- 230000005489 elastic deformation Effects 0.000 claims description 3
- 244000309466 calf Species 0.000 claims 1
- 230000007547 defect Effects 0.000 abstract description 3
- 230000035900 sweating Effects 0.000 abstract description 3
- 238000012360 testing method Methods 0.000 abstract description 2
- 210000000689 upper leg Anatomy 0.000 description 8
- 210000003414 extremity Anatomy 0.000 description 6
- 238000010586 diagram Methods 0.000 description 3
- 230000005484 gravity Effects 0.000 description 3
- 238000009434 installation Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 2
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- 206010039203 Road traffic accident Diseases 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 238000002266 amputation Methods 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
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- 238000004140 cleaning Methods 0.000 description 1
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- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
- A61B5/112—Gait analysis
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/1036—Measuring load distribution, e.g. podologic studies
- A61B5/1038—Measuring plantar pressure during gait
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/107—Measuring physical dimensions, e.g. size of the entire body or parts thereof
- A61B5/1071—Measuring physical dimensions, e.g. size of the entire body or parts thereof measuring angles, e.g. using goniometers
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2/68—Operating or control means
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2/68—Operating or control means
- A61F2002/6827—Feedback system for providing user sensation, e.g. by force, contact or position
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Abstract
The invention discloses a gait cycle recognition method based on torque and angle feedback fusion, which is characterized in that a ground support reaction model is established according to axial stress and bending moment of a leg prosthesis extension rod of a prosthesis wearer, ground support reaction data and support reaction distribution conditions borne by a prosthetic foot sole are obtained according to a pressure sensor arranged at the tail end of the leg prosthesis extension rod, and knee joint corner data are obtained according to an angle sensor arranged at a knee joint of a leg prosthesis; and determining the stage of the current gait cycle according to the support reaction force data and the knee joint corner data and by contrasting data in a gait database. The invention overcomes the defects that the measured data of the gait cycle identification method by electromyographic signals is easy to be interfered by the skin surface state and the gait cycle can not be accurately judged under the states of skin sweating or unclean and the like, and the test result of the sensor is reliable without the risk of falling off of the sensor.
Description
Technical Field
The invention relates to the technical field of computer identification, in particular to a gait identification method based on the fusion of torque and angle feedback.
Background
With the development of modern industry, accidental injuries such as natural disasters, traffic accidents, diseases and the like frequently occur, the number of thigh amputees is rapidly increasing, and for the thigh amputees, the amputation causes the thigh amputees to lose basic walking ability, and the installation of intelligent artificial limbs is an effective method for restoring the basic walking ability of the thigh amputees. One of the key technologies of the intelligent artificial limb is gait cycle recognition, so that the gait cycle recognition is researched, and the gait cycle recognition is of great significance for improving the life of thigh amputees.
The current gait cycle identification method mainly comprises the step of identifying the gait cycle by electromyographic signals. The gait cycle of the electromyographic signal recognition is that an electromyographic sensor is attached to the position of skin surface muscle of a thigh amputee subject, multichannel stump surface electromyographic signals in an asynchronous state are collected, the collected electromyographic signals are analyzed and preprocessed, feature values of the preprocessed electromyographic signals are extracted, corresponding feature vectors are constructed, and the gait cycle of the thigh amputee is recognized by using an improved supervised Kohonen neural network clustering algorithm. However, the electromyographic signal identification gait cycle needs to make the electromyographic sensor completely contact with the skin surface of a human body, the signal is weak, the dryness degree, the cleaning degree, the sweating condition and the like of the skin surface all influence the output signal of the electromyographic sensor, and the situations of inaccurate measuring result, wrong gait cycle judgment and the like easily occur.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a gait cycle recognition method based on the fusion of torque and angle feedback, which can accurately judge which stage of the gait cycle a human body is in at any period and determine the action which the intelligent artificial limb should do next, so that the intelligent artificial limb wearer can walk more naturally and comfortably.
The invention provides a gait cycle recognition method based on the fusion of torque and angle feedback, which is characterized in that a ground support reaction model is established according to the axial stress and bending moment of a leg prosthesis extension rod of a prosthesis wearer, ground support reaction data and support reaction distribution conditions borne by a prosthetic foot are obtained according to a pressure sensor arranged at the tail end of the leg prosthesis extension rod, and knee joint corner data are obtained according to an angle sensor arranged at the knee joint of the prosthetic leg; and determining the stage of the current gait cycle according to the support reaction force data and the knee joint corner data and by contrasting data in a gait database. And establishing a statistical table according to the distribution condition of the support reaction force for counting the gait cycle.
Wherein, establishing the ground support reaction force model comprises:
in the formula (I), the compound is shown in the specification,
is the stress of the front sole of the artificial foot matched with the artificial leg;
the upper heel and the lower heel of the artificial foot matched with the artificial leg are stressed;
the artificial leg is stressed in the axial direction by the extension rod;
bending moment of the leg prosthesis extension rod;
the distance from the center point of the sole to the shank of the foot;
the distance from the heel landing central point of the prosthetic foot to the lower leg.
The pressure sensor arranged at the tail end of the leg prosthesis extension rod is connected with the ankle joint of the artificial foot through an elastic sheet, the pressure sensor is arranged on the elastic sheet, and the axial pressure and the bending moment at the position of the leg prosthesis extension rod are calculated through the deformation of the strain gauge.
Wherein the gait database comprises a CGA gait database.
Wherein, the pressure sensor is a strain gauge type pressure sensor.
The strain gauge type pressure sensor expresses the borne pressure through deformation, converts elastic deformation formed by axial stress and bending moment into a voltage form to be output, and calculates the axial stress and the bending moment through the MCU processor on the leg prosthesis extension rod.
In the technical scheme of the invention, the defects that the measurement data of the gait cycle identification method by the electromyographic signals are easily interfered by the skin surface state and the gait cycle cannot be accurately judged under the states of skin sweating or unclean and the like are overcome, the test result of the sensor is reliable, and the risk of sensor falling is avoided.
Drawings
FIG. 1 is a schematic flow chart of a gait cycle recognition method according to an embodiment of the invention;
FIG. 2 is a schematic diagram of the sole reaction force exerted on the ground according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings by way of examples of preferred embodiments. It should be noted, however, that the numerous details set forth in the description are merely for the purpose of providing the reader with a thorough understanding of one or more aspects of the present invention, which may be practiced without these specific details.
In the gait cycle recognition method based on the fusion of torque and angle feedback provided by the embodiment, a flow schematic diagram is shown in fig. 1, specifically, a ground support reaction model is established according to the axial stress and bending moment of a leg prosthesis extension rod of a prosthesis wearer, ground support reaction data and support reaction distribution conditions received by a prosthetic foot sole are obtained according to a pressure sensor installed at the tail end of the leg prosthesis extension rod, and knee joint corner data is obtained according to an angle sensor installed at a knee joint of the prosthetic leg; and according to the support reaction data and the knee joint corner data, determining the stage of the current gait cycle by comparing the data in the CGA gait database.
Specifically, the present embodiment can be divided into four parts:
in the first part, in a gait cycle, the stress condition of the sole and the stress condition of the shank extension rod are analyzed:
in the gait cycle, the sole is acted by the ground support reaction force, and simultaneously, the distribution condition of the ground support reaction force applied to the sole is continuously changed due to the continuous deviation of the gravity center of the human body in the walking process. The ground support reaction force received by the sole can be transmitted to the artificial limb along the lower leg extension rod, axial stress is formed on the lower leg extension rod, the continuous change of the ground support reaction force distribution condition caused by the shift of the gravity center can also be transmitted to the artificial limb along the lower leg extension rod, and bending moment stress is formed on the lower leg extension rod.
Due to the structure of the foot, the front sole and the rear heel are in contact with the ground, the arch part is not in contact with the ground, and the analysis can be simplified into a schematic diagram shown in figure 2, wherein the front sole is stressed
At a vertical distance from the shank extension rod of
The heel is stressed by
At a vertical distance from the shank extension rod of
The shank extension rod is stressed by
The bending moment of the shank extension rod is
The force analysis was as follows:
axial stress of the shank extension rod:
bending moment of shank extension rod:
the following two equations are obtained:
in the formula (I), the compound is shown in the specification,
is the stress of the front sole of the artificial foot matched with the artificial leg;
the upper heel and the lower heel of the artificial foot matched with the artificial leg are stressed;
the artificial leg is stressed in the axial direction by the extension rod;
bending moment of the leg prosthesis extension rod;
the distance from the center point of the sole to the shank of the foot;
the distance from the heel landing central point of the prosthetic foot to the lower leg.
Therefore, the ground support reaction force condition received by the sole can be determined by measuring the axial force and bending moment of the shank extension rod.
The second part, the installation pressure sensor measures the axial atress and the moment of flexure of shank extension rod, confirms ground back-up force distribution condition:
as can be seen from the first section, the condition that the sole of a foot receives the ground support reaction can be determined by measuring the axial force and bending moment of the shank extension rod. The axial stress is the supporting reaction force of the ground to the shank extension rod, and the bending moment is a force generated on the shank extension rod due to the shift of the gravity center in the walking process of a human body. The pressure sensor arranged at the tail end of the leg prosthesis extension rod is connected with the ankle joint of the artificial foot through an elastic sheet, and the pressure sensor is arranged on the elastic sheet. The pressure sensor of the embodiment is a strain gauge type pressure sensor, the pressure born by the pressure sensor is expressed through deformation, elastic deformation formed by axial stress and bending moment is converted into a voltage form to be output, and the axial stress and the bending moment are calculated through an MCU processor on the extension rod of the artificial leg.
The third part, installation angle sensor measures the knee joint angle:
in the walking process of a person, the knee joint corner can be changed continuously according to different stages in one gait cycle, and an angle sensor is installed at the knee joint and used for measuring the knee joint corner.
And the fourth part identifies the gait of the thigh stump by referring to the CGA gait database data:
and comparing the measured ground support reaction force and knee joint rotation angle data with corresponding data curve threshold values in the CGA gait database to determine which stage the current gait cycle is in.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be construed as the protection scope of the present invention.
Claims (5)
1. A gait cycle identification method based on torque and angle feedback fusion is characterized in that a ground support reaction force model is established according to axial stress and bending moment of a leg prosthesis extension rod of a prosthesis wearer, ground support reaction force data and support reaction force distribution conditions of a prosthetic foot are obtained according to a pressure sensor arranged at the tail end of the leg prosthesis extension rod, and knee joint corner data are obtained according to an angle sensor arranged at a knee joint of the prosthetic leg; according to the support reaction data and the knee joint corner data, determining the stage of the current gait cycle by contrasting data in a gait database;
the method for establishing the ground support reaction force model comprises the following steps:
in the formula (I), the compound is shown in the specification,
is the stress of the front sole of the artificial foot matched with the artificial leg;
the upper heel and the lower heel of the artificial foot matched with the artificial leg are stressed;
the artificial leg is stressed in the axial direction by the extension rod;
bending moment of the leg prosthesis extension rod;
the distance from the center point of the sole to the shank of the foot;
the distance from the heel landing central point of the prosthetic foot to the lower leg.
2. The gait cycle recognition method according to claim 1, wherein the pressure sensor attached to the distal end of the leg prosthesis extension rod is connected to the ankle joint of the foot prosthesis at the distal end of the calf of the leg prosthesis by an elastic piece, and the pressure sensor is attached to the elastic piece.
3. A gait cycle identification method according to claim 1, characterized in that the gait database comprises a CGA gait database.
4. The gait cycle recognition method according to claim 2, wherein the pressure sensor is a strain gauge type pressure sensor.
5. The gait cycle recognition method according to claim 4, wherein the strain gauge type pressure sensor expresses the pressure by deformation, converts the elastic deformation formed by the axial force and the bending moment into voltage form for output, and calculates the axial force and the bending moment by the MCU processor on the leg prosthesis extension rod.
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| US6971267B2 (en) * | 2002-09-23 | 2005-12-06 | Honda Giken Kogyo Kabushiki Kaisha | Method and processor for obtaining moments and torques in a biped walking system |
| DE102005051646A1 (en) * | 2005-10-26 | 2007-05-10 | Otto Bock Healthcare Ip Gmbh & Co. Kg | Procedure for checking the setting of a prosthetic knee joint |
| CN101525011A (en) * | 2008-03-04 | 2009-09-09 | 王慧娟 | Jumping robot and motion optimization method adopting inertia matching |
| KR20110074520A (en) * | 2008-09-04 | 2011-06-30 | 아이워크, 아이엔씨. | Hybrid Terrain-Adaptive Prosthetic Systems |
| US11172331B2 (en) * | 2015-06-23 | 2021-11-09 | Ipcomm Llc. | Synchronizing data collection of motion and ground reaction force with the start of sporting activities |
| CN106420279B (en) * | 2016-12-01 | 2019-04-09 | 北京理工大学 | A gait-based wearable flexible knee-joint robotic exoskeleton |
| CN106805980A (en) * | 2017-01-24 | 2017-06-09 | 重庆小爱科技有限公司 | A kind of gait analysis system and analysis method |
| CN107137089A (en) * | 2017-04-07 | 2017-09-08 | 浙江大学 | A kind of Wearable sensing shoe system and gait evaluation method |
| CN109558685B (en) * | 2018-12-05 | 2021-07-13 | 北京航空航天大学 | Projectile fulcrum determination method, device, storage medium and electronic device |
| CN110334573B (en) * | 2019-04-09 | 2022-04-29 | 北京航空航天大学 | A Human Motion State Discrimination Method Based on Densely Connected Convolutional Neural Networks |
| CN110037891A (en) * | 2019-04-22 | 2019-07-23 | 哈工大机器人（合肥）国际创新研究院 | Lower limb knee ankle recovery training appliance for recovery based on plantar pressure Gait Recognition |
| CN110169850B (en) * | 2019-05-17 | 2020-07-17 | 上海理工大学 | Control method of passive hydraulic knee joint prosthesis |
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