CN117257284A - Fall risk processing method and device, intelligent artificial limb, terminal and storage medium - Google Patents
Fall risk processing method and device, intelligent artificial limb, terminal and storage medium Download PDFInfo
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- CN117257284A CN117257284A CN202311566140.0A CN202311566140A CN117257284A CN 117257284 A CN117257284 A CN 117257284A CN 202311566140 A CN202311566140 A CN 202311566140A CN 117257284 A CN117257284 A CN 117257284A
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- 238000003672 processing method Methods 0.000 title claims abstract description 15
- 238000013016 damping Methods 0.000 claims abstract description 122
- 210000000629 knee joint Anatomy 0.000 claims abstract description 64
- 210000003414 extremity Anatomy 0.000 claims abstract description 36
- 238000005452 bending Methods 0.000 claims abstract description 21
- 238000012545 processing Methods 0.000 claims abstract description 21
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- 230000001133 acceleration Effects 0.000 claims description 97
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- 238000010586 diagram Methods 0.000 description 6
- 238000004590 computer program Methods 0.000 description 5
- 244000309466 calf Species 0.000 description 4
- 230000000737 periodic effect Effects 0.000 description 4
- 206010016173 Fall Diseases 0.000 description 3
- 238000002266 amputation Methods 0.000 description 2
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- 230000001360 synchronised effect Effects 0.000 description 2
- 210000000689 upper leg Anatomy 0.000 description 2
- 238000003491 array Methods 0.000 description 1
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- 230000009977 dual effect Effects 0.000 description 1
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- 238000012502 risk assessment Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000008733 trauma Effects 0.000 description 1
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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—Detecting, measuring or recording 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, mobility of a limb
- A61B5/1116—Determining posture transitions
- A61B5/1117—Fall detection
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- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
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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
- A61F2/60—Artificial legs or feet or parts thereof
- A61F2/64—Knee joints
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/04—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
- G08B21/0438—Sensor means for detecting
- G08B21/0446—Sensor means for detecting worn on the body to detect changes of posture, e.g. a fall, inclination, acceleration, gait
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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
- A61F2/60—Artificial legs or feet or parts thereof
- A61F2002/607—Lower legs
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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
- A61F2002/689—Alarm means, e.g. acoustic
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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
- A61F2/76—Means for assembling, fitting or testing prostheses, e.g. for measuring or balancing, e.g. alignment means
- A61F2002/7615—Measuring means
- A61F2002/764—Measuring means for measuring acceleration
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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
- A61F2/76—Means for assembling, fitting or testing prostheses, e.g. for measuring or balancing, e.g. alignment means
- A61F2002/7695—Means for testing non-implantable prostheses
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Abstract
The invention discloses a tumble risk processing method, a tumble risk processing device, an intelligent artificial limb, a terminal and a storage medium, wherein the method comprises the following steps: acquiring rotational motion data of a user body and rotational motion data of the knee joint; determining the tumbling risk information of the user based on the rotational motion data and the rotational motion data; based on the fall risk information, damping data of the damping device is adjusted to increase bending resistance to the knee joint. According to the invention, the tumbling risk information of the user can be judged based on the rotation motion data of the body of the user and the rotation motion data of the rotating shaft in the knee joint, and then the damping data of the damping device is adjusted according to the determined tumbling risk information so as to increase the bending resistance of the knee joint, thereby ensuring the safety and stability of the intelligent artificial limb used by the user.
Description
Technical Field
The invention relates to the technical field of artificial limbs, in particular to a method and a device for processing falling risks, an intelligent artificial limb, a terminal and a storage medium.
Background
Along with the development of society, the convenience of traffic and the continuous improvement of industrial level, the patients who cause amputation due to machine trauma car accidents and the like are more and more, and the amputation brings a lot of inconvenience to the patients and loses basic life ability. It is therefore becoming increasingly urgent to develop a smart prosthesis that helps amputees achieve basic life capabilities. The intelligent artificial limb needs to have the functions of assisting a patient in walking, running and the like, the intelligent artificial limb needs to have the capability of identifying different movement modes of walking, running and the like, and the intelligent artificial limb needs to be controlled individually for users in different states.
In the prior art, the intelligent artificial limb is not intelligently controlled, and the falling risk of a user cannot be analyzed, so that the use safety and stability of the intelligent artificial limb cannot be ensured.
Accordingly, there is a need for improvement and advancement in the art.
Disclosure of Invention
The invention aims to solve the technical problems that the control of an intelligent artificial limb is not intelligent, the falling risk of a user cannot be analyzed, and therefore the use safety and stability of the intelligent artificial limb cannot be ensured.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
in a first aspect, the present invention provides a method for treating risk of falling, wherein the method for treating risk of falling is applied to an intelligent artificial limb, the intelligent artificial limb includes a knee joint and a shank portion located below the knee joint, a damping device is disposed in the shank portion, the damping device is used for providing extension resistance or bending resistance for the knee joint, and the method for treating risk of falling includes:
acquiring rotary motion data of the lower leg of a user and rotary motion data of the knee joint;
determining the tumbling risk information of the user based on the rotational motion data and the rotational motion data;
based on the fall risk information, damping data of the damping device is adjusted to increase bending resistance to the knee joint.
In one implementation, the determining the risk of falling information of the user based on the rotational motion data and the rotational motion data includes:
determining a rotational angular acceleration and a rotational angular acceleration based on the rotational motion data and the rotational motion data;
and determining the fall risk information based on the rotational angular acceleration and the rotational angular acceleration.
In one implementation, the determining the fall risk information based on the rotational angular acceleration and the rotational angular acceleration includes:
acquiring a preset first threshold range and a preset second threshold range, wherein the first threshold range comprises a plurality of rotation angle acceleration thresholds, two adjacent rotation angle acceleration thresholds form a gear interval, the second threshold range comprises a plurality of rotation angle acceleration thresholds, and two adjacent rotation angle acceleration thresholds form a gear interval;
matching the rotation angular acceleration with the first threshold range to obtain a first target gear section corresponding to the rotation angular acceleration;
matching the rotation angular acceleration with the second threshold range to obtain a second target gear interval corresponding to the rotation angular acceleration;
and determining the fall risk information based on the first target gear interval and the second target gear interval.
In one implementation, the determining the fall risk information based on the first target gear interval and the second target gear interval includes:
acquiring a first falling probability corresponding to the first target gear interval and a second falling probability corresponding to the second target gear interval;
determining a target probability of fall based on the first probability of fall and the second probability of fall;
and determining a falling risk gear corresponding to the target falling probability based on the target falling probability, and taking the falling risk gear as the falling risk information.
In one implementation, the determining the target probability of fall based on the first probability of fall and the second probability of fall includes:
comparing the first probability of falling with the second probability of falling;
and taking the larger one of the first falling probability and the second falling probability as the target falling probability.
In one implementation, the adjusting damping data of the damping device based on the fall risk information includes:
acquiring a damping adjustment scheme corresponding to the falling risk gear based on the falling risk gear corresponding to the falling risk information;
and adjusting damping data of the damping device based on the damping adjustment scheme.
In one implementation, the adjusting damping data of the damping device based on the damping adjustment scheme includes:
acquiring an adjusting speed and a damping maximum value in the damping adjusting scheme;
and gradually increasing damping data of the damping device according to the adjustment speed until the damping data is increased to the maximum damping value.
In a second aspect, an embodiment of the present invention further provides a fall risk processing apparatus, where the fall risk processing apparatus is applied to an intelligent prosthesis, the intelligent prosthesis includes a knee joint and a shank located below the knee joint, a damping device is disposed in the shank, the damping device is configured to provide extension resistance or bending resistance to the knee joint, and the fall risk processing apparatus includes:
the data acquisition module is used for acquiring rotary motion data of the lower leg of the user and rotary motion data of the knee joint;
the risk determination module is used for determining falling risk information of a user based on the rotation motion data and the rotation motion data;
and the damping adjustment module is used for adjusting damping data of the damping device based on the tumbling risk information so as to increase bending resistance to the knee joint.
In one implementation, the risk determination module includes:
an acceleration determining unit configured to determine a rotational angular acceleration and a rotational angular acceleration based on the rotational motion data and the rotational motion data;
and a fall risk determination unit configured to determine the fall risk information based on the rotational angular acceleration and the rotational angular acceleration.
In one implementation, the fall risk determination unit includes:
the device comprises a threshold range acquisition subunit, a first threshold range acquisition subunit and a second threshold range acquisition subunit, wherein the first threshold range comprises a plurality of rotation angular acceleration thresholds, two adjacent rotation angular acceleration thresholds form a gear range, the second threshold range comprises a plurality of rotation angular acceleration thresholds, and two adjacent rotation angular acceleration thresholds form a gear range;
the first threshold matching subunit is used for matching the rotation angular acceleration with the first threshold range to obtain a first target gear interval corresponding to the rotation angular acceleration;
the second threshold matching subunit is used for matching the rotation angular acceleration with the second threshold range to obtain a second target gear interval corresponding to the rotation angular acceleration;
and the gear interval analysis subunit is used for determining the falling risk information based on the first target gear interval and the second target gear interval.
In one implementation, the gear range analysis subunit includes:
the probability data acquisition subunit is used for acquiring a first falling probability corresponding to the first target gear interval and a second falling probability corresponding to the second target gear interval;
a falling probability determination subunit configured to determine a target falling probability based on the first falling probability and the second falling probability;
and the risk gear determining subunit is used for determining a falling risk gear corresponding to the target falling probability based on the target falling probability, and taking the falling risk gear as the falling risk information.
In one implementation, the damping adjustment module includes:
an adjustment scheme obtaining unit, configured to obtain a damping adjustment scheme corresponding to a falling risk gear based on the falling risk gear corresponding to the falling risk information;
and the damping data adjusting unit is used for adjusting damping data of the damping device based on the damping adjusting scheme.
In a third aspect, an embodiment of the present invention further provides an intelligent prosthesis, which is characterized in that the intelligent prosthesis includes a socket, a knee joint, a shank, and a fall risk treatment device according to the above-mentioned aspects.
In a fourth aspect, an embodiment of the present invention further provides a terminal, where the terminal includes a memory, a processor, and a fall risk processing program stored in the memory and capable of running on the processor, and when the processor executes the fall risk processing program, the processor implements the steps of the fall risk processing method in any one of the above schemes.
In a fifth aspect, an embodiment of the present invention further provides a computer readable storage medium, where a fall risk processing program is stored on the computer readable storage medium, where the fall risk processing program, when executed by a processor, implements the steps of the fall risk processing method according to any one of the above schemes.
The beneficial effects are that: compared with the prior art, the invention provides a tumble risk processing method, which comprises the steps of firstly acquiring the rotation motion data of the lower leg of a user and the rotation motion data of the knee joint. And then, based on the rotational motion data and the rotational motion data, determining the tumbling risk information of the user. Finally, based on the fall risk information, damping data of the damping device are adjusted to increase bending resistance to the knee joint. According to the invention, the tumbling risk information of the user can be judged based on the rotation movement data of the lower leg of the user and the rotation movement data of the rotating shaft in the knee joint, and then the damping data of the damping device is adjusted according to the determined tumbling risk information so as to increase the bending resistance of the knee joint, thereby ensuring the safety and stability of the intelligent artificial limb used by the user.
Drawings
Fig. 1 is a flowchart of a specific implementation of a method for treating a risk of falling according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of an intelligent artificial limb according to an embodiment of the present invention.
Fig. 3 is a functional schematic diagram of a fall risk processing device according to an embodiment of the present invention.
Fig. 4 is a schematic block diagram of a terminal according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and more specific, the present invention will be described in further detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment provides a method for processing risk of falling, which can judge falling risk information of a user based on rotation motion data of a lower leg of the user and rotation motion data of a rotating shaft in a knee joint, and then adjust damping data of a damping device according to the determined falling risk information so as to increase bending resistance of the knee joint, thereby ensuring safety and stability of the intelligent artificial limb used by the user. In specific application, the present embodiment first obtains rotational movement data of the user's lower leg and rotational movement data of the knee joint. And then, based on the rotational motion data and the rotational motion data, determining the tumbling risk information of the user. Finally, based on the fall risk information, damping data of the damping device are adjusted to increase bending resistance to the knee joint.
The falling risk processing method of the embodiment can be applied to an intelligent artificial limb, and the intelligent artificial limb comprises an intelligent controller for realizing the falling risk processing method. In addition, the method for processing the risk of falling down in the embodiment can be further applied to a terminal, and the terminal can be arranged in an intelligent artificial limb so as to realize the method for processing the risk of falling down through the terminal. The intelligent artificial limb comprises a knee joint and a shank part positioned below the knee joint, wherein a damping device is arranged in the shank part and used for providing stretching resistance or bending resistance for the knee joint. Specifically, as shown in fig. 1, the fall risk processing method of the present embodiment includes the steps of:
step S100, acquiring rotation motion data of a user body and rotation motion data of the knee joint.
As shown in fig. 2, the intelligent artificial limb of the embodiment comprises a shank 11 and a knee joint 12 rotatably connected with the shank 11 through a rotating shaft, wherein the rotating shaft is arranged on the knee joint 12 and is used for driving the shank to rotate so as to realize flexible movement of the knee joint 12, the knee joint 12 is positioned at the top of the shank 11, the intelligent artificial limb further comprises a receiving cavity 3, the receiving cavity 3 is fixedly connected with the knee joint 12, and the receiving cavity 3 is used for being installed on the thigh of a user. The damping device 2 is arranged in the lower leg 11 in this embodiment, and the damping device 2 may be a hydraulic cylinder, which may be used to provide extension resistance or flexion resistance to the knee joint, so that the knee joint 12 remains stable.
After the intelligent artificial limb is installed on the thigh of the user, the user can use the intelligent artificial limb to be applied to various scenes, in order to ensure the use safety of the intelligent artificial limb and also help the intelligent artificial limb to be better used by the user, the embodiment can acquire the rotation motion data of the calf 11 of the user and the rotation motion data of the knee joint 12 in real time, and the rotation motion data can be used for reflecting the rotation angle of the rotating shaft in the knee joint 12. In this embodiment, the rotational movement data and the rotational movement data may be acquired based on a preset inertial sensor, which may be disposed on the wearing device of the user and on the intelligent prosthesis, and the rotational movement data of the lower leg 1 of the user and the rotational movement data of the knee joint 12 may be acquired in real time, regardless of whether the user is standing or walking.
Step 200, determining the tumbling risk information of the user based on the rotation motion data and the rotation motion data.
After the terminal collects the rotary motion data and the rotary motion data, the terminal starts to comprehensively analyze the rotary motion data and the rotary motion data, and determines the falling risk information of the user, wherein the falling risk information reflects whether the user falls and how much the falling risk is.
In one implementation, the embodiment includes the following steps when determining the fall risk information:
step S201, based on the rotational motion data and the rotational motion data, determining rotational angular acceleration and rotational angular acceleration;
step S202, determining the fall risk information based on the rotational angular acceleration and the rotational angular acceleration.
Specifically, the terminal may compare and analyze the rotational movement data collected in real time to the user's calf portion 11, analyze the change of the rotational movement data, obtain rotational angle change data, and further determine rotational angular acceleration based on the rotational angle change data, where the rotational angular acceleration may be used to reflect the speed of the rotational angle change of the user's calf portion 11, so that based on the rotational angular acceleration, it may be determined whether the user suddenly tilts/rotates and whether the user rapidly tilts/rotates. Similarly, the terminal may further compare and analyze the rotational movement data of the knee joint 12 collected in real time, analyze the change of the rotational movement data, obtain rotational angle change data, and further determine rotational angular acceleration based on the rotational angle change data, where the rotational angular acceleration may be used to reflect the speed of rotation of the knee joint 12 of the intelligent prosthesis, that is, reflect the speed of swing of the calf portion 11, and further analyze whether the knee joint 12 suddenly rotates and whether it rotates rapidly. In the present embodiment, the rotation of the lower leg 11 can be used to reflect the rotation of the entire body of the user, such as a left turn or a right turn. The rotation of the knee joint 12 can be used to reflect the fore-and-aft swing of the lower leg 11. Therefore, after the terminal obtains the rotation angular acceleration and the rotation angular acceleration, the embodiment can further analyze to obtain the tumbling risk information of the user.
In one implementation, the present embodiment presets a first threshold range including a plurality of rotational angular acceleration thresholds, and two adjacent rotational angular acceleration thresholds form one gear range. For example, the first threshold range includes three rotational angular acceleration thresholds, so that four shift ranges can be formed. Similarly, in this embodiment, a second threshold range is preset, where the second threshold range includes a plurality of rotational angular acceleration thresholds, and two adjacent rotational angular acceleration thresholds form a gear range. Then, the terminal matches the rotation angular acceleration with the first threshold range to obtain a first target gear section corresponding to the rotation angular acceleration; and matching the rotation angular acceleration with the second threshold range to obtain a second target gear range corresponding to the rotation angular acceleration. The first target gear range and the second target gear range may be used to reflect the magnitudes of the rotational angular acceleration and the rotational angular acceleration, respectively.
After determining a first target gear interval and a second target gear interval, the embodiment respectively obtains a first falling probability corresponding to the first target gear interval and a second falling probability corresponding to the second target gear interval. In this embodiment, the first threshold range and the second threshold range are respectively set with a falling probability corresponding to each gear range, where the first falling probability may be used to reflect a probability of falling when the user is at the current rotational angular acceleration, and the second falling probability may be used to reflect a probability of falling when the intelligent prosthetic knee joint 12 is at the current rotational angular acceleration. Then, the terminal determines a target fall probability based on the first fall probability and the second fall probability.
In particular, the present embodiment may compare the first fall probability with the second fall probability. Then, the larger of the first fall probability and the second fall probability is taken as the target fall probability. Then, the terminal determines a falling risk gear corresponding to the target falling probability based on the target falling probability, and takes the falling risk gear as the falling risk information. In this embodiment, a correspondence relationship between a falling probability and a falling risk gear is preset, and the falling risk gear may be classified into a first gear, a second gear, and the like. When the target falling probability is determined, the falling risk gear corresponding to the target falling probability can be determined based on the corresponding relation, so that the risk of falling of the user is determined. In the present embodiment, when analyzing whether a user falls, the rotational angular acceleration of the user's lower leg 11 and the rotational angular acceleration of the knee joint 12 are considered respectively, and the risk of the user falling is analyzed from two dimensions, so that the risk analysis is more accurate. In addition, the embodiment also takes the larger falling probability of the falling probability corresponding to the oblique angle acceleration and the rotation angle acceleration as the target falling probability, so that the possibility of falling of the user can be more accurately determined, the falling risk is better avoided, and the safety of the user is ensured.
In another implementation manner, in the present embodiment, when the collected rotational motion data and the rotational motion data are analyzed, periodic variation data of the rotational motion data with regularity and periodic variation data of the rotational motion data with regularity may be respectively analyzed. The periodic variation data belong to the variation conditions of the corresponding rotation movement data and rotation movement data of the intelligent artificial limb during normal walking, so that the periodic variation data can be screened out during analysis of the falling risk information, the data quantity during analysis of the falling risk in the subsequent steps is reduced, the calculated quantity is reduced, and the accuracy of analysis of the falling risk information in the subsequent steps is guaranteed. Only when the analyzed rotational angular acceleration is in the first threshold range or the rotational angular acceleration is in the second threshold range, the step of performing the next fall risk information analysis is performed.
And step S300, adjusting damping data of the damping device based on the tumbling risk information so as to increase bending resistance of the knee joint.
After determining the risk information of falling, because the risk information of falling reflects the gear of falling, the user can know how much the possibility of falling at the moment, and in order to ensure the safety of the user, the terminal can adjust the damping data of the damping device 2 based on the risk information of falling, so as to increase the bending resistance of the knee joint 12, so that the user is safer and more stable when using the intelligent artificial limb.
In one implementation, the present embodiment includes the following steps when adjusting damping data:
step S301, acquiring a damping adjustment scheme corresponding to the falling risk gear based on the falling risk gear corresponding to the falling risk information;
step S302, based on the damping adjustment scheme, damping data of the damping device are adjusted.
Specifically, the embodiment may first obtain a damping adjustment scheme corresponding to the fall risk gear based on the fall risk gear corresponding to the fall risk information. The damping adjustment scheme comprises an adjustment speed corresponding to the falling risk gear at the moment and an adjusted damping maximum value. Therefore, after the damping adjustment scheme is obtained, the terminal can gradually increase the damping data of the damping device 2 according to the adjustment speed to the damping data of the damping device 2 until the damping data is increased to the damping maximum value. In this embodiment, when the determined gear of risk of falling is higher, it is indicated that the risk of falling of the user is also higher at this time, and the damping data needs to be increased at this time. Since there is a great risk of the user falling down, a greater bending resistance is required, so that the damping device 2 can provide a better elastic supporting force to support the user, and the damping device 2 on the intelligent prosthesis is also required to rapidly increase damping data so as to provide an elastic supporting force to support the user more quickly. Therefore, when the gear of the falling risk is higher, the corresponding adjusting speed is higher, and the damping maximum value is also higher, so that the falling of the user can be effectively avoided.
In summary, the embodiment can determine the falling risk information of the user based on the rotation motion data of the lower leg of the user and the rotation motion data of the rotating shaft in the knee joint, and then adjust the damping data of the damping device according to the determined falling risk information so as to increase the bending resistance of the knee joint, thereby ensuring the safety and stability of the intelligent artificial limb used by the user.
Based on the above embodiment, the invention also provides a falling risk processing device, which is applied to an intelligent artificial limb, wherein the intelligent artificial limb comprises a knee joint and a lower leg part below the knee joint, a damping device is arranged in the lower leg part, and the damping device is used for providing bending resistance or stretching resistance for the knee joint. Specifically, as shown in fig. 3, the fall risk processing device includes: a data acquisition module 10, a risk determination module 20 and a damping adjustment module 30. Specifically, the data acquisition module 10 is configured to acquire rotational motion data of the lower leg of the user and rotational motion data of the knee joint. The risk determination module 20 is configured to determine risk information of a user for falling based on the rotational motion data and the rotational motion data. The damping adjustment module 30 is configured to adjust damping data of the damping device based on the fall risk information, so as to increase bending resistance of the knee joint.
In one implementation, the risk determination module includes:
an acceleration determining unit configured to determine a rotational angular acceleration and a rotational angular acceleration based on the rotational motion data and the rotational motion data;
and a fall risk determination unit configured to determine the fall risk information based on the rotational angular acceleration and the rotational angular acceleration.
In one implementation, the fall risk determination unit includes:
the device comprises a threshold range acquisition subunit, a first threshold range acquisition subunit and a second threshold range acquisition subunit, wherein the first threshold range comprises a plurality of rotation angular acceleration thresholds, two adjacent rotation angular acceleration thresholds form a gear range, the second threshold range comprises a plurality of rotation angular acceleration thresholds, and two adjacent rotation angular acceleration thresholds form a gear range;
the first threshold matching subunit is used for matching the rotation angular acceleration with the first threshold range to obtain a first target gear interval corresponding to the rotation angular acceleration;
the second threshold matching subunit is used for matching the rotation angular acceleration with the second threshold range to obtain a second target gear interval corresponding to the rotation angular acceleration;
and the gear interval analysis subunit is used for determining the falling risk information based on the first target gear interval and the second target gear interval.
In one implementation, the gear range analysis subunit includes:
the probability data acquisition subunit is used for acquiring a first falling probability corresponding to the first target gear interval and a second falling probability corresponding to the second target gear interval;
a falling probability determination subunit configured to determine a target falling probability based on the first falling probability and the second falling probability;
and the risk gear determining subunit is used for determining a falling risk gear corresponding to the target falling probability based on the target falling probability, and taking the falling risk gear as the falling risk information.
In one implementation, the fall probability determination subunit includes:
a probability comparison subunit configured to compare the first fall probability with the second fall probability;
and the probability screening subunit is used for taking the larger one of the first falling probability and the second falling probability as the target falling probability.
In one implementation, the damping adjustment module includes:
an adjustment scheme obtaining unit, configured to obtain a damping adjustment scheme corresponding to a falling risk gear based on the falling risk gear corresponding to the falling risk information;
and the damping data adjusting unit is used for adjusting damping data of the damping device based on the damping adjusting scheme.
In one implementation, the damping data adjustment unit includes:
a damping obtaining subunit, configured to obtain an adjustment speed and a damping maximum value in the damping adjustment scheme;
and the damping increasing subunit is used for gradually increasing the damping data of the damping device according to the adjusting speed until the damping data is increased to the maximum damping value.
The working principle of each module in the tumbling risk processing device of the embodiment is the same as that of each step in the above method embodiment, and will not be described here again.
Based on the above embodiment, the invention further provides a smart prosthesis, wherein the smart prosthesis comprises a socket, a knee joint, a lower leg and the falling risk processing device in the above embodiment.
Based on the above embodiment, the present invention also provides a terminal, and a schematic block diagram of the terminal may be shown in fig. 4. The terminal may include one or more processors 100 (only one shown in fig. 4), a memory 101, and a computer program 102, such as a fall risk processing program, stored in the memory 101 and executable on the one or more processors 100. The one or more processors 100, when executing the computer program 102, may implement the various steps of an embodiment of a fall risk processing method. Alternatively, the one or more processors 100, when executing the computer program 102, may implement the functions of the various modules/units of the embodiment of the fall risk handling device, without limitation.
In one embodiment, the processor 100 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In one embodiment, the memory 101 may be an internal storage unit of the electronic device, such as a hard disk or a memory of the electronic device. The memory 101 may also be an external storage device of the electronic device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash card (flash card) or the like, which are provided on the electronic device. Further, the memory 101 may also include both an internal storage unit and an external storage device of the electronic device. The memory 101 is used to store computer programs and other programs and data required by the terminal. The memory 101 may also be used to temporarily store data that has been output or is to be output.
It will be appreciated by those skilled in the art that the functional block diagram shown in fig. 4 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the terminal to which the present inventive arrangements may be applied, as a specific terminal may include more or less components than those shown, or may be combined with some components, or may have a different arrangement of components.
Those skilled in the art will appreciate that implementing all or part of the above-described methods may be accomplished by way of a computer program, which may be stored on a non-transitory computer readable storage medium, that when executed may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, operational database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual operation data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (15)
1. The utility model provides a fall risk processing method, its characterized in that, fall risk processing method is applied to intelligent artificial limb, intelligent artificial limb includes knee joint and is located the shank below the knee joint, set up damping device in the shank, damping device is used for providing extension resistance or bending resistance to the knee joint, fall risk processing method includes:
acquiring rotary motion data of the lower leg of a user and rotary motion data of the knee joint;
determining the tumbling risk information of the user based on the rotational motion data and the rotational motion data;
based on the fall risk information, damping data of the damping device is adjusted to increase bending resistance to the knee joint.
2. The method of claim 1, wherein the determining the risk of falling information of the user based on the rotational motion data and the rotational motion data comprises:
determining a rotational angular acceleration and a rotational angular acceleration based on the rotational motion data and the rotational motion data;
and determining the fall risk information based on the rotational angular acceleration and the rotational angular acceleration.
3. The method according to claim 2, characterized in that the determining the fall risk information based on the rotational angular acceleration and the rotational angular acceleration includes:
acquiring a preset first threshold range and a preset second threshold range, wherein the first threshold range comprises a plurality of rotation angle acceleration thresholds, two adjacent rotation angle acceleration thresholds form a gear interval, the second threshold range comprises a plurality of rotation angle acceleration thresholds, and two adjacent rotation angle acceleration thresholds form a gear interval;
matching the rotation angular acceleration with the first threshold range to obtain a first target gear section corresponding to the rotation angular acceleration;
matching the rotation angular acceleration with the second threshold range to obtain a second target gear interval corresponding to the rotation angular acceleration;
and determining the fall risk information based on the first target gear interval and the second target gear interval.
4. The method of claim 3, wherein the determining the fall risk information based on the first target gear range and the second target gear range comprises:
acquiring a first falling probability corresponding to the first target gear interval and a second falling probability corresponding to the second target gear interval;
determining a target probability of fall based on the first probability of fall and the second probability of fall;
and determining a falling risk gear corresponding to the target falling probability based on the target falling probability, and taking the falling risk gear as the falling risk information.
5. The method of claim 4, wherein the determining a target probability of fall based on the first probability of fall and the second probability of fall comprises:
comparing the first probability of falling with the second probability of falling;
and taking the larger one of the first falling probability and the second falling probability as the target falling probability.
6. The method for risk of a fall according to claim 4, wherein the adjusting damping data of the damping device based on the fall risk information includes:
acquiring a damping adjustment scheme corresponding to the falling risk gear based on the falling risk gear corresponding to the falling risk information;
and adjusting damping data of the damping device based on the damping adjustment scheme.
7. The fall risk processing method according to claim 6, wherein the adjusting damping data of the damping device based on the damping adjustment scheme includes:
acquiring an adjusting speed and a damping maximum value in the damping adjusting scheme;
and gradually increasing damping data of the damping device according to the adjustment speed until the damping data is increased to the maximum damping value.
8. The utility model provides a risk of falling processing apparatus, its characterized in that, risk of falling processing apparatus is applied to intelligent artificial limb, intelligent artificial limb includes knee joint and is located the shank of knee joint below, set up damping device in the shank, damping device is used for right the knee joint provides extension resistance or bending resistance, risk of falling processing apparatus includes:
the data acquisition module is used for acquiring rotary motion data of the lower leg of the user and rotary motion data of the knee joint;
the risk determination module is used for determining falling risk information of a user based on the rotation motion data and the rotation motion data;
and the damping adjustment module is used for adjusting damping data of the damping device based on the tumbling risk information so as to increase bending resistance to the knee joint.
9. The fall risk processing device of claim 8, wherein the risk determination module comprises:
an acceleration determining unit configured to determine a rotational angular acceleration and a rotational angular acceleration based on the rotational motion data and the rotational motion data;
and a fall risk determination unit configured to determine the fall risk information based on the rotational angular acceleration and the rotational angular acceleration.
10. The fall risk processing device according to claim 9, wherein the fall risk determination unit includes:
the device comprises a threshold range acquisition subunit, a first threshold range acquisition subunit and a second threshold range acquisition subunit, wherein the first threshold range comprises a plurality of rotation angular acceleration thresholds, two adjacent rotation angular acceleration thresholds form a gear range, the second threshold range comprises a plurality of rotation angular acceleration thresholds, and two adjacent rotation angular acceleration thresholds form a gear range;
the first threshold matching subunit is used for matching the rotation angular acceleration with the first threshold range to obtain a first target gear interval corresponding to the rotation angular acceleration;
the second threshold matching subunit is used for matching the rotation angular acceleration with the second threshold range to obtain a second target gear interval corresponding to the rotation angular acceleration;
and the gear interval analysis subunit is used for determining the falling risk information based on the first target gear interval and the second target gear interval.
11. The fall risk processing device of claim 10, wherein the gear range analysis subunit includes:
the probability data acquisition subunit is used for acquiring a first falling probability corresponding to the first target gear interval and a second falling probability corresponding to the second target gear interval;
a falling probability determination subunit configured to determine a target falling probability based on the first falling probability and the second falling probability;
and the risk gear determining subunit is used for determining a falling risk gear corresponding to the target falling probability based on the target falling probability, and taking the falling risk gear as the falling risk information.
12. The fall risk handling device of claim 11, wherein the damping adjustment module comprises:
an adjustment scheme obtaining unit, configured to obtain a damping adjustment scheme corresponding to a falling risk gear based on the falling risk gear corresponding to the falling risk information;
and the damping data adjusting unit is used for adjusting damping data of the damping device based on the damping adjusting scheme.
13. A smart prosthesis comprising a socket, a knee joint, a shank and a fall risk handling device according to any one of claims 8 to 12.
14. A terminal comprising a memory, a processor and a fall risk handling program stored in the memory and operable on the processor, the processor implementing the steps of the fall risk handling method of any of claims 1-7 when executing the fall risk handling program.
15. A computer-readable storage medium, wherein a fall risk processing program is stored on the computer-readable storage medium, which when executed by a processor, implements the steps of the fall risk processing method according to any one of claims 1 to 7.
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