CN115317206A - Virtual prosthetic hand training platform for upper limb amputation rehabilitation - Google Patents
Virtual prosthetic hand training platform for upper limb amputation rehabilitation Download PDFInfo
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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
- A61F2/54—Artificial arms or hands or parts thereof
- A61F2/58—Elbows; Wrists ; Other joints; Hands
- A61F2/583—Hands; Wrist joints
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
- A61H1/00—Apparatus for passive exercising; Vibrating apparatus; Chiropractic devices, e.g. body impacting devices, external devices for briefly extending or aligning unbroken bones
- A61H1/02—Stretching or bending or torsioning apparatus for exercising
- A61H1/0274—Stretching or bending or torsioning apparatus for exercising for the upper limbs
- A61H1/0285—Hand
- A61H1/0288—Fingers
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N1/00—Electrotherapy; Circuits therefor
- A61N1/18—Applying electric currents by contact electrodes
- A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
- A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
- A61N1/36014—External stimulators, e.g. with patch electrodes
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
- A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
- A61H2201/16—Physical interface with patient
- A61H2201/1602—Physical interface with patient kind of interface, e.g. head rest, knee support or lumbar support
- A61H2201/165—Wearable interfaces
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
- A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
- A61H2201/50—Control means thereof
- A61H2201/5007—Control means thereof computer controlled
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
- A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
- A61H2201/50—Control means thereof
- A61H2201/5058—Sensors or detectors
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
- A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
- A61H2230/00—Measuring physical parameters of the user
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Abstract
The invention relates to a virtual prosthetic hand training platform for upper limb amputation rehabilitation, which is characterized by comprising a virtual prosthetic hand or a virtual prosthetic limb, a control system and a software interface, wherein the virtual prosthetic hand or the virtual prosthetic limb is driven by tendons, and the driving mode is similar to that of a human body; the control system is configured to simulate a pair of antagonistic muscles having a stretch reflex characteristic using a real-time simulation algorithm; the software interface is set to input the tactile information at the front end of the prosthetic finger into the upper limb sensory channel of the human body to form different tactile feelings. The invention can be used for rehabilitation training of upper limb amputation patients, various grasping scenes in daily life are simulated by the virtual environment, and the learning skills of the patients under the virtual environment are directly applied to the real artificial hands; amputees can get on hand quickly, completing more difficult daily tasks.
Description
Technical Field
The invention relates to a simulation training platform, in particular to a virtual prosthetic hand training platform for rehabilitation of upper limb amputation.
Background
Rehabilitation intervention for upper limb amputees is an important safeguard to help amputees quickly blend in with normal life, with the goal of helping amputees relearn lost motor skills and sensory functions in therapeutic practice and transferring these to functional activities in daily life. Due to the characteristics of high controllability, high stability and the like, the virtual simulation platform can help an amputee to learn and convert complex skills by controlling the physical properties of an object, and is widely applied to training and treatment of upper limb nerve rehabilitation functions. However, due to the high complexity of the real physical world, many current software simulation platforms omit the biomechanical characteristics and motion control characteristics of the prosthetic hand, and cannot truly evaluate the motion effect achieved by the prosthetic hand. Therefore, there is a need to design a virtual simulation platform that can simulate real-world physical contact while assisting the rehabilitation training of amputees, while maintaining the same control mechanism and sensory feedback as a real prosthetic hand.
A number of sensory feedback techniques have been developed in recent years that can be used to help amputees restore tactile sensory information to their hands. Non-invasive Transcutaneous Electrical Nerve Stimulation (TENS) is a viable method to feed tactile information from the tip of a prosthetic finger back to the amputee's stump. There are studies showing that mechanical sensations can induce missing finger sensations at the amputee stump, and that the application of TENS to the projected finger area of the amputee stump skin can induce the sensation of a locally matched finger. The sensory feedback technology is considered to be safe and stable, and is integrated on some real prosthetic hands, so that the upper limb sensory function reconstruction replacing the body sensory function can be realized.
However, the prior art has some disadvantages:
(1) The physical engine of the existing software simulation platform is not designed based on contact dynamics, the inverse dynamics modeling is not precise enough, large errors may occur in the aspects of soft object contact and the like on the complex dynamics behaviors of rich contact, and the contact between the prosthetic hand and the object in the physical world cannot be reflected really.
(2) The existing virtual simulation platform aims at controlling physical properties of an object mostly and limiting the physical properties within analyzed variables and ranges, so that inaccuracy caused by a complex environment is eliminated. The grasping process of the prosthetic hand in the real physical world cannot be reflected by the grasping of the virtual hand in the simulation platform, and the skills learned by a patient in a virtual environment cannot be quickly converted into the practical application in daily life due to a large amount of redundant information in daily life.
(3) Most of control modes of virtual hand grasping of many software simulation platforms are simple switches or linear control, and the neural compatibility of a control method in the rehabilitation training process is poor, so that the learning effect is slow, and the soft control capability similar to that of human hands is lacked.
(4) At present, perception feedback technologies used by a virtual simulation platform are mostly divided into invasive perception feedback and non-invasive perception feedback. Invasive feedback requires the patient to perform the electrode implantation procedure in advance, which is costly and the electrode array cannot be implanted into the body for a long period of time. Most of the non-invasive sensing feedback adopts a mechanical feedback mode, the feedback is substitute feedback, the lost hand feeling cannot be induced, and an amputee cannot establish a direct upper limb sensing feedback path.
Therefore, those skilled in the art are working to develop a virtual prosthetic hand training platform for upper limb amputation rehabilitation.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, the technical problems to be solved by the present invention are: (1) The virtual simulation platform for upper limb rehabilitation training needs to be established on a simulator based on a real physical engine, and the simulator needs to be capable of simulating physical contact of the real world; (2) The virtual simulation platform needs to be able to restore the prosthetic hand grasping task in the real physical world as much as possible. A virtual copy of a real artificial hand needs to be developed on a virtual simulation platform, and the virtual hand needs to have the compliance characteristic of a human-like hand and can complete the motion control of the human-like hand. The complexity of the real world needs to be considered when a virtual task is designed, so that the skills learned by a patient in a virtual environment can be quickly converted into actual life application; (3) The virtual simulation platform needs to be able to help the amputee restore his upper limb sensory feedback path.
In order to achieve the above purpose, the invention provides a virtual prosthetic hand training platform for upper limb amputation rehabilitation, which is characterized by comprising a virtual prosthetic hand or a virtual prosthetic limb, a control system and a software interface, wherein the virtual prosthetic hand or the virtual prosthetic limb is driven by tendons, and the driving mode is similar to that of a human body;
the control system is configured to simulate a pair of antagonistic muscles having a stretch reflex characteristic using a real-time simulation algorithm;
the software interface is set to input the touch information at the front end of the artificial limb finger into the upper limb sensory channel of the human body to form different touch feelings.
Further, tendon drive of the virtual prosthetic hand is based on tendon drive of real hand structures;
further, the virtual prosthetic hand comprises components, wherein the components are set to be in accordance with the real hand structure of a human body or be in accordance with the self-defining structure of the human body, and the number of the components is 1 or more.
Further, the assembly is configured to induce the sensory feedback information as either actually generated by the patient or as simulated; the assembly is configured to convey haptic information; the finger feeling feedback information is obtained by stimulating a stable finger feeling inducing area of an amputee by a percutaneous nerve electrical stimulation technology to transmit the feeling information or generating the feeling by vibration feedback or directly stimulating a middle nerve or an ulnar nerve area of the stump of the amputee.
Further, the tactile information includes sizes of different objects.
Further, the tactile information includes different softness and hardness.
Further, the haptic information includes slippage information when the virtual prosthetic hand is in contact with an object.
Further, the tactile information includes temperature information of a surface of a finger when the virtual prosthetic hand is in contact with an object.
Further, the tactile information comprises single finger information or a plurality of finger information, and the transmission mode of the tactile information is set to be single channel or multi-channel.
Further, the artificial hand further comprises a virtual body group, wherein the virtual body group comprises 1 or more virtual bodies, the virtual bodies are arranged to be in contact with the artificial hand, and the virtual bodies are arranged to have rigidity and weight based on physical characteristics of real-world objects or adopt idealized virtual models.
Further, the antagonistic muscle is set as any pair of antagonistic muscles of the upper limb, and the initial muscle length of the antagonistic muscle is set based on different muscle types.
The perception feedback technology is organically combined with the virtual simulation platform, a non-invasive transcutaneous nerve electrical stimulation perception feedback method is adopted, pressure information generated by a pressure sensor at the front end of the virtual artificial hand is fed back to an amputee through electrical stimulation coding, and the amputee can feel perception information of different sizes and modes on missing fingers when controlling the virtual artificial hand to finish training of grasping objects.
The invention is realized by the following technical scheme:
the method is technically characterized by comprising a virtual environment based on a physical engine, a virtual artificial hand model, a control method based on biological authenticity and a transcutaneous nerve electrical stimulation technology based on finger induction.
The training platform is based on a real physics engine implementation. A physics engine is a computer software that can provide an approximate physical system based on physical constraints of the real world. The training platform calculates movement by endowing the rigid objects with real physical attributes, simulates rigid body behaviors, has high calculation speed and accurate calculation capacity to calculate interaction when the objects are in contact with each other, and can simulate physical contact of the real world to the maximum extent.
The hand structure of the virtual artificial hand is mainly derived from a virtual modular artificial hand (vMPL) model, ten tendons are added at corresponding positions according to the anatomical structure of hand muscle tissues, and each tendon extends from the forearm to the end of each finger through a fixed anchor point. The palm side and the back side of each joint of the finger are provided with an anchor point which rotates along with the rotation of the joint. The axis of rotation of the joint is parallel to the palm side, so that the virtual prosthetic hand can only perform flexion/extension movements. The whole hand structure of the virtual artificial hand comprises five contact sensors, wherein the five contact sensors are attached to the fingertips of each finger and used for transmitting fingertip pressure when the finger is in contact with an object; fourteen joints, with the thumb having two joints and the other fingers each having three joints; the five tendons are flexor tendons and extensor tendons and are respectively wound on each joint of each finger and pulled under stress; ten force actuators, two for each finger, one to pull the flexor tendons to flex the finger and the other to pull the extensor tendons to stretch the finger.
The control system of the virtual artificial hand adopts a biological real control method and utilizes a computer program capable of achieving real-time calculation to simulate a pair of antagonistic muscles with stretch reflex characteristics. The pair of electromyographic sensors are attached to a pair of antagonistic muscles on the forearm of a human body, and are used for collecting surface electromyographic signals, amplifying and filtering the surface electromyographic signals and further using the surface electromyographic signals as a control signal source of the virtual prosthetic hand. The signal source is used as an alpha movement command and is sent to the muscle model through the motor neuron model to generate output force, meanwhile, the muscle spindle model senses the length change of the muscle at the moment in real time, and the sensory neuron model feeds the length change of the muscle back to the motor neuron model through the synapse model to regulate and control the output force of the muscle model. The muscle output forces generated by the flexor and extensor models act together on the tendons, pulling the various joints of the fingers into flexion/extension movements.
The sensory feedback system utilizes the percutaneous nerve electrical stimulation technology based on finger induction to enable the amputee to generate corresponding sensation. In the software simulation platform, when a testee controls a virtual hand to contact with other virtual objects, a contact sensor at the tail end of a virtual finger generates a pressure signal and sends the pressure signal to an external perception feedback system. The multi-channel multifunctional electrical stimulator in the perception feedback system converts pressure signals into electrical stimulation signals through certain codes, the generated current stimulation is a pulse sequence with two phases, charge balance and cathode priority, the interval between every two pulses is 10 mu s, and the pulse sequences are transmitted to a projected finger area (PFM), so that an amputee can generate corresponding pressure perception of fingers according to the change of the pressure of the finger tips of virtual fingers.
The beneficial technical effects of the invention are as follows:
(1) The virtual simulation platform developed by the invention is based on a real physical engine, can accurately simulate the physical contact of the real world, and is beneficial to the skill conversion from the virtual environment to the real environment after the rehabilitation training.
(2) The virtual simulation platform developed by the invention has the advantages of simulating a real upper limb sensory-motor system of a human, realizing anthropomorphic flexible control and combining a multi-modal sensory feedback channel. Compared with other virtual platforms, the neural compatibility is higher, a user can quickly get on the hand, and a training task with higher difficulty can be completed.
(3) The invention keeps the same control mechanism and perception capability as the real artificial hand, and the skill of the patient learned in the virtual environment can be directly applied to the real artificial hand.
(4) The invention is used as a rehabilitation training platform for the upper limbs of amputated patients, provides rich training environment, can carry out personalized training and customization, and can improve the interestingness and the participation of users. Meanwhile, a repeatable and high-stability environment can be provided for the functional verification during the design of the prosthetic hand.
Drawings
FIG. 1 is a block diagram of a prosthetic hand in a virtual environment;
FIG. 2 shows an entire virtual simulation platform;
fig. 3 is a signal flow diagram of a perceptual feedback system.
Detailed Description
The technical contents of the preferred embodiments of the present invention will be more clearly and easily understood by referring to the drawings attached to the specification. The present invention may be embodied in many different forms of embodiments and the scope of the invention is not limited to the embodiments set forth herein.
In the drawings, structurally identical elements are represented by like reference numerals, and structurally or functionally similar elements are represented by like reference numerals throughout the several views. The size and thickness of each component shown in the drawings are arbitrarily illustrated, and the present invention is not limited to the size and thickness of each component. The thickness of the components may be exaggerated where appropriate in the figures to improve clarity.
Example 1
The invention provides a virtual prosthetic hand training platform for rehabilitation of upper limb amputation.
FIG. 1 is a block diagram of a prosthetic hand in a virtual environment. As shown in fig. 1, the virtual prosthetic hand is driven by tendons, and has fourteen joints, ten tendons, and five contact sensors between fingers.
Fig. 2 shows the whole virtual simulation platform, a pair of simulated muscles is driven by an alpha motion command to generate muscle output force, and tendons of the virtual prosthetic hand are pulled to control the prosthetic hand to grasp an object. When the finger is in contact with an object, the pressure sensor at the tail end of the finger of the artificial limb hand senses the pressure applied to the finger, and the pressure information is transmitted to the amputee through the sensory feedback system in a percutaneous nerve electrical stimulation mode.
Fig. 3 is a signal flow diagram of a perceptual feedback system. The sensor at the end of the finger generates a pressure signal, and then generates an electrical stimulation to send to the amputee through a series of sensory modality codes.
The invention is realized based on a real physical engine, wherein the physical engine is computer software and can provide an approximate physical system according to physical constraints of the real world. The platform calculates movement by endowing rigid objects with real physical attributes, simulates rigid body behaviors, has high calculation speed and accurate calculation capacity to calculate interaction when the objects are in contact with each other, and can simulate physical contact of the real world to the maximum extent.
The hand structure of the virtual artificial hand is mainly derived from a virtual modular artificial hand (vMPL) model, and ten tendons are added at corresponding positions according to the anatomical structure of hand muscle tissues, wherein each tendon extends from the forearm to the tail end of each finger through a fixed anchor point. The palm side and the back side of each joint of the finger are provided with an anchor point which rotates along with the rotation of the joint. The axis of rotation of the joint is parallel to the palm side, so that the virtual prosthetic hand can only perform flexion/extension movements. The whole hand structure of the virtual artificial hand comprises five contact sensors, and the five contact sensors are attached to the fingertips of each finger and used for transmitting fingertip pressure when the finger is in contact with an object; fourteen joints, with the thumb having two joints and the other fingers each having three joints; the ten tendons, five flexor tendons and five extensor tendons are wound on each joint of each finger respectively and can be pulled under stress; ten force actuators, two for each finger, one to pull the flexor tendons to flex the finger and the other to pull the extensor tendons to extend the finger.
The control system adopts a biological real control method and utilizes a computer algorithm which can complete calculation in real time to simulate a pair of antagonistic muscles with the stretch reflex characteristics. The pair of electromyographic sensors are attached to a pair of antagonistic muscles on the forearm of a human body, and are used for collecting surface electromyographic signals, amplifying and filtering the surface electromyographic signals and further using the surface electromyographic signals as a control signal source of the virtual prosthetic hand. The signal source is used as an alpha motion command and is sent to the muscle model through the motor neuron model to generate output force, meanwhile, the muscle spindle model senses the length change of the muscle at the moment in real time, and the sensory neuron model feeds the length change of the muscle back to the motor neuron model through the synapse model to regulate and control the output force of the muscle model. The muscle output forces generated by the flexor and extensor models act together on the tendons, pulling the various joints of the fingers into flexion/extension movements.
The sensory feedback system utilizes the percutaneous nerve electrical stimulation technology based on finger induction to enable the amputee to generate corresponding sensation. In the software simulation platform, when a testee controls a virtual hand to contact with other virtual objects, a contact sensor at the tail end of a virtual finger generates a pressure signal and sends the pressure signal to an external perception feedback system. The multi-channel multifunctional electric stimulator in the perception feedback system converts pressure signals into electric stimulation signals through certain codes, the generated current stimulation is a pulse sequence with double phases, charge balance and cathode priority, the interval between every two pulses is 10 mu s, and the pulses are transmitted to a projected finger area (PFM), so that an amputee can generate corresponding pressure perception of fingers according to the change of the pressure of the fingertips of virtual fingers.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the prior art according to the concepts of the present invention should be within the scope of protection determined by the claims.
Claims (10)
1. A virtual prosthetic hand training platform for upper limb amputation rehabilitation is characterized by comprising a virtual prosthetic hand or a virtual prosthetic limb, a control system and a software interface, wherein the virtual prosthetic hand or the virtual prosthetic limb is driven by tendons in a similar way as a human body;
the control system is configured to simulate a pair of antagonistic muscles having a stretch reflex feature using a real-time simulation algorithm;
the software interface is set to input the touch information at the front end of the artificial limb finger into the upper limb sensory channel of the human body to form different touch feelings.
2. A virtual prosthetic hand training platform for upper limb amputation rehabilitation according to claim 1, wherein the tendon drive of the virtual prosthetic hand is based on the tendon drive of the real hand structure; the virtual artificial limb comprises components, wherein the components are set to be in accordance with the real hand structure of a human body or set to be in accordance with the self-defined structure of the human body, and the number of the components is 1 or more.
3. A virtual prosthetic hand training platform for upper limb amputation rehabilitation according to claim 2, wherein the assembly is configured such that the evoked sensory feedback information is either truly patient-generated or simulation-generated; the assembly is configured to convey haptic information.
4. A virtual prosthetic hand training platform for rehabilitation of upper extremity amputations as claimed in claim 3, wherein the haptic information includes the size of different objects.
5. The virtual prosthetic hand training platform for rehabilitation of upper extremity amputations according to claim 3, wherein the haptic information includes different degrees of softness.
6. The virtual prosthetic hand training platform for upper limb amputation rehabilitation according to claim 3, wherein the tactile information includes slippage information when the virtual prosthetic hand is in contact with an object.
7. The virtual prosthetic hand training platform for upper limb amputation rehabilitation according to claim 3, wherein the tactile information includes temperature information of a surface of a finger when the virtual prosthetic hand is in contact with an object.
8. A virtual prosthetic hand training platform for rehabilitation of upper limb amputation according to claim 3, characterized in that the tactile information comprises single finger information or multiple finger information, and the tactile information is transmitted in a single channel or multiple channels.
9. The virtual prosthetic hand training platform for upper limb amputation rehabilitation according to claim 1, further comprising a virtual body set comprising 1 or more virtual bodies, the virtual bodies being configured to be in contact with the prosthetic hand, the virtual bodies being configured to have a stiffness, a weight based on physical characteristics of real world objects or to employ an idealized virtual model.
10. A virtual prosthetic hand training platform for upper limb amputation rehabilitation according to claim 1, wherein the antagonistic muscle is set as any pair of antagonistic muscles of the upper limb, the initial muscle length of the antagonistic muscle being set based on different muscle types.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211062661.8A CN115317206A (en) | 2022-09-01 | 2022-09-01 | Virtual prosthetic hand training platform for upper limb amputation rehabilitation |
Applications Claiming Priority (1)
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| CN202211062661.8A CN115317206A (en) | 2022-09-01 | 2022-09-01 | Virtual prosthetic hand training platform for upper limb amputation rehabilitation |
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