CN114768199A - Rehabilitation training method, system and storage medium - Google Patents
Rehabilitation training method, system and storage medium Download PDFInfo
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B23/00—Exercising apparatus specially adapted for particular parts of the body
- A63B23/035—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously
- A63B23/12—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for upper limbs or related muscles, e.g. chest, upper back or shoulder muscles
- A63B23/16—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for upper limbs or related muscles, e.g. chest, upper back or shoulder muscles for hands or fingers
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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
- 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
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Abstract
The application discloses a rehabilitation training method, a rehabilitation training system and a storage medium, and relates to the technical field of medical treatment, wherein the method comprises the following steps: acquiring a first motion parameter from a hand rehabilitation training device; acquiring a threshold range corresponding to the first motion parameter according to the first motion parameter; and determining a training mode corresponding to the hand rehabilitation training device according to the threshold range, and controlling the hand rehabilitation training device to execute the training mode. The rehabilitation training method can match scientific and reasonable training modes according to the hand function state, and meets the rehabilitation training requirements of patients.
Description
Technical Field
The present application relates to the field of medical technology, and in particular, to a rehabilitation training method, a rehabilitation training system, and a storage medium.
Background
The cerebral apoplexy is a common cerebrovascular disease, the elderly population is high-incidence, clinical findings show that more than 75% of cerebral apoplexy patients are subjected to limb movement dysfunction with different degrees, the life quality of the patients is seriously influenced, and the cerebral apoplexy patients with hemiplegia can gradually recover part of the movement function with the help of rehabilitation treatment, so that the self-care of life and the return to families and society are realized. However, the recovery of the upper limb function, especially the hand function, of the stroke hemiplegia patients is slow, and the recovery of the upper limb function is an important factor for determining the life quality and the life independence of the stroke hemiplegia patients.
The traditional hand function rehabilitation training is usually completed by one-to-one patient assistance of medical staff, so that the requirement on the medical staff is large, meanwhile, the dependence of the patient on the medical staff is strong, the training process is monotonous and tedious, and the movement enthusiasm of the patient is not high. The existing glove for recovering hand function has single function and is difficult to meet the requirement of the recovery training of patients.
Disclosure of Invention
The present application is directed to solving at least one of the problems in the prior art. Therefore, the rehabilitation training method, the rehabilitation training system and the storage medium are provided, scientific and reasonable rehabilitation training modes can be matched according to the hand function states, and the rehabilitation training requirements of patients are met.
In order to solve the technical problems, the invention provides the following technical scheme:
an embodiment of a first aspect of the present application provides a rehabilitation training method applied to a rehabilitation training system, where the rehabilitation training system is in communication with a hand rehabilitation training device, and the method includes:
acquiring first motion parameters from the hand rehabilitation training device, wherein the first motion parameters comprise a first finger motion angle, a first finger separation angle, a first finger motion speed and first finger tip pressure data;
obtaining a threshold range corresponding to the first motion parameter according to the first motion parameter, wherein the threshold range comprises a first threshold range, a second threshold range and a third threshold range;
and determining a training mode corresponding to the hand rehabilitation training device according to the threshold range, and controlling the hand rehabilitation training device to execute the training mode, wherein the training mode comprises a passive training mode, an assisted training mode and an active training mode.
The rehabilitation training method according to the embodiment of the first aspect of the application has at least the following beneficial effects: the rehabilitation training system comprehensively evaluates the hand function state of a patient by acquiring the first motion parameter of the hand rehabilitation training device and judging the threshold range to which the first motion parameter belongs according to the finger motion angle, the finger separation angle, the finger motion speed and the pressure of the finger end of the patient, and determines a training mode suitable for the patient according to the hand function state of the patient so as to meet the rehabilitation training requirement of the patient through the hand rehabilitation training device; meanwhile, the selected training mode is executed by controlling the hand rehabilitation training device, so that the patient can perform rehabilitation training along with the hand rehabilitation training device, and the problem of insufficient medical staff is effectively solved.
According to some embodiments of the first aspect of the present application, the hand rehabilitation training device includes a driving part, a traction type exoskeleton structure, a plurality of pressure sensors, and a plurality of angle sensors, wherein the driving part is electrically connected to the traction type exoskeleton structure, the traction type exoskeleton structure includes a palm structure, five connecting structures, and five finger moving structures, and the palm structure is movably connected to the corresponding finger moving structures through the five connecting structures; the pressure sensor is arranged on the finger moving structure, and the angle sensor is arranged on the connecting structure;
prior to the acquiring the first motion parameter from the hand rehabilitation training device, comprising:
driving the traction type exoskeleton structure to move through the driving part, so that the pressure sensor acquires first pressure data of the finger end, and the angle sensor acquires a first movement angle of the finger, a first separation angle of the finger and a first movement speed of the finger;
the finger tip first pressure data are sent to the rehabilitation training system through the pressure sensor, and the finger first motion angle, the finger first separation angle and the finger first motion speed are sent to the rehabilitation training system through the angle sensor.
According to some embodiments of the first aspect of the present application, the first threshold range comprises at least one of: the finger first motion angle is smaller than or equal to a finger first motion angle threshold, the finger first separation angle is smaller than or equal to a finger first separation angle threshold, the finger first motion speed is smaller than or equal to a finger first motion speed threshold, and the finger end first pressure data is smaller than or equal to a finger end first pressure data threshold; and the number of the first and second groups,
the second threshold range includes at least one of: the finger first motion angle is greater than the finger first motion angle threshold and less than or equal to a finger second motion angle threshold, the finger first separation angle is greater than the finger first separation angle threshold and less than or equal to a finger second separation angle threshold, the finger first motion speed is greater than the finger first motion speed threshold and less than or equal to a finger second motion speed threshold, the finger end first pressure data is greater than the finger end first pressure data threshold and less than or equal to a finger end second pressure data threshold; and (c) a second step of,
the third threshold range includes at least one of: the first finger movement angle is larger than the second finger movement angle threshold and smaller than or equal to a third finger movement angle threshold, the first finger separation angle is larger than the second finger separation angle threshold and smaller than or equal to a third finger separation angle threshold, the first finger movement speed is larger than the second finger movement speed threshold and smaller than or equal to a third finger movement speed threshold, and the first finger end pressure data is larger than the second finger end pressure data threshold and smaller than or equal to a third finger end pressure data threshold.
According to some embodiments of the first aspect of the present application, the determining, according to the threshold range, a training mode corresponding to the hand rehabilitation training device, and controlling the hand rehabilitation training device to execute the training mode include one of:
determining a training mode corresponding to the hand rehabilitation training device as the passive training mode according to the first threshold range, and controlling the hand rehabilitation training device to execute the passive training mode; alternatively, the first and second electrodes may be,
determining a training mode corresponding to the hand rehabilitation training device as the assisted training mode according to the second threshold range, and controlling the hand rehabilitation training device to execute the assisted training mode; alternatively, the first and second electrodes may be,
and determining a training mode corresponding to the hand rehabilitation training device as the active training mode according to the third threshold range, and controlling the hand rehabilitation training device to execute the active training mode.
Some embodiments according to the first aspect of the present application are characterized in that each of the training patterns corresponds to a maximum finger movement range, a minimum finger movement range, a maximum upper finger pressure data and a maximum lower finger pressure data.
According to some embodiments of the first aspect of the present application, the virtual reality system further comprises a plurality of virtual reality scene modes, each of the training modes corresponds to the virtual reality scene mode, and each of the virtual reality scene modes corresponds to a virtual reality scene and a training time.
According to some embodiments of the first aspect of the application, the method further comprises:
acquiring second motion parameters from the hand rehabilitation training device, wherein the second motion parameters comprise a second finger motion angle, a second finger separation angle, a second finger motion speed and second finger tip pressure data;
comparing the difference value of the second motion parameter with the corresponding first motion parameter to obtain motion parameter comparison data;
and obtaining a training result corresponding to the hand rehabilitation training device according to the motion parameter comparison data.
According to some embodiments of the first aspect of the present application, the comparing the difference between the second motion parameter and the corresponding first motion parameter to obtain motion parameter comparison data comprises at least one of:
calculating the difference value of the second motion angle of the finger and the first motion angle of the finger to obtain first motion parameter comparison data; alternatively, the first and second liquid crystal display panels may be,
calculating a difference value between the second finger separation angle and the first finger separation angle to obtain second motion parameter comparison data; alternatively, the first and second electrodes may be,
calculating the difference value of the second movement speed of the finger and the first movement speed of the finger to obtain third movement parameter comparison data; alternatively, the first and second electrodes may be,
calculating the difference value of the second pressure data of the finger tip and the first pressure data of the finger tip to obtain fourth motion parameter comparison data;
wherein the motion parameter comparison data comprises the first motion parameter comparison data, the second motion parameter comparison data, the third motion parameter comparison data, and the fourth motion parameter comparison data.
An embodiment of a second aspect of the present application provides a simulation system of a hand rehabilitation training device, including:
at least one memory;
at least one processor;
at least one program;
the programs are stored in the memory, and the processor executes at least one of the programs to implement:
a rehabilitation training method according to any of the first aspect of the present application.
In a third aspect, embodiments of the present application provide a computer-readable storage medium, which stores computer-executable signals for performing:
a rehabilitation training method according to any of the first aspect of the present application.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
Additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic structural view of a hand rehabilitation training device according to some embodiments of the present application;
FIG. 2 is a flow chart of a rehabilitation training method provided by some embodiments of the present application;
FIG. 3 is a flow chart of a method of rehabilitation training provided by some embodiments of the present application for obtaining a first motion parameter;
fig. 4 is a flowchart of a rehabilitation training method provided in some embodiments of the present application for obtaining a training result corresponding to a hand rehabilitation training device;
fig. 5 is a block diagram of a rehabilitation training simulation system according to some embodiments of the present application.
Reference numerals: a traction exoskeleton structure 100; a palm structure 110; a finger activity structure 120; a pressure sensor 130; an angle sensor 140; a connecting structure 150; a processor 200; a memory 300.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
It should be noted that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different from that in the flowcharts. The terms and the like in the description and the claims, as well as in the drawings described above, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
In the description of the present application, if there are first and second described only for the purpose of distinguishing technical features, it is not understood that relative importance is indicated or implied or that the number of indicated technical features or the precedence of the indicated technical features is implicitly indicated or implied.
In the description of the present application, unless otherwise specifically limited, terms such as set, installed, connected and the like should be understood broadly, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present application in combination with the specific contents of the technical solutions.
Referring to fig. 2, in a first aspect, the present application provides a rehabilitation training method, including but not limited to steps S110, S120, and S130.
Step S110, acquiring first motion parameters from a hand rehabilitation training device, wherein the first motion parameters comprise a first finger motion angle, a first finger separation angle, a first finger motion speed and first finger tip pressure data;
step S120, obtaining a threshold range corresponding to the first motion parameter according to the first motion parameter, wherein the threshold range comprises a first threshold range, a second threshold range and a third threshold range;
and S130, determining a training mode corresponding to the hand rehabilitation training device according to the threshold range, and controlling the hand rehabilitation training device to execute the training mode, wherein the training mode comprises a passive training mode, an assisted training mode and an active training mode.
It can be understood that the rehabilitation training method is applied to a rehabilitation training system, and the rehabilitation training system is communicated with the hand rehabilitation training device.
According to an embodiment of the application, for conveniently observing the hand functional state of a patient, the hand rehabilitation training device of the application is provided with a plurality of monitoring nodes, each monitoring node is provided with a sensor component such as a pressure sensor 130 or an angle sensor 140, and the monitoring nodes correspond to the pressure sensors 130 or the angle sensors 140 one to one so as to measure various motion parameters of the hand of the patient in real time and accurately evaluate the hand functional state of the patient. Since the individual patient has lost the motion ability of the autonomously active hand, the hand of the patient needs to be used with the hand rehabilitation training device in the process of simulating the functional state of the hand of the patient, and then the driving means, such as the electrodes, are needed to drive the pull-type exoskeleton structure 100 of the hand rehabilitation training device to move, so as to acquire the first motion parameter through the pressure sensor 130 and the angle sensor 140 on the pull-type exoskeleton structure 100. The first motion parameters comprise a first motion angle of the fingers, a first separation angle of the fingers, a first motion speed of the fingers and first pressure data of the finger tips, the first motion angle of the fingers refers to the motion angle of the fingers of a patient relative to a palm, the first separation angle of the fingers refers to the motion angle of a single finger of the patient relative to other fingers, the first motion speed of the fingers refers to the motion speed of the fingers of the patient in motion, and the first pressure data of the finger tips refers to pressure values of the upper finger tips and the lower finger tips of the patient. After the sensor part collects the first motion parameters, the first motion parameters are sent to a rehabilitation training system for controlling the hand rehabilitation training device, so that the rehabilitation training system can store the first motion parameters conveniently and judge the current hand function state of the patient.
Specifically, after the rehabilitation training system stores the first motion parameter, the threshold range corresponding to the first motion parameter needs to be determined, in order to accurately determine the current hand function state of the patient, subsequent rehabilitation training is facilitated, and the rehabilitation training system sets the first motion parameter related to the first threshold range, the second threshold range and the third threshold range from low to high. If the first motion parameter of the patient belongs to the first threshold range, the patient is currently in a flaccid paralysis stage, the hand function capability of the patient in the flaccid paralysis stage is poor, the patient basically has no automatic motion capability, the hand muscle strength is weak, and the serious patient has complete muscle weakness; if the first motion parameter of the patient belongs to the second threshold range, the patient is currently in a spastic period or early recovery period, and the muscle strength of the patient in the spastic period or early recovery period is lower; if the first motion parameter of the patient belongs to the third threshold range, the patient is currently in the middle recovery period or the later recovery period, and the patient in the middle recovery period or the later recovery period has certain automatic motion capability and coordination. After the rehabilitation training system judges the current hand function state of the patient, the training mode corresponding to the hand rehabilitation training device is selected according to the current hand function state of the patient, and the hand rehabilitation training device is controlled to execute the selected training mode.
Referring to fig. 1, fig. 1 is a schematic structural view of a hand rehabilitation training device according to some embodiments of the present application; it can be understood that the hand rehabilitation training device comprises driving parts, a traction type exoskeleton structure 100, a plurality of pressure sensors 130 and a plurality of angle sensors 140, wherein the driving parts are electrically connected with the traction type exoskeleton structure 100, the traction type exoskeleton structure 100 comprises a palm structure 110, five connecting structures 150 and five finger moving structures 120, and the palm structure 110 is movably connected with the corresponding finger moving structures 120 through the five connecting structures 150; the pressure sensor 130 is arranged on the finger moving structure 120, and the angle sensor 140 is arranged on the connecting structure 150;
referring to fig. 3, the present application provides a method for obtaining a first motion parameter in a rehabilitation training method, and before step S110, the method further includes, but is not limited to, steps S210 and S220.
Step S210, driving the traction type exoskeleton structure to move through the driving part, enabling the pressure sensor to acquire first pressure data of a finger end, and enabling the angle sensor to acquire a first movement angle of a finger, a first separation angle of the finger and a first movement speed of the finger;
step S220, the first pressure data of the finger tip is sent to the rehabilitation training system through the pressure sensor, and the first motion angle of the finger, the first separation data of the finger and the first motion speed of the finger are sent to the rehabilitation training system through the angle sensor.
It is understood that before the first motion parameters from the hand rehabilitation training device are acquired, the method comprises the following steps: the traction type exoskeleton structure 100 is driven to move through the driving parts, so that the pressure sensor 130 acquires first pressure data of a finger end, and the angle sensor 140 acquires a first movement angle, a first separation angle and a first movement speed of the finger; the finger tip first pressure data is transmitted to the rehabilitation training system through the pressure sensor 130 and the finger first movement angle, the finger first separation angle and the finger first movement speed are transmitted to the rehabilitation training system through the angle sensor 140.
It should be noted that the hand rehabilitation training device of the present application includes a driving part and a pull-type exoskeleton structure 100, the driving part is electrically connected to the pull-type exoskeleton structure 100, and the pull-type exoskeleton structure 100 simulates a structure of a hand of a human body, wherein the pull-type exoskeleton structure 100 includes a palm structure 110 and a finger activity structure 120, the palm structure 110 simulates a shape of a palm of the human body, and the finger activity structure 120 simulates a shape of a finger of the human body, so that the hand rehabilitation training device of the present application is more suitable for a hand of a patient, and can facilitate rehabilitation training of the patient and improve use experience of the patient. Palm structure 110 and finger active structure 120 are connected by a plurality of connection structure 150 between, are equipped with a plurality of angle sensor 140 on the connection structure 150, and when the patient trained in the hand rehabilitation training device who uses this application, angle sensor 140 was used for gathering the first motion angle of finger, finger second motion angle data, the first separation angle of finger, finger second separation angle data, the first motion speed of finger and finger second motion speed data. The finger activity structure 120 is provided with a plurality of pressure sensors 130, and when the patient is trained, the pressure sensors 130 are used for collecting first pressure data of the finger tip and second pressure data of the finger tip.
Referring to fig. 4, the embodiment of the present application provides a method for obtaining a training result by a rehabilitation training method, and after step S130, the method includes, but is not limited to, steps S310, S320, and S330.
Step S310, acquiring second motion parameters from the hand rehabilitation training device, wherein the second motion parameters comprise a second finger motion angle, a second finger separation angle, a second finger motion speed and second finger end pressure data;
step S320, comparing the difference value between the second motion parameter and the corresponding first motion parameter to obtain motion parameter comparison data;
and step S330, obtaining a training result corresponding to the hand rehabilitation training device according to the motion parameter comparison data.
According to an embodiment of the present application, after the hand rehabilitation training device formally starts training, the pressure sensor 130 and the angle sensor 140 obtain the second motion parameters again, where the second motion parameters include the second finger motion angle, the second finger separation angle, the second finger motion speed, and the second finger tip pressure data, that is, the finger motion angle, the finger separation angle, the finger motion speed, and the finger tip pressure data of the patient in the current state. After the pressure sensor 130 and the angle sensor 140 collect the second motion parameter, the second motion parameter is sent to the rehabilitation training system for controlling the hand function device. Specifically, the rehabilitation training system stores a second motion parameter, calculates a difference value between the first motion parameter and the second motion parameter by combining the stored first motion parameter to obtain motion parameter comparison data, observes and evaluates a training result of the hand function of the patient according to the motion parameter comparison data, analyzes the first motion parameter and the second motion parameter to obtain a trend of the hand function change of the patient, and analyzes the rationality and effectiveness of a training mode and a treatment plan according to the trend of the hand function change of the patient.
It is understood that comparing the difference between the second motion parameter and the corresponding first motion parameter results in motion parameter comparison data, including at least one of:
calculating the difference value of the second motion angle of the finger and the first motion angle of the finger to obtain first motion parameter comparison data; alternatively, the first and second electrodes may be,
calculating the difference value of the second separation angle of the finger and the first separation angle of the finger to obtain second motion parameter comparison data; alternatively, the first and second electrodes may be,
calculating the difference value of the second movement speed of the finger and the first movement speed of the finger to obtain third movement parameter comparison data; alternatively, the first and second electrodes may be,
calculating the difference value of the second pressure data of the finger end and the first pressure data of the finger end to obtain fourth motion parameter comparison data; the motion parameter comparison data comprises first motion parameter comparison data, second motion parameter comparison data, third motion parameter comparison data and fourth motion parameter comparison data.
It should be noted that the first motion parameter includes a first motion angle of the finger, a first separation angle of the finger, a first motion speed of the finger, and a first pressure data of the finger tip, and the second motion parameter includes a second motion angle of the finger, a second separation angle of the finger, a second motion speed of the finger, and a second pressure data of the finger tip, so that the difference between the first motion parameter and the second motion parameter includes a first motion parameter comparison data, a second motion parameter comparison data, a third motion parameter comparison data, and a fourth motion parameter comparison data. And the rehabilitation training system evaluates the rehabilitation training effect of the patient according to the motion parameter comparison data, and if the first motion parameter comparison data, the second motion parameter comparison data, the third motion parameter comparison data and the fourth motion parameter comparison data are all larger than zero, the hand function of the patient is gradually recovered.
Specifically, when a patient trains by using the hand rehabilitation training device, the patient fixes the affected hand on the traction-type exoskeleton structure 100, the driving part drives the traction-type exoskeleton structure 100 to enable the affected hand of the patient to be drawn by the traction-type exoskeleton structure 100 to train, in the training process, the angle sensor 140 and the pressure sensor 130 collect first motion parameters or second motion parameters, and after the collection is completed, the angle sensor 140 and the pressure sensor 130 send the first motion parameters or the second motion parameters to the rehabilitation training system, so that the rehabilitation training system can conveniently detect the hand function state of the patient in real time.
It can be understood that the rehabilitation training system obtains a threshold range corresponding to the first motion parameter according to the first motion parameter, where the threshold range includes a first threshold range, a second threshold range, and a third threshold range, and the first threshold range includes at least one of the following: the first finger movement angle is smaller than or equal to a first finger movement angle threshold, the first finger separation angle is smaller than or equal to a first finger separation angle threshold, the first finger movement speed is smaller than or equal to a first finger movement speed threshold, and the first finger tip pressure data is smaller than or equal to a first finger tip pressure data threshold; and the number of the first and second groups,
the second threshold range includes at least one of: the first finger movement angle is larger than the first finger movement angle threshold and smaller than or equal to the second finger movement angle threshold, the first finger separation angle is larger than the first finger separation angle threshold and smaller than or equal to the second finger separation angle threshold, the first finger movement speed is larger than the first finger movement speed threshold and smaller than or equal to the second finger movement speed threshold, and the first finger end pressure data is larger than the first finger end pressure data threshold and smaller than or equal to the second finger end pressure data threshold; and (c) a second step of,
the third threshold range includes at least one of: the first finger movement angle is larger than the second finger movement angle threshold and smaller than or equal to the third finger movement angle threshold, the first finger separation angle is larger than the second finger separation angle threshold and smaller than or equal to the third finger separation angle threshold, the first finger movement speed is larger than the second finger movement speed threshold and smaller than or equal to the third finger movement speed threshold, and the first finger end pressure data is larger than the second finger end pressure data threshold and smaller than or equal to the third finger end pressure data threshold.
It should be noted that the rehabilitation training system sets the first motion parameter related to the first threshold range, the second threshold range and the third threshold range from low to high.
According to one embodiment of the present application, when at least one of the following is satisfied: the first motion angle of the finger is smaller than or equal to a first motion angle threshold of the finger, the first separation angle of the finger is smaller than or equal to a first separation angle threshold of the finger, the first motion speed of the finger is smaller than or equal to a first motion speed threshold of the finger, the first pressure data of the finger end is smaller than or equal to a first pressure data threshold of the finger end, the first motion parameter belongs to a first threshold range, and the rehabilitation training system judges that the patient is in the soft paralysis stage.
When at least one of the following is satisfied: the first motion angle of the finger is larger than a first motion angle threshold of the finger and smaller than or equal to a second motion angle data threshold of the finger, the first separation angle of the finger is larger than a first separation angle threshold of the finger and smaller than or equal to a second separation angle data threshold of the finger, the first motion speed of the finger is larger than a first motion speed threshold of the finger and smaller than or equal to a second motion speed data threshold of the finger, the first pressure data of the finger end is larger than a first pressure data threshold of the finger end and smaller than or equal to a second pressure data threshold of the finger end, the first motion parameter belongs to a second threshold range, and the rehabilitation training system judges that the patient is in a spasm stage or an early stage of paralysis/early stage of recovery.
When at least one of the following is satisfied: the first motion angle of the finger is larger than the data threshold of the second motion angle of the finger and smaller than or equal to the data threshold of the third motion angle of the finger, the first separation angle of the finger is larger than the data threshold of the second separation angle of the finger and smaller than or equal to the data threshold of the third separation angle of the finger, the first motion speed of the finger is larger than the data threshold of the second motion speed of the finger and smaller than or equal to the data threshold of the third motion speed of the finger, the first pressure data of the finger end is larger than the data threshold of the second pressure data of the finger end and smaller than or equal to the data threshold of the third pressure data of the finger end, the first motion parameter belongs to the range of the third threshold, and the rehabilitation training system judges that the patient is in the middle or later recovery period.
According to an embodiment of the application, when the first motion angle of the finger is smaller than or equal to the first motion angle threshold of the finger, the first separation angle of the finger is larger than the first separation angle threshold of the finger, the first motion speed of the finger is larger than the first motion speed threshold of the finger, and the first pressure data of the finger tip is larger than the first pressure data threshold of the finger tip, it is still determined that the first motion parameter belongs to the first threshold range at this time, and the patient is still in the soft paralysis stage until the first motion angle of the finger is larger than the first motion angle threshold of the finger.
It can be understood that, according to the threshold range, the training mode corresponding to the hand rehabilitation training device is determined, and the hand rehabilitation training device is controlled to execute the training mode, which includes one of the following: determining that a training mode corresponding to the hand rehabilitation training device is a passive training mode according to the first threshold range, and controlling the hand rehabilitation training device to execute the passive training mode; alternatively, the first and second electrodes may be,
determining a training mode corresponding to the hand rehabilitation training device as an assisted training mode according to the second threshold range, and controlling the hand rehabilitation training device to execute the assisted training mode; alternatively, the first and second liquid crystal display panels may be,
and determining the training mode corresponding to the hand rehabilitation training device as an active training mode according to the third threshold range, and controlling the hand rehabilitation training device to execute the active training mode.
According to an embodiment of the present application, when the rehabilitation training system determines that the first motion parameter falls within the first threshold range, the patient is in a flaccid paralysis period. Because the functional ability of the hands of the patient in the flaccid paralysis period is poor, the patient basically has no active motor ability, the muscle strength of the hands is weak, and the serious patient has no complete muscle weakness, the passive training mode is selected by the rehabilitation training system, and the rehabilitation training system controls the hand rehabilitation training device to execute the passive training mode so as to perform rehabilitation training on the patient. It can be understood that the passive training mode is that the hand of the patient moves under the driving of the traction-type exoskeleton structure 100 during training, and the traction-type exoskeleton structure 100 trains the patient according to the parameters set in the passive training mode and the selected corresponding virtual reality scene mode.
When the rehabilitation training system judges that the first motion parameter belongs to the second threshold range, the patient is in a spasm stage or in an early recovery stage, the rehabilitation training system selects the assisted training mode because the muscle strength of the patient in the spasm stage or in the early recovery stage is low, and the rehabilitation training system controls the hand rehabilitation training device to execute the assisted training mode to perform rehabilitation training on the patient. It can be understood that the assisted training mode is that the hand of the patient still needs to move with the assistance of the traction-type exoskeleton structure 100 during training, and the traction-type exoskeleton structure 100 trains the patient according to the parameters set in the assisted training mode and the selected corresponding virtual reality scene mode.
When the rehabilitation training system judges that the first motion parameter belongs to the third threshold range, the patient is in the middle stage of recovery or in the later stage of recovery at the moment, and the patient in the middle stage of recovery or in the later stage of recovery has certain autonomous motion capability and coordination, so that the subjective consciousness of the patient is strong, the rehabilitation training system selects an active training mode, and the rehabilitation training system controls the hand rehabilitation training device to execute the active training mode to perform rehabilitation training on the patient. It can be understood that the active training mode is that the traction-type exoskeleton structure 100 plays an auxiliary role during training, and the traction-type exoskeleton structure 100 trains the patient according to the parameters set in the active training mode and the selected corresponding virtual reality scene mode.
It should be noted that each training mode corresponds to a maximum movement range of the finger, a minimum movement range of the finger, maximum pressure data of the upper finger tip, and maximum pressure data of the lower finger tip. The virtual reality scene training system is characterized by further comprising a plurality of virtual reality scene modes, each training mode corresponds to a virtual reality scene mode, and each virtual reality scene mode corresponds to a virtual reality scene and training time.
According to an embodiment of the present application, the training goal of the passive training mode is to train the hand of the patient to perform a certain degree of flexion and extension movements, so as to increase the muscle strength and muscle tension of the patient, when the hand rehabilitation training device executes the passive training mode, the hand of the patient is driven by the traction-type exoskeleton structure 100 to move, the traction-type exoskeleton structure 100 reciprocates between the maximum movement range of the finger and the minimum movement range of the finger according to the maximum movement range of the finger, the minimum movement range of the finger, the maximum pressure data of the upper finger end and the maximum pressure data of the lower finger end set in the passive training mode, and the value of each training period is fixed. Meanwhile, the passive training mode has a corresponding virtual reality scene mode, each virtual reality scene mode has a corresponding virtual reality scene and training time, and a patient trains in the virtual reality scene in the training process, and repeatedly imagines and simulates to execute by combining with feedback of language, characters, sound effect, rendering special effect and the like, so that the brain feels motion signals to excite.
According to one embodiment of the present application, the training goal of the assisted power training mode is to train the patient's hand to complete the maximum finger movement range, minimum finger movement range, maximum upper finger end pressure data and maximum lower finger end pressure data set for the assisted power training mode under the assistance of the pull-type exoskeleton structure 100. The patient is repeatedly trained to complete the thumb-index finger pinching action and the five-finger grabbing action, and one action is accurately completed through a large amount of exercises. Meanwhile, the patient combines a virtual reality scene mode to continuously observe, imagine and simulate hand movement in training.
According to one embodiment of the present application, a patient performing an active training mode has been able to perform a two-finger pinch, three-finger grab and grip function. As the hand function of the patient is gradually recovered, the virtual reality scene in the virtual reality scene mode in the active training mode has higher challenge and interest, the maximum motion range of the fingers, the minimum motion range of the fingers, the maximum pressure data of the upper finger end and the maximum pressure data of the lower finger end are properly changed, and the training of the motion speed is added to meet the requirements of the patient.
It should be noted that, when the patient considers that the motion parameter in the current training mode is not reasonable, the patient may also actively adjust the motion parameter of the hand rehabilitation training device of the present application, and meanwhile, when the single finger of the patient is not coordinated with other fingers, and the maximum motion range and the minimum motion range of the single finger are both less than or equal to those of other fingers, the hand rehabilitation training device of the present application may also train the single finger.
In a second aspect, referring to fig. 5, an embodiment of the present application provides a simulation system for a hand rehabilitation training device, including:
at least one memory 300;
at least one processor 200;
at least one program;
the programs are stored in the memory 300, and the processor 200 executes at least one program to realize:
a rehabilitation training method as in any one of the embodiments of the first aspect of the present application.
The processor 200 and the memory 300 may be connected by a bus or other means.
The memory 300 is one type of non-transitory readable storage medium that may be used to store non-transitory software instructions as well as non-transitory executable instructions. Further, the memory 300 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. It will be appreciated that the memory 300 may alternatively comprise memory 300 located remotely from the processor 200, and that such remote memory 300 may be coupled to the processor 200 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The processor 200 implements a rehabilitation training method according to the first embodiment by executing non-transitory software instructions, instructions and signals stored in the memory 300 to perform various functional applications and data processing.
The non-transitory software instructions and instructions required to implement the simulation system of a hand rehabilitation training device of the above-described embodiments are stored in the memory 300, and when executed by the processor 200, perform a rehabilitation training method according to the first aspect of the present application, for example, performing the above-described method steps S110 to S130 in fig. 2, method steps S210 to S220 in fig. 3, and method steps S310 to S330 in fig. 4.
In a third aspect, an embodiment of the present application provides a computer-readable storage medium storing computer-executable signals for performing:
a method of rehabilitation training as in any one of the embodiments of the first aspect of the application.
For example, the above-described method steps S110 to S130 in fig. 2, method steps S210 to S220 in fig. 3, and method steps S310 to S330 in fig. 4 are performed.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
From the above description of embodiments, those of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable signals, data structures, instruction modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer-readable signals, data structures, instruction modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as is known to those of ordinary skill in the art.
The embodiments of the present application have been described in detail with reference to the drawings, but the present application is not limited to the embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present application.
Claims (10)
1. A rehabilitation training method applied to a rehabilitation training system in communication with a hand rehabilitation training device, the method comprising:
acquiring first motion parameters from the hand rehabilitation training device, wherein the first motion parameters comprise a first finger motion angle, a first finger separation angle, a first finger motion speed and first finger tip pressure data;
obtaining a threshold range corresponding to the first motion parameter according to the first motion parameter, wherein the threshold range comprises a first threshold range, a second threshold range and a third threshold range;
and determining a training mode corresponding to the hand rehabilitation training device according to the threshold range, and controlling the hand rehabilitation training device to execute the training mode, wherein the training mode comprises a passive training mode, an assisted training mode and an active training mode.
2. The rehabilitation training method of claim 1, wherein the hand rehabilitation training device comprises a driving part, a traction-type exoskeleton structure, a plurality of pressure sensors and a plurality of angle sensors, wherein the driving part is electrically connected with the traction-type exoskeleton structure, the traction-type exoskeleton structure comprises a palm structure, five connecting structures and five finger moving structures, and the palm structure is movably connected with the corresponding finger moving structures through the five connecting structures; the pressure sensor is arranged on the finger moving structure, and the angle sensor is arranged on the connecting structure;
prior to the acquiring the first motion parameter from the hand rehabilitation training device, comprising:
driving the traction type exoskeleton structure to move through the driving part, so that the pressure sensor acquires first pressure data of the finger end, and the angle sensor acquires a first movement angle of the finger, a first separation angle of the finger and a first movement speed of the finger;
the finger tip first pressure data are sent to the rehabilitation training system through the pressure sensor, and the finger first motion angle, the finger first separation angle and the finger first motion speed are sent to the rehabilitation training system through the angle sensor.
3. The rehabilitation training method of claim 1, wherein the first threshold range comprises at least one of: the finger first motion angle is smaller than or equal to a finger first motion angle threshold, the finger first separation angle is smaller than or equal to a finger first separation angle threshold, the finger first motion speed is smaller than or equal to a finger first motion speed threshold, and the finger tip first pressure data is smaller than or equal to a finger tip first pressure data threshold; and (c) a second step of,
the second threshold range includes at least one of: the first finger movement angle is larger than the first finger movement angle threshold and smaller than or equal to a second finger movement angle threshold, the first finger separation angle is larger than the first finger separation angle threshold and smaller than or equal to a second finger separation angle threshold, the first finger movement speed is larger than the first finger movement speed threshold and smaller than or equal to a second finger movement speed threshold, and the first finger end pressure data is larger than the first finger end pressure data threshold and smaller than or equal to a second finger end pressure data threshold; and the number of the first and second groups,
the third threshold range includes at least one of: the first finger movement angle is larger than the second finger movement angle threshold and smaller than or equal to a third finger movement angle threshold, the first finger separation angle is larger than the second finger separation angle threshold and smaller than or equal to a third finger separation angle threshold, the first finger movement speed is larger than the second finger movement speed threshold and smaller than or equal to a third finger movement speed threshold, and the first finger end pressure data is larger than the second finger end pressure data threshold and smaller than or equal to a third finger end pressure data threshold.
4. The rehabilitation training method according to any one of claims 1-3, wherein the determining a training mode corresponding to the hand rehabilitation training device according to the threshold range controls the hand rehabilitation training device to execute the training mode, and the determining includes one of:
determining a training mode corresponding to the hand rehabilitation training device as the passive training mode according to the first threshold range, and controlling the hand rehabilitation training device to execute the passive training mode; alternatively, the first and second electrodes may be,
determining a training mode corresponding to the hand rehabilitation training device as the assisted training mode according to the second threshold range, and controlling the hand rehabilitation training device to execute the assisted training mode; alternatively, the first and second liquid crystal display panels may be,
and determining a training mode corresponding to the hand rehabilitation training device as the active training mode according to the third threshold range, and controlling the hand rehabilitation training device to execute the active training mode.
5. The rehabilitation training method of claim 4, wherein each training mode corresponds to a maximum finger movement range, a minimum finger movement range, maximum upper finger pressure data and maximum lower finger pressure data.
6. The rehabilitation training method according to claim 4, further comprising a plurality of virtual reality scene modes, each of the training modes corresponding to the virtual reality scene mode, each of the virtual reality scene modes corresponding to a virtual reality scene and a training time.
7. The rehabilitation training method according to any one of claims 1 to 3, characterized in that the method further comprises:
acquiring second motion parameters from the hand rehabilitation training device, wherein the second motion parameters comprise a second finger motion angle, a second finger separation angle, a second finger motion speed and second finger tip pressure data;
comparing the difference value of the second motion parameter with the corresponding first motion parameter to obtain motion parameter comparison data;
and obtaining a training result corresponding to the hand rehabilitation training device according to the motion parameter comparison data.
8. The rehabilitation training method of claim 7, wherein the comparing the difference between the second motion parameter and the corresponding first motion parameter to obtain the motion parameter comparison data comprises at least one of:
calculating the difference value of the second finger motion angle and the first finger motion angle to obtain first motion parameter comparison data; alternatively, the first and second electrodes may be,
calculating a difference value between the second finger separation angle and the first finger separation angle to obtain second motion parameter comparison data; alternatively, the first and second liquid crystal display panels may be,
calculating the difference value of the second movement speed of the finger and the first movement speed of the finger to obtain third movement parameter comparison data; alternatively, the first and second electrodes may be,
calculating the difference value of the second pressure data of the finger tip and the first pressure data of the finger tip to obtain fourth motion parameter comparison data;
wherein the athletic parameter comparison data includes the first athletic parameter comparison data, the second athletic parameter comparison data, the third athletic parameter comparison data, and the fourth athletic parameter comparison data.
9. A simulation system of a hand rehabilitation training device, comprising:
at least one memory;
at least one processor;
at least one program;
the programs are stored in the memory, and the processor executes at least one of the programs to implement:
a method of rehabilitation training according to any one of claims 1 to 8.
10. A computer-readable storage medium having computer-executable signals stored thereon for performing:
a method of rehabilitation training according to any one of claims 1 to 8.
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