CN113926160A - Upper limb flexor resistance training auxiliary system for household personnel - Google Patents
Upper limb flexor resistance training auxiliary system for household personnel Download PDFInfo
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- CN113926160A CN113926160A CN202111173997.7A CN202111173997A CN113926160A CN 113926160 A CN113926160 A CN 113926160A CN 202111173997 A CN202111173997 A CN 202111173997A CN 113926160 A CN113926160 A CN 113926160A
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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
- A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
- A63B24/0075—Means for generating exercise programs or schemes, e.g. computerized virtual trainer, e.g. using expert databases
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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
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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
- A63B2208/00—Characteristics or parameters related to the user or player
- A63B2208/02—Characteristics or parameters related to the user or player posture
- A63B2208/0228—Sitting on the buttocks
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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
- A63B2220/00—Measuring of physical parameters relating to sporting activity
- A63B2220/50—Force related parameters
- A63B2220/51—Force
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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
- A63B2230/00—Measuring physiological parameters of the user
- A63B2230/60—Measuring physiological parameters of the user muscle strain, i.e. measured on the user
Abstract
The invention belongs to the field of rehabilitation training, and relates to an upper limb flexor resistance training auxiliary system for household personnel, which integrates muscle function assessment and resistance training auxiliary monitoring; the system comprises a force data acquisition device, a force data processing module, a force data quantification module and a training guidance module; the invention processes the force data acquired by the force data acquisition device through the force data processing module to obtain the duration and rest time of the muscle in different states and corresponding force data; based on the force data, a force data quantification module is adopted to quantify to obtain the force generation capacity and the force retention capacity of the upper limb flexor of the trainer; combining the processing result of the force data processing module and the quantization result of the force data quantization module with an expected training target, and outputting a training guidance result; the invention can accurately depict the muscle strength characteristics of the trainer, combines the training times of the trainer and the expected training target, can accurately output the training guidance result, and improves the effective rate of the training guidance.
Description
Technical Field
The invention relates to the field of rehabilitation training, in particular to an upper limb flexor resistance training auxiliary system integrating muscle function assessment and resistance training auxiliary monitoring.
Background
Resistance exercise, as an effective physical rehabilitation training method, is often recommended by organizations such as the american college of health and exercise and the american heart association for improving the strength of muscles, endurance of muscles, physical functions, and neuromuscular functions of trainers. In addition, the home resistance training is a substitute method for the traditional hospital-based or rehabilitation center-based rehabilitation training, and is receiving attention from more researchers.
However, in the case of home resistance training, it is impossible to determine whether a trainee has completed a prescribed training dose and training action as required without the supervision and guidance of a physical therapist; the lack of objective measures may limit physiotherapists and researchers to objectively assess resistance training effects. Meanwhile, because the actual muscle function, strength and endurance of the trainer are not accurately evaluated, a proper training dosage cannot be selected according to the actual body function condition of the trainer.
The currently common evaluation method mainly adopts subjective bare-handed muscle strength evaluation and objective instrument and equipment measurement. The bare-handed muscle strength assessment method has the advantages that the method basically has no requirements on equipment, but has higher requirements on the experience of an evaluator and the adaptability of the evaluator, the examination result is greatly influenced by subjective factors, and the real muscle strength level of the examinee is difficult to objectively and accurately reflect. The method of measuring by using objective instruments and equipment can be divided into the following steps according to different detection signals:
1. the muscle function of the trainer is indirectly quantified by measuring the muscle strength of the trainer in a certain movement, such as isokinetic muscle strength test, simple instrument test using a gripe dynamometer, a handheld dynamometer and the like, and the like;
2. by measuring the nerve electrophysiological signals generated by the muscles on the body surface or in the body of a trainer in the process of movement, the muscle strength condition of the muscles, the joint muscle activation mode, the conduction speed of motor neurons, the number of movement units and the like are more directly quantified. However, the maximum arm grip reflects only the performance of the evaluated person at a certain moment, and the evaluation of the whole process is lacking. Meanwhile, the constant velocity muscle strength test process needs to keep the constant movement speed of the limbs, so the used equipment is expensive, is commonly used for the muscle function test of athletes, and is not suitable for the muscle function evaluation of household personnel. In addition, although the neuroelectrophysiological signals can reflect the activation state of muscles relatively truly, the correlation between the signal characteristic parameters and the muscle force is unclear, and it is difficult to obtain the activation signals of muscles deep in the body.
In summary, how to design an anti-resistance training auxiliary system capable of accurately evaluating muscle functions in upper limb flexor resistance training of a household person and providing corresponding training feedback is a technical problem to be solved urgently.
Disclosure of Invention
The invention aims to design an upper limb flexor resistance training auxiliary system for household personnel, which is used for realizing the functions of muscle function evaluation and resistance training auxiliary monitoring in upper limb flexor resistance training. The auxiliary monitoring of the household resistance training process is mainly achieved, and a proper resistance training mode and a proper training dosage are given by evaluating the actual physical function of a trainer.
The invention adopts the following technical scheme:
an upper limb flexor resistance training assistance system for a domestic person, the system comprising:
the force data acquisition device is used for acquiring force data of upper limb flexor resistance training of a training person;
the force data processing module is used for carrying out segmentation processing on the acquired force data to obtain training group number, training times and corresponding force data; and obtaining the duration and rest time of the muscle in different states and corresponding force data; the states comprise a concentric contraction state, an isometric contraction state, an eccentric contraction state and a rest state;
the force data quantization module is used for quantizing the force generation capacity and the force retention capacity of the upper limb flexor of the trainer according to the force data of the muscles in the concentric contraction state and the isometric contraction state;
and the training guidance module is used for outputting a training guidance result according to the processing result of the force data processing module and the quantization result of the force data quantization module and in combination with an expected training target.
Furthermore, the force data acquisition device comprises a force sensor elastic belt for upper limb flexor resistance training, the force sensor elastic belt comprises a force sensor, a buckle A, an elastic belt, a buckle B, a handle, a digital-to-analog converter, a control panel and a bolt-provided ring buckle, one end of the force sensor is provided with the buckle A, and the other end of the force sensor is provided with the bolt-provided ring buckle; two ends of the elastic belt are respectively connected with the buckle A and the buckle B, and the handle is fixedly connected with the buckle B; the force sensor outputs a modulus electric signal, the modulus electric signal is converted into a digital signal through a digital-to-analog converter, and the digital signal is transmitted to an upper computer through a control panel.
Further, the force data processing module comprises a repetition number segmentation unit and a force action state segmentation unit;
the repetition frequency segmentation unit adopts a repetition frequency segmentation algorithm, divides the acquired force data into data segments with a plurality of repetition cycles according to the length of the training cycle, and obtains the number of training groups, the training frequency and the corresponding force data;
the force action segmentation unit adopts a muscle force action state segmentation algorithm, in a data segment corresponding to each repetition period, the force data of the data segment is subjected to time derivation to obtain a corresponding force derivative number, and the maximum value and the minimum value of the force derivative number are calculated; and dividing the force data into a concentric contraction stage, an eccentric contraction stage, an isometric contraction stage and a rest stage by taking the maximum value and the minimum value of the force derivative as limiting conditions, and obtaining the force data corresponding to each stage.
Further, the force data quantization module comprises a first quantization unit and a second quantization unit;
the first quantification unit calculates force generation capacity according to the ratio of the acceleration stage time to the deceleration stage time of the concentric contraction state;
the second quantization unit takes the force data in the isometric contraction state as an abscissa and takes the corresponding force derivative as an ordinate, and a force phase diagram is obtained through drawing; the dispersion coefficient of the data points in the force phase diagram is taken as the force retention capability.
Further, the training guidance module comprises a training recommendation unit, a training comparison unit and a training guidance unit;
the training recommendation unit is used for recommending an expected training target matched with the family personnel according to basic information of the family personnel;
the training comparison unit is used for comparing the processing result of the force data processing module and the quantization result of the force data quantization module with the expected training target to determine the difference of training times and the difference of training intensity;
and the training guide unit is used for outputting the training time difference and the training intensity difference.
Compared with the prior art, the invention has the following advantages:
1. the force data acquisition device is connected with the elastic band by using the force sensor, the resistance of the elastic band is measured and uploaded to the upper computer, important information in the force data is obtained through the force data processing module, the resistance training process is quantized and recorded according to the important information, and the force data acquisition device is convenient for trainers to use and assist in monitoring the training process.
2. Compared with the existing modes of human eye identification and manual segmentation, the force data processing module is integrated with a repetition frequency segmentation unit and a force action state segmentation unit; the method can be realized by programming, and experimental tests prove that the algorithm has the advantages of high segmentation efficiency and no influence of subjective factors of segmenters.
3. The force data quantification module quantifies the force generation capacity of the muscle of the arm flexor of a trainer by using the acceleration and deceleration time ratio of the CON stage, and reflects the force maintaining capacity of the muscle of the arm flexor by using the fluctuation characteristic of force data of the ISOM stage; therefore, the muscle force characteristic and the muscle state characteristic of the trainer can be accurately depicted.
4. The training guidance module calls the processing result of the force data processing module to determine the actual training intensity and the training completion degree, and calls the quantization result of the force data quantization module to determine the muscle function evaluation index; obtaining muscle function evaluation according to the result obtained by the force data quantification module; and combining with an expected training target, and obtaining a training guidance result after comprehensive evaluation.
Drawings
FIG. 1 is a diagram of an auxiliary system for training upper limb flexor resistance of a household person according to an embodiment of the present invention;
FIG. 2 is a scene diagram of an upper limb flexor resistance training auxiliary system for a household person according to an embodiment of the present invention;
FIG. 3 is a diagram of a data segmentation scenario for a force data processing module in an embodiment of the present invention;
FIG. 4 is a block diagram of a force data quantification module in an embodiment of the invention;
FIG. 5 is a schematic diagram of a training guidance module according to an embodiment of the present invention;
FIG. 6 is a scene diagram of an upper limb flexor resistance training auxiliary system for a household person according to the preferred embodiment of the present invention;
FIG. 7 is a software architecture diagram of a training assistance system in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a structural diagram of an upper limb flexor resistance training assistance system for a household person according to an embodiment of the present invention, as shown in fig. 1, the upper limb flexor resistance training assistance system includes:
100. the force data acquisition device is used for acquiring force data of upper limb flexor resistance training of a training person;
fig. 2 is a force data acquisition device in an embodiment of the present invention, as shown in fig. 2, in an embodiment of the present invention, the force data acquisition device includes a force sensor elastic band for upper limb flexor resistance training, the force sensor elastic band includes a force sensor, a buckle a, an elastic band, a buckle B, a grip, a digital-to-analog converter, a control panel, and a ring buckle with a bolt, one end of the force sensor is provided with the buckle a, and the other end is provided with the ring buckle with a bolt; two ends of the elastic belt are respectively connected with the buckle A and the buckle B, and the handle is fixedly connected with the buckle B; the force sensor outputs a modulus electric signal, the modulus electric signal is converted into a digital signal through a digital-to-analog converter, the digital signal is transmitted to an upper computer through a control panel, and the digital signal is force data of upper limb flexor resistance training of a training person.
Wherein, in the collection process that power data acquisition device accomplished the training of resistance of the bent muscle to the user, power data acquisition device links to each other with external environment through the ring knot for the one end of this device of fixed. The user holds the handle with hand to crooked arm, thereby the crooked in-process, the elastic webbing is stretched and is produced the resistance, and the resistance is monitored and produces the mould electric signal by force transducer, reads the mould electric signal that the sensor produced by digital analog converter to convert it into digital signal, pass through the computer serial ports with digital signal through the control panel, transmit to the host computer.
It will be appreciated that the force data acquisition means includes physical and electrical connections, with electrical connections between the force sensor and the digital to analogue converter and between the data converter and the control board, and physical connections between other components. Namely, the circular ring buckle, the force sensor, the buckle A, the elastic band, the buckle B and the handle are installed in series; the force sensor, the digital-to-analog converter and the control panel are installed in series through data lines.
It is worth mentioning that both ends of the elastic band are connected with other components by means of a snap, so that the elastic band can be replaced from the force data acquisition device during use. Therefore, the size of the anti-resistance load acted on the hand by the equipment in the process of stretching the elastic rope can be changed by increasing the number of the elastic belts or changing the type and the category of the elastic belts.
In addition, it is worth to be noted that the handle and the buckle B are connected through a nylon rope, so that the length of the whole device can be changed by changing the length of the nylon rope, thereby meeting the requirements of different users on the length of the device.
200. The force data processing module is used for carrying out segmentation processing on the acquired force data to obtain training group number, training times and corresponding force data; and obtaining the duration and rest time of the muscle in different states and corresponding force data; the states include a concentric contracted state, an isometric contracted state, an eccentric contracted state, and a rest state.
In the embodiment of the invention, the force data processing module comprises a repetition number segmentation unit and a force action state segmentation unit; the repeated times segmentation unit is embedded with a repeated times segmentation algorithm, and the force action state segmentation unit is embedded with a force action state segmentation algorithm.
Fig. 3 is a data segmentation scene diagram of the force data processing module according to the embodiment of the present invention, as shown in fig. 3, the resistance data acquired by the force data acquisition device in the embodiment is used; segmenting the force data into different groups and data segments with different repetition times by using a repetition time segmentation unit, wherein the force data are assumed to be segmented into N data segments; each segmented data segment Fi(t) (i ∈ {1, 2.,. N }) each calculating a force derivative, and determining a maximum value and a minimum value of the force derivative of the current data segment; based on the force data and the maximum value and the minimum value of the corresponding force derivative, a Concentric Contraction (CON) data segment, an Eccentric contraction (ECC) data segment, an Isometric contraction (isometry contraction, ISOM) data segment and a REST period REST data segment are segmented by using a muscle force action state module.
The two division units will be described in detail below in conjunction with the repetition number division algorithm and the force action state division algorithm.
The repetition frequency segmentation unit adopts a repetition frequency segmentation algorithm, divides the acquired force data into data segments with a plurality of repetition cycles according to the length of the training cycle, and obtains the number of training groups, the training frequency and the corresponding force data;
in the embodiment of the invention, the repeated times division is a preprocessing stage, aiming at dividing the force data into a plurality of segments only containing a single period according to the training period; because the resistance signal shows strong periodicity characteristic in the upper limb flexor resistance training process and has obvious wave crests and wave troughs, repeated periodic data can be divided into data segments only containing one wave crest and one wave trough.
Specifically, firstly, an average value of resistance data is acquired from a force data acquisition device, the average value is taken as a segmentation threshold value, the force data is divided into a plurality of data segments containing peaks and troughs, and the troughs are determined from the data segments by adopting a peak detection method; dividing the resistance data into a plurality of data segments by taking the trough value as a data segment dividing point, wherein each data segment represents a training period, and each training period comprises a concentric contraction stage, an eccentric contraction stage, an isometric contraction stage and a rest stage.
The force action segmentation unit adopts a muscle force action state segmentation algorithm, in a data segment corresponding to each repetition period, the force data of the data segment is subjected to time derivation to obtain a corresponding force derivative number, and the maximum value and the minimum value of the force derivative number are calculated; and dividing the force data into a concentric contraction stage, an eccentric contraction stage, an isometric contraction stage and a rest stage by taking the maximum value and the minimum value of the force derivative as limiting conditions, and obtaining the force data corresponding to each stage.
In the embodiment of the invention, during the resistance training process of the upper limb flexor and the like, the muscle can be in four different contraction states in a single training period, including a concentric contraction state, an eccentric contraction state, an isometric contraction state and a rest state. Influenced by the personal ability, will and fatigue of the user, there is usually no clear demarcation point between the CON, ISOM, ECC and rest phases; if the demarcation point can be found in a certain mode, the segmentation effect can be greatly improved; therefore, the invention utilizes a muscle force action state algorithm to find the demarcation point between different states; thereby separating data parameters of different state stages; finally, parameters such as rest Time, duration-Time (TUT) in a tensioning state, speed and muscle state can be calculated.
During CON contraction, the force derivative increases rapidly and reaches a maximum value, and then decreases rapidly to zero. During the ISOM contraction, the subject held his forearm quasi-static for a few seconds, during which time the force derivative did not change much. During ECC contraction, the subject extends the forearm and the force derivative increases gradually after reaching a minimum value; the force data of the different phases of the state can thus be distinguished by the force derivatives.
The embodiment may adopt a segmentation threshold to adjust the maximum value of the force derivative and the minimum value of the force derivative; a fixed ratio value of the maximum value and the minimum value can be used as a segmentation threshold value, the adjusted maximum value and the adjusted minimum value are used as range threshold values of all contraction stages in the rough segmentation model, and the force data are divided into four stages; calculating a trend line (y ═ fi (t), i ═ 1-3) of the force data in each stage by adopting a linear regression algorithm; and dividing the intersection point of the trend line and the x axis and the intersection point between the trend lines to obtain the parameter data corresponding to each stage.
In the embodiment of the present invention, the rough segmentation model is represented as:
wherein F (t) represents the elastic belt resistance; CON represents concentric contraction; ISOM represents isometric contraction; ECC denotes eccentric contraction; REST represents a REST state; a denotes a division threshold.
It can be understood that, in the above process, since the force derivative values of the isometric contraction state and the rest state both approach 0, the two states cannot be distinguished directly through the force derivative values, in the present application, the two states are considered to be distinguished from each other, and a normal data segment sequentially includes a rest state, a concentric contraction state, an isometric contraction state, an eccentric contraction state, and a rest state; therefore, the corresponding isometric contraction state and the rest state can be judged directly according to the force data or the range of the abscissa in the force derivative, and when the force derivative approaches 0, the judgment is carried out according to the trend of the front and back force derivatives or the front and back position relation of the front and back force derivatives and other two known state data.
In the embodiment of the invention, the intersection point of the trend line of the concentric contraction stage and the x axis is taken as a first state division point; taking the intersection point of the trend line of the concentric contraction stage and the isometric contraction stage as a second state division point; taking the intersection point of the trend line of the isometric contraction stage and the eccentric contraction stage as a third state division point; taking the intersection point of the trend line of the eccentric contraction stage and the x axis as a fourth state division point; taking the data segment limited by the first state division point and the second state division point as the fine division data of the concentric contraction stage; taking the data segments limited by the second state segmentation points and the third state segmentation points as the fine segmentation data of the isometric contraction stage; taking the data segment limited by the third state division point and the fourth state division point as the fine division data of the eccentric contraction stage; and taking the data segment limited by the first state segmentation point and the left end point of the current data segment and the data segment limited by the third state segmentation point and the right end point of the current data segment as the fine segmentation data of the rest stage.
In the embodiment of the present invention, after dividing each data segment into a concentric contraction state, an isometric contraction state, an eccentric contraction state, and a rest state, the duration and the rest time of the muscle in each data segment can be determined, and meanwhile, in the embodiment of the present invention, data corresponding to the concentric contraction state and the eccentric contraction state need to be separately extracted, and the data are used for the subsequent quantization processing.
300. The force data quantization module is used for quantizing the force generation capacity and the force retention capacity of the upper limb flexor of the trainer according to the force data of the muscles in the concentric contraction state and the isometric contraction state;
in the embodiment of the present invention, as shown in fig. 4, the force data quantization module 300 includes a first quantization unit 301 and a second quantization unit 302;
the first quantization unit 301 performs an acceleration phase time T according to the concentric contraction state1And the deceleration stage time T2Calculating the ratio of the two to obtain the force generation capacity; the first quantization unit reflects the training process of the upper limb flexor of the trainer in resistance through the burst characteristic of the impedance force data in the CON stageThe force generating capability of.
The second quantization unit 302 uses the force data in the isometric contraction state as an abscissa, uses the corresponding force derivative as an ordinate, and draws a force phase diagram (coeffient of Variation); taking the discrete coefficient of the data points in the force phase diagram as the force retention capability; the second quantification unit reflects the force maintaining capacity of the upper limb flexor of the trainer in the resistance resisting training process through the fluctuation characteristics of the resistance resisting data in the ISOM stage.
In some preferred embodiments, the force data quantification module may further comprise other expansion quantification units, for example, quantification analysis may be performed by means of musculoskeletal modeling.
400. And the training guidance module is used for outputting a training guidance result according to the processing result of the force data processing module and the quantization result of the force data quantization module and in combination with an expected training target.
In an embodiment of the present invention, fig. 5 is a schematic structural diagram of a training guidance module in an embodiment of the present invention, and as shown in fig. 5, the training guidance module 400 includes a training recommendation unit 401, a training comparison unit 402, and a training guidance unit 403;
the training recommendation unit 401 is configured to recommend an expected training target adapted to the home staff according to basic information of the home staff;
in this embodiment of the present invention, the training recommendation unit 401 may recommend an expected training target suitable for the home person according to the information of the home person, such as the sex, age, and physical state.
The training comparison unit 402 is configured to compare the processing result of the force data processing module and the quantization result of the force data quantization module with the expected training target, and determine a training frequency difference and a training intensity difference;
in this embodiment of the present invention, the training comparison unit 402 may compare the number of training sets and the number of training times determined according to the duration and the rest time in different states output by the force data processing module with the number of training times recommended by an expected training target, so as to determine a difference between the number of training times; and comparing the force generation capacity and the force retention capacity of the upper limb flexor of the trainer output by the force data quantification module with the force generation capacity and the force retention capacity recommended by an expected training target so as to determine the training intensity difference.
The training guidance unit 403 is configured to output a training time difference and a training intensity difference.
In this embodiment of the present invention, the training guidance unit 403 may output the result of the training time difference and the result of the training intensity difference to a household person or other instructor.
In a specific embodiment, for the training guidance module 400, during the training process, the patient needs to be guided to complete the set (set), the repetition times (repetition), the duration of different muscle action states, the training intensity, and other variables. The selection of the recommended value in the system is currently set according to the recommendation of the National physical fitness Association (National institute and Conditioning Association), according to the following: a well-designed elderly resistance training regimen should include an individualized, periodic approach. It is desirable to perform 2-3 sets of 1-2 multi-joint exercises for each major muscle group, with training intensity reaching 70-85% of 1 maximal repeat intensity, 2-3 times per week, including power exercises performed at a higher rate in a medium intensity concentric exercise (i.e., 40-60% of 1 maximal repeat intensity). Reference documents: fragalia, Maren S, Cadore, et al, resistance tracking for Older adapters, Position State From the National Strength and Conditioning Association.
The method comprises the following specific steps: the software interface comprises a training set number and a repetition number counter, and the number of completed sets can be automatically recorded and prompted in real time; by recording the resistance data of the elastic belt and performing segmentation processing on the force data, the duration of CON, ISOM, ECC and rest stages and the training intensity can be obtained; whether to increase or decrease the training intensity is determined based on the force generation ability and force retention ability index of the upper limb flexor obtained by the force data quantification module 300, and the determination is based on the fact that the number of times and intensity of training can be appropriately decreased in the case where the force generation ability and force retention ability of the patient are weak.
Fig. 6 is a schematic view of a scenario of an upper limb flexor resistance training assistance system for a household person according to an embodiment of the present invention, and as shown in fig. 6, an example of assisting a trainer sitting on a wheelchair to complete resistance training is shown to illustrate a flow scenario of an implementation of a technical solution of the assistance system according to the present invention.
In this embodiment, during the exercise of resistance of the user's flexor muscles, one end of the force data acquisition device is connected to the external environment through the ring buckle, and the other end is fixed to the wheelchair. The trainer holds the grip and bends the arm, the elastic band is stretched to generate resistance in the bending process, the resistance is monitored by the force sensor and generates a modulus electric signal, the modulus electric signal generated by the sensor is read by the digital-to-analog converter and converted into a digital signal, and the digital signal is transmitted to the upper computer through the control panel; determining the number of training groups, the training times and the corresponding data segments through a repetition time segmentation algorithm; processing each data segment by adopting a force action state segmentation algorithm, and determining duration and rest time of an output state and corresponding force data; obtaining a force generation capacity index for the CON data and a force maintenance capacity index for the ISOM data; recording the training times, the duration time of the force state and the rest time, and forming a training record; deriving training records to form actual training intensity and training completion; deriving the force generation capacity index, the force retention capacity index and the internal state parameter of the single muscle to form muscle function evaluation; and then combining with an expected training target to obtain a training guide result, and feeding the training guide result back to a trainer, wherein the trainer can adjust according to the corresponding guide result.
It is worth to be noted that the actual training intensity and the completion degree of the trainer and the quantitative muscle function evaluation indexes are provided for the trainer and other people in the training process through the quantification and evaluation functions of the system, so that the trainer and other people are helped to provide training guidance and suggestions for the trainer according to expected training targets.
In some preferred embodiments of the present invention, fig. 7 is a diagram illustrating a software architecture of a training assistance system in an embodiment of the present invention, as shown in fig. 7, the software architecture mainly includes: the system comprises a real-time display interface for unprocessed results, a real-time display interface for processed results, buttons and a user input interface; the auxiliary system software interface is used as an upper computer to obtain the resistance uploaded by the customized elastic band, and the functional interface comprises a real-time display interface of unprocessed results, a real-time display interface of processed results and a corresponding button interface.
It should be noted that each interface only includes a part of functional interfaces, and the content of the functional interfaces in the system can be increased and changed by expansion.
In a preferred embodiment of the present invention, a software interface may comprise: the button and user input interface comprises a Start button (Start), a pause button (Stop), a Save button (Save), and a Serial port input port (Serial); the real-time display interface of the unprocessed result comprises a real-time display bar of the resistance value, a timer and the like; the real-time display interface of the processed result comprises an ISOM stage duration time recorder, a training frequency recorder and the like, and is mainly used for recording real-time training details.
When the trainer uses the device, firstly, a serial port number is input, a Start button (Start) is clicked, and the upper computer receives the anti-resistance data transmitted by the elastic band through the input serial port number and displays the anti-resistance data on a real-time display panel in real time. The user needs to set an anti-resistance threshold and a duration threshold in advance, and starts to count when the anti-resistance of the elastic band is larger than the threshold until the counted time exceeds the given duration threshold, the training time recorder completes the operation of adding one to the number, and the duration is recorded by the duration recorder and displayed on the training detail recording panel.
In addition, after the training is finished, a pause button (Stop) is clicked, and the upper computer stops recording data transmitted from the elastic band end; and clicking a Save button (Save), and automatically saving information such as a strength data signal, training details and the like into a txt document by the software system for post-processing.
It should be noted that the contents of the functional interface displayed in the software interface only represent some functions of the present invention, and it should not be assumed that the specific implementation of the software of the present invention is limited to the above-mentioned contents.
In some preferred embodiments of the present invention, the present invention also provides an upper limb flexor resistance training assistance method for a household person, the method comprising:
collecting force data of upper limb flexor resistance training of a training person;
carrying out segmentation processing on the acquired force data to obtain training group number, training times and corresponding force data; obtaining the duration and rest time of the muscle in different states and corresponding force data; wherein the muscle state comprises concentric contraction state, isometric contraction state, eccentric contraction state and rest state;
according to the force data of muscles in the concentric contraction state and the isometric contraction state, the force generation capacity and the force maintenance capacity of the upper limb flexor of the trainer are obtained quantitatively;
determining the actual training times according to the training group number and the training times, determining the actual training intensity according to the force generation capacity and the force retention capacity, and outputting a training guidance result by combining an expected training target.
It is understood that the training aid method can help to understand the training aid system of the present invention, and the corresponding features of the two can be mutually cited, which is not described in detail in the present invention.
Furthermore, it will be apparent to those skilled in the art that several simple deductions or substitutions may be made without departing from the spirit of the invention, such as modifying the device of the invention for training and monitoring of resistance of shoulder muscles, which should be considered as falling within the scope of the invention.
In the description of the present invention, it is to be understood that the terms "coaxial", "bottom", "one end", "top", "middle", "other end", "upper", "one side", "top", "inner", "outer", "front", "center", "both ends", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "disposed," "connected," "fixed," "rotated," and the like are to be construed broadly, e.g., as meaning fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; the terms may be directly connected or indirectly connected through an intermediate, and may be communication between two elements or interaction relationship between two elements, unless otherwise specifically limited, and the specific meaning of the terms in the present invention will be understood by those skilled in the art according to specific situations.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (5)
1. An upper limb flexor resistance training assistance system for a household person, the system comprising:
the force data acquisition device is used for acquiring force data of upper limb flexor resistance training of a training person;
the force data processing module is used for carrying out segmentation processing on the acquired force data to obtain training group number, training times and corresponding force data; and obtaining the duration and rest time of the muscle in different states and corresponding force data; the states comprise a concentric contraction state, an isometric contraction state, an eccentric contraction state and a rest state;
the force data quantization module is used for quantizing the force generation capacity and the force retention capacity of the upper limb flexor of the trainer according to the force data of the muscles in the concentric contraction state and the isometric contraction state;
and the training guidance module is used for outputting a training guidance result according to the processing result of the force data processing module and the quantization result of the force data quantization module and in combination with an expected training target.
2. The upper limb flexor resistance training auxiliary system for the household personnel as claimed in claim 1, wherein the force data acquisition device comprises a force sensor elastic belt for upper limb flexor resistance training, the force sensor elastic belt comprises a force sensor, a buckle A, an elastic belt, a buckle B, a handle, a digital-to-analog converter, a control panel and a bolt ring buckle, one end of the force sensor is provided with the buckle A, and the other end is provided with the bolt ring buckle; two ends of the elastic belt are respectively connected with the buckle A and the buckle B, and the handle is fixedly connected with the buckle B; the force sensor 1 outputs a modulus electric signal which is converted into a digital signal through a digital-to-analog converter, and the digital signal is transmitted to an upper computer through a control panel.
3. The upper limb flexor resistance training assistance system for a domestic person according to claim 1, wherein the force data processing module includes a repetition number segmentation unit and a force action state segmentation unit;
the repetition frequency segmentation unit adopts a repetition frequency segmentation algorithm, divides the acquired force data into data segments with a plurality of repetition cycles according to the length of the training cycle, and obtains the number of training groups, the training frequency and the corresponding force data;
the force action segmentation unit adopts a muscle force action state segmentation algorithm, in a data segment corresponding to each repetition period, the force data of the data segment is subjected to time derivation to obtain a corresponding force derivative number, and the maximum value and the minimum value of the force derivative number are calculated; and dividing the force data into a concentric contraction stage, an eccentric contraction stage, an isometric contraction stage and a rest stage by taking the maximum value and the minimum value of the force derivative as limiting conditions, and obtaining the force data corresponding to each stage.
4. The upper limb flexor training assistance system for a domestic person according to claim 1, wherein the force data quantification module comprises a first quantification unit and a second quantification unit;
the first quantification unit calculates force generation capacity according to the ratio of the acceleration stage time to the deceleration stage time of the concentric contraction state;
the second quantization unit takes the force data in the isometric contraction state as an abscissa and takes the corresponding force derivative as an ordinate, and a force phase diagram is obtained through drawing; the dispersion coefficient of the data points in the force phase diagram is taken as the force retention capability.
5. The upper limb flexor resistance training auxiliary system for the household person according to claim 1, wherein the training guide module comprises a training recommendation unit, a training comparison unit and a training guide unit;
the training recommendation unit is used for recommending an expected training target matched with the family personnel according to basic information of the family personnel;
the training comparison unit is used for comparing the processing result of the force data processing module and the quantization result of the force data quantization module with the expected training target to determine the difference of training times and the difference of training intensity;
and the training guide unit is used for outputting the training time difference and the training intensity difference.
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