CN114098713B - Finger movement assessment method and finger movement assessment device - Google Patents
Finger movement assessment method and finger movement assessment device Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 56
- 230000005057 finger movement Effects 0.000 title claims description 19
- 238000011156 evaluation Methods 0.000 claims abstract description 106
- 230000033001 locomotion Effects 0.000 claims abstract description 99
- 230000036541 health Effects 0.000 claims abstract description 52
- 210000003811 finger Anatomy 0.000 claims description 159
- 239000002360 explosive Substances 0.000 claims description 29
- 210000003813 thumb Anatomy 0.000 claims description 25
- 230000009471 action Effects 0.000 claims description 22
- 210000004932 little finger Anatomy 0.000 claims description 21
- 238000012360 testing method Methods 0.000 claims description 7
- 230000002093 peripheral effect Effects 0.000 claims description 6
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- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1124—Determining motor skills
- A61B5/1125—Grasping motions of hands
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/22—Ergometry; Measuring muscular strength or the force of a muscular blow
- A61B5/224—Measuring muscular strength
- A61B5/225—Measuring muscular strength of the fingers, e.g. by monitoring hand-grip force
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Abstract
The invention provides a finger motion assessment method and a finger motion assessment device, comprising the following steps of obtaining motion data of each finger of a single hand and obtaining assessment rules; based on the motion data and the evaluation rules, an evaluation result for the hand is obtained. According to the finger-dividing motion assessment method, the motion data of each finger of a single hand is read, and the assessment result of the hand is obtained by combining a certain rule, so that the advantage that the hand function in the human body can effectively represent the health state is fully utilized, the hand can be assessed accurately by the motion data of each finger, and the technical effect of high-efficiency and accurate assessment of the physical quality is realized.
Description
Technical Field
The invention relates to the technical field of sports quality health assessment, in particular to a finger-dividing sports assessment method and a finger-dividing sports assessment device.
Background
With the continuous improvement of living standard, people's attention to their health is increasing, and the quality of daily life forms such as diet, work and rest, exercise, etc. is also becoming the focus of attention. Wherein, it is an important link to physical movement quality health evaluation. By monitoring the physical movement quality of the body, the physical state can be effectively reflected, so that people can select a proper movement mode and know the health level of the body in a targeted manner.
In the existing exercise monitoring technology, more equipment such as electrocardiograph monitoring and blood pressure monitoring is needed to be worn, and after effective exercise is carried out, monitoring results can be obtained, so that time is wasted, the exercise is difficult to carry out at any time, and more preparation work is needed. Therefore, it is needed to provide a convenient and rapid exercise evaluation method, so as to quickly reflect the functions and health states of the body.
Disclosure of Invention
The invention provides a finger motion assessment method, which comprises the following steps:
acquiring motion data of each finger of a single hand, and acquiring an evaluation rule;
Based on the motion data and the evaluation rules, an evaluation result for the hand is obtained.
Preferably, the motion data includes a maximum grip strength value of each of the fingers, and the evaluation result includes a full hand maximum explosive force of the hand; the evaluation rule includes: the maximum explosive force of the whole hand comprises: the sum of the product of the maximum grip value of the thumb and the first weight, the product of the maximum grip value of the index finger and the second weight, the product of the maximum grip value of the middle finger and the third weight, the product of the maximum grip value of the ring finger and the fourth weight, and the product of the maximum grip value of the little finger and the fifth weight.
Preferably, the first weight ranges from 0.2 to 0.3, the second weight ranges from 0.15 to 0.25, the third weight ranges from 0.15 to 0.25, the fourth weight ranges from 0.05 to 0.2, and the fifth weight ranges from 0.01 to 0.15.
Preferably, the evaluation result further includes a grip strength value of the hand health evaluation; the evaluation rule further includes: continuously obtaining at least five times of full-hand maximum explosive force; and obtaining the hand health evaluation grip strength value based on the sum of the maximum explosive force of the whole hand and the acquisition times of the maximum explosive force of the whole hand.
Preferably, the movement data comprises a grip strength value-time curve of each of the fingers, and the evaluation result is a full hand grip strength level of the hand; the evaluation rule includes: acquiring a preset grip strength threshold value, and acquiring an average value and a standard deviation of grip strength based on the grip strength numerical value-time curve; the Quan Shouwo-force endurance level includes at least one of a grip achievement time obtained based on the grip numerical value-time curve and the preset grip threshold, a sum of curve integrals of the grip numerical value-time curve of each finger, and a number of times the grip numerical value-time curve fluctuates by more than one of the standard deviations with respect to the average value.
Preferably, the motion data comprises a maximum grip strength value of each finger and a strength value of a reaction motion of each finger corresponding to a prompt signal, the prompt signals comprise prompt signals for requesting at least one finger to perform motion, and the evaluation result is a coordinated motion quality of the hand; the evaluation rule includes: determining that the finger does not require to act according to the prompt signal; judging whether the force value of the finger which does not require action exceeds 10% -30% of the maximum grip strength value, if so, recording as one false action; and obtaining the coordinated movement quality of the hand based on the number of false actions and the number of sending out of the prompt signal.
According to another aspect of the present invention, there is provided a finger movement health assessment device including:
The finger separation testing device comprises a device main body, a thumb key, an index finger key, a middle finger key, a ring finger key, a little finger key and a pressure sensing component, wherein the pressure sensing component is arranged inside the device main body, and the thumb key, the index finger key, the middle finger key, the ring finger key and the little finger key are sequentially arranged on the surface of the device main body and are connected with the pressure sensing component, and the pressure sensing component is used for acquiring the motion data of each finger of a single hand through the thumb key, the index finger key, the middle finger key, the ring finger key and the little finger key;
the storage module is at least used for storing the evaluation rule;
And the evaluation module is connected with the storage module and the pressure sensing component and is used for executing the finger dividing movement evaluation method, and the evaluation result is obtained based on the movement data and the evaluation rule.
Preferably, the finger test device further comprises a reset key, wherein the reset key is used for inputting an instruction for commanding the evaluation module to re-execute the finger motion evaluation method; the device main body is provided with a top surface, a bottom surface and an outer peripheral surface, wherein the top surface and the bottom surface are mutually deviated, the thumb key is arranged on the top surface, the reset key is arranged on the bottom surface, and the index finger key, the middle finger key, the ring finger key and the little finger key are arranged on the outer peripheral surface along the same direction and are sequentially far away from the thumb key.
Preferably, the device main body, the thumb key, the index finger key, the middle finger key, the ring finger key and the little finger key are all symmetrical structures and share a symmetrical plane.
According to a further aspect of the present invention, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the finger motion assessment method according to any of claims to.
According to the finger-dividing motion assessment method, the motion data of each finger of a single hand is read, and the assessment result of the hand is obtained by combining a certain rule, so that the advantage that the hand in the human body can intensively reflect the health state is fully utilized, the hand can be assessed more accurately by the motion data of each finger, and the technical effect of efficiently and accurately assessing the physical quality is achieved.
Drawings
Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the following drawings in which:
fig. 1 is a flowchart of a first embodiment of a finger motion estimation method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a flow chart of a fourth embodiment according to an embodiment of the present application;
Fig. 3 is a schematic diagram of a finger motion estimation device according to an embodiment of the present application.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. For convenience of description, only parts related to the invention are shown in the drawings.
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.
The finger dividing movement in the invention mainly aims at measuring the grip strength and comprises other parameters such as the gripping time. The grip strength is a main mode of hand strength, is an index which is very effective in evaluating human health and strength movement quality, can be used as one of important indexes for predicting the strength and health state of upper limbs of a human body, and has reference significance for judging the nerve state of special people such as old people.
The finger movement evaluation method provided by the embodiment of the invention can be executed in an evaluation module in the finger movement health evaluation device and obtain an evaluation result, or can be executed by uploading movement data of each finger to a network server and the like. The finger movement evaluation method provided by the invention is not limited to the type of the executed main body, and can be a terminal such as a personal computer, a mobile phone and the like, a network server and the like.
As shown in fig. 1, a first embodiment of the present invention provides a finger motion estimation method, which includes the following processes:
s101, acquiring motion data of each finger of a single hand, and acquiring an evaluation rule;
S102, based on the motion data and the evaluation rules, an evaluation result of the hand is obtained.
In the process S101, the motion data of each finger, that is, the grip-based data such as the maximum grip value, the grip value-time curve, etc. generated based on the gripping action of each finger, may be selected according to different evaluation rules. The main way to obtain motion data is to obtain the maximum grip value in a period of time by using a pressure sensing component, such as a piezoelectric pressure sensing component or a strain gauge pressure sensing component, and sampling the motion data at a certain sampling frequency, such as sampling every 0.1 second or sampling every 0.01 second, or drawing a grip value-time curve according to the grip value obtained by sampling and the sampling time, which are all technical means known to those skilled in the art. The process S101 of acquiring motion data of each finger of a single hand mainly refers to acquiring motion data of five fingers (possibly four fingers due to physical defects or the like) on one hand at the same time, so that motion of the hand can be described more accurately.
The evaluation rule in the process S101 mainly refers to an arithmetic processing method capable of obtaining a result pair reflecting a state such as a grip strength, a reaction speed, a physical health level, and the like from the motion data of each finger by combining a certain arithmetic processing procedure using the motion data described above. The implementation of which will be described in one-to-one manner in the following embodiments. The evaluation rules may be pre-stored in a storage device in the finger-motion health evaluation device described below, or may be stored in a web server, etc., and the process of obtaining the evaluation rules in the process S101 may be correspondingly read from the storage device, or downloaded from the web server, etc., which are well known to those skilled in the art, and are not repeated herein.
In the process S102, based on the motion data and the evaluation rule, the evaluation result of the hand may be obtained, which includes only operations, for example, a process of calculating the maximum explosive force of the whole hand based on the maximum grip strength of each finger described in the second embodiment of the present invention, or may include a calculation process and a judgment process, for example, after calculating the maximum explosive force of the whole hand, whether the result reaches a certain standard, such as a set standard: if the grip strength is greater than 60kg, it is determined whether the calculated maximum full-hand explosive force exceeds 60kg, and if so, an excellent result is obtained, and the determination process and implementation are well known to those skilled in the art.
According to the finger-dividing motion assessment method, the motion data of each finger of a single hand is read, and the assessment result of the hand is obtained by combining a certain rule, so that the advantage that the hand in the human body can intensively reflect the health state is fully utilized, the hand can be assessed more accurately by the motion data of each finger, and the technical effect of efficiently and accurately assessing the physical quality is achieved.
In a preferred embodiment, the second embodiment of the finger motion estimation method provided by the invention mainly aims at estimating the maximum explosive force of the whole hand. The maximum burst force of the whole hand mainly refers to the maximum grip force which can be achieved in one gripping action of the hand, can reflect the muscular development degree and the health state of the hand more accurately, and is an important physiological index.
In the second embodiment of the finger-dividing motion estimation method provided by the invention, the motion data comprise maximum grip strength values of each finger, and the estimation result comprises maximum explosive force of the whole hand; the maximum grip strength value of each finger refers to the maximum grip strength value which can be achieved by one finger in one grasping process, and specifically comprises a thumb, an index finger, a middle finger, a ring finger and a little finger. Correspondingly, the evaluation rule comprises: the maximum explosive force of the whole hand comprises: the product of the maximum grip value of the thumb and the first weight, the product of the maximum grip value of the index finger and the second weight, the product of the maximum grip value of the middle finger and the third weight, the product of the maximum grip value weight of the ring finger and the sum of the product of the maximum grip value of the little finger and the fifth weight. The maximum explosive force of the whole hand can be directly equal to the sum of the products of the fingers and the corresponding weights, or can be multiplied by a coefficient after the sum of the products of the fingers and the corresponding weights is obtained, for example, the maximum explosive force of the whole hand of a boxer during the boxing is measured under a static condition, and as the boxing process can disperse part of muscles related to the hand to the boxing action, an empirical coefficient is required to be set according to experience, and the empirical coefficient can be obtained according to specific requirements and combined with limited experiments, and can be realized by a person skilled in the art.
Preferably, in calculating the sum of the products of the respective fingers and the corresponding weights, the first weight ranges from 0.2 to 0.3, preferably 0.25; the second weight ranges from 0.15 to 0.25, preferably 0.25; the third weight ranges from 0.15 to 0.25, preferably 0.25; the fourth weight ranges from 0.05 to 0.2, preferably 0.15; the fifth weight ranges from 0.01 to 0.15, preferably 0.10. In one grasping action, the thumb has the largest output effect, is larger than the index finger, the middle finger and the ring finger, has smaller output effect and gives consideration to the balance effect, and the little finger has the balance effect as the main part.
After the maximum explosive force of the whole hand is obtained through the second embodiment of the present invention, preferably, the evaluation result further includes a grip strength value for evaluating the health of the hand, and the evaluation rule further includes:
Continuously obtaining at least five times of full hand maximum explosive force; and obtaining the hand health evaluation grip strength value based on the total sum of the maximum explosive force of the whole hand and the acquisition times of the maximum explosive force of the whole hand.
The above process is actually an average value of the maximum explosive force of the whole hand tested for a plurality of times, but combines the characteristic of the force of the hand. The human hand is composed of a plurality of small muscle groups, the force characteristic of the small muscle groups is strong in explosive force but weak in continuous force compared with the large muscle groups, so that when the full-hand maximum explosive force is continuously tested, especially when the full-hand maximum explosive force is more than five times, whether the small muscle groups of the hand can continuously exert the force or not can show the degree of development of the hand muscles and the health degree of cardiovascular and other tissues, and therefore, the average value of the full-hand maximum explosive force more than five times can be continuously obtained to serve as the hand health evaluation grip strength value, and the whole health level of a human body can be effectively evaluated.
In a preferred embodiment, the third embodiment of the finger movement assessment method provided by the present invention is mainly aimed at the full hand endurance level. The full hand holding force endurance level mainly refers to the grasping endurance level which can be achieved in one continuous grasping action of the hand, so that the strength endurance level of the upper limb and the heart-lung endurance level of the human body are reflected.
In a third embodiment of the split-finger exercise assessment method provided by the invention, the exercise data comprises a grip strength value-time curve of each finger, and the assessment result is the full hand grip strength level of the hand; the evaluation rule includes: acquiring a preset grip strength threshold value, and acquiring an average value and a standard deviation of grip strength based on a grip strength numerical value-time curve; the full hand grip endurance level includes at least one of a grip achievement time based on a grip value-time curve and a preset grip threshold, a sum of curve integrals of the grip value-time curves of each finger, and a number of times the grip value-time curve fluctuates by more than one standard deviation from the average.
The preset grip strength threshold in the third embodiment of the finger-dividing motion estimation method provided by the invention mainly refers to a grip strength value capable of judging when to start a continuous gripping motion and when to end a continuous gripping motion, for example, before a person tests, when the grip strength value is set to be greater than a certain value n according to the information such as gender, age and weight, the person starts timing and collects various data, and when the grip strength value is less than the certain value n for 2-3 seconds, the timing and the data collection are stopped, so that the start and the end of a continuous gripping motion can be accurately judged.
The grip strength value-time curve in the third embodiment of the finger motion estimation method provided by the invention refers to a curve in which the horizontal axis unit is a time unit and the vertical axis unit is a change of grip strength value depicted in a coordinate system of grip strength units along with the change of time. The specific acquisition implementation here may be to acquire a grip value versus time curve plotted by the grip value over a period of time in combination with the sampling time by setting a sampling frequency, such as sampling every 0.1 seconds or every 0.01 seconds. The grip strength value-time curve can be subjected to integral and differential processing to obtain more detailed values, such as average value, standard deviation, etc., and methods for obtaining average value and standard deviation based on a section of function curve are well known to those skilled in the art, such as dividing the section of function curve by the cross-axis range of the function curve after integrating, or calculating standard deviation after fitting the function curve, etc., which will not be described herein.
The full hand holding endurance level in the third embodiment of the finger movement assessment method provided by the invention comprises one of the following three indexes:
index 1: the grip strength reaching time is obtained based on a grip strength numerical value-time curve and a preset grip strength threshold value;
index 2: the sum of the curve integrals of the grip strength value-time curves of each finger;
Index 3: the grip number versus time curve fluctuates more than one standard deviation from the average.
All three indicators can be used to describe the full hand endurance level separately, for example, indicator 1 can describe the duration of time that a preset grip threshold is met during a continuous grip, the longer the duration of time, the better the endurance is; the index 2 may describe the sum of the output levels of the grip forces during the continuous gripping of five fingers of one hand, and if the value is larger, it means that more grip forces can be output or the time required to output the same grip force is shorter in the same time, while the index 3 can describe the stability of the grip force, and the smaller the fluctuation number, the smaller the number of times of occurrence of "fatigue".
In a preferred embodiment, the full hand endurance level in the third embodiment of the finger motion estimation method provided by the present invention includes the above-mentioned index 1, index 2 and index 3, and the comparison process may be: firstly, comparing the index 1, namely the time of reaching the standard of the grip strength in one continuous gripping action, and when the time of reaching the standard of the grip strength is the same, integrating the curves of the grip strength numerical value-time curves of all the fingers and calculating the sum of the integrals to judge the output degree of the grip strength; when the output degree of the grip strength is the same, the comparison index 3, that is, the number of times the grip strength value-time curve fluctuates by more than one standard deviation with respect to the average value, and the smaller the number of times, the higher the level of the full grip strength is. Therefore, the grip strength endurance level among different people can be accurately compared, and compared with the existing method for simply comparing the grip strength values, the grip strength endurance level detection method has the advantages of being rich and detailed in index system and data, more accurate in test and finer in crowd assessment division.
In a preferred embodiment, the fourth embodiment of the finger movement assessment method provided by the invention is mainly aimed at assessing the coordinated movement quality of hands. The evaluation mode at this time mainly includes sending out a prompt signal requesting at least one finger to act, and judging the motion coordination of the hand by judging whether other fingers move along with the moving finger. The method is characterized in that a plurality of fingers of a single hand are controlled by the same nerve plexus, in the transmission process of nerve signals, if the coordinated movement quality of the hands is high, the movement signal of each finger can be accurately and independently sent, so that the situation of spontaneous movement of non-moving fingers is avoided, and if the coordinated movement quality of the fingers is deficient, the situation of false movement of fingers which do not require movement is easy to occur.
In the fourth embodiment of the finger-dividing motion estimation method provided by the invention, the motion data corresponding to the estimation includes the maximum grip strength value of each finger and the strength value of the response motion of the prompt signal corresponding to each finger, the prompt signal includes the prompt signal for requesting at least one finger to perform motion, the prompt signal may be a text signal, such as a word of "grip ring finger" displayed on the screen in front of the estimated person, or may be a sound signal, such as the voice of "grip ring finger", or may be other various forms such as a graphic signal capable of enabling the estimated person to accurately learn the next motion required to be performed.
In a fourth embodiment of the finger motion estimation method provided by the present invention, the estimation rule includes the following processes, as shown in fig. 2:
s1021: determining that the finger does not require to act according to the prompt signal;
s1022: judging whether the force value of the finger which does not require action exceeds 10% -30% of the maximum grip strength value, if so, recording as one false action;
s1023: and obtaining the coordinated movement quality of the hand based on the number of false actions and the number of sending out of the prompt signals.
The non-required-operation fingers in the processing 1021 are all evaluated fingers except the finger required to be operated by the prompt signal, for example, the prompt signal requires the index finger to be operated, and the remaining thumb, middle finger, ring finger and little finger are all the non-required-operation fingers.
In the process S1022, the maximum grip strength value of the finger may be obtained from the previous evaluation record of the person to be evaluated, or may be obtained from the finger motion corresponding to the previous prompt signal in this evaluation. The force value of the false action can be preferably 15% of the maximum grip force value, so that whether the false action is the false action or not can be accurately judged, and other actions such as finger tremble can be screened out.
In the process S1023: based on the number of false actions and the number of sending out the prompt signals, a specific implementation manner of the coordinated movement quality of the hand can be obtained, wherein a quotient of the number of false actions divided by the number of sending out the prompt signals is used as a specific numerical value of the coordinated movement quality of the hand, and the higher the quotient is, the lower the coordinated movement quality of the hand is; the quotient obtained by dividing the number of times of false actions by the number of times of sending out the prompt signal may be used as a specific value of the hand's coordinated motion quality, and the higher the quotient, the higher the hand's coordinated motion quality. In a preferred implementation mode, the coordinated motion quality of the hand can be calculated after the prompt signal commands all fingers to move for more than 10 times, so that the accuracy of the result can be improved.
In a preferred embodiment, the finger motion estimation method provided by the invention further comprises the following steps:
S103, acquiring a health evaluation rule, wherein the health evaluation rule comprises at least two health grades and a range of evaluation results corresponding to the health grades;
and S104, obtaining the health grade based on the health evaluation rule and the evaluation result.
In the above embodiments, different types of evaluation results of the finger-dividing exercise evaluation method provided by the present invention have been described, but these evaluation results are often professional or difficult to understand, for example, the maximum explosive force of the whole hand of the hand, and simply looking at the value, it may be difficult for the person to understand what level the maximum explosive force of the whole hand of the person to be evaluated is, so in the process S103, the health evaluation rule corresponding to the evaluation result may be obtained for the different types of evaluation results, for example, the grip strength of 20kg-30kg is defined as three levels, the grip strength of 30kg-40kg is defined as two levels, the grip strength of 40kg-50kg is defined as one level, and the health evaluation rule corresponding to the evaluation result may be obtained by performing corresponding setting according to the specific evaluation result.
In the process S104, after the health evaluation rule and the evaluation result are obtained, a simple and easily understood health grade can be obtained, so that the readability of the evaluation result is greatly improved.
As a preferred embodiment, the invention also provides a finger movement health assessment device, as shown in fig. 3. The finger-dividing sports health assessment device comprises
The finger separation testing device 1 comprises a device main body 10, a thumb key 11, an index finger key 12, a middle finger key 13, a ring finger key 14, a little finger key 15 and a pressure sensing component 16, wherein the pressure sensing component 16 is arranged inside the device main body 10, the thumb key 11, the index finger key 12, the middle finger key 13, the ring finger key 14 and the little finger key 15 are sequentially arranged on the surface of the device main body 10 and are connected with the pressure sensing component 16, and the pressure sensing component 16 is used for acquiring the motion data of each finger of a single hand through the thumb key 11, the index finger key 12, the middle finger key 13, the ring finger key 14 and the little finger key 15;
the storage module 2 is at least used for storing the evaluation rule;
The evaluation module 3, the evaluation module 3 is connected to the storage module 2 and the pressure sensing component 16 and is used for executing the finger movement evaluation methods according to the first to fourth embodiments, and the evaluation result is obtained based on the movement data and the evaluation rule.
As shown in fig. 3, the storage module 2 and the evaluation module 3 may be embedded in the device main body 10, or may be wirelessly connected with the pressure sensing component 16 through a bluetooth connection to be disposed outside the device main body 10, for example, the storage module 2 and the evaluation module 3 may be integrally configured as a personal computer capable of wirelessly connecting with the pressure sensing component 16 through a bluetooth connection, so as to meet the requirements of storing, processing data, displaying, and the like. The memory module 2 may be in various forms such as a Static Random Access Memory (SRAM), a Dynamic Random Access Memory (DRAM), and the like. Of course, other auxiliary components such as a display screen and a storage battery may be further disposed on the device main body 10, which will not be described in detail.
A reset key 17, wherein the reset key 17 is used for inputting an instruction for the command evaluation module 3 to execute the finger dividing motion evaluation method again;
As shown in fig. 3, the device body 10 preferably includes a top surface 100 and a bottom surface 101 facing away from each other, and an outer peripheral surface 102 connecting the top surface 100 and the bottom surface 101, the thumb key 11 is provided on the top surface 100, the reset key 17 is provided on the bottom surface 101, and the index finger key 12, the middle finger key 13, the ring finger key 14, and the little finger key 15 are arranged on the outer peripheral surface 102 in the same direction and are sequentially separated from the thumb key 11. Thus, the utility model is more ergonomic and is convenient to hold and exert force. The device main body 10, the thumb key 11, the index finger key 12, the middle finger key 13, the ring finger key 14 and the little finger key 15 can be set to different ergonomic shapes according to different ages and different hand shapes of the targeted crowd, and the specific design modes are not repeated one by one, so that the requirements of ergonomics can be met.
Preferably, the device body 10, the thumb button 11, the index button 12, the middle button 13, the ring button 14 and the little button 15 are all symmetrical structures and share a symmetrical plane. Therefore, the finger-dividing motion health assessment device provided by the embodiment of the invention can meet the holding and assessment requirements of the left hand and the right hand, and can be used for assessing the two hands under the same holding condition, so that the assessment cost is reduced.
The application also provides a computer readable medium having stored thereon a computer program which, when executed by a processor, implements a finger motion assessment method as described above. The computer readable media includes both permanent and non-permanent, removable and non-removable media, and the media may be implemented in any method or technology for storage of information. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
The above description is only illustrative of the preferred embodiments of the present application and of the principles of the technology employed. It will be appreciated by persons skilled in the art that the scope of the application referred to in the present application is not limited to the specific combinations of the technical features described above, but also covers other technical features formed by any combination of the technical features described above or their equivalents without departing from the inventive concept. Such as the above-mentioned features and the technical features disclosed in the present application (but not limited to) having similar functions are replaced with each other.
Claims (9)
1. The finger movement assessment method is characterized by comprising the following steps of:
acquiring motion data of each finger of a single hand, and acquiring an evaluation rule;
Obtaining an evaluation result for the single hand based on the motion data and the evaluation rule;
The motion data comprises a grip strength value-time curve of each finger, and the evaluation result is the full hand grip strength level of the single hand;
The evaluation rule includes:
acquiring a preset grip strength threshold value, and acquiring an average value and a standard deviation of grip strength based on the grip strength numerical value-time curve;
the Quan Shouwo-force endurance level includes at least one of a grip achievement time obtained based on the grip numerical value-time curve and the preset grip threshold, a sum of curve integrals of the grip numerical value-time curve of each finger, a number of times the grip numerical value-time curve fluctuates by more than one of the standard deviations with respect to the average;
When the Quan Shouwo force endurance level simultaneously comprises the time reaching the standard of the grip obtained based on the grip numerical value-time curve and the preset grip threshold, the sum of curve integrals of the grip numerical value-time curve of each finger, and the times of fluctuation of the grip numerical value-time curve relative to the average value exceeding one standard deviation, firstly comparing the time reaching the standard of the grip obtained based on the grip numerical value-time curve and the preset grip threshold, when the time reaching the standard of the grip is the same, integrating the curves of the grip numerical value-time curve of each finger and solving the sum of the integrals, judging the output degree of the grip, and when the output degree of the grip is the same, comparing the times of fluctuation of the grip numerical value-time curve relative to the average value exceeding one standard deviation;
Also included is a method of manufacturing a semiconductor device,
Acquiring a health evaluation rule, wherein the health evaluation rule comprises at least two health grades and a range of evaluation results corresponding to the health grades;
based on the health evaluation rule and the evaluation result, a health grade is obtained.
2. The finger movement assessment method according to claim 1, wherein,
The motion data comprises a maximum grip strength value of each finger, and the evaluation result comprises a full-hand maximum explosive force of the single hand;
The evaluation rule includes: the maximum explosive force of the whole hand comprises: the sum of the product of the maximum grip value of the thumb and the first weight, the product of the maximum grip value of the index finger and the second weight, the product of the maximum grip value of the middle finger and the third weight, the product of the maximum grip value of the ring finger and the fourth weight, and the product of the maximum grip value of the little finger and the fifth weight.
3. The finger motion estimation method according to claim 2, wherein the first weight ranges from 0.2 to 0.3, the second weight ranges from 0.15 to 0.25, the third weight ranges from 0.15 to 0.25, the fourth weight ranges from 0.05 to 0.2, and the fifth weight ranges from 0.01 to 0.15.
4. The finger movement assessment method according to claim 2, wherein,
The evaluation result also comprises a grip strength value of the single hand health evaluation;
the evaluation rule further includes:
Continuously obtaining at least five times of full-hand maximum explosive force;
And obtaining the health evaluation grip strength value of the single hand based on the sum of the maximum explosive force of the whole hand and the acquisition times of the maximum explosive force of the whole hand.
5. The finger movement assessment method according to claim 1, wherein,
The motion data comprise a maximum grip strength value of each finger and a strength value of a reaction motion of each finger corresponding to a prompt signal, the prompt signals comprise prompt signals for requesting at least one finger to perform motion, and the evaluation result is the coordinated motion quality of the single hand;
The evaluation rule includes:
Determining that the finger does not require to act according to the prompt signal;
judging whether the force value of the finger which does not require action exceeds 10% -30% of the maximum grip strength value, if so, recording as one false action;
and obtaining the coordinated movement quality of the single hand based on the times of the false actions and the sending times of the prompt signals.
6. A finger-dividing exercise health assessment device, comprising:
The finger separation testing device (1) comprises a device main body (10), a thumb key (11), an index finger key (12), a middle finger key (13), a ring finger key (14), a little finger key (15) and a pressure sensing component (16), wherein the pressure sensing component (16) is arranged inside the device main body (10), the thumb key (11), the index finger key (12), the middle finger key (13), the ring finger key (14) and the little finger key (15) are sequentially arranged on the surface of the device main body (10) and are connected with the pressure sensing component (16), and the pressure sensing component (16) is used for acquiring motion data of each finger of a single hand through the thumb key (11), the index finger key (12), the middle finger key (13), the ring finger key (14) and the little finger key (15);
A storage module (2), the storage module (2) being at least for storing evaluation rules;
An evaluation module (3), the evaluation module (3) being connected to the storage module (2) and the pressure sensing assembly (16) and being configured to perform the finger-motion evaluation method according to any one of claims 1 to 5, the evaluation result being obtained based on the motion data and the evaluation rules;
The motion data comprises a grip strength value-time curve of each finger, and the evaluation result is the full hand grip strength level of the single hand;
The evaluation rule includes:
acquiring a preset grip strength threshold value, and acquiring an average value and a standard deviation of grip strength based on the grip strength numerical value-time curve;
the Quan Shouwo-force endurance level includes at least one of a grip achievement time obtained based on the grip numerical value-time curve and the preset grip threshold, a sum of curve integrals of the grip numerical value-time curve of each finger, a number of times the grip numerical value-time curve fluctuates by more than one of the standard deviations with respect to the average;
When the Quan Shouwo force endurance level simultaneously comprises the time reaching the standard of the grip obtained based on the grip numerical value-time curve and the preset grip threshold, the sum of curve integrals of the grip numerical value-time curve of each finger, and the times of fluctuation of the grip numerical value-time curve relative to the average value exceeding one standard deviation, firstly comparing the time reaching the standard of the grip obtained based on the grip numerical value-time curve and the preset grip threshold, when the time reaching the standard of the grip is the same, integrating the curves of the grip numerical value-time curve of each finger and solving the sum of the integrals, judging the output degree of the grip, and when the output degree of the grip is the same, comparing the times of fluctuation of the grip numerical value-time curve relative to the average value exceeding one standard deviation;
Also included is a method of manufacturing a semiconductor device,
Acquiring a health evaluation rule, wherein the health evaluation rule comprises at least two health grades and a range of evaluation results corresponding to the health grades;
based on the health evaluation rule and the evaluation result, a health grade is obtained.
7. The finger movement health assessment device according to claim 6, wherein the finger test device (1) further comprises a reset key (17), the reset key (17) being used for inputting instructions instructing the assessment module (3) to re-execute the finger movement assessment method;
The device body (10) is provided with a top surface (100) and a bottom surface (101) which are deviated from each other, and an outer peripheral surface (102) which is connected with the top surface (100) and the bottom surface (101), the thumb key (11) is arranged on the top surface (100), the reset key (17) is arranged on the bottom surface (101), the index finger key (12), the middle finger key (13), the ring finger key (14) and the little finger key (15) are arranged on the outer peripheral surface (102) along the same direction and are sequentially far away from the thumb key (11).
8. The finger-separating sports health assessment device according to claim 7, wherein said device body (10), said thumb key (11), said index finger key (12), said middle finger key (13), said ring finger key (14) and said little finger key (15) are all symmetrical structures and are common symmetry planes.
9. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the finger motion assessment method according to any one of claims 1 to 5.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2441580C1 (en) * | 2010-08-19 | 2012-02-10 | Владимир Александрович Орлов | Method for estimation of reserves of physical health and working capacity of population |
| CN103251419A (en) * | 2013-04-25 | 2013-08-21 | 西安交通大学苏州研究院 | Data gloves for function rehabilitation training and assessment of hands and monitoring method thereof |
| CN105726047A (en) * | 2016-02-04 | 2016-07-06 | 杭州爱握科技有限公司 | Comprehensive grip testing system and testing method thereof |
| CN108430329A (en) * | 2015-05-19 | 2018-08-21 | 巴黎笛卡尔大学 | Method for assessing hand flexibility |
| CN108972540A (en) * | 2017-05-30 | 2018-12-11 | 佳能株式会社 | Robot, the control method of robot and robot device |
| CN109512443A (en) * | 2018-11-23 | 2019-03-26 | 史东平 | A kind of intelligence muscular strength detector |
| CN113425574A (en) * | 2021-05-17 | 2021-09-24 | 自贡市第一人民医院 | Multifunctional rehabilitation device |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7631557B2 (en) * | 2007-01-24 | 2009-12-15 | Debeliso Mark | Grip force transducer and grip force assessment system and method |
| US20180126219A1 (en) * | 2016-11-10 | 2018-05-10 | Koninklijke Philips N.V. | Methods and apparatuses for handgrip strength assessment using pressure-sensitive elements |
-
2021
- 2021-10-29 CN CN202111280346.8A patent/CN114098713B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2441580C1 (en) * | 2010-08-19 | 2012-02-10 | Владимир Александрович Орлов | Method for estimation of reserves of physical health and working capacity of population |
| CN103251419A (en) * | 2013-04-25 | 2013-08-21 | 西安交通大学苏州研究院 | Data gloves for function rehabilitation training and assessment of hands and monitoring method thereof |
| CN108430329A (en) * | 2015-05-19 | 2018-08-21 | 巴黎笛卡尔大学 | Method for assessing hand flexibility |
| CN105726047A (en) * | 2016-02-04 | 2016-07-06 | 杭州爱握科技有限公司 | Comprehensive grip testing system and testing method thereof |
| CN108972540A (en) * | 2017-05-30 | 2018-12-11 | 佳能株式会社 | Robot, the control method of robot and robot device |
| CN109512443A (en) * | 2018-11-23 | 2019-03-26 | 史东平 | A kind of intelligence muscular strength detector |
| CN113425574A (en) * | 2021-05-17 | 2021-09-24 | 自贡市第一人民医院 | Multifunctional rehabilitation device |
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