CN113069752A - Operation trend judgment method based on force acquisition device - Google Patents
Operation trend judgment method based on force acquisition device Download PDFInfo
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
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- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
- A63B71/0622—Visual, audio or audio-visual systems for entertaining, instructing or motivating the user
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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
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0686—Timers, rhythm indicators or pacing apparatus using electric or electronic means
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- A—HUMAN NECESSITIES
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- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
- A63B71/0622—Visual, audio or audio-visual systems for entertaining, instructing or motivating the user
- A63B2071/0625—Emitting sound, noise or music
- A63B2071/063—Spoken or verbal instructions
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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
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
- A63B2071/065—Visualisation of specific exercise parameters
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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
- A63B2230/08—Measuring physiological parameters of the user other bio-electrical signals
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Abstract
The invention provides an operation trend judgment method based on a force acquisition device. The strength collection device comprises: training frame, training movable part, strength acquisition sensor, microprocessor, display module, voice broadcast module. The force acquisition sensor acquires force signals at multiple moments in real time in each period and transmits the force signals to the microprocessor; the microprocessor preprocesses the force signal acquired in real time in each period through data to obtain a preprocessed force signal in each period; and the microprocessor calculates the accelerations in two adjacent periods according to the preprocessed force signals in each period, further performs trend judgment according to the accelerations in the two adjacent periods, updates the data of the display module according to the result of the trend judgment, and controls the voice broadcasting module to perform voice broadcasting counting. The invention has the advantages that the system structure is optimized compared with the trend judgment by using infrared equipment, the accuracy of the trend judgment is improved, and the method has the characteristic of no interference of light.
Description
Technical Field
The invention belongs to the technical field of microcontroller application, and particularly relates to an operation trend judgment method based on a force acquisition device.
Background
The leg trainer is a device for training leg strength and speed of track and field athletes. Traditional shank strength training ware does not contain the electric part, and training data need lean on artifical the record at every turn, and the strength size of training at every turn is unknown, and the time interval of two training is timed by the manual work, has certain error, and simultaneously all motion data of sportsman can't upload to the system automatically and store, and these are not convenient for do detailed analysis and make corresponding training plan to sportsman's training situation.
Increase electrical equipment and count time to the sportsman's training condition, need judge the motion trend of sportsman in the training, prior art adopts infrared equipment to carry out the trend and judges, and the judged result easily receives infrared light to influence, and the rate of accuracy is not high, and equipment system structure is complicated and to service environment light requirement higher, can't satisfy sportsman's training operation requirement.
Disclosure of Invention
Based on the technical problem of the background art, the invention provides an operation trend judgment method based on a force acquisition device.
The technical scheme of the invention is an operation trend judgment method based on a force acquisition device.
The strength collection device comprises: the training frame, the training movable part, the strength acquisition sensor, the microprocessor, the display module and the voice broadcasting module;
the strength acquisition sensor is fixed on the training frame and is connected with the training movable part through a bolt; the microprocessor is respectively connected with the force acquisition sensor, the display module and the voice broadcast module in sequence in a wired mode;
the force acquisition sensor acquires force signals at multiple moments in real time in each period and transmits the force signals to the microprocessor;
the microprocessor acquires force signals at a plurality of moments in real time in each period to realize the operation trend judgment method and obtain force statistical signals;
the microprocessor controls the voice broadcasting module to carry out voice broadcasting counting according to the force statistical signal;
the microprocessor displays training time, training times and maximum training force values through the display module, wherein the training time is the interval time from the beginning of the first effective training to the end of the last effective training, the times are the total times that the force exceeds the force threshold value in the training process, namely, the training time is counted once when each running trend is judged to be changed from forward to sequential and the maximum force value exceeds the force threshold value, the maximum value of the single training is the maximum force value stored in the process from the judgment of the running trend to the judgment of the running trend in the backward process, the maximum value in the training is the maximum value in the maximum force value of each training in the training process, the training is restarted after the training is suspended in the middle of the training time and the times, and the data are obtained after recalculation;
the operation trend determination method comprises the following steps:
step 1: the force acquisition sensor acquires force signals at multiple moments in real time in each period and transmits the force signals to the microprocessor;
step 1, acquiring force signals at multiple moments in real time in each period, specifically defining as:
datai,j
i∈[1,M],j∈[1,N]
wherein, the datai,jThe force signals of the jth acquisition moment in the ith acquisition period are represented, M represents the number of the acquisition periods, and N represents the number of the force signals acquired in each acquisition period;
step 2: the microprocessor preprocesses the force signal acquired in real time in each period through data to obtain a preprocessed force signal in each period;
and step 2, the data preprocessing comprises the following steps: data oni,1,datai,2,...,datai,NAnd (3) the maximum value and the minimum value are screened out, and the average value is calculated in the rest N-2 force signals, so that the preprocessed force signals in each period are obtained as follows: powi,i∈[1,M]；
And step 3: the microprocessor calculates accelerations in two adjacent periods according to the preprocessed force signals in each period, further performs trend judgment according to the accelerations in the two adjacent periods, updates display module data according to the result of the trend judgment, and controls the voice broadcasting module to perform voice broadcasting counting;
and 3, calculating the acceleration in two adjacent periods as follows:
wherein, powiRepresenting the preprocessed force signal, pow, in the ith cyclei-1Representing the preprocessed force signal in the (i-1) th period, wherein M represents the number of acquisition periods;
and 3, further performing trend judgment according to the acceleration in two adjacent periods:
if it is
Judging that the movement trend is forward;
if it is
Judging that the movement trend is backward;
the timer in the microprocessor records the time of the first movement trend as time1,start
If the first adjacent period and the second adjacent period in the four continuous adjacent periods have forward motion trends and the third adjacent period and the fourth adjacent period have backward motion trends, judging to be a reciprocating training and recording as a c-th reciprocating training;
if the motion trends of two continuous adjacent periods appear forward and the motion trends of two continuous adjacent periods appear backward for the first time after a period of time, judging the training as the first reciprocating training and recording as the c-th reciprocating training;
respectively recording the starting time of the first adjacent period in the c-th reciprocating training as time by the internal timer of the microprocessorc,1The starting time of the second adjacent period in the c-th reciprocating training is timec,2The starting time of the third adjacent period in the c-th reciprocating training is timec,3The starting time of the fourth adjacent period in the c-th reciprocating training is timec,4；
Respectively recording the start time of the first adjacent period in the (c + 1) th reciprocating training as time by the internal timer of the microprocessorc+1,1And the starting time of the second adjacent period in the (c + 1) th reciprocating training is timec+1,2And the starting time of the third adjacent period in the (c + 1) th reciprocating training is timec+1,3And the starting time of the fourth adjacent period in the (c + 1) th reciprocating training is timec+1,4；
At timec,1And timec+1,1The microprocessor collects a plurality of strength signals from the c-th reciprocating training to the c + 1-th reciprocating training through the strength sensor, and further screens out the maximum value of the strength signal in each reciprocating training to be maxpowerc；
The timer in the microprocessor records the time of the last backward trend in the last time, namely the first count reciprocating training as the timecount,end；
The time of training is further calculated as: timecount,end-time1,start；
The training times are as follows: count;
the maximum values of the strength signals in each reciprocating training are as follows in sequence: maxpower1,maxpower2,...,maxpowercount(ii) a The training maximum force magnitude is: maxpower1,maxpower2,...,maxpowercountTake the maximum value as
maxpowerMP；
Step 3 according to the result update display module data, the control of trend judgement the voice broadcast module carries out the voice broadcast count, specifically does:
training times count, training maximum force value maxpowerMPUpdating the display;
control time of voice broadcast module voice broadcast trainingcoun,tend-time1,startTraining times count and training maximum force magnitude maxpowerMP。
The beneficial effects of the invention are as follows:
in the invention, the force acquisition device is adopted for trend judgment, compared with a system for judging the trend by using infrared equipment, the system structure is optimized by reducing the use types and the number of the sensors, and meanwhile, the system is not interfered by light rays, so that the accuracy of the trend judgment is improved.
The installation method of the information acquisition device is flexible, other modules except the information acquisition module of the whole system can be arranged outside or designed into a whole with the training equipment, the information acquisition device can be applied to newly designed equipment and can also be used for modifying old equipment, the application range is wide, and the information acquisition device can be used for leg training equipment, hand training equipment and the like.
Drawings
FIG. 1 is a block diagram of a system according to the present invention;
FIG. 2 is a flow chart of a method according to the present invention;
detailed description of the invention
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments.
The technical scheme of the specific implementation mode of the invention is an operation trend judgment method based on a force acquisition device.
The strength collection device comprises: the training frame, the training movable part, the strength acquisition sensor, the microprocessor, the display module and the voice broadcasting module;
the strength acquisition sensor is fixed on the training frame and is connected with the training movable part through a bolt; the microprocessor is respectively connected with the force acquisition sensor, the display module and the voice broadcast module in sequence in a wired mode;
the force acquisition sensor acquires force signals at multiple moments in real time in each period and transmits the force signals to the microprocessor;
the microprocessor acquires force signals at a plurality of moments in real time in each period to realize the operation trend judgment method and obtain force statistical signals;
the microprocessor controls the voice broadcasting module to carry out voice broadcasting counting according to the force statistical signal;
the microprocessor displays training time, training times and maximum training force values through the display module, wherein the training time is the interval time from the beginning of the first effective training to the end of the last effective training, the times are the total times that the force exceeds the force threshold value in the training process, namely, the training time is counted once when each running trend is judged to be changed from forward to sequential and the maximum force value exceeds the force threshold value, the maximum value of the single training is the maximum force value stored in the process from the judgment of the running trend to the judgment of the running trend in the backward process, the maximum value in the training is the maximum value in the maximum force value of each training in the training process, the training is restarted after the training is suspended in the middle of the training time and the times, and the data are obtained after recalculation.
The model of the force acquisition sensor is a DYLF-102 spoke type weighing sensor;
the type of the display module is DMT10768T080 Diwen smart screen;
the voice broadcasting module is a MY1680 voice module;
the microprocessor is selected to be an STC15W microcontroller;
the operation trend determination method comprises the following steps:
step 1: the force acquisition sensor acquires force signals at multiple moments in real time in each period and transmits the force signals to the microprocessor;
step 1, acquiring force signals at multiple moments in real time in each period, specifically defining as:
datai,j
i∈[1,M],j∈[1,N]
wherein, the datai,jRepresenting the force signals of the j-th acquisition time in the ith acquisition period, wherein M is 10 to represent the number of acquisition periods, and N is 5 to represent the number of the force signals acquired in each acquisition period;
step 2: the microprocessor preprocesses the force signal acquired in real time in each period through data to obtain a preprocessed force signal in each period;
and step 2, the data preprocessing comprises the following steps: data oni,1,datai,2,...,datai,NAnd (3) the maximum value and the minimum value are screened out, and the average value is calculated in the rest N-2 force signals, so that the preprocessed force signals in each period are obtained as follows: powi,i∈[1,M]；
And step 3: the microprocessor calculates accelerations in two adjacent periods according to the preprocessed force signals in each period, further performs trend judgment according to the accelerations in the two adjacent periods, updates display module data according to the result of the trend judgment, and controls the voice broadcasting module to perform voice broadcasting counting;
and 3, calculating the acceleration in two adjacent periods as follows:
wherein, powiRepresenting the preprocessed force signal, pow, in the ith cyclei-1Representing the preprocessed force signal in the (i-1) th period, wherein M represents the number of acquisition periods;
and 3, further performing trend judgment according to the acceleration in two adjacent periods:
if it is
Judging that the movement trend is forward;
if it is
Judging that the movement trend is backward;
the timer in the microprocessor records the time of the first movement trend as time1,start
If the first adjacent period and the second adjacent period in the four continuous adjacent periods have forward motion trends and the third adjacent period and the fourth adjacent period have backward motion trends, judging to be a reciprocating training and recording as a c-th reciprocating training;
if the motion trends of two continuous adjacent periods appear forward and the motion trends of two continuous adjacent periods appear backward for the first time after a period of time, judging the training as the first reciprocating training and recording as the c-th reciprocating training;
respectively recording the starting time of the first adjacent period in the c-th reciprocating training as time by the internal timer of the microprocessorc,1The starting time of the second adjacent period in the c-th reciprocating training is timec,2The starting time of the third adjacent period in the c-th reciprocating training is timec,3The starting time of the fourth adjacent period in the c-th reciprocating training is timec,4；
Respectively recording the start time of the first adjacent period in the (c + 1) th reciprocating training as time by the internal timer of the microprocessorc+1,1And the starting time of the second adjacent period in the (c + 1) th reciprocating training is timec+1,2And the starting time of the third adjacent period in the (c + 1) th reciprocating training is timec+1,3And the starting time of the fourth adjacent period in the (c + 1) th reciprocating training is timec+1,4；
At timec,1And timec+1,1The microprocessor collects a plurality of strength signals from the c-th reciprocating training to the c + 1-th reciprocating training through the strength sensor, and further screens out the maximum value of the strength signal in each reciprocating training to be maxpowerc；
The timer in the microprocessor records the time of the last backward trend in the last time, namely the first count reciprocating training as the timecount,end；
The time of training is further calculated as: timecount,end-time1,start；
The training times are as follows: count;
the maximum values of the strength signals in each reciprocating training are as follows in sequence: maxpower1,maxpower2,...,maxpowercount(ii) a The training maximum force magnitude is: maxpower1,maxpower2,...,maxpowercountTake the maximum value as
maxpowerMP；
Step 3 according to the result update display module data, the control of trend judgement the voice broadcast module carries out the voice broadcast count, specifically does:
training times count, training maximum force value maxpowerMPUpdating the display;
control time of voice broadcast module voice broadcast trainingcoun,tend-time1,startTraining times count and training maximum force magnitude maxpowerMP。
The above description is only one of the embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should cover the technical scope of the present invention, the technical solutions of the present invention and the inventive concept thereof with equivalent replacement or change.
Claims (4)
1. A method for judging operation trend based on a force acquisition device is characterized in that,
the strength collection device comprises: the training frame, the training movable part, the strength acquisition sensor, the microprocessor, the display module and the voice broadcasting module;
the strength acquisition sensor is fixed on the training frame and is connected with the training movable part through a bolt; the microprocessor is respectively connected with the force acquisition sensor, the display module and the voice broadcast module in sequence in a wired mode;
the force acquisition sensor acquires force signals at multiple moments in real time in each period and transmits the force signals to the microprocessor;
the microprocessor acquires force signals at a plurality of moments in real time in each period to realize the operation trend judgment method and obtain force statistical signals;
the microprocessor controls the voice broadcasting module to carry out voice broadcasting counting according to the force statistical signal;
the microprocessor displays training time, training times and maximum training force values through the display module, wherein the training time is the interval time from the beginning of the first effective training to the end of the last effective training, the times are the total times that the force exceeds the force threshold value in the training process, namely, the training time is counted once when each running trend is judged to be changed from forward to sequential and the maximum force value exceeds the force threshold value, the maximum value of the single training is the maximum force value stored in the process from the judgment of the running trend to the judgment of the running trend in the backward process, the maximum value in the training is the maximum value in the maximum force value of each training in the training process, the training is restarted after the training is suspended in the middle of the training time and the times, and the data are obtained after recalculation;
the operation trend determination method comprises the following steps:
step 1: the force acquisition sensor acquires force signals at multiple moments in real time in each period and transmits the force signals to the microprocessor;
step 2: the microprocessor preprocesses the force signal acquired in real time in each period through data to obtain a preprocessed force signal in each period;
and step 3: the microprocessor calculates accelerations in two adjacent periods according to the preprocessed force signals in each period, further performs trend judgment according to the accelerations in the two adjacent periods, updates display module data according to the result of the trend judgment, and controls the voice broadcasting module to perform voice broadcasting counting.
2. The power-harvesting-device-based operational trend determination method according to claim 1,
step 1, acquiring force signals at multiple moments in real time in each period, specifically defining as:
datai,j
i∈[1,M],j∈[1,N]
wherein, the datai,jThe force signals of the j acquisition time in the ith acquisition period are shown, M shows the number of acquisition periods, and N shows the number of the force signals acquired in each acquisition period.
3. The power-harvesting-device-based operational trend determination method according to claim 1,
and step 2, the data preprocessing comprises the following steps: data oni,1,datai,2,...,datai,NAnd (3) the maximum value and the minimum value are screened out, and the average value is calculated in the rest N-2 force signals, so that the preprocessed force signals in each period are obtained as follows: powi,i∈[1,M]。
4. The power-harvesting-device-based operational trend determination method according to claim 1,
and 3, calculating the acceleration in two adjacent periods as follows:
wherein, powiRepresenting the preprocessed force signal, pow, in the ith cyclei-1Representing the preprocessed force signal in the (i-1) th period, wherein M represents the number of acquisition periods;
and 3, further performing trend judgment according to the acceleration in two adjacent periods:
if it is
Judging that the movement trend is forward;
if it is
Judging that the movement trend is backward;
the timer in the microprocessor records the time of the first movement trend as time1,start
If the first adjacent period and the second adjacent period in the four continuous adjacent periods have forward motion trends and the third adjacent period and the fourth adjacent period have backward motion trends, judging to be a reciprocating training and recording as a c-th reciprocating training;
if the motion trends of two continuous adjacent periods appear forward and the motion trends of two continuous adjacent periods appear backward for the first time after a period of time, judging the training as the first reciprocating training and recording as the c-th reciprocating training;
respectively recording the starting time of the first adjacent period in the c-th reciprocating training as time by the internal timer of the microprocessorc,1The starting time of the second adjacent period in the c-th reciprocating training is timec,2The starting time of the third adjacent period in the c-th reciprocating training is timec,3The starting time of the fourth adjacent period in the c-th reciprocating training is timec,4.
Respectively recording the start time of the first adjacent period in the (c + 1) th reciprocating training as time by the internal timer of the microprocessorc+1,1And the starting time of the second adjacent period in the (c + 1) th reciprocating training is timec+1,2And the starting time of the third adjacent period in the (c + 1) th reciprocating training is timec+1,3And the starting time of the fourth adjacent period in the (c + 1) th reciprocating training is timec+1,4；
At timec,1And timec+1,1The microprocessor collects a plurality of strength signals from the c-th reciprocating training to the c + 1-th reciprocating training through the strength sensor, and further screens out the maximum value of the strength signal in each reciprocating training to be maxpowerc；
The timer in the microprocessor records the time of the last backward trend in the last time, namely the first count reciprocating training as the timecount,end；
The time of training is further calculated as: timecount,end-time1,start；
The training times are as follows: count;
the maximum values of the strength signals in each reciprocating training are as follows in sequence: max power1,max power2,...,max powercount；
The training maximum force magnitude is: max power1,max power2,...,max powercountTake the maximum value as max powerMP；
Step 3 according to the result update display module data, the control of trend judgement the voice broadcast module carries out the voice broadcast count, specifically does:
training times count, training maximum force magnitude max powerMPUpdating the display;
control time of voice broadcast module voice broadcast trainingcount,end-time1,startTraining times count and maximum force value max powerMP。
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| CN113945314A (en) * | 2021-10-14 | 2022-01-18 | 成都拟合未来科技有限公司 | Force measuring method |
| CN113945314B (en) * | 2021-10-14 | 2024-06-07 | 成都拟合未来科技有限公司 | Force measuring method |
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