TWI902311B - Physical fitness testing and training method and system thereof - Google Patents

Abstract

The present invention provides a physical fitness testing and training method, which includes: a training personnel data input step, a training mode selection step, a training content confirmation step, a training implementation step, a judging training personnel training status step, a training content ending step and a training record value return step. In addition, the present invention also provides a physical fitness testing and training system.

Description

Methods and systems for testing and training physical fitness

This invention relates to a physical fitness testing and training technique, and more particularly to a method and system for testing and training physical fitness.

Due to technological advancements and changes in people's economic lives, most people rely on machines for work and commuting. From initially walking or cycling to work, there are now numerous public transportation options. While this has increased work efficiency and made commuting more convenient, it has also reduced physical activity. More and more people are experiencing symptoms such as cardiovascular disease, mainly because they are too busy with work and have forgotten about regular exercise.

In view of this, there is an urgent need to develop a new type of fitness testing and training device that can combine technology and sports, making exercise more convenient. Compared with ordinary running, sports that combine technology can not only reduce the time required to achieve the desired exercise effect, but also reduce the occurrence of sports injuries.

Therefore, in order to address the aforementioned problems, the purpose of this invention is to provide a method for testing and training physical fitness, including: a trainee data input step, in which basic information of a trainee is input; and a training mode selection step, in which the training mode to be performed by the trainee is selected. The training program includes a training content confirmation step to confirm the training content items in the training mode; a training implementation step where the trainee begins implementing the training content; a training status assessment step to determine whether the trainee has completed the actions or whether any abnormalities have occurred during the training process; a training content completion step to confirm whether the training content items have been completed; and a training record value feedback step to send the training record values performed by the trainee back to a cloud database, which can be viewed through a webpage connected to the cloud database.

The method described above further includes a training record value comparison step, which compares the training record value with a simulation setting target to confirm whether the training record value has reached the simulation setting target.

As described above, the training content confirmation step further includes an exercise intensity confirmation step to confirm the type of exercise intensity in the training mode. The exercise intensity type includes low-intensity exercise, moderate-intensity exercise, and high-intensity exercise. The type of exercise intensity is defined using an effective heart rate range formula, wherein the effective heart rate range formula includes moderate-intensity exercise... The effective heart rate range for high-intensity exercise is equal to (220 - age - resting heart rate) × (40% to 59%) + resting heart rate. The effective heart rate range for high-intensity exercise is greater than (220 - age - resting heart rate) × (59%) + resting heart rate, and the effective heart rate range for low-intensity exercise is less than (220 - age - resting heart rate) × (40%) + resting heart rate.

As described above, the exercise intensity confirmation step further includes an input intensity type step, which selects one type of exercise intensity from the types of exercise intensity for training; an initial heart rate acquisition step, which measures and records the trainee's resting heart rate; and an effective heart rate calculation step, which uses the obtained resting heart rate of the trainee to calculate the effective heart rate range of the selected exercise intensity using the effective heart rate range formula.

In the method described above, the training content confirmation step further includes an exercise intensity confirmation step to confirm the type of exercise intensity in the training mode. The type of exercise intensity includes low-intensity exercise, moderate-intensity exercise, and high-intensity exercise. The type of exercise intensity is defined using a maximum heart rate range formula. The maximum heart rate range formula includes the maximum heart rate range of moderate-intensity exercise equal to (220 - age) × (64% to 74%), the maximum heart rate range of high-intensity exercise equal to (220 - age) × (85% to 90%), and the maximum heart rate range of low-intensity exercise equal to (220 - age) × (50% to 63%).

In the method described above, the step of judging the training status of the trainee includes using an image recognition method to obtain the trainee's motion images and analyze and judge the number of movements of the trainee. The image recognition method includes: a trainee image acquisition step, which obtains the trainee's motion images; a trainee image processing step, which processes the trainee's motion images and analyzes them to obtain the point coordinates of each part, and sets the limbs on both sides of the joint as vector a and vector b, respectively, using any joint as a vector reference point; and a trainee image judgment step, which substitutes the vector a and the vector b into the inner product formula. Calculate the one-vector angle between the limbs on both sides of the joint. Through the angle of that vector To determine the number of repetitions for the trainee.

Another objective of this invention is to provide a physical fitness testing and training system, comprising: a controller; a trainee data input module connected to the controller for inputting basic data of a trainee; a training mode selection module connected to the controller for selecting the training mode to be performed by the trainee; a training content confirmation module connected to the controller for confirming the training content items in the training mode; a training start implementation module connected to the controller for initiating the training content by the trainee, wherein the training start implementation module includes an image monitoring module connected to the controller for acquiring motion images of the trainee; and a system for determining the trainee's training progress. The status module, connected to the controller, is used to determine whether the trainee has completed the action or whether any abnormality has occurred during the training process. This training status determination module further includes: a safety warning module, connected to the controller, for issuing safety warning messages; and an action incomplete reminder module, connected to the controller, for issuing action incomplete reminders. The system includes: a reminder message; a training content completion module connected to the controller to confirm whether the training content item has been completed; and a training record value feedback module connected to the controller to feed back the training record values performed by the trainee to a cloud database, and to allow viewing of the training record values through a webpage connected to the cloud database.

The system described above further includes a training record value comparison module that connects to the cloud database and compares the training record value with a simulation setting target to confirm whether the training record value has reached the simulation setting target.

In the system described above, the training content completion module further includes a training standard attainment module to confirm whether the trainee's training results meet the training standards.

In the system described above, the start training implementation module includes a heart rate and blood oxygenation module connected to the controller for monitoring heart rate and blood oxygenation.

Therefore, this invention is designed to help people who don't have much time or don't usually exercise but want to exercise but don't know where to start. Users can train their health through this device, which provides personalized settings so that those who don't know how to train can follow the functions provided by the device. Currently, there are no products on the market designed with "physical fitness testing and training methods" in mind. This invention can systematically train users while utilizing multi-functional program diagnostics, integrating parameters such as heart rate and limb movements to achieve more efficient training results. The device can be controlled via an app and monitored by a camera or three-axis sensor. Multi-module guided judgment and detection can effectively prevent accidents and reduce sports injuries caused by exercise.

The purpose of this invention and its structural and functional advantages will be explained based on the structure shown in the following figures, along with specific embodiments, so that the review committee can have a deeper and more concrete understanding of this invention.

In the latest "2020 Global Fitness Trends Survey" released by the American College of Sports Medicine (ACSM), High-Intensity Interval Training (HIIT) ranked second. It has become increasingly popular around the world in recent years. HIIT is a type of exercise that combines high intensity with interval training. Its characteristic is that it trains to achieve changes in physical fitness through short periods of high-energy exercise followed by short periods of rest. Therefore, referring to Figures 1 and 2 simultaneously, this invention provides a method 1 for testing and training physical fitness and its program flow. This method 1 includes: a trainee data input step 11, inputting the basic information of a trainee; a training mode selection step 12, selecting the training mode to be performed by the trainee; a training content confirmation step 13, confirming the training content items in the training mode; and a training implementation step 14, where the trainee... The training content is implemented; a step 15 is to determine the trainee's training status, whether the trainee has completed the actions or whether any abnormalities have occurred during the training process; a step 16 is to confirm whether the training content has been completed; and a step 17 is to transmit the training record data back to a cloud database, and the training record data can be viewed through a webpage connected to the cloud database.

In some embodiments, the fitness testing and training method 1 further includes a training record value comparison step 18, which compares the training record value with a simulated target to confirm whether the training record value has reached the simulated target, as shown in Figure 1. In this embodiment, the basic information of the trainee includes age or gender, but is not limited to these, and may also include height or weight. The training mode includes cardiorespiratory capacity training, muscle capacity training, or reaction capacity training, etc., to meet the needs of different ability training. The simulation target can be physical fitness statistics of a country's people, but is not limited to that. It can also be physical fitness statistics of a school's students, recommended physical fitness data from a research unit or government unit, or recommended physical fitness data obtained after artificial intelligence processing.

Furthermore, in this embodiment, referring to Figure 3, to allow trainees to select appropriate exercise intensity, training content confirmation step 13 also includes an exercise intensity confirmation step 130, which confirms the type of exercise intensity in the training mode. This type of exercise intensity includes low-intensity exercise, moderate-intensity exercise, and high-intensity exercise. The type of exercise intensity is defined using an effective heart rate range formula. The formula for the effective heart rate range includes the following: the effective heart rate range for moderate-intensity exercise is equal to (220 - age - resting heart rate) × (40% to 59%) + resting heart rate; the effective heart rate range for high-intensity exercise is greater than (220 - age - resting heart rate) × (59%) + resting heart rate; and the effective heart rate range for low-intensity exercise is less than (220 - age - resting heart rate) × (40%) + resting heart rate.

Please refer to Figure 3. In this embodiment, the exercise intensity confirmation step 130 further includes: an input intensity type step 131, which selects one type of exercise intensity from the types of exercise intensity for training; an initial heart rate acquisition step 132, which measures and records the trainee's heart rate at rest; and an effective heart rate calculation step 133, which uses the obtained heart rate of the trainee at rest to calculate the effective heart rate range of the selected exercise intensity using the effective heart rate range formula.

However, not limited thereto, in another embodiment, the invention provides another exercise intensity confirmation step to confirm the type of exercise intensity in the training mode. The type of exercise intensity includes low-intensity exercise, moderate-intensity exercise, and high-intensity exercise. The type of exercise intensity is defined using a maximum heart rate range formula, wherein the maximum heart rate range formula includes the maximum heart rate range of the moderate-intensity exercise equal to (220 - age) × (64% to 74%), the maximum heart rate range of the high-intensity exercise equal to (220 - age) × (85% to 90%), and the maximum heart rate range of the low-intensity exercise equal to (220 - age) × (50% to 63%).

Understandably, in some embodiments, when the maximum heart rate is used as the calculation standard, the effective heart rate calculation step 133 in the exercise intensity confirmation step 130 above can be transformed into a maximum heart rate calculation step, so that the obtained resting heart rate of the trainee can be used to calculate the maximum heart rate range of the selected exercise intensity using the maximum heart rate range formula.

Furthermore, it is understandable that the aforementioned types of exercise intensity are primarily defined using an effective heart rate range or a maximum heart rate range. Heart rate (or simply heart rate) is mainly directly related to cardiopulmonary function training, while its relationship with muscle strength training is less direct. Therefore, when the training content in the training mode is confirmed to be muscle strength training, step 13 of the training content confirmation includes an input of load weight and repetitions to define the load weight and repetitions included in the training content. The intensity of exercise can be defined by different ranges of load weight and repetitions. Similarly, when the training content in the training mode is confirmed to be reaction training, since reaction training is also directly related to cardiopulmonary function training, the type of exercise intensity can be the same as or similar to that of cardiopulmonary function training. However, it is not limited to this, and other methods can also be used to define the magnitude of exercise intensity. Therefore, in the training content confirmation step 13, an intensity input step can be included to define the intensity of the reaction training included in the training content.

In this embodiment, referring to Figures 4 and 5, step 15 of judging the training status of the trainee includes using an image recognition method 150 to obtain the trainee's motion image and analyze and judge the number of movements of the trainee. The image recognition method 150 includes: a trainee image acquisition step 151, obtaining the trainee's motion image; a trainee image processing step 152, processing the trainee's motion image and analyzing it to obtain the point coordinates of each part, and using any joint as a vector reference point, setting the limbs on both sides of the joint as vector a and vector b respectively; and a trainee image judgment step 153, substituting the vector a and the vector b into the inner product formula. Calculate the one-vector angle between the limbs on both sides of the joint. Through the angle of that vector To determine the number of repetitions for the trainee.

In addition, in this embodiment, referring to Figures 5 and 6, the trainee image processing step 152 may also include a color tone conversion step 154 to adjust and convert the color tone of the trainee's motion image; a body part coordinate acquisition step 155 to obtain the coordinates of the body parts of the trainee's motion image; and a vector acquisition step 156 to convert the coordinates of the body parts of the trainee's motion image into vectors.

Understandably, in the image processing step 152 of the trainee, during the identification and analysis process, the coordinates of each part will obtain a key parameter called visibility, with a value between 0 and 1. If the value is lower than 0.5, the part is usually considered invisible, which means that the coordinates of the point may be incorrect, and therefore the point will not be used or drawn. The image identification method 150 mentioned above obtains the coordinates of various parts of the human body from the image through an algorithm. The image identification method 150 converts the coordinates of the parts of the human body image that need to be measured into vectors, and uses the inner product formula to obtain the vector angles. Finally, the number of times various movements are determined by the angles of various parts of the human body image.

It's worth noting that if a trainee's movements remain unchanged for an extended period during exercise, or if the camera fails to capture the trainee for a long time, a signal will be sent to activate a buzzer, as shown in Figure 5. If the identification result remains abnormal, a signal will be sent to the warning system for further processing. Furthermore, if a trainee's movements are not standard during training, causing the image sensor calculation to deviate from the angular standard, the movement will be deemed incomplete, and an audio or visual alert will be issued to the trainee. In other words, step 15 of the trainee training status assessment determines whether the trainee has completed the movement or whether any abnormalities have occurred during the training process. Completion of the movement includes whether the posture is correct, the intensity of the exercise is sufficient, the number of repetitions is sufficient, and whether the movement is completed within the allotted time. Abnormalities include sports injuries or accidents. Therefore, step 15 of the trainee training status assessment also includes a step to remind relevant personnel of the current training status, including trainers, safety personnel, and monitoring personnel.

Referring to Figure 7, this invention provides a physical fitness testing and training system 2, comprising: a controller 21; a trainee data input module 22 connected to the controller 21 for inputting basic data of a trainee; a training mode selection module 23 connected to the controller 21 for selecting the training mode to be performed by the trainee; a training content confirmation module 24 connected to the controller 21 for confirming the training content items in the training mode; and a training start implementation module 25 connected to the controller 21 for allowing the trainee to start training. The trainee begins implementing the training content. The training implementation module 25 includes an image monitoring module 251 connected to the controller 21 to acquire images of the trainee's movements. However, it is not limited to this; the training implementation module 25 also includes a sensing module 252 connected to the controller 21 to confirm whether the trainee has reached the target area. This sensing module 252 includes an infrared sensor, an optical sensor, or a pressure sensor, etc., to determine the trainee's training progress. The status module 26, connected to the controller 21, is used to determine whether the trainee has completed the action or whether any abnormality has occurred during the training process. The training status determination module 26 further includes a safety warning module 261, connected to the controller 21, for issuing safety warning information; an action incomplete reminder module 262, connected to the controller 21, for issuing action incomplete reminder information; and a training content completion module 27, connected to the controller 21, for confirming whether the training content item has been completed. A training record data feedback module 28, connected to the controller 21, is used to feed back the training record data performed by the trainee to a cloud database D, and the training record data can be viewed through a webpage W connected to the cloud database D; and a training record data comparison module 29, connected to the cloud database D, compares the training record data with a simulation setting target to confirm whether the training record data has reached the simulation setting target, and the comparison result can be viewed through the webpage W connected to the cloud database D.

It is understood that the connection between the controller 21 and various modules can be wired or wireless. Different signal connection methods can be designed according to different needs. Wireless connection can be achieved using various wireless transmission tools, such as WIFI and 5G. The web page W can be connected wirelessly to personal computers, smartphones, or tablets. In this embodiment, referring to Figure 7, the training content completion module 27 further includes a training standard attainment module 271, which is used to confirm whether the trainee's training results have reached the previously set training standards. These training standards include exercise intensity standards or exercise frequency standards.

Furthermore, in this embodiment, the initial training module 25 includes a heart rate and blood oxygenation module 253 connected to the controller for monitoring heart rate and blood oxygenation. It is understood that this heart rate and blood oxygenation module 253 can be worn by the trainee to obtain real-time physiological data such as heart rate and blood oxygenation. Moreover, in this embodiment, the trainee's basic information includes age and gender, and the training mode includes cardiorespiratory fitness training, muscle strength training, and reaction time training. The cardiorespiratory fitness training includes running, cycling, rope skipping, swimming, etc.

In this embodiment, referring to Figure 8, the training content confirmation module 24 includes an exercise intensity confirmation module 241, which further includes: an input intensity type module 241a, which selects one type of exercise intensity from the types of exercise intensity for training; an initial heart rate acquisition module 241b, which measures and records the trainee's heart rate at rest; and an effective heart rate calculation module 241c, which calculates the effective heart rate range of the selected exercise intensity by using the obtained heart rate of the trainee at rest according to the effective heart rate range formula. Understandably, in some embodiments, when the maximum heart rate is used as the calculation standard, the effective heart rate calculation module 241c can be transformed into a maximum heart rate calculation module to calculate the maximum heart rate range of the selected exercise intensity by using the maximum heart rate range formula to obtain the trainee's resting heart rate.

Referring to Figure 9, in some embodiments, the trainee training status assessment module 26 includes an image recognition module 263, which comprises: a trainee image acquisition module 2631 for acquiring the trainee's motion images; a trainee image processing module 2632 for processing and analyzing the trainee's motion images to obtain the point coordinates of each part, and using any joint as a vector reference point, setting the limbs on both sides of the joint as vector a and vector b respectively; and a trainee image assessment module 2633 for processing the vector a... ) and the vector b ( Substitute into the dot product formula Calculate the vector angle θ between the limbs on both sides of the joint, and use this vector angle θ to determine the number of repetitions of the trainee. Understandably, the image recognition module 263 here can be integrated with the aforementioned image monitoring module 251. In other words, the image monitoring module 251, which has the function of acquiring the trainee's action images, can directly transmit the image data to the trainee image processing module 2632 in the image recognition module 263 for processing, without having to obtain the trainee's action images through the trainee image acquisition module 2631. However, this is not the only option. Another option is that the trainee image acquisition module 2631 in the image recognition module 263 is not integrated with the image monitoring module 251, but is a separate module to adapt to different functions and needs.

Furthermore, referring to Figure 9, in this embodiment, the trainer image processing module 2632 includes: a color tone conversion module 2632a, used to perform color tone adjustment and conversion on the trainer's motion image; a body part coordinate acquisition module 2632b, used to acquire the coordinates of the body parts of the trainer's motion image; and a vector acquisition module 2632c, used to convert the coordinates of the body parts of the trainer's motion image into vectors.

Based on the aforementioned detection and training method and system, the present invention establishes the following specific implementation example. Training is generally monotonous; therefore, this invention adds some variability to the training process, allowing a simple exercise to achieve more and better results. To achieve this, a combination of Raspberry Pi and various modules is used. The training method uses five devices with a Raspberry Pi mainboard. Each device contains an RGB LED, a communication module, a microcontroller, and an infrared sensor. The placement of the devices changes according to the selected mode.

According to the formula for the effective heart rate range mentioned above: the effective heart rate range for moderate-intensity exercise = (220 - age - resting heart rate) × (40%~59%) + resting heart rate. A higher heart rate range indicates high-intensity exercise, while a lower range indicates low-intensity exercise. For example, a 35-year-old with a resting heart rate of 70 beats per minute would need to reach a heart rate of 138 beats per minute or higher to be considered high-intensity exercise. Therefore, the following training modes can be divided into three types based on the programming.

Mode 1: Running Training

Please refer to Figure 10. On the track, place a device E every 20 meters. Sprint to the designated point according to the light signal on device E (which corresponds to the indicator light on the main control panel), and press the corresponding button. The second light will then illuminate. Repeat this process. After all five devices E have illuminated, you will enter rest mode (the indicator light will be green). Slowly walk back to the starting point, measure your heart rate, and report it back. After the rest period, prepare for the second set of running training (the indicator light will be yellow). Press the start button on the main control panel and sprint according to the light signal on device E.

1. Low-intensity exercise: light exercise

When device E lights up, walk, jog, or stretch to the designated spot and press the button, repeating the action. Due to its extremely high safety, it is suitable for the elderly, those with cardiovascular diseases, and others.

2. Moderate-intensity exercise: Reduced-intensity high-intensity training (REHIT)

Reduced-exertion high-intensity training (REHIT) is a high-intensity interval training program with a lower number of sprints, typically following a pattern of "2 minutes warm-up, 20 seconds sprint, 3 minutes recovery, 20 seconds sprint again, and 3 minutes cool-down." Like other past studies on HIIT, REHIT may be a more cost-effective way to improve cardiovascular fitness.

3. High-Intensity Exercise: High-Intensity Interval Training (HIIT)

High-intensity interval training (HIIT) involves sprinting 150 meters at 82% of your maximum heart rate, counting the seconds and heart rate. The first 10 minutes of recovery (cool-down) should be 60 seconds, and the next 10 minutes of recovery (cool-down) should be 120 seconds. Each session should last 20 minutes, 3 times a week. This is a feasible form of HIIT.

Intensity comparison: taking 18-year-olds as an example

For trainees of a specific age, such as 18, this invention provides a suggested simulation for setting goals, with the intensity of the suggested goals listed below: Average recommended time per group It is recommended to reach the heart rate value rest time Low-intensity exercise without 80~100 (beats/minute) without Moderate intensity exercise 16s (100m) 128~148 (downs per minute) 3 points High-intensity exercise 20s (150m) 170~180 (down/minute) 1~2 points

Mode Two: Muscle Training

In Taiwan, one in ten elderly people suffers from sarcopenia. Sarcopenia is characterized by the rapid loss of muscle mass with age, which can eventually lead to disability, inability to care for oneself, and in severe cases, even death. Therefore, it is crucial to maintain muscle mass properly to prevent muscle loss. This invention provides the following seven exercises for muscle training, with 3-5 sets per session and a maximum of 5 sets per week.

Push-ups (arm training), lunge jumps (leg training), high knees (leg training), parachute drills (leg training), plank exercises (full-body training), sit-ups (full-body training), burpees (full-body training).

Mode 3: Reaction Training

As people age, it is normal for physical strength and reaction time to decline, but this is preventable. Regular training can slow down the decline in reaction time. Reaction time is important because the brain and nervous system control the entire body. This invention presents two training modes.

Option 1: T1

Place the device around the user or in different locations, with lights turning on randomly, and see how many points the user can score within a time limit.

Option 2: T2

Place the device around the user or in different locations, and the light will randomly illuminate 15 times to record how much time the user spends using it.

The hardware design principle of this invention is illustrated in Figure 11, which includes the NRF24L01+ wireless communication module 31, the Raspberry Pi 4B control board 32, and multiple remote sensors 33. The web page creation in the software development of this invention is illustrated in Figure 12. The complete web page is written in five languages, including HTML, CSS, JavaScript, PHP, and MySQL. This invention utilizes these languages to create the web page, which includes real-time images and displays and stores various data. Furthermore, the image recognition in the software development of this invention is a type of computer vision. Deep learning requires a large amount of data to train the algorithm model. For example, image recognition typically requires millions of image data points to train the model and find the most suitable weight parameters to achieve optimal accuracy. As the neural network receives more data, it can be readjusted to produce more accurate predictions. Through image recognition, the algorithm obtains the coordinates of various parts of the human body, converts the coordinates of the parts to be measured into vectors, uses the dot product formula to obtain the angles, and finally uses the angles of various parts of the human body to set the number of movements.

Furthermore, the controller syntax in the software development of this invention is written and controlled using a Raspberry Pi. The Raspberry Pi is essentially a small computer with powerful and versatile serial ports, capable of connecting many digital components. This invention uses its programming language, "Python," for programming. The microcontroller syntax is written and controlled using an Arduino, serving as a remote controller for wireless transmission and reception, and RGB color adjustment. This invention uses its programming language, "C++," for programming.

Based on the above information, the device of this invention can effectively change one's physical fitness and cardiopulmonary capacity. In fact, this device can effectively increase one's maximum oxygen uptake, reduce body fat, and improve metabolic capacity. However, since these data can only be measured in a hospital or with professional equipment, please refer to Figure 13, which provides a reference for the data and benefits that can be calculated by this invention.

In summary, this invention combines multiple modules to create a device that trains cardiac endurance, reaction time, and muscular endurance. This fun and weight-loss-friendly device represents a completely new attitude towards exercise, using visual cues to motivate users to constantly challenge their speed and reaction limits, thereby increasing training intensity. Combined with a web page and image recognition, users can design and monitor their athletic performance with precision down to the second, allowing them to see their progress.

After training with the device of this invention, the device will make some minor adjustments to the data based on the user's age and the distance they choose. Since everyone's physical parameters are different, how to adjust the data collection standards is something this invention needs to study more deeply. Furthermore, this invention found that without actual heart rate monitoring, it is often just low-intensity gymnastics. Especially for people with poor muscle strength and fitness, they often don't reach the true "high intensity" defined by heart rate standards, and their legs and arms become sore and they can't continue, mistakenly believing they have done "high-intensity training." Many people believe that as long as they exercise until they feel tired, their fitness level will continuously improve, so they should do more and more. However, doing more doesn't necessarily mean more effect; it may only lead to more sports injuries. In fact, as long as you use the right methods and exercise regularly, the effects will appear quickly.

This invention utilizes a system training approach while employing diverse program diagnostics, integrating parameters such as heart rate and limb movement calculations to achieve more efficient training results. The device can be controlled via an app and includes a camera or three-axis sensor to monitor the user. Multi-module guided judgment and detection effectively prevent accidents and reduce sports injuries caused by exercise.

However, the illustrations and descriptions above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any other equivalent changes or modifications made by those skilled in the art based on the features of the present invention should be considered as not departing from the design scope of the present invention.

1: Methods for testing and training physical fitness

11: Trainer Data Input Steps

12: Training Mode Selection Steps

13: Steps for confirming training content

130: Steps to confirm exercise intensity

131: Input Strength Type Steps

132: Obtaining the starting heart rate step

133: Steps for calculating effective heart rate

14: Begin training and implementation steps

15: Steps to assess the training status of trainees

150: Image Recognition Methods

151: Steps for obtaining images of trainees

152: Image processing steps for trainees

153: Steps for training personnel in image interpretation

154: Steps for color tone conversion

155: Steps to obtain coordinates of different parts of the body

156: Steps to obtain vectors

16: Training content completion steps

17: Steps for transferring training records back to the computer

18: Steps for comparing training record values

2: Physical Fitness Testing and Training System

21: Controller

22: Trainer Data Input Module

23: Training Mode Selection Module

24: Training Content Confirmation Module

241: Exercise Intensity Confirmation Module

241a: Input Intensity Type Module

241b: Obtain the initial heart rate module

241c: Effective Heart Rate Calculation Module

25: Begin training and implementation of the module

251: Image Monitoring Module

252: Sensing Module

253: Heart Rate and Blood Oxygen Module

26: Module for assessing trainee training status

261: Security Warning Module

262: Action Incomplete Reminder Module

263: Image Recognition Module

2631: Trainee Image Acquisition Module

2632: Image processing module for trainees

2632a: Color Conversion Module

2632b: Body Part Coordinate Acquisition Module

2632c: Vector Acquisition Module

2633: Image Judgment Module for Trainees

27: Training Content End Module

271: Training Standard Achievement Module

28: Training Record Numerical Feedback Module

29: Training Record Value Comparison Module

31: Wireless communication module

32: Control panel

33: Remote sensor

D: Cloud Database

E: Device

W: Webpage

Figure 1 is a flowchart of a physical fitness testing and training method according to the present invention. Figure 2 is a program flowchart of a physical fitness testing and training method according to the present invention. Figure 3 is a flowchart of the exercise intensity confirmation step in Figure 1. Figure 4 is a flowchart of an image recognition method according to the present invention. Figure 5 is a program flowchart of an image recognition method according to the present invention. Figure 6 is a flowchart of the image processing step for trainees in Figure 4. Figure 7 is a configuration diagram of a physical fitness testing and training system according to the present invention. Figure 8 is a configuration diagram of the training content confirmation module in the physical fitness testing and training system of Figure 7. Figure 9 is a configuration diagram of the image recognition module in the physical fitness testing and training system of Figure 7. Figure 10 is a conceptual diagram of a fitness testing and training system for cardiopulmonary training according to the present invention. Figure 11 is a schematic diagram of the component configuration of the hardware design principle of the present invention. Figure 12 is a schematic diagram of a webpage created using software according to the present invention. Figure 13 is a schematic diagram of the data calculated by the testing and training method of the present invention.

1: Methods for testing and training physical fitness

11: Trainer Data Input Steps

12: Training Mode Selection Steps

13: Steps to confirm training content

14: Begin training implementation steps

15: Steps to assess trainees' training status

16: Steps to conclude the training content

17: Steps for transferring training records back to the database

18: Steps for comparing training record values

Claims (9)

A method for testing and training physical fitness includes: a trainee data input step, inputting the trainee's basic information; a training mode selection step, selecting the training mode to be performed by the trainee; a training content confirmation step, confirming the training content items in the training mode; a training implementation step, where the trainee begins to implement the training content; a trainee status assessment step, determining whether the trainee has completed the movements or whether any abnormalities have occurred during the training process; and a training content completion step, confirming whether the training content items have been completed; and A training record data feedback step transmits the training record data performed by the trainee to a cloud database, and the training record data can be viewed through a webpage connected to the cloud database; the step of judging the trainee's training status includes using an image recognition method to obtain the trainee's motion images and analyze and judge the number of movements of the trainee, and the image recognition method includes: a trainee image acquisition step, which obtains the trainee's motion images; A training personnel image processing step involves processing and analyzing the training personnel's motion images to obtain the coordinates of each part of the body. Using any joint as a vector reference point, the limbs on either side of that joint are designated as vectors a and b, respectively. A training personnel image judgment step involves substituting vectors a and b into the inner product formula a ⃗⋅b ⃗=|a ⃗||b ⃗|cosθ to calculate the angle θ between the limbs on either side of the joint. This angle θ is then used to determine the number of times the training personnel have moved. The method as described in claim 1 further includes: a training record comparison step, comparing the training record value with a simulation setting target to confirm whether the training record value has reached the simulation setting target. The method described in claim 1, wherein the training content verification step further includes: The exercise intensity confirmation step confirms the type of exercise intensity in the training mode. The type of exercise intensity includes low-intensity exercise, moderate-intensity exercise, and high-intensity exercise. The type of exercise intensity is defined using an effective heart rate range formula. The effective heart rate range formula includes the following: the effective heart rate range of moderate-intensity exercise is equal to (220 - age - resting heart rate) × (40%~59%) + resting heart rate; the effective heart rate range of high-intensity exercise is greater than (220 - age - resting heart rate) × (59%) + resting heart rate; and the effective heart rate range of low-intensity exercise is less than (220 - age - resting heart rate) × (40%) + resting heart rate. The method as described in claim 3, wherein the exercise intensity confirmation step further includes: an input intensity type step, selecting one intensity type of exercise from the types of exercise intensity for training; an initial heart rate acquisition step, measuring and recording the trainee's resting heart rate; and an effective heart rate calculation step, using the acquired resting heart rate of the trainee to calculate the effective heart rate range of the selected intensity exercise using the effective heart rate range formula. The method described in claim 1, wherein the training content confirmation step further includes: an exercise intensity confirmation step, confirming the type of exercise intensity in the training mode, the type of exercise intensity including low-intensity exercise, moderate-intensity exercise and high-intensity exercise, and the type of exercise intensity is defined using a maximum heart rate range formula to define the low-intensity exercise, the moderate-intensity exercise and the high-intensity exercise, wherein the maximum heart rate range formula includes the maximum heart rate range of the moderate-intensity exercise equal to (220 - age) × (64% to 74%), the maximum heart rate range of the high-intensity exercise equal to (220 - age) × (85% to 90%), and the maximum heart rate range of the low-intensity exercise equal to (220 - age) × (50% to 63%). A physical fitness testing and training system includes: a controller; a trainee data input module connected to the controller for inputting basic data of a trainee; a training mode selection module connected to the controller for selecting the training mode to be performed by the trainee; a training content confirmation module connected to the controller for confirming the training content items in the training mode; and a start training implementation module connected to the controller for initiating the training content by the trainee, wherein the start training implementation module includes an image monitoring module connected to the controller for acquiring motion images of the trainee. A training status determination module, connected to the controller, is used to determine whether the trainee has completed the action or whether any abnormality has occurred during the training process. The training status determination module further includes: a safety warning module, connected to the controller, for issuing safety warning messages; and an action incomplete reminder module, connected to the controller, for issuing action incomplete reminder messages; a training content completion module, connected to the controller, for confirming whether the training content item has been completed; and A training record data feedback module is connected to the controller to feed back the training record data of the trainee to a cloud database, and the training record data can be viewed through a webpage connected to the cloud database. The system as described in claim 6 further includes: a training record value comparison module, connected to the cloud database, which compares the training record value with a simulation setting target to confirm whether the training record value has reached the simulation setting target. The system as described in claim 6 further includes, in the training content completion module: a training standard attainment module for confirming whether the trainee's training results meet the training standards. The system as described in claim 6, wherein the start training implementation module includes a heart rate and blood oxygenation module connected to the controller for monitoring heart rate and blood oxygenation.