TWI887104B - Neuromuscular fatigue detection and assessment system - Google Patents

Abstract

A neuromuscular fatigue detection and assessment system includes a first wearable device, a second wearable device and an electronic apparatus. The first wearable device is provided with an inertial measurement unit and is worn behind the waist of the subject. The second wearable device is provided with a near-infrared spectrometer and is worn on the skin of the vastus lateralis muscle belly of the thigh of the subject. The electronic apparatus is equipped with a wireless device and is wirelessly connected to the first wearable device and the second wearable device through the wireless device. With the subject performing a vertical jump, the first wearable device and the second wearable device respectively collect detection data including acceleration information and muscle oxygenation concentration change generated by the subject during the vertical jump, and the detection data are wirelessly transmitted to the electronic apparatus for analysis to determine the degree of neuromuscular fatigue of the subject.

Description

Neuromuscular fatigue detection and assessment system

This invention relates to the technical field of sports science and biomedicine, and particularly to a neuromuscular fatigue detection and evaluation system.

Monitoring and controlling sports training load is an important means of scientific competitive training, which can be used to maximize training adaptation and benefits and avoid sports injuries. Sports training load can be divided into internal loads such as oxygen uptake, heart rate, blood lactate, Rating of Perceived Exertion (RPE) and training impulse, and external loads such as strength, acceleration, distance and speed, which must cover the scope of sports physiology, sports biomechanics and sports psychology.

The existing monitoring of sports training load is mostly limited to the collection and analysis of single instrument data, such as simply monitoring heart rate or vertical jump, and there is no integrated real-time monitoring system. For example, in the existing market of related testing methods, only commercially available mobile phone applications (APPs) are used to analyze the jumping height of multiple jumps. They mainly use the smartphone camera to shoot the jumping action of the human body, and then use the APP function to manually select the take-off time and landing time in the jumping image. The two time points define the space time and then calculate the jumping height. However, the purpose of most software is only to monitor jumping performance, not to evaluate the degree of neuromuscular fatigue. In addition, the relevant commercially available mobile phone apps are shot with a camera and analyzed by manual visual judgment. Therefore, in addition to the high test error, there is no technology that combines other different physiological indicators to conduct real-time analysis and assessment of neuromuscular fatigue.

Therefore, there are still many deficiencies in the existing design of sports training load monitoring and there is a need for improvement.

The main purpose of this invention is to provide a neuromuscular fatigue detection and assessment system, which provides more valuable information on the athlete's overall fatigue, training load and sports performance through multi-dimensional monitoring of sports training load and fatigue, and uses physiological and mechanical multi-dimensional indicators to conduct an integrated assessment of neuromuscular fatigue, which can improve the quality and effectiveness of training and achieve high-precision detection.

To achieve the above-mentioned purpose, the present invention provides a neuromuscular fatigue detection and evaluation system for detecting and evaluating the neuromuscular fatigue state of a detected object, comprising: a first wearable device on which an inertia measurement unit is disposed, and the first wearable device is used to be worn behind the waist of the detected object; a second wearable device on which a near-infrared spectrometer is disposed, and the second wearable device is used to be worn on the skin at the belly position of the vastus lateralis muscle of the thigh of the detected object; and an electric The electronic device is equipped with a wireless device and is wirelessly connected to the first wearable device and the second wearable device. When the detected object performs a vertical jump, the first wearable device and the second wearable device respectively collect detection data including acceleration information and changes in muscle oxygenation concentration generated by the detected object during the vertical jump, and wirelessly transmit the detection data to the electronic device for analysis, so as to determine the neuromuscular fatigue level of the detected object.

The above overview and the following detailed description are of an exemplary nature and are intended to further illustrate the scope of the patent application of the present invention. The remaining purposes and advantages of the present invention will be elaborated in the subsequent description and drawings.

1: Neuromuscular fatigue detection and assessment system

90: Object to be tested

11: First wearable device

12: Second wearable device

20: Electronic equipment

21: Wireless devices

80: Platform

P1, P2, P3, P4: Processing procedures

S401~S403, S406~S408, S421~S424, S501~S508: Steps

Figure 1 shows a schematic diagram of the neuromuscular fatigue detection and assessment system of the present invention.

Figures 2A, 2B and 2C show schematic diagrams of the action sequence of a drop jump.

Figures 3A and 3B are schematic diagrams showing the sequence of movements of a squat jump in a series of multiple squat jumps.

Figure 4A shows the algorithm flow of the inertial measurement unit.

Figure 4B shows the near-infrared spectrometer calculation process.

Figure 5 shows the fatigue level grading process.

In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the attached drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the implementation of the present invention and are not intended to limit the present invention.

FIG1 shows a schematic diagram of the neuromuscular fatigue detection and evaluation system of the present invention, wherein the neuromuscular fatigue detection and evaluation system 1 is used to detect and evaluate the neuromuscular fatigue state of a detected object 90, and mainly includes a first wearable device 11, a second wearable device 12 and an electronic device 20. The first wearable device 11 is provided with an inertial measurement unit (IMU for short), and the first wearable device 11 is used to be worn on the back of the waist (lumbar spine) of the detected object 90; the second wearable device 12 is provided with a near-infrared spectrometer (Near-Infrared Spectrometer) Spectrometer, referred to as NIRS), and the second wearable device 12 is used to be worn on the skin of the belly of the vastus lateralis muscle of the detected object 90; the electronic device 20 is equipped with a wireless device 21 and is wirelessly connected to the first wearable device 11 and the second wearable device 12 by the wireless device 21, wherein the wireless device 21 can be a Bluetooth wireless device or a WiFi wireless device, and the electronic device 20 can be a tablet computer, a laptop computer, a personal computer, a smart phone, etc., but this is only an example, and the present invention is not limited to this.

When the neuromuscular fatigue detection and evaluation system 1 of the present invention is used to test the subject 90, the subject 90 performs a vertical jump, and during the vertical jump, the first wearable device 11 and the second wearable device 12 respectively collect the detection data including acceleration information and muscle oxygenation concentration changes generated by the subject 90 during the vertical jump, and transmit the detection data wirelessly to the electronic device 20 for analysis, so as to determine the neuromuscular fatigue level represented by the subject 90.

The aforementioned vertical jump includes a drop jump and a continuous multiple squat jumps. Figures 2A, 2B and 2C show schematic diagrams of the action sequence of the drop jump, wherein, when performing the drop jump, the detected object 90 stands at a high place with the hands placed at the hip joint (hands on waist) (Figure 2A), then falls to a low place (2B), and then jumps up again (Figure 2C), for example, standing on a platform 80 placed on the ground, falling to the ground and then jumping up, thereby completing the aforementioned drop jump. Furthermore, FIGS. 3A and 3B show schematic diagrams of the action sequence of one squat jump in a series of multiple squat jumps, wherein when performing the squat jump, the detected object 90 first squats with its hands at the hip joint (hands on waist) (FIG. 3A), and then jumps up (FIG. 3B), and the hands do not leave the hip joint position during the squat jump, thereby completing one squat jump in the series of multiple squat jumps.

In the aforementioned testing process, please also refer to the processing procedures P1, P2, P3 and P4 of the electronic device 20 in the neuromuscular fatigue detection and assessment system 1 of the present invention shown in FIG1 . The first wearable device 11 and the second wearable device 12 worn on the tested object 90 each transmit the sensed detection data to the electronic device 20 in a wireless manner and are received by the wireless device 21 of the electronic device 20. Accordingly, the electronic device 20 collects the detection data (processing procedure P1). Next, the electronic device 20 identifies the first eigenvalue and the second eigenvalue in the aforementioned collected detection data (processing procedure P2) for identification, determination, analysis and evaluation of the detection data, wherein the first eigenvalue is the eigenvalue of the detection data of the inertial measurement unit (IMU) of the first wearable device 11, and the second eigenvalue is the eigenvalue of the detection data of the near infrared spectrometer (NIRS) of the second wearable device 12.

In more detail, FIG. 4A and FIG. 4B respectively show the inertial measurement unit (IMU) calculation process and the near infrared spectrometer (NIRS) calculation process in the aforementioned processing procedure P2. As shown in the inertial measurement unit (IMU) calculation process of FIG. 4A , when performing a drop jump (DJ) test, the value of the Z-axis (vertical to the ground) acceleration is first input (step S401). Then, the space time and the contact time are calculated (step S402), which are judged by the peak value and the turning point in the Z-axis acceleration curve, and one contact time and one space time are defined as completing one jump. After completion, the input of values is stopped and the result is displayed (step S403). The aforementioned steps S401-S403 may be repeated several times (for example, repeated 3 times), and then enter the continuous multiple squat jump (CMJ) test. When performing the continuous multiple squat jump (CMJ) test, first input the value of the Z-axis acceleration (step S406), then calculate the space time and the ground contact time (step S407), which is determined by the peak value and turning point in the Z-axis acceleration curve, and define 1 ground contact time and 1 space time as completing 1 jump. Among them, the continuous multiple squat jump (CMJ) test requires multiple jumps (for example, 15 jumps), so steps S406 and S407 need to be executed multiple times (for example, 15 times). After completion, stop inputting values and display the results (step S408).

Furthermore, as shown in the near infrared spectrometer (NIRS) calculation process of FIG. 4B , the muscle oxygenation concentration value is first input (step S421 ) and the first jump is completed (if the first jump has not been completed, step S421 needs to be executed again). Next, record timestamp-1 (step S422) and perform multiple jumps (e.g. 15 jumps), wherein each jump is judged by the inertial measurement unit (IMU) calculation process, and the peak value and turning point in the Z-axis acceleration curve are used for judgment, and one contact time and one space time are defined as completing one jump. After completing multiple (15) jumps, record timestamp-2 (step S423), then stop inputting values and display the results (step S424), and use timestamp-1 and timestamp-2, as well as the oxygenation concentration value at that time, to calculate the deoxygenation rate.

After the aforementioned processing procedure P2, based on the aforementioned identified first characteristic value and second characteristic value, the electronic device 20 determines, calculates and generates several indicators corresponding to the aforementioned vertical jump (processing procedure P3), wherein the several indicators include the air time during the vertical jump, the best and lowest air time and jump height, the drop jump percentage (Percentage DJ), the drop percentage (PD score), the reaction muscle strength (RSI) and the deoxygenation rate (Deoxy rate). Accordingly, the electronic device 20 can calculate all the aforementioned indicators, and use the calculation results to evaluate the comprehensive fatigue level of the detected object 90 and grade it (processing procedure P4). Furthermore, the aforementioned indicators can be output in real time and presented on the software screen and report, and can provide real-time feedback or long-term log output, thereby achieving the effect of correct real-time analysis and evaluation of neuromuscular fatigue.

In more detail, FIG5 shows the fatigue level calculation process in the aforementioned processing procedures P3 and P4. As shown in the figure, first, the muscle oxygenation concentration value and the jump value are input (step S501). Then, the descent percentage (PD score), drop jump percentage (Percentage DJ), deoxygenation rate (Deoxy rate), reaction muscle strength (RSI), drop jump/continuous multiple squat jump (DJ/CMJ) and other indicators are calculated (step S502). Among them, PD score is based on the highest DJ value to calculate the jump height decrease rate; Percentage DJ is based on the highest DJ value to calculate the jump decay; Deoxy rate is the deoxygenation rate of the oxygen concentration of the acting muscle; RSI is the ratio of jump height to ground contact time, taking the average of the highest 5 records; DJ/CMJ ratio is the ratio of drop jump to squat jump height. Then, the above indicators are compared with the normative data in the database and risk scores are given respectively (step S503). Then, the risk score is input (step S504). Among them, when two numerical scores reach high risk, it displays extremely high risk (step S505), when one numerical score reaches high risk, it displays high risk (step S506), when zero numerical scores reach high risk, it displays medium risk (step S507), otherwise it displays low risk (step S508).

From the above description, it can be seen that the present invention can provide more valuable information on the athlete's overall fatigue, training load and sports performance through multi-dimensional monitoring of sports training load and fatigue. Moreover, since the object of sports training and technology is the human body, monitoring and evaluation are carried out with an integrated concept. By integrating relevant information of sports physiology, sports biomechanics and sports psychology, the actual situation can be fully presented, and the neuromuscular state can be detected and real-time feedback can be given accordingly, so as to achieve real-time tracking and evaluation of neuromuscular fatigue state, thereby improving the quality and effectiveness of training. In addition, the present invention will use the characteristic values of the inertial measurement unit (IMU) and the near infrared spectrometer (NIRS) to conduct an integrated assessment of neuromuscular fatigue using multiple physiological and mechanical indicators. The accuracy of the test will be much higher than the conventional test of simply measuring the jumping height.

The above embodiments are only given for the convenience of explanation. The scope of rights claimed by the present invention shall be subject to the scope of the patent application, and shall not be limited to the above embodiments.

1: Neuromuscular fatigue detection and assessment system

90: Object to be tested

11: First wearable device

12: Second wearable device

20: Electronic equipment

21: Wireless devices

P1, P2, P3, P4: Processing procedures

Claims (10)

A neuromuscular fatigue detection and evaluation system for detecting and evaluating the neuromuscular fatigue state of a detected object, comprising: a first wearable device, on which an inertia measurement unit is arranged, the first wearable device is used to be worn behind the waist of the detected object; a second wearable device, on which a near-infrared spectrometer is arranged, the second wearable device is used to be worn on the skin at the belly position of the vastus lateralis muscle of the thigh of the detected object; and an electronic device, equipped with A wireless device is wirelessly connected to the first wearable device and the second wearable device, wherein the detected subject performs a vertical jump, and the first wearable device and the second wearable device respectively collect detection data including acceleration information and muscle oxygenation concentration changes generated by the detected subject during the vertical jump, and wirelessly transmit the detection data to the electronic device for analysis, so as to determine the neuromuscular fatigue level of the detected subject. A neuromuscular fatigue detection and assessment system as described in claim 1, wherein the vertical jump includes a drop jump and multiple consecutive squat jumps. The neuromuscular fatigue detection and assessment system as described in claim 2, wherein, when performing the squat jump, the subject being tested places the hands at the hip joint (hands on waist), and the hands do not leave the hip joint position during the squat jump. A neuromuscular fatigue detection and assessment system as described in claim 2, wherein the electronic device identifies the first characteristic value and the second characteristic value in the detection data. The neuromuscular fatigue detection and assessment system as described in claim 4, wherein the first characteristic value is the characteristic value of the detection data of the inertia measurement unit, and the second characteristic value is the characteristic value of the detection data of the near-infrared spectrometer. A neuromuscular fatigue detection and assessment system as described in claim 5, wherein, based on the identified first characteristic value and the second characteristic value, the electronic device determines, calculates and generates a plurality of indicators corresponding to the vertical jump. A neuromuscular fatigue detection and assessment system as described in claim 6, wherein the plurality of indicators include the air time, the best and the lowest air time and the jump height, the percentage of the fall jump, the percentage of the descent, the reaction muscle strength and the oxygen desorption rate during the vertical jump. The neuromuscular fatigue detection and assessment system as described in claim 7, wherein the electronic device calculates the several indicators and uses the calculation results to assess the comprehensive fatigue level of the subject being tested and grade it. A neuromuscular fatigue detection and assessment system as described in claim 1, wherein the wireless device is a Bluetooth wireless device. A neuromuscular fatigue detection and assessment system as described in claim 1, wherein the wireless device is a WiFi wireless device.

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