Wearable operation behavior capability digital intelligence evaluation method, system, medium and equipment

Abstract

The invention provides a wearable operation behavior capability digital intelligent evaluation method and system, a medium and equipment. The wearable operation behavior capability digital intelligent evaluation method comprises the following steps: S1, acquiring motion data of one or more limbs of a measurement person through a wearable sensor; and S2, resolving the collected motion data to obtain a digital behavioral ability portrait of the measurement personnel, and performing behavioral ability evaluation on the measurement personnel according to the digital behavioral ability portrait. According to the invention, precise and non-sensitive remote monitoring and tracking of the operation behavior of the measured object are realized through the wearable sensor, and digital evaluation and grading of the operation capability and physical strength of the measurement personnel are realized through data calculation.

Description

Technical Field

[0001] This invention relates to the field of motion capture technology, and more specifically, to a method, system, medium, and device for digitally assessing wearable work behavior capabilities. Background Technology

[0002] Motion capture, also known as motion capture, involves placing trackers on key parts of a moving object. A processing system captures the tracker's position, and the data is then processed by a computer to obtain three-dimensional spatial coordinates. Once the data is recognized by the computer, it can be applied in fields such as animation production, gait analysis, biomechanics, and ergonomics.

[0003] Sports activities are popular worldwide, suitable for recreational enthusiasts as well as elite or professional athletes. Athletes use body movements to perform many sports actions (e.g., drop shots, volleys, drops, spikes, smashes, serves, clears, returns, etc.). Athletes can use inertial sensors to capture and analyze their performance on one or more sports actions (e.g., key, basic, and / or frequently repetitive movements) to seek improvements in their performance in their chosen sports.

[0004] However, most existing motion capture and recognition systems currently use high-speed camera systems, which are usually very expensive. Therefore, the implementation and use costs of traditional motion capture and recognition systems are very high, and they cannot provide kinematic analysis for athletes. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method, system, medium, and device for digitally assessing wearable work behavior capabilities.

[0006] A digital assessment method for wearable work behavior ability provided by the present invention includes:

[0007] Step S1: Collect motion data of one or more limbs of the person being measured using wearable sensors;

[0008] Step S2: Solve the collected motion data to obtain a digital behavioral ability profile of the measurement personnel, and assess the behavioral ability of the measurement personnel based on the digital behavioral ability profile.

[0009] Preferably, the behavioral ability assessment includes: digital assessment and grading of the operator's work ability, and digital assessment and grading of the operator's physical fitness.

[0010] Preferably, the method for obtaining the digital behavioral capability profile includes: characterizing and analyzing the behavior of the person being measured, and quantifying the behavior of the person being measured through a machine learning model.

[0011] Preferably, the method for acquiring motion data includes: using wireless communication anti-crosstalk technology and channel matching mechanism to collect data in a distributed manner from multiple wearable sensors during the collective operation of the measurement object.

[0012] A wearable digital assessment system for operational behavior capabilities according to the present invention includes:

[0013] Module M1: Collects motion data of one or more limbs of a person using wearable sensors;

[0014] Module M2: It processes the collected motion data to obtain a digital behavioral capability profile of the measurement personnel, and assesses the personnel's behavioral capabilities based on the digital behavioral capability profile.

[0015] Preferably, the behavioral ability assessment includes: digital assessment and grading of the operator's work ability, and digital assessment and grading of the operator's physical fitness.

[0016] Preferably, the method for obtaining the digital behavioral capability profile includes: characterizing and analyzing the behavior of the person being measured, and quantifying the behavior of the person being measured through a machine learning model.

[0017] Preferably, the method for acquiring motion data includes: using wireless communication anti-crosstalk technology and channel matching mechanism to collect data in a distributed manner from multiple wearable sensors during the collective operation of the measurement object.

[0018] According to the present invention, a computer-readable storage medium storing a computer program is characterized in that, when the computer program is executed by a processor, it implements the steps of the wearable work behavior capability digital evaluation method.

[0019] An electronic device according to the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the computer program, when executed by the processor, implements the steps of the wearable work behavior capability digital assessment method.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] 1. This invention achieves precise and non-intrusive remote monitoring and tracking of the work behavior of the measurement object through wearable sensors, and realizes digital assessment and level classification of the measurement personnel's work ability and physical fitness through data calculation.

[0022] 2. This invention can accurately monitor and track multidimensional behavioral information of athletes during the execution of professional movements. Based on the collected large sample athlete data and machine learning algorithms, it can accurately represent, extract features and perform high-order analysis on relevant important movement processes. It adopts a multidimensional evaluation algorithm to achieve accurate evaluation of athletes' professional skill level. Based on the evaluation results, it can effectively adjust technical movements during training, thereby shortening the training cycle.

[0023] 3. This invention can provide scientific, quantitative, intelligent, and efficient evaluation methods and safeguard technologies for the selection, training, and extension of the career cycle of professionals. Attached Figure Description

[0024] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0025] Figure 1 Flowchart of a digital assessment method for wearable work behavior capabilities. Detailed Implementation

[0026] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the scope of protection of the present invention.

[0027] This invention discloses a digital and intelligent assessment method for wearable work behavior capabilities. As an important integrated application of microelectromechanical sensing technology, wearable electronics, and artificial intelligence technology in motion capture systems, this method mainly includes: a micro-nano sensor hardware system developed based on high-precision multi-node wearable motion capture perception technology, and a work capability intelligent assessment and prediction software system developed based on machine learning and big data analysis algorithms.

[0028] Specifically, refer to Figure 1 As shown, the digital assessment method for wearable work behavior capabilities includes the following steps:

[0029] Step S1: Collect motion data of one or more limbs of the person being measured using wearable sensors.

[0030] Step S2: Solve the collected motion data to obtain a digital behavioral ability profile of the measurement personnel, and assess the behavioral ability of the measurement personnel based on the digital behavioral ability profile.

[0031] In one specific implementation, the wearable sensor includes devices such as wearable smart bracelets, rings, and wristbands, which can be selectively worn by the subject. Measurement signals can be transmitted wirelessly or via wired means, and the data is ultimately collected and analyzed at a data management terminal.

[0032] The method for obtaining the digital behavioral competence profile in step S2 includes: representing and analyzing the behavior of the measurement personnel, and quantifying the behavior of the measurement personnel through a machine learning model. Behavioral competence assessment includes: digital assessment and grading of the measurement personnel's operational abilities, and digital assessment and grading of the measurement personnel's physical fitness.

[0033] Specifically, this integrated system enables precise and seamless remote monitoring and tracking of the work behavior of the measurement subjects. Through data processing, it achieves digital assessment and grading of the work ability and physical fitness of the measurement personnel. This includes precise characterization and high-level analysis of the behavioral ability of the measurement subjects in various tasks, accurate quantification of the behavioral ability profile of the measurement subjects through a core competency model, construction of a multi-dimensional assessment algorithm to predict the behavioral ability of the measurement subjects, and personalized tracking assessment and closed-loop feedback adjustment of the behavioral ability throughout the entire occupational cycle.

[0034] The main indicators of work performance include the accuracy of motion capture of the work behavior of the measured object in multiple work scenarios, the wearability and portability of the behavior monitoring sensor, the accuracy of the work performance evaluation algorithm, and the accuracy of the predictive model of the behavior development ability of the measured object.

[0035] In a preferred embodiment, the wearable sensor employs a stacked design, offering high integration advantages. The core component measures only 1cm x 2cm and weighs approximately 8g. It utilizes wireless communication anti-crosstalk technology and a channel matching mechanism, enabling simultaneous distributed multi-channel stable communication and broadband data transmission for multiple sensor modules during collective operations of the measured object. The motion perception system employs micro-nano sensing technology, achieving an acceleration measurement resolution of 0.0005g / LSB. Based on a multi-dimensional information fusion algorithm, it finely calculates the key behavioral process information of the measured object's operation, achieving a motion recognition accuracy of 98.3%. Optimized power management technology supports continuous use for up to 30 days.

[0036] The wearable sensor in this invention is based on a unique mechanical design and the application of advanced materials. This device is effectively resistant to sweat, dirt, and water in extreme and underwater environments. Thanks to the stacked design of the micro-nano sensing modules, the device offers advantages in miniaturization and portability, enabling rapid wear and stable, non-intrusive data acquisition in actual working scenarios, and resisting signal loss caused by significant movement during operation.

[0037] The present invention will be further described below with reference to specific application scenarios.

[0038] This invention involves attaching multi-node miniature motion capture sensors to different parts of the bodies of professional athletes (no fewer than 100 individuals) to accurately monitor and track multidimensional behavioral information during the execution of professional movements. Based on the collected large-sample athlete data and machine learning algorithms, it performs precise characterization, feature extraction, and high-order analysis of relevant important movement processes. A multi-dimensional evaluation algorithm is employed to accurately assess the athletes' professional skill levels. During training, techniques are effectively adjusted based on the evaluation results, shortening the training cycle. The method provided by this invention effectively improves athletes' training efficiency and digital training standards, playing a significant positive role in improving athletic performance and greatly shortening the training cycle for high-level professional athletes.

[0039] Currently, this method has undergone multiple technological iterations in terms of packaging integration, wireless data communication, and power management to adapt to the hardware usage requirements of different application scenarios and special environments.

[0040] This invention can also be used to assess the operational capabilities of professionals. These individuals typically operate in extremely complex environments, perform highly complex tasks, and face extremely demanding skill requirements. Therefore, assessing and improving their operational capabilities is a crucial issue.

[0041] The main application scenarios include: 1) "Professional" competency profiling. Based on the classification of work competency levels and comprehensive quality evaluation, this achievement is extended to accurately characterize and deconstruct the technical movements, physical fitness, and fine motor skills of measurement subjects with outstanding professional behavioral abilities, obtaining a radar chart of "professional" competency and a core competency model; 2) Assessment and prediction of new employees. Based on the "professional" competency model, a multi-dimensional assessment algorithm is constructed for measurement subjects to assess their basic situation and work performance, and predict their potential development; 3) Tracking of the entire career cycle of measurement subjects. Through the application of non-intrusive and precise monitoring technology, the monitoring and analysis of the daily work behavior of measurement subjects is improved, forming a comprehensive, intelligent, and personalized assessment and analysis of the entire career cycle of measurement personnel, enabling timely early warning and adjustment to maintain their competency level.

[0042] This invention can provide scientific, quantitative, intelligent, and efficient evaluation methods and safeguard technologies for the selection, training, and extension of the career cycle of professionals.

[0043] The present invention also provides a wearable intelligent assessment system for work behavior capabilities. The wearable intelligent assessment system for work behavior capabilities can be implemented by executing the process steps of the wearable intelligent assessment method for work behavior capabilities. That is, those skilled in the art can understand the wearable intelligent assessment method for work behavior capabilities as a preferred embodiment of the wearable intelligent assessment system for work behavior capabilities.

[0044] This invention provides a wearable digital assessment system for work behavior capabilities, comprising:

[0045] Module M1: Collects motion data of one or more limbs of a person using wearable sensors.

[0046] Specifically, motion data acquisition methods include: using wireless communication anti-crosstalk technology and channel matching mechanisms to distribute data acquisition from multiple wearable sensors during collective operation of the measurement object.

[0047] Module M2: It processes the collected motion data to obtain a digital behavioral capability profile of the measurement personnel, and assesses the personnel's behavioral capabilities based on the digital behavioral capability profile.

[0048] The behavioral competence assessment includes: a digital assessment and grading of the measurement personnel's operational abilities, and a digital assessment and grading of their physical fitness. The methods for obtaining the digital behavioral competence profile include: representing and analyzing the measurement personnel's behavior, and quantifying the behavior through machine learning models.

[0049] The present invention also provides a computer-readable storage medium storing a computer program, such as a USB flash drive or optical disc, wherein the steps of implementing the wearable work behavior capability digital assessment method are implemented when the computer program is executed by a processor.

[0050] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the wearable work behavior capability digital assessment method.

[0051] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0052] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A digital assessment method for wearable work behavior capabilities, characterized in that, include: Step S1: Collect motion data of one or more limbs of the person being measured using wearable sensors; Step S2: Solve the collected motion data to obtain a digital behavioral ability profile of the measurement personnel, and assess the behavioral ability of the measurement personnel based on the digital behavioral ability profile.

2. The wearable work behavior ability digital assessment method according to claim 1, characterized in that, The behavioral competence assessment includes: digital assessment and grading of the operator's work ability, and digital assessment and grading of the operator's physical fitness.

3. The wearable work behavior ability digital assessment method according to claim 1, characterized in that, The method for obtaining the digital behavioral capability profile includes: characterizing and analyzing the behavior of the person being measured, and quantifying the behavior of the person being measured through a machine learning model.

4. The wearable work behavior ability digital assessment method according to claim 1, characterized in that, The method for acquiring motion data includes: using wireless communication anti-crosstalk technology and channel matching mechanism to collect data in a distributed manner from multiple wearable sensors during the collective operation of the measurement object.

5. A wearable digital assessment system for work behavior capabilities, characterized in that, include: Module M1: Collects motion data of one or more limbs of a person using wearable sensors; Module M2: It processes the collected motion data to obtain a digital behavioral capability profile of the measurement personnel, and assesses the personnel's behavioral capabilities based on the digital behavioral capability profile.

6. The wearable work behavior ability digital assessment system according to claim 5, characterized in that, The behavioral competence assessment includes: digital assessment and grading of the operator's work ability, and digital assessment and grading of the operator's physical fitness.

7. The wearable work behavior ability digital assessment system according to claim 5, characterized in that, The method for obtaining the digital behavioral capability profile includes: characterizing and analyzing the behavior of the person being measured, and quantifying the behavior of the person being measured through a machine learning model.

8. The wearable work behavior ability digital assessment system according to claim 5, characterized in that, The method for acquiring motion data includes: using wireless communication anti-crosstalk technology and channel matching mechanism to collect data in a distributed manner from multiple wearable sensors during collective operation of the measurement object.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the digital assessment method for wearable work behavior capabilities as described in any one of claims 1 to 4.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the computer program is executed by the processor, it implements the steps of the digital assessment method for wearable work behavior capabilities as described in any one of claims 1 to 4.

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