A nursing system and method for monitoring movement

Abstract

This invention relates to a nursing system and method for monitoring movement. The nursing system guides trainees in rehabilitation training using the following methods: guiding trainees to perform specific exercises based on a predetermined program; monitoring the trainee's movement parameters while performing the exercises and adjusting the difficulty of the predetermined program based on these parameters; and monitoring the trainee's movement parameters again after adjustment. The nursing system adaptively adjusts the difficulty of the predetermined program according to the trainee's movement parameters, ensuring that the program consistently has a positive reinforcing effect on the trainee's psychology. This maintains the trainee's motivation, improves their balance, and fully guarantees the effectiveness of the rehabilitation training while supervising and guiding their rehabilitation.

Description

Technical Field

[0001] This invention relates to the field of motion monitoring technology, and more particularly to a nursing system and method for monitoring motion. Background Technology

[0002] As people age, their balance gradually declines, making them more prone to falls and slips, which can lead to accidental injuries to the hips, wrists, and lower back. Rehabilitation training can help restore or improve a patient's balance by training muscles and nerves. While rehabilitation training often utilizes existing mechanical equipment, most of this equipment assists trainees in performing exercises. This is typically a one-way control model, where the trainee either controls the equipment or the equipment moves the trainee, lacking human-machine interaction.

[0003] For example, CN213698689U discloses a training mat, including a sports mat and an indicator structure. The indicator structure is disposed on the sports mat and includes multiple spaced-apart touch elements. The multiple touch elements are arranged and combined to form a movement path. When training, the trainee can perform various movements on the sports mat by touching each touch element in sequence along the indicated movement path. In the process of touching each touch element with both hands or feet, the trainee's limb coordination and mental agility are improved.

[0004] Aside from some patients who have difficulty moving independently, this type of training not only fails to motivate trainees with sufficient independent movement ability, leading to over-reliance on the training equipment and a lack of awareness and control over their own muscles and movements, resulting in very limited training effects, but also poses a high risk of injury due to incorrect muscle exertion. Furthermore, these devices lack an assessment and correction process for the patient's movements. Trainees rely solely on the structure of the device for movement correction, but are limited by the limited adjustment range of the mechanical structure and the trainee's understanding of using such equipment. This is especially true for trainees who belong to a group with neuromuscular degeneration, making it difficult for them to adjust the device to a training mode that truly suits their needs. This particularly highlights the limitations of drone-interactive rehabilitation training equipment.

[0005] CN109731292B provides a balance ability testing and training system and method based on virtual display technology. The system includes: a test customization module for customizing test plans; a training customization module for generating training plans based on balance ability reports; a virtual scene module for presenting simulated virtual training scenes based on test plans and creating virtual training scenes based on training plans for balance training; and a posture capture module for acquiring motion data and center of gravity coordinates in simulated virtual training scenes, outputting them to a test evaluation module to form a balance ability report, and performing posture detection and acquiring center of gravity coordinates in virtual training scenes.

[0006] This invention integrates human-computer interaction into the rehabilitation training process using virtual display technology. It guides trainees through movement exercises and assesses their balance during training, generating a balance test report. However, the human-computer interaction in this prior art is primarily intended to provide a more professional method for assessing balance, rather than primarily aimed at promoting rehabilitation.

[0007] Reinforcement theory is a process-oriented motivation theory. It posits that human behavior is a function of the stimuli received; if the stimulus is beneficial, the behavior will be repeated; if it is detrimental, the behavior will weaken or even disappear. Reinforcement theory has wide applications in education, management, and other fields, and is particularly important in the behavioral development stage. Rehabilitation product design involves multiple disciplines, including psychology, medicine, behavioral science, and design. A thorough understanding of the rehabilitation patient is crucial for controlling their psychology. Based on the patient's psychological state, rehabilitation equipment can be adjusted to motivate and reinforce their active participation in rehabilitation training, fully mobilizing their autonomy. Combining reinforcement theory with human-computer interaction in rehabilitation training equipment not only greatly motivates patients and exerts positive reinforcement to improve training efficiency, but also allows for adjustments to the training program based on the patient's emotions and feelings, ensuring the program consistently adapts to their physical condition and maintains a positive reinforcement effect.

[0008] Furthermore, on the one hand, there are differences in understanding among those skilled in the art; on the other hand, the applicant studied a large number of documents and patents when making this invention, but due to space limitations, not all details and contents were listed in detail. However, this does not mean that the present invention does not possess the features of these prior art. On the contrary, the present invention already possesses all the features of the prior art, and the applicant reserves the right to add relevant prior art to the background art. Summary of the Invention

[0009] To address the shortcomings of existing technologies, this invention provides a nursing system for monitoring movement. The system guides trainees to perform specific exercises based on a predetermined program. While the trainees perform these exercises, the system monitors their movement parameters and adjusts the difficulty of the predetermined program based on these parameters. The monitoring includes balance monitoring and accuracy monitoring. The movement parameters include path velocity and swing distance parameters for determining the minimum pressure center of the trainee's balance, and pressure center position offset information for determining the accuracy of the trainee's movements. The system includes a control module that calculates the trainee's exercise achievement index based on the movement parameters and adjusts the difficulty of the predetermined program based on this index. The system then monitors the trainee's movement parameters based on the adjusted program.

[0010] Preferably, the predetermined guidance program can be set in advance, allowing trainees to complete relevant movements according to the program, thus assisting in balance training. The nursing system assesses the trainee's balance and movement accuracy through contact and mechanical interaction with the exercise device during movement. Based on the automatic detection results, it can readjust the difficulty of the predetermined guidance program. Therefore, when trainees use the nursing system for balance training, it not only achieves the training effect but also automatically adjusts the predetermined guidance program based on the trainee's usage and movement accuracy, adapting the difficulty to the trainee's specific situation. Furthermore, it can use voice prompts and other methods to correct trainees' movements based on deviations, ensuring accuracy and training effectiveness. Correct and proactive exercise training allows trainees to fully experience proper muscle activation, increasing their confidence and motivating them to actively focus on and maintain accurate movements.

[0011] According to a preferred embodiment, the exercise parameters further include physiological parameters of the trainee during exercise. The control module calculates the trainee's mental index based on the physiological parameters. The control module also calculates a matching index between the current predetermined guidance program and the trainee's balance based on the trainee's mental index and the exercise achievement index. The control module grades the matching index and calculates an adjustment gradient for the difficulty of the predetermined guidance program based on the grade number of the matching index. The control module then adjusts the predetermined guidance program according to the calculated difficulty adjustment gradient.

[0012] When using this nursing system for training, trainees first have a certain understanding of their own balance ability. During the training process, trainees can make an initial self-assessment of the difficulty of the predetermined guidance procedure, which can be derived from the energy values ​​of different wavebands of their EEG during the training. The nursing system collects the trainee's EEG information and calculates the energy of each waveband to preliminarily estimate the relative difficulty of the current predetermined guidance procedure for the trainee. Simultaneously, combining this with the actual difficulty of the current predetermined guidance procedure obtained from balance and accuracy monitoring by the nursing system, and analyzing the data from both, a matching index between the current predetermined guidance procedure and the trainee's actual balance ability can be preliminarily calculated. Based on the magnitude of this matching index, the appropriate difficulty range of the predetermined guidance procedure for the trainee's balance ability can be estimated.

[0013] By classifying the matching index, the control module can determine the appropriate difficulty level for adjusting the pre-defined guidance program based on the matching index score. A high matching index indicates that the current difficulty level is suitable for the trainee's actual balance; adjustments can then be made with a smaller difficulty level around the current guidance program's difficulty value to quickly reach the optimal training difficulty. Conversely, a low matching index indicates that the current exercise difficulty is far from the trainee's actual balance; adjustments require a larger difficulty level to quickly adjust to a level suitable for the trainee's balance. This adjustment method significantly reduces adjustment time, minimizes the impact of unsuitable exercise intensity on the trainee's body, shortens the time it takes for exercise to damage confidence, reduces negative psychological reinforcement, quickly adjusts to a suitable training range, improves training accuracy, protects the trainee's health, and increases the positive psychological reinforcement effect of using the system, thereby enhancing training motivation and effectiveness.

[0014] According to a preferred embodiment, the matching index is graded as follows: based on reinforcement theory, the difference in physiological parameters between any two adjacent gradations of the matching index is constant.

[0015] By prioritizing the trainee's physiological parameters as the grading standard, the trainee's psychological cognition and feelings can be used as a priority condition for adjusting the training difficulty. This effectively reduces the negative reinforcement effect of inappropriately difficult exercise training on the trainee's psychology. When the current exercise training has a negative reinforcement effect on the trainee's psychology, the training difficulty can be quickly reduced to help gradually rebuild the trainee's training confidence and mobilize the trainee's enthusiasm for exercise. The grading method is, for example, based on the trainee's physiological parameters. When the trainee's theta wave energy value is high, that is, when the trainee is frustrated in the current training process, and the theta wave energy value is higher than the beta wave energy value, the matching index value under the current physiological parameters is defined as a low matching degree, thereby quickly reducing the exercise difficulty. Conversely, when the trainee's beta wave energy value is higher than the theta wave energy value and the duration exceeds a certain duration T, the matching index under the current physiological parameters is defined as high, thereby slowly increasing the exercise difficulty. Preferably, the matching index classification also includes a first threshold. When the matching index is greater than this first threshold, the game difficulty is increased to decrease the matching index, thereby improving the trainee's focus, preventing relaxation, and enhancing the training effect. When the matching index is less than the first threshold, the game difficulty is decreased to increase the trainee's confidence and maintain their motivation. Preferably, the first threshold is the matching index when the energy value of the theta wave equals the energy value of the beta wave. The value of the first threshold varies depending on the accuracy of the trainee's movements, thus this differentiated calculation method can fully adapt to the training needs of different trainees.

[0016] According to a preferred embodiment, the difference in physiological parameters is determined based on the magnitude of the changes in physiological parameters experienced by the trainee during the most difficult and least difficult guided exercise programs. This approach determines the relative difficulty of the current nursing system's overall exercise difficulty in the trainee's self-assessment. Based on this relative difficulty, the impact of each difficulty adjustment gradient on the trainee's physiological parameter changes is preliminarily estimated. Grading the physiological parameters based on the difference in these differences better reflects the actual changes in the trainee's psychological state. The magnitude of the changes in physiological parameters experienced by the trainee during the most difficult and least difficult guided exercise programs can be determined before the nursing system runs the guided exercise program.

[0017] According to a preferred embodiment, the first threshold is a range value. When the matching index equals the first threshold, the control module adjusts the difficulty adjustment gradient of the predetermined guidance program to zero. That is, when the matching index is at the first threshold, the trainee's physiological parameters and accuracy values ​​are most suitable for the current predetermined guidance program's difficulty. Maintaining training at this first threshold can simultaneously consider the trainee's training confidence and the training effect produced by the training process. Preferably, since the accuracy value can be communicated to the trainee through an audio-visual prompt module or the trainee's visual perception, a low accuracy value will affect the trainee's physiological parameters, further causing changes in the matching index and the grading. In summary, the grading method based on the trainee's physiological parameters can only maintain stable game difficulty when the trainee's accuracy index reaches a certain value and the physiological parameters are in the process of positive reinforcement.

[0018] According to a preferred embodiment, the nursing system further includes a movement device placed on the ground for trainees to exercise according to a predetermined guided procedure. The movement device is capable of detecting at least some of the movement parameters. The movement device has at least a plurality of sensors arranged in an array. The control module, based on the array position information of the sensors that have returned pressure data, determines the center position of the sensors whose returned data is not zero. The control module compares the center position with the center position of the predetermined guided procedure to determine an offset, and determines an accuracy index based on the offset. The movement parameters include path velocity and swing distance parameters for determining the minimum pressure center of the trainee's balance force. The control module determines the trainee's balance index at the center position based on the path velocity and swing distance parameters, and calculates an exercise achievement index based on the accuracy index and the balance index.

[0019] When trainees take steps above the exercise device according to the pre-programmed prompts, this setup calculates and adjusts the next step position based on parameters such as the trainee's actual foot size and leg length. This avoids situations where differences in foot size and height limit the scientific nature of the exercise, affecting the assessment of balance and accuracy, and consequently the adjustment of the difficulty of the pre-programmed instructions, ultimately impacting the effectiveness of the exercise. By combining foot size and height parameters with the trainee's information, the control module determines the appropriate next step placement for the current difficulty level and estimates balance and accuracy based on this determined placement. This ensures that the actual training process is not limited by foot size and that the assessment process is more scientific and reliable.

[0020] According to a preferred embodiment, the control module calculates the mental index based on the energy values ​​of the theta wave and the beta wave.

[0021] The control module calculates the matching index based on the exercise achievement index and the mental index, whereby the matching index is the sum of the exercise achievement index and the mental index. By simultaneously considering both the exercise achievement index and the trainee's feelings when adjusting the training difficulty, both training effectiveness and trainee motivation can be balanced.

[0022] In another aspect, the present invention provides a nursing method for monitoring movement, the method comprising at least:

[0023] The trainees are guided to perform corresponding actions according to a predetermined procedure, and their motor skill and physiological parameters are monitored.

[0024] A matching index is generated between the current established guidance program and the trainee's balance level based on the exercise level parameters and physiological parameters, and the established guidance program is adjusted according to the matching index;

[0025] The trainees' exercise level and physiological parameters are monitored based on the adjusted established guidance procedures. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the data connection relationship of the nursing system of the present invention;

[0027] Figure 2 This is a logical schematic diagram of the nursing method of the present invention.

[0028] List of reference numerals

[0029] 100: Control module; 200: Motion device. Detailed Implementation

[0030] Example 1

[0031] This embodiment discloses a nursing system for monitoring exercise, which can be used to train the balance of elderly people with declining balance and monitor the exercise training process. The system guides trainees to perform exercises on an exercise device 200 according to a predetermined exercise program, and detects and evaluates the trainees' movements according to the guidance. When the trainees' movements are not standard, the system points out the errors. The system also includes multiple predetermined programs of varying difficulty. The system can adjust the predetermined programs according to the trainees' level of movement accuracy to reduce the difficulty of the exercise, increase the accuracy of the movements, ensure the training effect, and improve the trainees' motivation.

[0032] According to a preferred embodiment, the exercise device 200 includes at least a sensor, an audio-visual prompting module, and a control module 100. The sensor detects the exercise state and the standardization of the trainee's movements. The audio-visual prompting module guides the trainee to exercise according to a predetermined program. Preferably, the audio-visual prompting module is capable of generating at least a first audio-visual prompt to provide pre-movement guidance and a second audio-visual prompt to indicate post-movement. The control module 100 is data-connected to the sensor, receives data from the sensor, analyzes the received data, and generates control signals to control the audio-visual prompting module to generate corresponding audio-visual prompts. The audio-visual prompting module is data-connected to the control module 100, receives the control signals sent by the control module 100, converts them into action signals that it can respond to, and generates audio-visual prompts based on the action signals.

[0033] According to a preferred embodiment, the exercise device 200 can be implemented as an exercise mat that can be laid flat on the ground for trainees to exercise on. Preferably, the exercise mat can have a multi-layered structure. For example, it includes at least a first layer for stable contact with the ground, a second layer for mounting sensors and audio-visual prompting modules, and a third layer for covering and protecting the sensors and audio-visual prompting modules while allowing light generated by the audio-visual prompting modules on the second layer to pass through. The first, second, and third layers are stacked sequentially and connected together by pressing, adhesive, double-sided tape, screws, heat fusion, or other methods, thereby preventing the first, second, and third layers from separating when the trainee exercises on the exercise mat and ensuring the stability and durability of the connection structure of the first, second, and third layers. Preferably, the audio-visual prompting module can be disposed on the second layer and protected by a light-transmitting third layer; or, the audio-visual prompting module can be disposed on the third layer to produce sufficiently conspicuous prompts. The audio-visual prompting module can be implemented to include at least one sound-emitting element and several light-emitting elements. Preferably, the sound-emitting element can be implemented as a buzzer. Preferably, the light-emitting element can be implemented as an LED light. Preferably, the control module 100 can be disposed on any layer of the exercise device 200, more preferably on the second layer. Preferably, the control module 100 can also be remotely connected to the exercise device 200 via wireless signal. The exercise mat can be made of flexible materials such as rubber, silicone, and canvas to provide cushioning when used by trainees, reduce joint injuries during exercise, and prevent vibrations generated during use from being transmitted to downstairs residents; and after training, it can be rolled up for easy storage. Preferably, the shape of the exercise mat can be various shapes such as rectangle, square, circle, and oval, without specific limitations.

[0034] According to a preferred embodiment, the exercise device 200 is composed of several uniformly sized grids connected together, or has a pattern on its surface dividing the exercise device 200 into several uniformly sized grids. The trainee steps on the corresponding grids according to guidance. The grids to be stepped on and those being stepped on constitute the trainee's movement path, guiding the trainee to move and walk along the path, thus improving balance. Preferably, the size of the grids is suitable for most people's shoe sizes. Preferably, each grid contains several light-emitting elements arranged in a specific shape. These light-emitting elements can be controlled by the control module 100 to emit light simultaneously. The resulting prompt shape, combined with the voice prompt generated by a buzzer based on the control signal simultaneously sent by the control module 100 to the buzzer, constitutes a first audio-visual prompt to guide the trainee to step on the grid.

[0035] According to a preferred embodiment, the motion device 200 is an integral device, with a plurality of light-emitting elements evenly distributed on its surface. When guidance is needed for trainees, the control module 100 controls at least some of the light-emitting elements to emit light, arranging them into desired prompting shapes at different positions on the motion device 200. These prompting shapes, together with a voice prompt generated by a buzzer based on a control signal simultaneously sent by the control module 100 to the buzzer, constitute a first audio-visual prompt to guide trainees in their movements on the motion device 200. The prompting shapes can be directional arrows, dots, footprints, or other patterns that serve a guiding function.

[0036] According to a preferred embodiment, the nursing system further includes a border detection module disposed around the grid edge or at least partially light-emitting elements of the motion device 200, the border detection module being data-connected to the control module 100. Preferably, the nursing system further includes a center detection module for detecting whether there is stepping or contact around the center of a predetermined landing point, the center detection module being data-connected to the control module 100. The center detection module in the landing point detects whether the trainee has accurately stepped around the predetermined landing point. When no stepping around the predetermined landing point is detected within the detection cycle, a control signal is sent to the audio-visual prompt module to control the audio-visual prompt module to issue a second audio-visual prompt to indicate that the trainee's movement is not standard and / or to guide the trainee to adjust the movement. When a trainee is detected stepping onto the area around a predetermined landing point, the border detection module around the predetermined landing point detects the stepping or contact action in the area around the grid edge or at least part of the light-emitting element, and transmits the detected data to the control module 100. The control module 100 determines whether the area around the grid edge or at least part of the light-emitting element has been stepped on or touched based on the detection data from the border detection module, thereby determining whether the trainee has stepped out of bounds. If the control module determines that the trainee has stepped out of bounds, it sends a control signal to the audio-visual prompt module to issue a second audio-visual prompt, indicating that the trainee's action is not standard and / or instructing the trainee to adjust their action. Preferably, the border detection module can be implemented as one or more detection elements such as a pressure detector, an infrared detector, or an electromagnetic detector, capable of detecting and generating detection data of the trainee's stepping or contact.

[0037] According to a preferred embodiment, the nursing system includes multiple predetermined training modes of varying difficulty to provide different levels of training for trainees with different motor abilities. Preferably, the nursing system includes at least a beginner training mode, an intermediate training mode, and an advanced training mode with increasing difficulty. The lowest difficulty beginner training mode may have the smallest stride length along the direction of movement and the largest lateral stride length perpendicular to the direction of movement. The medium difficulty intermediate training mode has a small stride length along the direction of movement and a small lateral stride length perpendicular to the direction of movement. The highest difficulty advanced training mode has the largest stride length along the direction of movement and the smallest lateral stride length perpendicular to the direction of movement. Preferably, the difficulty adjustment of the nursing system can be a fixed adjustment method that allows for automatic control via voice / action or manual control of the exercise device 200 via individual / combined buttons before the start of exercise. Preferably, the difficulty adjustment of the nursing system can also be automatically performed by the control system based on the trainee's EEG data and the accuracy data of the actual movements.

[0038] According to a preferred embodiment, the difficulty of the exercise in the nursing system can be increased by switching between predetermined training modes of varying difficulty. The guidance mode of the exercise device 200 can be based on the predetermined training mode, presenting the training route in the predetermined training mode before training begins. However, this method limits the training modes that can be changed in actual use, and the difficulty difference between each adjusted training mode is relatively large, resulting in limited matching with the trainee's actual balance state. Preferably, the difficulty of the exercise in the nursing system can also be increased by adjusting the stride length and lateral stride perpendicular to the direction of movement with smaller data changes, thereby adjusting the difficulty of the nursing system with a smaller difficulty gradient, which can improve the matching between the training mode and the trainee's actual balance state. Preferably, the nursing system can also increase the difficulty of the exercise by raising the standard of judgment accuracy.

[0039] According to a preferred embodiment, the size of the light-emitting range formed by the light-emitting element, which emits light at least partially based on the control of the control module 100, can vary depending on the difficulty of the mode. For example, as the training difficulty increases, the light-emitting range of the light-emitting device decreases sequentially; at the same time, the detection range of the device also decreases sequentially, thereby increasing the judgment criteria of the motion device 200 on the accuracy of stepping, so that the trainee needs to step more accurately to be judged as having a standard movement.

[0040] According to a preferred embodiment, the guidance mode of the exercise device 200 can also be adjusted in real time and gradually displayed based on the trainee's training progress, the accuracy of the movements, and the trainee's perception of the current training difficulty level. That is, when the trainee steps on the first stepping point and stands firmly, the exercise device 200 displays a unique stepping position for the next step, and at the same time, the sound device synchronously prompts the location of the unique stepping position relative to the current stepping position, so that the trainee can identify the next stepping point. The stepping position for the next step can be obtained by the following method: the control module 100 calculates the center landing point of the next step as the light-emitting center point based on the current user's shoe size, height information, leg length information, and normal stride size, and analyzes and calculates the current light-emitting radius according to the currently selected predetermined difficulty mode, and sends control signals to the light-emitting elements around the light-emitting center point and the light-emitting elements around the current light-emitting radius to activate the light-emitting elements at the current light-emitting center point and the current light-emitting radius, and at the same time emits light to provide an indication to the trainee. Simultaneously, the control module 100 activates sensors within the current light-emitting center and radius based on the calculation results to detect whether the trainee has stepped into the light-emitting radius. The control module 100 also activates the border detection module around the light-emitting radius based on the calculation results to detect whether the trainee's footing point has shifted, and judges the accuracy of the trainee's movements based on the magnitude of the shift. Through this setup, the current training mode and light emission can be intelligently adjusted according to the trainee's foot size and stride length. Furthermore, the border detection module can adapt to changes in the current light-emitting center point and radius, adaptively changing its detection position as the difficulty of the training mode increases.

[0041] According to a preferred embodiment, the exercise device 200 is equipped with at least a plurality of sensors arranged in an array. The control module 100 determines the center position of the sensors whose returned pressure data is non-zero based on the array position information of the sensors that have returned pressure data. The control module 100 compares the center position with the center position of the predetermined guidance program to determine the offset, and determines the accuracy index based on the offset. The control module 100 determines the balance index of the trainee at the center position through the path speed and swing distance parameters of the minimum pressure center. The control module 100 calculates the exercise achievement index based on the accuracy index and the balance index.

[0042] Preferably, the accuracy index is calculated according to the following method:

[0043] The accuracy index can be a vector value between the sensor's center position and a preset center position in a predetermined guidance program. The sensor's center position can be calculated based on the location of the maximum pressure value and the coordinate information of all sensors whose returned data is not zero.

[0044] Preferably, the balance index is calculated according to the following method:

[0045] The absolute energies of the β1 and α bands for the trainees were calculated separately; the α and β1 bands represent the brainwave ranges of 8-12Hz and 15-18Hz, respectively. The energy calculation methods for the α and β1 bands can include preprocessing the acquired brainwave signals using the EEGLAB toolkit, including filtering the signal, using independent component analysis (ICA) to remove noise and eliminate eye movement artifacts, and then segmenting the ICA-processed signal and applying windowing to obtain the time-domain signal x. m The signal is converted to the frequency domain by performing a Fast Fourier Transform. The total spectral energy of the signal is calculated by taking the square of the frequency domain signal, and finally the average spectral energy is calculated. The balance index = mE α -n E β1 Where m and n are E α and E β1 The weight values ​​are , where m can be 1, 2 or 3; n can be 1, 2 or 3.

[0046] Preferably, the exercise achievement index is calculated according to the following method:

[0047] The exercise achievement index = a Balance Index + b Accuracy Index, where a and b are the weight values ​​of the balance index and accuracy index, respectively. The values ​​of a and b can be determined by the user based on the actual situation.

[0048] Example 2

[0049] This embodiment is a further improvement on embodiment 1, and repeated content will not be described again.

[0050] This embodiment discloses a nursing method for monitoring movement, which includes at least guiding the trainee to perform corresponding actions according to a predetermined guidance procedure and monitoring the trainee's movement parameters.

[0051] The exercise achievement index and mental index of the current trainee are generated based on the exercise parameters. The matching index between the established guidance program and the trainee's balance level is calculated based on the exercise achievement index and mental index. The established guidance program is adjusted based on the matching index.

[0052] The trainee's motion parameters, including physiological parameters, are monitored based on the adjusted established guidance procedure.

[0053] Preferably, the physiological parameters are the user's real-time electroencephalogram (EEG) data. The control module 100 preprocesses the EEG signals acquired by the sensor; it then performs a Fourier transform on the preprocessed EEG signals to obtain the corresponding frequency band energies E in the β-wave and θ-wave bands. β and E θTheta waves, with a frequency of 4-7 Hz, are highly prominent in adults experiencing frustration and depression, as well as in patients with mental illness. However, this wave is a major component of the EEG in adolescents (10-17 years old). Beta waves, with a frequency of 14-30 Hz, appear during periods of mental tension, emotional excitement, or agitation. When a person is awakened from sleep, the original slow wave rhythm can be immediately replaced by this rhythm. When the energy value of theta waves in a trainee is high, it indicates that the trainee is experiencing frustration during the current training process, and the energy value of theta waves is E... θ Energy values ​​higher than β waves E β Furthermore, when the duration is relatively long, the matching index value under the current physiological parameters is defined as a low level of matching, thereby quickly reducing the difficulty of the exercise. Conversely, when the energy value E of the trainee's β wave... β Energy value E higher than the theta wave θ Furthermore, when the duration is long, the matching index under the current physiological parameters is defined as high, thereby slowly increasing the difficulty of the exercise.

[0054] Preferably, the mental index can also be calculated using the following method:

[0055] Mental Index = E θ / E β When the mental index is greater than 1, the control module 100 reduces the difficulty of the predetermined boot program; when the mental index is less than 1, the control module 100 increases the difficulty of the predetermined boot program.

[0056] Preferably, the mental index can be calculated using the following method:

[0057] Define the theta wave energy value E θ The β-wave energy value E is negative. β A positive value indicates that the mental index is equal to the theta wave energy value E. θ Add the aforementioned β-wave energy value E β。

[0058] When the mental index is negative, the control module 100 reduces the difficulty of the predetermined boot program;

[0059] When the mental index is positive, the control module 100 increases the difficulty of the predetermined boot program.

[0060] Preferably, the motion parameters are detected by at least two detection modules with distinct detection logic disposed on the motion device 200; for example, they may be a balance force parameter detection module and a pressure magnitude or position detection module.

[0061] According to a preferred embodiment, the control module 100 calculates the matching index based on the exercise achievement index and the mental index, wherein the matching index is the sum of the exercise achievement index and the mental index. By simultaneously considering the exercise achievement index and the trainee's feelings when adjusting the difficulty, both training effectiveness and the trainee's motivation can be balanced.

[0062] According to a preferred embodiment, the matching index can also be calculated using a linear function equation, where the matching index equals k times the mental index plus the exercise achievement index, and k is greater than 1. Increasing the value of k increases the weight of the mental index in the calculation of the matching index.

[0063] It should be noted that the specific embodiments described above are exemplary. Those skilled in the art can devise various solutions inspired by the disclosure of this invention, and these solutions all fall within the scope of this invention and its protection. Those skilled in the art should understand that this specification and its accompanying drawings are illustrative and do not constitute a limitation on the claims. The scope of protection of this invention is defined by the claims and their equivalents. This specification contains multiple inventive concepts; terms such as "preferredly," "according to a preferred embodiment," or "optionally" indicate that the corresponding paragraph discloses an independent concept. The applicant reserves the right to file divisional applications based on each inventive concept. Throughout the text, features introduced by "preferredly" are merely optional and should not be construed as mandatory. Therefore, the applicant reserves the right to abandon or delete relevant preferred features at any time.

Claims

1. A care system for monitoring movement, the care system guiding a trainee to perform a specific movement based on a predetermined guide program, monitoring movement parameters of the trainee while the trainee performs the specific movement, and adjusting a difficulty level of the predetermined guide program based on the movement parameters; characterized in that, the monitoring comprises balance monitoring and accuracy monitoring; the care system comprises a control module, the control module calculating a movement compliance index and a mental index of the trainee based on the movement parameters, and adjusting the movement difficulty level of the predetermined guide program based on the movement compliance index and the mental index, the care system monitoring the movement parameters of the trainee based on the adjusted predetermined guide program, the movement parameters further comprise physiological parameters of the trainee during the movement, the control module calculating the mental index of the trainee based on the physiological parameters, the control module calculating a balance index of the trainee based on the movement parameters, the control module calculating a matching index of the predetermined guide program and the balance of the trainee based on the mental index and the movement compliance index, the matching index being a sum of the movement compliance index and the mental index, the control module calculating the mental index based on energy values of theta waves and beta waves, the control module grading the matching index, the control module calculating a difficulty adjustment gradient of the predetermined guide program based on the grading number of the matching index, and adjusting the predetermined guide program according to the calculated difficulty adjustment gradient, the grading method of the matching index being that, based on reinforcement theory, a difference value of the physiological parameters of any two adjacent graded matching indexes is constant, the difference value of the physiological parameters being determined according to a size of a physiological parameter change value of the trainee during movement in a maximum difficulty level predetermined guide program and movement in a minimum difficulty level predetermined guide program, the care system comprising a movement device for placing on the ground for the trainee to perform movement according to the predetermined guide program and for detecting the movement parameters, the movement device being provided with an array of sensors, the control module determining a center position of the sensors with non-zero return data based on array position information of the sensors with pressure data return, comparing the center position with a center position of the predetermined guide program to determine an offset, and determining an accuracy index according to the offset, the control module calculating the movement compliance index based on the accuracy index and the balance index. When the matching index is within a first threshold range, the control module (100) adjusts the difficulty adjustment gradient of the predetermined guide program to be zero. The control module (100) selects to reduce or increase the difficulty level of the predetermined guide program based on the physiological parameters, The physiological parameters are energy values of brain waves, when the energy value of theta waves is higher than the energy value of beta waves, the control module (100) reduces the difficulty level of the predetermined guide program; When the energy value of theta waves is lower than the energy value of beta waves, the control module (100) increases the difficulty level of the predetermined guide program. The first threshold is a numerical value of the matching index when the energy value of theta waves is equal to the energy value of beta waves. The control module (100) determines the balance index of the trainee at the center position through path speed and swing distance parameters of the minimum pressure center. ​ ​ 2. The care system according to claim 1, characterized in that ​ 3. The care system according to claim 2, characterized in that ​ ​ ​ 4. The care system according to claim 3, characterized in that ​ 5. The care system according to claim 4, characterized in that ​

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