Motion control method of wearable device, wearable device, wearable equipment and medium

Abstract

The embodiment of the invention provides a motion control method of a wearable device, the wearable device, wearable equipment and a medium, and belongs to the technical field of embedded development. The method is applied to a wearable device and comprises the following steps: detecting sensor data of the wearable device through each sensor; selecting a target device from the at least two wearable devices, and sharing the sensor data with the target device through each wearable device; gait analysis is carried out on the collected sensor data of all the wearable devices through the target device to obtain global gait data; generating a control instruction of each wearable device according to the global gait data; and sending a control instruction to each wearable device through the target device, so that each wearable device controls the motor according to the control instruction. According to the embodiment of the invention, the working reliability of the wireless wearable device can be improved.

Description

Technical Field

[0001] This application relates to the field of embedded development technology, and in particular to a motion control method for a wearable device, a wearable device, a wearable equipment, and a medium. Background Technology

[0002] Currently, wearable devices used to assist human walking (such as exoskeletons) typically use wired connections for data communication between components, making these devices quite complex to wear. To improve the convenience of wearable devices in assisting walking, wireless communication technology can be used for transmission; however, compared to wired transmission, wireless transmission has lower communication stability. Therefore, ensuring the reliability of wireless transmission in wearable devices has become a pressing technical problem to be solved. Summary of the Invention

[0003] The main objective of this application is to provide a motion control method, wearable device, wearable equipment, and medium for a wearable device, aiming to improve the operational reliability of wireless wearable devices.

[0004] To achieve the above objectives, a first aspect of this application proposes a motion control method for a wearable device, applied to the wearable device, which includes at least two wearable devices located at different positions, the positions including the foot; each wearable device includes a motor and multiple sensors, the multiple sensors being used to detect pressure, acceleration, and angular velocity corresponding to the wearable device, the motor being used to drive the wearable device to assist motion, the method comprising: Sensor data of the wearable device is detected by each of the aforementioned sensors; Select a target device from at least two wearable devices, and share the sensor data with the target device through each wearable device; The target device performs gait analysis on the sensor data of all the wearable devices collected to obtain global gait data; Control commands for each wearable device are generated based on the global gait data. The target device sends the control command to each of the wearable devices, so that each wearable device controls the motor according to the control command.

[0005] In some embodiments, the step of performing gait analysis on the sensor data of all the wearable devices collected by the target device to obtain global gait data includes: For each wearable device, gait data calculation is performed on the sensor data to obtain local gait data; The local gait data is shared with the target device through each of the wearable devices; The target device integrates all the local gait data and the sensor data to obtain the global gait data.

[0006] In some embodiments, sharing the local gait data with the target device through each of the wearable devices includes: The swing state of the wearable device is determined based on the local gait message; wherein the swing state is used to indicate whether the wearable device is in an active state or a supported state. If the swing state of the wearable device indicates that the wearable device is active, then the local gait data is shared with the target device.

[0007] In some embodiments, sharing the sensor data with the target device through each of the wearable devices includes: Determine the target identifier based on the target device; The source identifier is determined based on the sensor; The message type is determined based on the type of the sensor; Construct a message header based on the target identifier, the source identifier, and the message type; A sensing detection message is constructed based on the message header and the sensor data, and the sensing detection message is sent to the target device.

[0008] In some embodiments, generating control commands for each of the wearable devices based on the global gait data includes: Obtain the movement speed of each wearable device; The target acceleration is obtained by calculating the acceleration based on the movement speed and the global gait data. The control command is generated based on the target acceleration.

[0009] In some embodiments, selecting a target device from at least two wearable devices includes: The target device is selected from at least two wearable devices based on the current bandwidth data of all wearable devices or preset hardware configuration data; or, All of the wearable devices are considered as the target device.

[0010] In some embodiments, before selecting a target device from at least two wearable devices and performing gait analysis on the sensor data collected from all the wearable devices through the target device to obtain global gait data, the method further includes: Acquire wireless communication signals from an external device; wherein, the external device is not the wearable device in the wearable device. A communication channel is established between the external device and each of the wearable devices based on the wireless communication signal. In response to a control request issued by the control device node, a target control device is determined from at least two wearable devices based on the control request, and a control command corresponding to the target control device is generated. The control command is obtained through the communication channel between the external device and the target control device, so that the target control device controls the motor according to the control command.

[0011] To achieve the above objectives, a second aspect of this application provides a wearable device comprising at least two wearable devices located at different positions, the positions including the feet; each wearable device includes a motor and multiple sensors, the multiple sensors being used to detect pressure, acceleration and angular velocity corresponding to the wearable device, and the motor being used to drive the wearable device to assist movement; The wearable device located at the foot also includes rollers, and the motor is used to control the rotation or stopping of the rollers.

[0012] To achieve the above objectives, a third aspect of this application provides a wearable device, the wearable device including a controller, the controller including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method described in the first aspect.

[0013] To achieve the above objectives, a fourth aspect of the present application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in the first aspect.

[0014] The motion control method, wearable device, wearable equipment, and medium proposed in this application obtain sensor data from each individual wearable device corresponding to a sensor. Then, a target device is selected, and each wearable device shares its own sensor data with the target device. Each wearable device can be considered an edge node, and the various wearable devices within the wearable device collectively form a distributed network. Subsequently, gait analysis is performed through the target device to obtain global gait data reflecting the user's current state. Accurate control commands are then generated based on the global gait data, and finally, the target device sends corresponding control commands to each wearable device to achieve accurate control of each motor. Traditional wired wearable devices typically use a fixed centralized processing unit to execute complex tasks. Compared to this transmission technology, the method in this application utilizes the parallel processing capabilities of a distributed computing network, enabling the wearable device to respond in real time and efficiently process large amounts of sensor data. It also allows for flexible selection of the target device from multiple wearable devices to ensure efficient task execution. Therefore, the method in this embodiment not only enhances the stability of wireless communication during operation, allowing the wearable device to maintain high efficiency and reliable performance, but also provides users with a more comfortable and smooth assisted movement experience. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of a wearable device provided in an embodiment of this application; Figure 2 This is a right view of a wearable device provided in an embodiment of this application; Figure 3 yes Figure 2 A top view of the sole of the foot in a wearable device; Figure 4 This is a schematic diagram of a wearable device provided in an embodiment of this application; Figure 5 This is a flowchart of the motion control method for the wearable device provided in the embodiments of this application; Figure 6 yes Figure 5 The flowchart of step S502 in the document; Figure 7 This is a module interaction diagram of a wearable device provided in an embodiment of this application; Figure 8 This is another module interaction diagram of the wearable device provided in the embodiments of this application; Figure 9 yes Figure 5 The flowchart of step S503 in the process; Figure 10 yes Figure 9 The flowchart of step S702 in the process; Figure 11yes Figure 5 The flowchart of step S504 in the process; Figure 12 This is another flowchart of the motion control method for the wearable device provided in the embodiments of this application; Figure 13 This is a schematic diagram of the hardware structure of a controller for a wearable device provided in an embodiment of this application. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0017] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0019] First, let's analyze some of the terms used in this application: A real-time operating system (RTOS) is an operating system that can accept and process external events or data at a sufficiently fast speed, and whose processing results can control the production process or respond quickly to the processing system within a specified time, schedule all available resources to complete real-time tasks, and control all real-time tasks to run in a coordinated manner.

[0020] Bare machine (or bare metal): refers to an electronic computer without an operating system or other software installed. Bare machine programs do not use traditional operating systems (such as Windows, Linux, etc.) or real-time operating systems (RTOS), but directly access hardware resources. Bare machine programming typically involves direct manipulation and control of the hardware; all task scheduling, resource management, and system operation must be manually managed by the developer.

[0021] Currently, wearable devices used to assist human walking (such as exoskeletons) typically use wired connections for data communication between components, making these devices quite complex to wear. To improve the convenience of wearable devices in assisting walking, wireless communication technology can be used for transmission; however, compared to wired transmission, wireless transmission has lower communication stability. Therefore, ensuring the reliability of wireless transmission in wearable devices has become a pressing technical problem to be solved.

[0022] Based on this, embodiments of this application provide a motion control method for a wearable device, a wearable device, a wearable equipment, and a medium, aiming to improve the operational reliability of wireless wearable devices.

[0023] The motion control method, wearable device, wearable equipment, and medium for wearable devices provided in this application are specifically described through the following embodiments. Before describing the motion control method of the wearable device in the embodiments of this application, let's first combine... Figures 1 to 3 The document also introduces the hardware devices required for the motion control method, along with specific embodiments.

[0024] Please see Figure 1 , Figure 1 This is a schematic diagram of a wearable device provided in an embodiment of this application. This application provides a wearable device comprising at least two wearable devices located at different positions, including the foot. Figure 1 For example, wearable devices positioned at the feet include wearable device 1 and wearable device 2. In other embodiments, in addition to the aforementioned pair of wearable devices positioned at the feet, the wearable device may also include wearable devices 3 and 4 positioned at the knees, and wearable devices 5 and 6 positioned at the thighs. The positions of the wearable devices may also include the lower legs and ankles. This application embodiment only requires that at least two wearable devices in the wearable device are used to be worn on the user's feet. The number of other wearable devices in the wearable device, and their positions relative to the user when worn, are not strictly limited.

[0025] Furthermore, each wearable device includes a motor and multiple sensors. The sensors are used to detect pressure, acceleration, and angular velocity corresponding to the wearable device, and the types of sensors can be adjusted according to actual needs. The motor is used to drive the wearable device to assist in movement.

[0026] In this embodiment, the wearable device located at the foot can be an electric shoe, the structure of which can be found in [reference needed]. Figure 2 and Figure 3 , Figure 2 This is a right view of a wearable device provided in an embodiment of this application. Figure 3This is a top view of the foot portion of the wearable device. The device also includes wheels, with a motor controlling their rotation and stopping. Load sensors are embedded in the heel, midfoot, and forefoot areas of the electric shoe's bottom structure to detect pressure data. The electric shoe also incorporates an inertial sensor and a motor encoder; the inertial sensor detects data such as linear acceleration and angular velocity.

[0027] Please see Figure 4 , Figure 4 This is a schematic diagram of a wearable device module provided in an embodiment of this application. In some embodiments, each wearable device further includes a controller, and the controller includes two control chips, wherein the first control chip is connected to multiple sensors, and the second control chip is connected to a motor. The first control chip and the second control chip realize bidirectional communication. Further, the second control chip transmits motor-related data to the first control chip, the first control chip sends control commands to the second control chip, and the second control chip controls the motor of the device according to the control commands.

[0028] In some embodiments, the first control chip employs a real-time operating system (RTOS) for management and control, enabling efficient task scheduling and resource management. The second control chip, however, does not rely on an operating system and implements control functions directly through bare-metal programming, thereby providing lower system overhead and higher real-time response capabilities. This application does not strictly limit the specific models of the first and second control chips.

[0029] The application process of the wearable device described above will be explained in detail in subsequent specific embodiments of the motion control method of the wearable device, and will not be repeated here.

[0030] Please see Figure 5 In some embodiments, the motion control method for the wearable device provided in this application is applied to the wearable device provided in this application. The method may include, but is not limited to, steps S501 to S505: Step S501: Detect sensor data from the wearable device using each sensor.

[0031] Step S502: Select a target device from at least two wearable devices and share sensor data with the target device through each wearable device.

[0032] Step S503: Gait analysis is performed on the sensor data of all wearable devices collected by the target device to obtain global gait data.

[0033] Step S504: Generate control commands for each wearable device based on global gait data.

[0034] Step S505: The target device sends a control command to each wearable device so that each wearable device controls the motor according to the control command.

[0035] Steps S501 to S505 of this embodiment first obtain sensor data from the individual wearable device corresponding to each sensor. Then, a target device is selected, and each wearable device shares its own sensor data with the target device. Each wearable device can be regarded as an edge node, and the various wearable devices within the wearable device together constitute a distributed network. Subsequently, gait analysis is performed through the target device to obtain global gait data that reflects the user's current gait. Then, accurate control commands are generated based on the global gait data, and finally, the target device sends the corresponding control commands to each wearable device to achieve accurate control of each motor. Traditional wired wearable devices typically use a fixed centralized processing unit to execute complex tasks. Compared with this transmission technology solution, the method of this embodiment utilizes the parallel processing capability of a distributed computing network, enabling the wearable device to respond in real time and efficiently process a large amount of sensor data. At the same time, it can flexibly select the target device from multiple wearable devices to ensure efficient task execution. Therefore, the method of this embodiment not only enhances the stability of wireless communication during the operation of the wireless wearable device, enabling the wearable device to maintain efficient and reliable performance, but also provides users with a more comfortable and smooth assisted movement experience.

[0036] In step S501 of some embodiments, sensor data refers to physical quantity data collected by each wearable device from various sensors within the device, which may include data such as pressure, acceleration, angular velocity, and Euler angles corresponding to the wearable device. This sensor data can be acquired by connecting to a control chip via a sensor interface, transmitting the analog or digital signals collected by the sensors to the control chip to obtain the sensor data.

[0037] In step S502 of some embodiments, in this embodiment, the target device refers to the core device responsible for performing gait analysis, which can be any wearable device in the wearable device, usually the device with the most powerful functions and the strongest processing capabilities.

[0038] This application preferably employs a publish / subscribe (Pub / Sub) model for data sharing. In this embodiment, each wearable device has two control chips, one of which has a real-time operating system installed, and the other is a taskless system. In traditional embedded development, to achieve wireless communication between different chips, it is usually necessary to write communication code separately for each chip. This not only increases the development workload but may also lead to compatibility issues between different chips. However, by adopting the publish / subscribe (Pub / Sub) model, each chip in the wearable device, as well as different chips in different wearable devices, can act as an independent communication node, enabling data exchange through a unified topic, thereby achieving cross-platform and cross-operating system compatibility. Furthermore, since this application involves a small number of wearable devices, the middleware used is relatively lightweight, thus forming a lightweight and efficient routing system.

[0039] Using a publish / subscribe (Pub / Sub) model, data that needs to be transmitted wirelessly is encapsulated into messages. For details, please refer to [link to relevant documentation]. Figure 6 In some embodiments, step S502 includes, but is not limited to, steps S601 to S605: Step S601: Determine the target identifier based on the target device.

[0040] Step S602: Determine the source identifier based on the sensor.

[0041] Step S603: Determine the message type based on the sensor type.

[0042] Step S604: Construct a message header based on the target identifier, source identifier, and message type.

[0043] Step S605: Construct a sensing detection message based on the message header and sensor data, and send the sensing detection message to the target device.

[0044] In step S601 of some embodiments, the target identifier refers to a unique identifier used in communication to identify the target device receiving the message.

[0045] In step S602 of some embodiments, the source identifier refers to the device or sensor used in communication to identify the source of message data. In some embodiments, two or more sensors may be connected to the controller through the same port, in which case the source identifier includes a port identifier and a sensor device identifier. In this embodiment, relying solely on the port identifier is insufficient to distinguish which sensor generated the current data; therefore, a sensor device identifier can be added to determine this.

[0046] In step S603 of some embodiments, the message type may include pressure, acceleration, angular velocity, and temperature, but is not limited thereto.

[0047] In step S604 of some embodiments, the target identifier, the port identifier of the source identifier, the sensor device identifier, and the message type can be packaged as fields and then a 4-byte message header can be constructed according to a specific format (such as JSON, XML, binary format, etc.).

[0048] In step S605 of some embodiments, the message header is merged with the collected sensor data to form a complete message content, and then the message is sent to the target device through middleware (such as message queue middleware, message broker or Pub / Sub system) via a specified communication protocol.

[0049] Steps S601 to S605 as shown in the embodiments of this application establish a clear identification system between the target device and the sensor, and combine it with the type of sensor data to effectively construct a lightweight message header structure for inter-device communication. This provides extremely high communication efficiency in resource-constrained microcontroller environments without the need for complex network middleware.

[0050] It should be noted that this application provides two options for selecting the target device: selecting the target device from at least two wearable devices based on the current bandwidth data of all wearable devices or preset hardware configuration data; or using all wearable devices as the target device.

[0051] For the first selection scheme: a target device is selected from at least two wearable devices based on the current bandwidth data of all wearable devices or preset hardware configuration data. That is, one target device is determined as the primary control device among multiple wearable devices, and the rest are secondary control devices. Further, the current bandwidth data refers to the actual network bandwidth used by each wearable device during communication. By detecting the data transmission rate and network bandwidth usage of each wearable device, the communication load of each device can be determined. If a wearable device has low bandwidth usage, it means that the network load of that device is light, making it suitable for undertaking more tasks or serving as the target device for data processing. Hardware configuration data refers to the hardware performance information of each wearable device, including processor clock speed, memory, etc. Further, the hardware configuration data of all wearable devices can be compared, and the specific values ​​of the hardware configuration data determine the device with the best hardware performance as the target device. For example, the wearable device with the highest processor clock speed is selected as the target device. In other embodiments, the current bandwidth data of all wearable devices can be detected in real time, and the wearable device corresponding to the lowest current bandwidth data can be selected as the target device.

[0052] In this embodiment, all secondary control devices transmit sensor data to the primary control device, which then generates control commands for each wearable device (including its own control commands). The primary control device then sends each control command back to the secondary control devices. For example, please refer to [link to example]. Figure 7 , Figure 7 This is a module interaction diagram of a wearable device provided in an embodiment of this application. Figure 7 In the illustrated embodiment, the wearable device includes two wearable devices located on the foot: a left shoe and a right shoe. The left shoe is designated as the primary control device, and the right shoe as the secondary control device. The first control chip in the left shoe generates control commands for each wearable device based on sensor data from its own device and the secondary control device, and sends these control commands back to the secondary control device. Within each wearable device, the first control chip sends control commands to the second control chip.

[0053] For the second option: use all wearable devices as the target device. It should be noted that in step S502 of this embodiment, each wearable device receives sensor data from all wearable devices. For an example, please refer to... Figure 8 , Figure 8 This is another module interaction diagram of the wearable device provided in the embodiments of this application. Figure 8 In the illustrated embodiment, the wearable device includes two wearable devices located on the foot: a left shoe and a right shoe. For the left shoe, the left shoe calculates its own control command based on its own sensor data, and simultaneously receives sensor data from the right shoe to calculate the right shoe's control command, which is then sent back to the right shoe. The same logic is applied to the right shoe, calculating its own control command and the left shoe's control command, and then sending the left shoe's control command to the left shoe.

[0054] Both of the aforementioned module interaction schemes can employ full-duplex and half-duplex communication methods. In full-duplex mode, both parties communicate during their earliest available time. In half-duplex mode, one party only sends a message after receiving one from the other.

[0055] In step S503 of some embodiments, the global gait data includes all raw sensor data and gait characteristics calculated based on each sensor data, including key parameters such as stride length, stride speed, gait cycle, and center of pressure. For wearable devices located on the foot, it may also include ankle joint torque.

[0056] In some embodiments, the target device may calculate the gait data of the corresponding wearable device for each sensor data.

[0057] In other embodiments, the wearable device may first calculate its own gait data, which in this case only reflects local gait characteristics. Subsequently, the wearable device transmits its local gait data and sensor data together to the target device, allowing the target device to integrate this data and generate global gait data. For details, please refer to... Figure 9 Step S503 may include, but is not limited to, steps S901 to S903: Step S901: For each wearable device, gait data calculation is performed on the sensor data to obtain local gait data.

[0058] Step S902: Share local gait data with the target device through each wearable device.

[0059] Step S903: The target device integrates all local gait data and sensor data to obtain global gait data.

[0060] In step S901 of some embodiments, the local gait data includes a pressure center, an estimated ankle joint position, and an ankle joint torque. For example, the pressure center can be calculated based on the position of the load sensor in the wearable device and the detected pressure value. The estimated ankle joint position vector is then determined based on the position of the pressure center in preset x-axis and y-axis directions. Subsequently, the ankle joint torque is calculated based on the estimated ankle joint position vector, the position of the load sensor, and the detected pressure value. The specific calculation method can be adjusted according to the geometric positions between different sensors of the wearable device and the mechanical model of the wearable device, and is not strictly limited here.

[0061] In step S902 of some embodiments, it can be understood that data transmission between different devices can be achieved through subscription / pattern. The specific implementation process of message encapsulation for different types of data is consistent with the specific embodiments of steps S601 to S605, and will not be described in detail here.

[0062] Please see Figure 10 In some embodiments, for wearable devices positioned at the feet, cross-device data transmission can be determined based on the current swing state of the wearable device. Step S902 may include, but is not limited to, steps S1001 to S1002: Step S1001: Determine the swing state of the wearable device based on the local gait message; wherein the swing state is used to indicate whether the wearable device is in an active state or a supported state.

[0063] Step S1002: If the swing state of the wearable device indicates that the wearable device is in an active state, then share the local gait data with the target device.

[0064] In step S1001 of some embodiments, the active state means that the user is in the process of raising or lifting their foot, and the supporting state means that the user is either placing the device on the ground or supporting themselves. This can be determined based on the sensing data from the load sensors. For example, when all load sensors detect a reaction force perpendicular to the ground, the swinging state can be determined as the supporting state. When all or some of the load sensors do not detect a reaction force perpendicular to the ground, the swinging state can be determined as the active state.

[0065] In step S1002 of some embodiments, if the swing state of the wearable device indicates that the wearable device is in a supported state, then no data transmission is performed. This is because when the wearable device is in a supported state, its force situation is more complex than when it is in an active state, and more tasks need to be processed. Performing tasks such as message encapsulation at this time may result in a waste of computing resources.

[0066] Steps S1001 to S1002, as illustrated in this embodiment, determine whether to share local gait data by judging the swing state of the wearable device based on local gait messages, thereby achieving more efficient and stable wireless data transmission. Through intelligent judgment of the device's swing state, the system can ensure timely data sharing when the device is active, avoiding unnecessary data transmission and delays. Furthermore, this solution effectively reduces the communication burden and improves the wireless communication stability and response speed of the wearable device by reducing the frequency of data transmission and optimizing the timing of data transmission.

[0067] In step S903 of some embodiments, global gait data can be calculated according to a preset algorithm model (e.g., a weighted average based on gait cycles).

[0068] Steps S901 to S903, as illustrated in the embodiments of this application, achieve distributed data processing and integration by sharing local gait data and sensor data from each wearable device with the target device, thus avoiding the problem of excessive load on a single device. While ensuring the comprehensiveness and accuracy of gait data, the calculation process is also optimized, improving the operating efficiency of the wearable device. Furthermore, the distributed data processing and transmission mechanism enhances the reliability of the wireless wearable device.

[0069] In step S504 of some embodiments, in this embodiment, the control command refers to the command generated based on the gait analysis results to control the actions of each wearable device. The control command includes, but is not limited to, controlling the start, stop, and acceleration adjustment of the motor.

[0070] Specifically, please refer to Figure 11 In some embodiments, step S504 may include, but is not limited to, steps S1101 to S1103: Step S1101: Obtain the movement speed of each wearable device.

[0071] Step S1102: Acceleration is calculated based on movement speed and global gait data to obtain the target acceleration.

[0072] Step S1103: Generate control commands based on the target acceleration.

[0073] In step S1101 of some embodiments, the movement speed refers to the linear speed of the wearable device during movement, which is usually detected by an accelerometer or an inertial sensor.

[0074] In step S1102 of some embodiments, for each wearable device, local gait data (including) and movement speed corresponding to it are determined from the global gait data.

[0075] For example, the target acceleration can be calculated analytically using the following expression: (1), Where t represents the current time step. This represents the target acceleration at the current time step. n represents the total number of time steps. This indicates the maximum allowable acceleration magnitude at the current time step. This represents the preset width parameter, whose value is greater than 0. s represents the normalized acceleration phase, and its value range is (0,1). This represents the peak phase of the preset normal curve, with a value range of (0,1).

[0076] Furthermore, It can be determined by the following analytical expression: (2), in, This indicates the speed at which the wearable device moves. This represents a coefficient related to movement speed. This represents the peak ankle joint reading detected over n time steps. This represents the median of the peak ankle torque within the most recent preset number of time steps.

[0077] about Its definition can be found in the following analytical expression: (3), Where M is the preset quantity, and median{} refers to performing the median operation.

[0078] about Its definition can be found in the following analytical expression: (4), in, This is a preset parameter, and its value is greater than 0. These are preset initial velocity-related parameters, and their values ​​are greater than 0.

[0079] Furthermore, the definition of the normalized acceleration phase can be found in the following analytical expression: (5), in, This indicates the time step at which the peak ankle joint torque occurs. This indicates the time step in which the linear velocity of an active wearable device reaches its maximum value.

[0080] In step S1103 of some embodiments, control commands can be generated in conjunction with the driving characteristics of the motor. For example, when the target acceleration is positive, the control command controls the motor to increase its speed to provide the required acceleration. If the target acceleration is negative (e.g., during braking), the control command will require the motor to operate in the opposite direction.

[0081] Steps S1101 to S1103, as illustrated in the embodiments of this application, enable precise calculation of the target acceleration based on the movement speed and global gait data of each wearable device, and generate control commands accordingly. Through dynamic calculation of acceleration, the system can respond to the user's movement needs in real time, ensuring the control accuracy of the wearable device.

[0082] In step S505 of some embodiments, after each wearable device receives a control command, it adjusts the motor's movement according to the command, such as starting, stopping, or adjusting the motor's speed and direction, thereby assisting the user in completing the expected exercise.

[0083] Please see Figure 12 In some embodiments, prior to step S502, external devices (such as mobile phones, tablets, or computers) can be directly connected to the network to control the wearable device. Specifically, this may include, but is not limited to, steps S1201 to S1204: Step S1201: Obtain wireless communication signals from an external device; wherein, the external device is not the wearable device in the wearable device.

[0084] Step S1202: Establish a communication channel between the external device and each wearable device based on the wireless communication signal.

[0085] Step S1203: In response to a control request issued by a control device node, a target control device is determined from at least two wearable devices based on the control request, and a control command corresponding to the target control device is generated.

[0086] Step S1204: Obtain control commands through the communication channel between the external device and the target control device, so that the target control device can control the motor according to the control commands.

[0087] In step S1201 of some embodiments, the wireless communication signal refers to a signal transmitted wirelessly by an external device.

[0088] In step S1202 of some embodiments, the external device sends signals to surrounding devices through a preset wireless communication protocol (such as Bluetooth, Wi-Fi, Zigbee, BLE Mesh network settings, etc.) so that the wearable device can identify and establish a communication channel.

[0089] In step S1203 of some embodiments, the target control device refers to the device selected according to the control request. The control command is generated by the system based on the current state of the device and the task requirements, and is used to instruct the target control device to perform a specific action. For example, if an external device requests the electric shoe of the right foot to reach a desired speed, the target control device is the electric shoe corresponding to the right foot, and the acceleration is determined based on the desired speed and the current speed of the electric shoe, thereby generating a control command based on the acceleration.

[0090] In step S1204 of some embodiments, the target control device obtains control commands from an external device through an established communication channel. After receiving the control commands, the target control device controls the motor according to the commands.

[0091] Steps S1201 to S1204 shown in this embodiment of the application, by adopting this distributed architecture based on wireless communication, enable multiple devices to freely access and disconnect, simplifying communication design and management. When facing the need to temporarily add or delete communication nodes, it avoids the connection complexity brought about by traditional wired communication methods and improves the collaboration efficiency between wearable devices.

[0092] The method in this application embodiment also includes a regenerative braking mechanism for the motor. Specifically, each wearable device is further provided with a small battery pack for powering the wearable device. When the motor is subjected to a large external torque, the motor will switch to generator mode, thereby generating a voltage rise and causing a reverse current to flow back to the battery pack, thus charging the battery.

[0093] This application also provides a wearable device, which includes a controller, a memory, and a processor. The memory stores a computer program, and the processor executes the computer program to implement the motion control method of the wearable device described above. This wearable device can be any smart terminal, including electric shoes, electric skateboards, and exoskeleton devices.

[0094] Please see Figure 13 , Figure 13 The hardware structure of a controller for a wearable device according to another embodiment is illustrated. The controller includes: The processor 1301 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 1302 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 1302 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1302 and is called and executed by the processor 1301 to execute the motion control method of the wearable device according to the embodiments of this application. The input / output interface 1303 is used to implement information input and output; The communication interface 1304 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 1305 transmits information between various components of the device (e.g., processor 1301, memory 1302, input / output interface 1303, and communication interface 1304); The processor 1301, memory 1302, input / output interface 1303 and communication interface 1304 are connected to each other within the device via bus 1305.

[0095] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the motion control method of the wearable device described above.

[0096] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0097] The motion control method, wearable device, wearable equipment, and storage medium provided in this application embodiment obtain sensor data from each individual wearable device corresponding to a sensor. Then, a target device is selected, and each wearable device shares its own sensor data with the target device. Each wearable device can be considered an edge node, and the various wearable devices within the wearable device collectively form a distributed network. Subsequently, gait analysis is performed through the target device to obtain global gait data reflecting the user's current state. Accurate control commands are then generated based on the global gait data, and finally, the target device sends corresponding control commands to each wearable device to achieve accurate control of each motor. Traditional wired wearable devices typically use a fixed centralized processing unit to execute complex tasks. Compared to this transmission technology solution, the method in this application embodiment utilizes the parallel processing capabilities of a distributed computing network, enabling the wearable device to respond in real time and efficiently process large amounts of sensor data. It also allows for flexible selection of the target device from multiple wearable devices to ensure efficient task execution. Therefore, the method in this embodiment not only enhances the stability of wireless communication during operation, enabling the wearable device to maintain efficient and reliable performance, but also provides users with a more comfortable and smooth assisted movement experience.

[0098] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0099] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0100] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0101] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0102] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0103] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0104] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0105] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0106] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0107] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0108] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A motion control method for a wearable device, characterized in that, An application is made to a wearable device comprising at least two wearable devices located at different positions, the positions including the foot; each wearable device includes a motor and multiple sensors, the multiple sensors being used to detect pressure, acceleration, and angular velocity corresponding to the wearable device, the motor being used to drive the wearable device to assist movement, the method comprising: Sensor data of the wearable device is detected by each of the aforementioned sensors; Select a target device from at least two wearable devices, and share the sensor data with the target device through each wearable device; The target device performs gait analysis on the sensor data of all the wearable devices collected to obtain global gait data; Control commands for each wearable device are generated based on the global gait data. The target device sends the control command to each of the wearable devices, so that each wearable device controls the motor according to the control command.

2. The method according to claim 1, characterized in that, The step involves performing gait analysis on the sensor data collected from all the wearable devices using the target device to obtain global gait data, including: For each wearable device, gait data calculation is performed on the sensor data to obtain local gait data; The local gait data is shared with the target device through each of the wearable devices; The target device integrates all the local gait data and the sensor data to obtain the global gait data.

3. The method according to claim 2, characterized in that, The sharing of the local gait data from each wearable device to the target device includes: The swing state of the wearable device is determined based on the local gait message; wherein the swing state is used to indicate whether the wearable device is in an active state or a supported state. If the swing state of the wearable device indicates that the wearable device is active, then the local gait data is shared with the target device.

4. The method according to claim 1, characterized in that, The sharing of sensor data from each wearable device to the target device includes: Determine the target identifier based on the target device; The source identifier is determined based on the sensor; The message type is determined based on the type of the sensor; Construct a message header based on the target identifier, the source identifier, and the message type; A sensing detection message is constructed based on the message header and the sensor data, and the sensing detection message is sent to the target device.

5. The method according to any one of claims 1 to 4, characterized in that, The step of generating control commands for each wearable device based on the global gait data includes: Obtain the movement speed of each wearable device; The target acceleration is obtained by calculating the acceleration based on the movement speed and the global gait data. The control command is generated based on the target acceleration.

6. The method according to any one of claims 1 to 4, characterized in that, The step of selecting a target device from at least two wearable devices includes: The target device is selected from at least two wearable devices based on the current bandwidth data of all wearable devices or preset hardware configuration data; or, All of the wearable devices are considered as the target device.

7. The method according to any one of claims 1 to 4, characterized in that, Before selecting a target device from at least two wearable devices and performing gait analysis on the sensor data of all the collected wearable devices through the target device to obtain global gait data, the method further includes: Acquire wireless communication signals from an external device; wherein, the external device is not the wearable device in the wearable device. A communication channel is established between the external device and each of the wearable devices based on the wireless communication signal. In response to a control request issued by the control device node, a target control device is determined from at least two wearable devices based on the control request, and a control command corresponding to the target control device is generated. The control command is obtained through the communication channel between the external device and the target control device, so that the target control device controls the motor according to the control command.

8. A wearable device, characterized in that, The wearable device includes at least two wearable devices located at different positions, the positions including the feet; each wearable device includes a motor and multiple sensors, the multiple sensors being used to detect pressure, acceleration and angular velocity corresponding to the wearable device, and the motor being used to drive the wearable device to assist movement; The wearable device located at the foot also includes rollers, and the motor is used to control the rotation or stopping of the rollers.

9. A wearable device, characterized in that, The wearable device includes a controller, the controller including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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