Multi-user exoskeleton shared rental management method and system

Abstract

The application discloses a multi-user exoskeleton sharing and leasing management method, which comprises the following steps: initiating a leasing request and uploading identity information; carrying out cloud triple identity authentication; carrying out cloud matching and calling of personalized control parameters; issuing parameters and automatically adapting equipment; unlocking and using equipment and uploading real-time data collection; dynamically charging and automatically settling accounts; returning equipment and confirming a double disinfection state; triggering remote locking through a geographic fence if the equipment is not returned within a period of time. The application further provides a multi-user exoskeleton sharing and leasing management system.

Description

Technical Field

[0001] This invention relates to the field of exoskeleton technology, and in particular to a multi-user exoskeleton sharing rental management method and system. Background Technology

[0002] As the population ages, the demand for rehabilitation assistive devices among the elderly is increasing. Exoskeleton robots, as rehabilitation assistive devices, can help elderly people with limited mobility or those requiring rehabilitation training regain their motor skills. However, the current price of exoskeleton devices ranges from tens of thousands to hundreds of thousands of yuan, making them unaffordable for ordinary elderly families. Existing equipment is mostly procured and managed by hospitals and rehabilitation institutions, limiting individual access, and household utilization is generally less than 10%, resulting in resource waste. The shared rental model is one way to address the accessibility of high-value equipment, but for medical rehabilitation equipment like exoskeletons—which have personalized needs, involve user safety and hygiene, and are expensive—existing rental systems still face technical challenges in large-scale operation.

[0003] In particular, the adaptation of exoskeleton devices requires users to manually adjust the mechanical structure and control parameters, making it impossible to quickly complete personalized configurations based on individual physical characteristics; and in scenarios where multiple people use them alternately, there is a lack of standardized disinfection procedures and effectiveness verification mechanisms, posing a risk of cross-infection. Therefore, an exoskeleton sharing and rental management solution that can solve the above problems is needed. Summary of the Invention

[0004] In view of the shortcomings of the prior art, the technical problem to be solved by the present invention is to provide a multi-user exoskeleton sharing rental management method and system that can solve the above-mentioned technical bottlenecks.

[0005] The present invention provides a multi-user exoskeleton sharing and rental management method, comprising the following steps: Step S1: The user initiates a rental request and uploads their identity information via the terminal; Step S2: The cloud management server verifies the user's identity; Step S3: After identity verification, the cloud management server retrieves the personalized control parameters uniquely bound to the current user; Step S4: The cloud management server sends the personalized control parameters to the user's rented exoskeleton device. After receiving and parsing the parameters, the exoskeleton device automatically performs device physical structure adaptation and running algorithm parameter adaptation. Step S5: After the device completes the pairing, it enters the unlocking state. The user unlocks and uses the device. During operation, the device continuously collects and uploads location data, device operation data, and user physiological motion data to the cloud management server. Step S6: After the equipment is returned, the cloud management server automatically calculates the rental fee based on the actual usage time and completes the settlement; Step S7: After the equipment is returned, perform disinfection verification. Once the verification is passed, update the equipment status to idle and available.

[0006] In step S1, the terminal has a built-in optical character recognition processing module that performs real-time text recognition on the collected document images. After performing a preliminary verification of the compliance and completeness of the key field information identified, the rental request data, user face image data, and identity qualification document data are uploaded to the cloud management server through an encrypted communication protocol.

[0007] Specifically, the verification in step S2 includes: Step S21: Compare the live face image collected and uploaded by the user in real time with the face image extracted from the ID card image, and set the preset similarity threshold as the first threshold. Step S22: Call the OCR recognition interface to extract structured information from the document image, and set the preset recognition accuracy threshold as the second threshold; Step S23: Cross-verify the structured field information extracted by document OCR recognition with the user's pre-registered platform registration information, requiring all key field information to match completely; If all three sub-steps above pass the verification, the identity verification is deemed successful; if any one of them fails, the rental request is rejected.

[0008] The personalized control parameters mentioned in step S3 include user height, weight, exclusive gait mode, joint range of motion parameters, rehabilitation training intensity level parameters, and auxiliary torque target parameters for each joint. These personalized control parameters are based on the user's previous rehabilitation assessment data, historical usage behavior data, and preset rehabilitation goal configuration, and are then fixed and stored in a cloud database after iterative optimization.

[0009] The physical structure adaptation of the exoskeleton device in step S4 includes: the device drives the mechanical adjustment structure to adaptively adjust the length of the mechanical leg based on the user's height and weight parameters; the adaptation of the running algorithm parameters includes: the exoskeleton device updates the built-in motor drive control algorithm parameters according to the user's exclusive gait running mode, joint range of motion and the target value of the auxiliary torque of each joint.

[0010] In step S5, the exoskeleton device continuously collects location information at a fixed sampling frequency and achieves continuous indoor and outdoor positioning through a GPS and UWB dual-mode positioning fusion mechanism. The data collected by the exoskeleton device is transmitted to the cloud management server via a cellular network in real-time streaming mode. The server categorizes the monitoring data and writes it into a user-specific rehabilitation data form.

[0011] In step S6, the system pre-design fee mode includes billing by the hour, billing by the day, and billing by rehabilitation course. The cloud management server calculates the rental fee based on the actual effective usage time recorded by the equipment and the pre-design fee rule model. After completion, it calls the third-party payment interface to complete the deduction settlement.

[0012] Specifically, the disinfection verification in step S7 includes: the ultraviolet disinfection sensor collects ultraviolet irradiation intensity parameters in real time, and the preset disinfection qualification judgment condition is that the ultraviolet irradiation intensity is not lower than the first preset value and the continuous action time is not less than the second preset value.

[0013] Specifically, the disinfection verification in step S7 includes: the exoskeleton device is equipped with a miniature camera component, which captures images of the chemical indicator stickers on the key contact parts of the exoskeleton; the cloud management server calls an image classification algorithm based on a convolutional neural network to judge the color change of the indicator stickers in order to determine whether the disinfection is qualified.

[0014] This also includes step S8: The cloud management server continuously monitors the online status and location information of the leased equipment, and sends a remote locking command to the equipment when the equipment is not returned on time or crosses the preset geofence.

[0015] On the other hand, the present invention also provides a multi-user exoskeleton sharing and rental management system, including a user terminal, a management server, and several modules installed on the exoskeleton device: The user terminal is used to initiate rental requests, collect and upload user identity information, and receive and display feedback information from the management server; The management server includes a computing and verification module, a cloud database, a communication and interface module, and a monitoring and alarm module. The computing and verification module is used to perform identity verification and dynamically optimize personalized control parameters. The cloud database is used to store user rehabilitation records, equipment records, and rental order information. The communication and interface module is used to perform bidirectional data interaction with user terminals and exoskeleton devices. The monitoring and alarm module is used to track the device location in real time and trigger boundary crossing alarms and remote locking. The exoskeleton device is equipped with a communication module, a control and computing unit, a positioning module, a power output module, a data acquisition sensor group, and a disinfection status monitoring module. The communication module is used to interact with the management server. The control and computing unit is used to parse personalized parameters and perform adaptation calculations. The positioning module includes a GPS submodule and a UWB submodule to achieve indoor and outdoor dual-mode positioning. The power output module is used to output auxiliary torque according to control commands and cut off power output after receiving a locking command. The data acquisition sensor group is used to collect multi-dimensional data during use. The disinfection status monitoring module is used to detect the intensity and duration of ultraviolet irradiation during disinfection.

[0016] This invention provides a multi-user exoskeleton sharing and rental management method and system. By constructing a closed-loop management system covering identity verification, personalized adaptation, intelligent monitoring, automatic billing, and safe return, it effectively solves the technical problems faced by exoskeleton equipment in shared rental scenarios, such as low reliability of identity verification, poor efficiency of parameter adaptation, difficulty in equipment supervision, and high hygiene and safety risks. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart illustrating a preferred embodiment of the multi-user exoskeleton sharing and rental management method described in this invention.

[0018] Figure 2 yes Figure 1 A schematic diagram of step S2.

[0019] Figure 3 yes Figure 1 A schematic diagram of step S4.

[0020] Figure 4 This is a schematic diagram of a preferred embodiment of a multi-user exoskeleton sharing and rental management method of the present invention. Detailed Implementation

[0021] The invention will now be further described with reference to the accompanying drawings.

[0022] Reference Figure 1 As shown, the preferred embodiment of the multi-user exoskeleton sharing and rental management method provided by the present invention includes: Step S1: Initiate rental request and upload identity information.

[0023] Users can access and browse a list of available exoskeleton devices in a cloud database through a dedicated rental application installed on their smartphones or a dedicated handheld terminal device. Users can select the target exoskeleton model according to their needs (for example, the "Rehabilitation Star-R1" model rehabilitation exoskeleton device), set rental parameters such as the rental duration, and submit a rental request after completing the basic rental information configuration.

[0024] During the rental request submission process, users follow the on-screen instructions of the dedicated rental application to complete the real-time facial image capture and upload, resident ID card image capture and upload, and / or senior citizen card image capture and upload in sequence, thus submitting the rental user's identity qualification certificate for subsequent identity verification.

[0025] To reduce the amount of invalid data transmission between the terminal and the cloud, the rental application has a built-in optical character recognition (OCR) processing module. After users upload images of various documents, the terminal's OCR module automatically performs real-time text recognition on the collected images of ID cards, senior citizen cards, and other documents. It performs preliminary compliance and completeness checks on the key fields of the recognized documents, removes invalid document data such as blurry or damaged data, and retains only compliant and valid data for transmission.

[0026] After completing local data preprocessing and initial verification on the terminal, the rental application uploads the rental request message data, user facial image data, and various identity and qualification document data to the cloud management server via HTTPS encrypted communication protocol. HTTPS encryption is used to prevent data from being tampered with or stolen during transmission.

[0027] Step S2: Cloud-based triple authentication.

[0028] After receiving the rental request data and identity qualification information uploaded by the user terminal, the cloud management server initiates a three-tier identity verification process to verify the authenticity of the user's identity and the validity of their qualifications at each level. The specific verification steps are as follows: Figure 2 As shown: Step S21: Face similarity comparison and verification. The server calls the preset face recognition API to compare the live face image uploaded by the user in real time with the face image extracted from the ID card image. The system presets the similarity threshold to 95% (this threshold can also be changed to other values ​​according to actual needs). When the actual similarity is greater than or equal to this threshold, this verification is deemed to be qualified.

[0029] Step S22: High-precision recognition and verification of document information. The server calls the ID card OCR recognition API and the senior citizen card OCR recognition API respectively to extract structured information from the corresponding document image data, capturing key fields such as user name, ID card number, and date of birth. The preset document information recognition accuracy threshold is 98% (this threshold can also be changed to other values ​​according to actual needs). When the recognition accuracy meets this standard, this recognition verification is deemed qualified.

[0030] Step S23: Information Cross-Consistency Verification. The server cross-compares all structured field information extracted from the aforementioned ID card and senior citizen card by OCR recognition with the platform registration information pre-stored by the user, requiring all key field information to match completely.

[0031] If all three sub-steps above pass verification, the cloud management server determines that the current rental user's identity is genuine and their qualifications are valid. The server creates or retrieves a cloud-based rehabilitation file uniquely linked to the user's ID number, pushes a successful identity verification notification to the user's rental terminal, and proceeds to the next rental process. If any of the above three sub-steps fails verification, the server rejects the exoskeleton device rental request, sends a verification error message to the user's terminal, and guides the user to re-collect and upload identity and qualification information and re-initiate the rental application.

[0032] Step S3: Cloud matching and retrieval of personalized control parameters.

[0033] After user identity verification is successful, the cloud management server retrieves and accesses the corresponding personalized rehabilitation file from the cloud database based on the user's unique identifier (user ID). This file stores device control parameters adapted to the user's individual physical characteristics and rehabilitation needs, including: basic physical characteristics such as the user's height and weight, the user's specific gait mode (e.g., slow and stable gait mode), range of motion parameters for each joint (e.g., flexion and extension range of motion of the knee joint), rehabilitation training intensity level parameters (mild, moderate, and severe), and auxiliary torque target parameters for each joint of the exoskeleton device (e.g., 15 N·m auxiliary torque setting for the left knee joint).

[0034] The aforementioned personalized control parameters are based on the user's previous rehabilitation assessment data, historical usage data of the exoskeleton device, and the user's preset rehabilitation goal configuration. After iterative optimization, they are permanently stored in a cloud database. When the server completes user identity verification and responds to rental requests, it directly reads and retrieves the complete set of personalized control parameters corresponding to that user in batches, without requiring repeated configuration on the terminal.

[0035] Step S4: Parameter distribution and automatic device adaptation.

[0036] After the cloud management server retrieves the user's personalized rehabilitation parameters, it uses a 4G / 5G cellular mobile communication network and lightweight IoT communication protocols such as MQTT and CoAP to encrypt and send the user's exclusive personalized control parameter set to the rehabilitation exoskeleton device selected by the user for this rental.

[0037] After receiving and parsing the personalized control parameters sent from the cloud, the built-in internal control unit of the exoskeleton device automatically performs a two-dimensional adaptive matching operation, including adaptation of the device's physical structure and adaptation of the operating algorithm parameters, such as... Figure 3 As shown: Step S41: Based on the user's height and weight parameters, the device drives the mechanical adjustment structure to adaptively adjust the length of the mechanical leg, so that the mechanical structure size of the device matches the physiological size of the user's limbs.

[0038] Step S42: The device updates its built-in motor drive control algorithm based on the user's specific gait mode, joint range of motion, and target values ​​of auxiliary torque for each joint. For example, the user's gait cycle target is calibrated to 1.5s, and the soft limit parameters of knee joint flexion and extension movements are calibrated and updated simultaneously.

[0039] After the exoskeleton device completes the physical structure adaptation and algorithm parameter update, the internal control unit generates an adaptation completion feedback signal and sends a confirmation of device adaptation completion to the cloud management server via the Internet of Things. Upon receiving the confirmation signal, the cloud management server updates the status of this device rental order to "pending unlock," indicating that the device has completed personalized adaptation preprocessing and is in a ready state.

[0040] Step S5: Unlock the device and collect and upload real-time data.

[0041] Once the device enters the unlock ready state, the user can unlock the exoskeleton device by scanning the exclusive unlock verification code or confirming the rental order information through the device, thus unlocking the device's power lock protection mechanism and putting the device into a working state.

[0042] During rehabilitation training using the exoskeleton device, the device's internal control system continuously collects real-time location information at a sampling frequency of 1Hz, achieving continuous positioning through an indoor / outdoor dual-mode positioning fusion mechanism. In outdoor scenarios, relying on the device's built-in GPS positioning module, the positioning accuracy is between 2m and 5m; in indoor scenarios, it switches to the UWB ultra-wideband positioning module, combined with pre-deployed positioning base stations, achieving a positioning accuracy of 10cm to 30cm. This adaptive switching between indoor and outdoor positioning modes eliminates positioning blind spots.

[0043] During operation, the device continuously collects and uploads data on its operation and usage, including cumulative usage time, rehabilitation walking distance, effective training steps, remaining battery power, and real-time auxiliary torque output data for each joint. In other embodiments, the device may also integrate sensing devices such as heart rate sensors, blood oxygen sensors, inertial measurement units, and force sensors. The inertial measurement unit has a sampling frequency of 100Hz and can monitor the user's heart rate (normal monitoring range 60 to 120 beats per minute), blood oxygen saturation (normal monitoring range 95% to 100%), real-time angles of limb joints, trunk posture, and ground reaction force of the feet in real time.

[0044] All location data, device operation data, and user physiological and movement data collected by the device are transmitted to the cloud management server in real-time streaming via a 4G / 5G cellular network module. Upon receiving the data, the server categorizes and writes it into a unique rehabilitation data form linked to the user's ID number, thus achieving chronological archiving of rehabilitation training data.

[0045] Step S6: Dynamic billing and automatic settlement.

[0046] After the user completes rehabilitation training and returns the exoskeleton device, the cloud management server obtains the actual usage time data reported by the device and automatically calculates the rental fee based on the system's preset billing rule model. The system's preset billing models include hourly billing, daily billing, and billing by rehabilitation course, which are executed according to the user's rental selection and scenario.

[0047] In one embodiment, the system's hourly billing price is preset to 30 yuan / hour, and the server calculates the fee based on the actual effective usage time recorded by the device. If the actual usage time is 2.5 hours, the rental fee is 75 yuan. The billing parameters and calculation logic are pre-stored in the server's algorithm program.

[0048] After the fee calculation is completed, the cloud management server calls the preset third-party payment interface, compatible with WeChat Pay, Alipay, and other channels, to transfer the rental fee from the user's pre-linked payment account, completing the order payment settlement. Upon successful payment, the server generates an order billing file containing equipment usage details, billing rules, a fee calculation list, and an electronic invoice, and pushes it to the user's terminal device. The server simultaneously updates the exoskeleton rental order status to "Completed".

[0049] Step S7: Equipment return and double disinfection status confirmation.

[0050] After the exoskeleton equipment is returned to the designated return point and the return registration is confirmed by the management personnel, the cloud management server initiates equipment location verification to check whether the equipment's real-time positioning coordinates are within the UWB beacon coverage area of ​​the return point. Once the location verification is successful, the server updates the exoskeleton equipment's status to "awaiting disinfection" and locks the equipment rental access.

[0051] The administrator initiates the ultraviolet disinfection operation on the equipment, and the ultraviolet disinfection sensor (e.g., GUVA-S12SD) on the equipment collects ultraviolet irradiation intensity parameters in real time. The preset disinfection qualification criteria are: ultraviolet irradiation intensity not less than 100μW / cm², and continuous action time not less than 5 minutes.

[0052] In other embodiments, disinfectant chemical indicator stickers may be affixed to key human contact areas of the device. A miniature camera component on the device captures images of the chemical indicator stickers at each key contact area. After disinfection, the chemical indicator sticker changes from its initial blue to pink. The cloud management server then uses an image classification algorithm based on a convolutional neural network to extract features and determine color changes in the indicator sticker image, thus assessing the effectiveness of the disinfection operation.

[0053] To ensure more rigorous execution of the disinfection procedure and control over its effectiveness, step S7 can employ a dual disinfection verification mechanism combining ultraviolet parameter verification and intelligent image recognition. If both verifications pass, the server updates the device status to idle and available, and adds it back to the cloud-based list of rentable devices. If either verification fails, the server marks the device as being in an abnormal disinfection state, locks its rental permissions, generates an operation and maintenance alarm, and pushes it to the operation and maintenance terminal.

[0054] Step S8: Failure to return the item by the due date triggers remote locking via geofencing.

[0055] During the equipment rental period, the cloud management server continuously monitors the online status of the rented equipment and collects data on the equipment's return registration status and location. When the equipment exceeds the preset rental deadline and is not returned after a cumulative overdue period of 24 hours, the server pushes overdue return reminders and renewal guidance to the user's terminal.

[0056] If the user fails to confirm renewal or return the equipment within the preset grace period, the cloud management server sends a remote locking control command to the corresponding exoskeleton device via the IoT communication channel. After receiving and parsing the locking command, the device's internal control unit executes a power-off or lock-up action within a preset time (e.g., 30 seconds), cutting off the motor's power output or controlling the motor to enter a mechanical lock-up state, causing the device to lose its walking assistance power.

[0057] Each equipment rental location is pre-configured with an electronic geofence area, such as a circular boundary with a radius of 500m centered on the rental location. During the rental period, if the device's real-time location data exceeds the geofence boundary, the server triggers an out-of-bounds alarm and pushes a warning message to the user's terminal. If the device does not return to the geofence area within the preset out-of-bounds buffer time (10 minutes), the system remotely locks it.

[0058] Abnormal locking events such as equipment overdue locking and out-of-bounds locking are recorded by the server in the leasing business log, which serves as the basis for overdue billing calculation, user leasing credit assessment, and risk control judgment of leasing behavior.

[0059] Beyond the entire process, the management server backend continuously accumulates all users' historical usage data and rehabilitation progress, dynamically optimizes each user's personalized control parameters using reinforcement learning-based machine learning algorithms (such as automatically lowering the auxiliary torque or increasing the training intensity based on the previous week's training performance), and generates predictive maintenance warnings based on the operating data uploaded by the equipment, such as the cumulative running time of the motor and the number of battery charge and discharge cycles, forming a complete closed-loop management covering rental, use, return, disinfection, billing, security control, and data-driven optimization.

[0060] Please refer to Figure 4As shown, the present invention also provides a multi-user exoskeleton sharing and rental management system, the preferred embodiment of which includes a user terminal 1, a management server 2, and several modules disposed on the exoskeleton device 3.

[0061] The user terminal 1 is a front-end hardware device for users to interact with the system. It is usually a smartphone, tablet computer or dedicated handheld terminal device, on which the application program of this invention is installed, forming the entry point for the rental service.

[0062] The user terminal 1 includes basic components such as a touch screen, camera, communication module, and processor. The user terminal can display a list of nearby rentable exoskeleton devices and their real-time status (model, available / used, rental price, disinfection status) for users to browse and select. It captures real-time facial images, ID card photos, and senior citizen card photos of the user via the camera as original authentication credentials. The built-in OCR module utilizes the terminal's computing resources to perform preliminary recognition and field verification on the document photos, reducing invalid data transmission. Through a cellular network or Wi-Fi module, and via HTTPS security protocol, it conducts bidirectional communication with the management server to complete operations such as submitting rental requests, uploading identity information, receiving unlock codes, and viewing usage records.

[0063] The management server 2 can be deployed in the cloud or a data center, and includes a computing and verification module 20, a cloud database 21, a communication and interface module 22, and a monitoring and alarm module 23. The computing and verification module 20 is used to run a facial recognition deep learning model and an OCR recognition algorithm to achieve identity verification. At the same time, the computing and verification module 20 is also used to analyze the user's historical rehabilitation data and dynamically optimize personalized control parameters.

[0064] The cloud database 21 is used to store rehabilitation records for all registered users, including identity information, personalized control parameters (height, weight, gait pattern, joint range of motion, rehabilitation intensity, assistive torque value, etc.), historical usage data, and rehabilitation progress records. The cloud database 21 is also used to store equipment files (model, maintenance records, cumulative runtime) and rental order information (rental time, billing records, disinfection status).

[0065] The communication and interface module 22 is equipped with a 4G / 5G gateway and an IoT communication protocol stack (supporting MQTT, CoAP, etc.) for bidirectional data interaction with the exoskeleton device 3, sending personalized parameters and remote locking commands, receiving location information, usage data and disinfection status uploaded by the device 3, and integrating third-party payment interfaces (WeChat Pay, Alipay) to provide HTTPS API interfaces for user terminals to call.

[0066] The monitoring and alarm module 23 is used to track the location information of all rented devices 3 in real time, compare it with preset geofence parameters, and trigger an alarm if the device crosses the boundary. The monitoring and alarm module 23 is also used to monitor the rental period and trigger a remote locking process if the device is not returned on time.

[0067] In this embodiment, the exoskeleton device 3 is equipped with a communication module 30, a control and computing unit 31, a positioning module 32, a power output module 33, a data acquisition sensor group 34, a disinfection status monitoring module 35, and a power supply module 36.

[0068] The communication module 30 integrates a 4G / 5G cellular communication module and a Wi-Fi module, enabling the exoskeleton device 3 to maintain a connection with the management server 2 in different usage environments (home, community, rehabilitation center). This communication module 30 receives personalized control parameters and remote locking commands from the management server 2, and simultaneously transmits the device 3's status data back.

[0069] The control and computing unit 31 may be equipped with an embedded processor (MCU or ARM architecture chip) to receive personalized parameters from the communication module 30, perform parameter parsing and adaptation calculations, and control the action of the motor drive module; at the same time, it receives data from various sensors, performs fusion processing, and generates data packets to be uploaded.

[0070] The positioning module 32 includes a GPS submodule and a UWB submodule, equipped with a dual-mode positioning system. In outdoor environments, the GPS submodule provides positioning information with an accuracy of 2 to 5 meters; in indoor environments, the UWB submodule, in conjunction with a pre-deployed indoor base station network, achieves a positioning accuracy of 10 to 30 centimeters. The two systems work alternately or collaboratively at a frequency of 1 Hz to achieve continuous indoor and outdoor positioning, with positioning data uploaded to the management server 2 in real time.

[0071] The power output module 33 includes a servo motor, a reducer, a drive circuit, and a power management system. It outputs auxiliary torque based on calculations from the control and calculation unit to drive the joints of the exoskeleton 3, assisting the user in walking or rehabilitation training. The power output module 33 also allows the control unit to cut off the motor power or lock the motor within 30 seconds of receiving a remote locking command, thus preventing the device 3 from losing power output and preventing theft or overdue use.

[0072] The data acquisition sensor group 34 is used to collect multi-dimensional data during user operation. Specifically, the data acquisition sensor group 34 includes an encoder, a force sensor, and a battery monitoring chip. The encoder is used to monitor joint angles, the force sensor is used to monitor auxiliary torque output, and the battery monitoring chip is used to monitor battery status. In other embodiments, the data acquisition sensor group 34 may also integrate a heart rate sensor, a blood oxygen saturation sensor, an inertial measurement unit, and a plantar pressure sensor.

[0073] The disinfection status monitoring module 35 is installed on the outer shell or key contact parts of the exoskeleton device 3 to detect the intensity and duration of ultraviolet irradiation during the disinfection process. In other embodiments, the exoskeleton device 3 may also be equipped with a miniature camera to capture images of the color changes of the chemical indicator patch. The data collected by the disinfection status monitoring module 35 is uploaded to the management server 2 to determine whether the disinfection is qualified.

[0074] The power module 36 can use a high-energy-density rechargeable lithium battery pack to provide power to all electronic components and motors. It also has charge and discharge management, overcharge and over-discharge protection and power monitoring functions. Data such as the number of battery cycles are incorporated into the parameter system for predictive maintenance.

[0075] This invention provides a multi-user exoskeleton sharing and rental management method and system. By constructing a closed-loop management system covering identity verification, personalized adaptation, monitoring, billing and safe return, it solves the technical problems faced by exoskeleton equipment in shared rental scenarios, such as low reliability of identity verification, poor efficiency of parameter adaptation, difficulty in equipment supervision and high hygiene and safety risks.

[0076] During the identity verification process, the system employs a triple mechanism: facial similarity comparison, document OCR recognition, and cross-verification of information. The document recognition accuracy threshold is preset at 98%, and the facial comparison threshold at 95%. Only after all three verifications are passed can the rental process begin, preventing identity forgery and impersonation. After user identity is confirmed, the system retrieves personalized rehabilitation parameters bound to the user ID from the cloud database, including gait patterns, joint range of motion, and target auxiliary torque values, and transmits them to the target device via encrypted 4G / 5G links. The device automatically adjusts the mechanical leg length and updates the motor control algorithm parameters accordingly, eliminating the need for manual on-site adjustments and ensuring consistency of rehabilitation training parameters across different devices.

[0077] During rental, the system utilizes a dual-mode GPS and UWB positioning mechanism to achieve continuous indoor and outdoor tracking, with an outdoor accuracy of 2-5 meters and an indoor accuracy of 10-30 centimeters, eliminating blind spots. Based on the linkage between positioning information and electronic geofences, the system implements progressive intervention for boundary violations and overdue returns: a reminder is sent after 24 hours of overdue return; exceeding the grace period or boundary violation timeout triggers remote power-off locking to prevent equipment loss and unauthorized occupation. After use, the system introduces a dual disinfection verification mechanism that intelligently judges ultraviolet irradiation intensity and chemical indicator sticker images, confirming disinfection compliance from both physical irradiation dose and chemical response dimensions, avoiding misjudgments or omissions due to a single detection method.

[0078] The system backend continuously accumulates user behavior data, supporting dynamic optimization of personalized parameters based on reinforcement learning and predictive maintenance based on device operation data. The integration of the dynamic billing model with third-party payment interfaces automates the entire process from order generation and usage metering to billing.

[0079] The above description merely illustrates preferred embodiments of the present invention and is quite specific and detailed; however, it should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the inventive concept, and these all fall within the scope of protection of the present invention. Therefore, the scope of protection of this invention should be determined by the appended claims.

Claims

1. A multi-user exoskeleton sharing and rental management method, characterized in that, Includes the following steps: Step S1: The user initiates a rental request and uploads their identity information via the terminal; Step S2: The cloud management server verifies the user's identity; Step S3: After identity verification, the cloud management server retrieves the personalized control parameters uniquely bound to the current user; Step S4: The cloud management server sends the personalized control parameters to the user's rented exoskeleton device. After receiving and parsing the parameters, the exoskeleton device automatically performs physical structure adaptation and running algorithm parameter adaptation. Step S5: After the exoskeleton device is fully adapted, it enters the unlocking state. The user unlocks and uses the exoskeleton device. During operation, the location data, operation data of the exoskeleton device and the user's physiological movement data are continuously collected and uploaded to the cloud management server. Step S6: After the exoskeleton equipment is returned, the cloud management server automatically calculates the rental fee based on the actual usage time and completes the settlement; Step S7: After the exoskeleton equipment is returned, disinfection and verification are performed. After the verification is completed, the equipment status is updated to idle and available.

2. The multi-user exoskeleton sharing and rental management method according to claim 1, characterized in that, In step S1, the terminal's built-in optical character recognition processing module performs real-time text recognition on the collected document images. After performing preliminary verification of the compliance and completeness of the identified key field information, the rental request data, user face image data, and identity qualification document data are uploaded to the cloud management server through an encrypted communication protocol.

3. The multi-user exoskeleton sharing and rental management method according to claim 1, characterized in that, The verification in step S2 specifically includes: Step S21: Compare the live face image collected and uploaded by the user in real time with the face image extracted from the ID card image, and set the preset similarity threshold as the first threshold. Step S22: Call the OCR recognition interface to extract structured information from the document image, and set the preset recognition accuracy threshold as the second threshold; Step S23: Cross-verify the consistency of the structured field information extracted by the document OCR recognition with the user's pre-registered platform registration information; If all three sub-steps above pass the verification, the identity verification is deemed successful; if any one of them fails, the rental request is rejected.

4. The multi-user exoskeleton sharing and rental management method according to claim 1, characterized in that, The personalized control parameters mentioned in step S3 include user height, weight, exclusive gait mode, joint range of motion parameters, rehabilitation training intensity level parameters, and auxiliary torque target parameters for each joint. These personalized control parameters are based on the user's previous rehabilitation assessment data, historical usage behavior data, and preset rehabilitation goal configuration, and are then fixed and stored in a cloud database after iterative optimization.

5. The multi-user exoskeleton sharing and rental management method according to claim 1, characterized in that, The physical structure adaptation of the exoskeleton device in step S4 includes: adaptively adjusting the length of the mechanical leg rods by driving the mechanical adjustment structure according to the user's height and weight parameters; the adaptation of the running algorithm parameters includes: updating the built-in motor drive control algorithm parameters of the exoskeleton device according to the user's exclusive gait running mode, joint range of motion and target values ​​of auxiliary torque of each joint.

6. The multi-user exoskeleton sharing and rental management method according to claim 1, characterized in that, In step S5, the exoskeleton device continuously collects location information at a fixed sampling frequency and achieves continuous indoor and outdoor positioning through a GPS and UWB dual-mode positioning fusion mechanism. The data collected by the exoskeleton device is uploaded and transmitted to the cloud management server in real time, and the server classifies the monitoring data and writes it into a user-specific rehabilitation data form.

7. The multi-user exoskeleton sharing and rental management method according to claim 1, characterized in that, It also includes step S8: The cloud management server continuously monitors the online status and location information of the rented exoskeleton equipment, and sends a remote locking command to the equipment when the equipment is not returned on time or goes beyond the preset geofence.

8. The multi-user exoskeleton sharing and rental management method according to claim 1, characterized in that, The disinfection verification in step S7 specifically includes: the ultraviolet disinfection sensor collects ultraviolet irradiation intensity parameters in real time, and the preset disinfection qualification judgment conditions are that the ultraviolet irradiation intensity is not lower than the first preset value and the continuous action time is not less than the second preset value.

9. The multi-user exoskeleton sharing and rental management method according to claim 1, characterized in that, The disinfection verification in step S7 specifically includes: the exoskeleton device is equipped with a miniature camera component, which captures images of the chemical indicator stickers on the key contact parts of the exoskeleton; the cloud management server judges the color change of the indicator stickers to determine whether the disinfection is qualified.

10. A multi-user exoskeleton sharing and rental management system, characterized in that, Includes user terminals, management servers, and several modules installed on the exoskeleton device: The user terminal is used to initiate rental requests, collect and upload user identity information, and receive and display feedback information from the management server; The management server includes a computing and verification module, a cloud database, a communication and interface module, and a monitoring and alarm module. The computing and verification module is used to perform identity verification and dynamically optimize personalized control parameters. The cloud database is used to store user rehabilitation records, equipment records, and rental order information. The communication and interface module is used to perform bidirectional data interaction with user terminals and exoskeleton devices. The monitoring and alarm module is used to track the device location in real time and trigger boundary crossing alarms and remote locking. The exoskeleton device is equipped with a communication module, a control and computing unit, a positioning module, a power output module, a data acquisition sensor group, and a disinfection status monitoring module. The communication module is used to interact with the management server. The control and computing unit is used to parse personalized parameters and perform adaptation calculations. The positioning module includes a GPS submodule and a UWB submodule to achieve indoor and outdoor dual-mode positioning. The power output module is used to output auxiliary torque according to control commands and cut off power output after receiving a locking command. The data acquisition sensor group is used to collect multi-dimensional data during use. The disinfection status monitoring module is used to detect the intensity and duration of ultraviolet irradiation during disinfection.

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