A patrol service robot for PET / CT waiting rooms

Abstract

This invention discloses a patrol robot for PET / CT waiting rooms. The robot comprises a sensing and monitoring module for real-time monitoring of dynamic data about patients and the environment in the waiting room; a control system for planning the robot's path and assigning task instructions based on this dynamic data; a mobile platform for moving the robot to designated locations within the waiting room based on path planning; an interaction module for providing human-machine interaction and guiding patients through pre-examination preparations; and a task execution module for executing the robot's active intervention tasks based on task instructions. By leveraging multi-sensor fusion, intelligent control, and human-machine interaction technologies, the robot addresses issues such as patient management, radiation protection, and waste of medical resources.

Description

Technical Field

[0001] The present invention relates to the technical field of robots, and in particular to a patrol service robot used in a PET / CT waiting room. Background Art

[0002] PET / CT, as an important medical imaging technology, is widely used in tumor diagnosis, heart disease examinations, and a variety of other diseases. With the increasing demand for medical care, the number of patients undergoing PET / CT examinations has increased significantly. However, this process also brings several challenges, particularly in terms of waiting room management and radiation protection.

[0003] First, inadequate management of patient behavior in the waiting room is a significant factor affecting the quality of PET / CT examinations. To obtain high-quality scan images, patients are typically required to remain seated and avoid frequent movement before the examination. However, due to long waiting times, patients may move frequently due to impatience or a lack of understanding of the procedures, resulting in decreased image quality. This not only increases the likelihood of repeated examinations but also wastes valuable medical resources. Second, radiation protection issues are becoming increasingly prominent. PET / CT examinations involve the use of radioactive drugs, and medical staff face the risk of radiation exposure during contact with patients. Although lead aprons and protective walls are currently widely used, these traditional methods do not fundamentally address the health risks associated with frequent contact, especially in waiting areas, where staff are required to conduct inspections, provide guidance, and provide explanations, increasing their chances of radiation exposure.

[0004] Several medical service robots are already available on the market, such as navigation robots and accompanying robots for patient guidance. These devices can, to a certain extent, assist medical staff with simple communication and guidance tasks. However, these robots are limited in their functionality and struggle to meet the specialized needs of PET / CT waiting rooms. For example, they lack the ability to monitor patient movement in real time, making it difficult to effectively guide patients in behavioral adjustments or handle emergencies. Furthermore, existing robots primarily serve as patient education reminders, broadcasting through a central speaker console. They are unable to provide personalized services, such as measuring blood pressure or reminding patients to urinate.

[0005] Therefore, there is an urgent need for a patrol service robot for PET / CT waiting rooms. Summary of the Invention

[0006] The present invention provides a patrol service robot for PET / CT waiting room to solve the above problems existing in the prior art.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] A patrol service robot for a PET / CT waiting room, comprising:

[0009] Sensing and monitoring module, used to monitor the dynamic data of patients and environment in the waiting room in real time;

[0010] The control system is used to plan the robot path and assign task instructions based on dynamic data;

[0011] A mobile platform is used to move the robot to a designated location in the waiting room based on path planning;

[0012] The interactive module is used to provide human-computer interaction functions and guide patients to complete the preparations before the examination;

[0013] The task execution module is used to execute the robot's active intervention task based on the task instructions.

[0014] Among them, the sensing and monitoring module includes: multimodal sensors and patient status monitoring system;

[0015] Multimodal sensors are used to collect the movement status and biometric characteristics of patients in the waiting room in real time and generate dynamic data reports;

[0016] The patient status monitoring submodule is used to identify abnormal patient behavior by analyzing dynamic data reports.

[0017] Among them, the control system includes: a central control unit, an edge computing module and a communication module;

[0018] Central control unit, used to support remote control and ensure flexibility of robot operation;

[0019] Edge computing module, used to analyze dynamic data in real time, connect with the hospital management system, and generate optimized path planning and task allocation solutions;

[0020] Communication module, used to transmit dynamic data to the hospital management system in real time.

[0021] The mobile platform includes: a tracked or wheeled mobile chassis, a battery pack and an autonomous navigation module;

[0022] Tracked or wheeled mobile chassis, used to provide stable mobile support for the robot;

[0023] Battery pack, used to adopt a new power management system to ensure long-term stable operation of the robot;

[0024] The autonomous navigation module is used to achieve accurate perception and navigation of the waiting room environment based on SLAM technology combined with lidar and visual sensors, and generate environmental maps and navigation paths.

[0025] Among them, the interactive module includes: touch screen, speech recognition and synthesis submodule and multi-language support submodule;

[0026] Touch screen, used to provide an operation interface to help patients obtain examination-related information;

[0027] The speech recognition and synthesis submodule is used to communicate through voice, play precautions, guide patients to prepare for the examination, and generate voice interaction records;

[0028] The multi-language support sub-module is used to intelligently identify patients' language preferences, provide multi-language switching and personalized services.

[0029] Among them, the task execution module includes: a robotic arm, a disinfection nozzle or air purification submodule, and an alarm submodule;

[0030] A robotic arm to assist with patient mobility and calm agitation, generating patient comfort assessments;

[0031] Disinfection nozzles or air purification submodules are used to automatically disinfect the area around the patient's seat and generate environmental hygiene status reports;

[0032] The alarm submodule is used to monitor abnormal situations, provide real-time warnings, and generate safety warning information.

[0033] Among them, the multimodal sensors include: infrared sensors, pressure sensors, and biometric recognition cameras;

[0034] Infrared sensors are used to accurately locate the patient's movements and posture in the waiting room by detecting changes in the patient's body temperature and heat radiation patterns, and to determine the patient's current state, including stillness, walking, or sitting;

[0035] Pressure sensors to monitor changes in a patient's weight distribution, sitting or lying posture;

[0036] Biometric cameras to monitor patients' facial expressions and physiological responses.

[0037] Among them, generating optimized path planning and task allocation solutions includes:

[0038] Compare the current patient dynamic data in the waiting room with the preset standards in the hospital management system;

[0039] When the patient's motion state or biometric characteristics in the current dynamic data exceed the corresponding preset standards, it is determined that the service demand in the waiting room has increased, the patient distribution in each area of the waiting room is obtained, and the number of patients in adjacent areas is merged to obtain the regional patient density;

[0040] Compare the patient density in different areas of the waiting room to determine the patient distribution ratio in the waiting room. Based on the patient distribution ratio and data from the hospital management system, adjust the current path planning and generate a real-time optimization plan.

[0041] Among them, dynamic data include the patient's movement status, heart rate, blood oxygen saturation, body temperature and behavioral norms;

[0042] When the patient's motion status and biometric characteristics in the current dynamic data are within the preset standard range, it is determined that the service demand in the waiting room is normal;

[0043] When the patient's motion status and biometrics in the current dynamic data are within the preset standard range, the service demand in the waiting room is determined to be normal, including:

[0044] Get the current time and determine the time interval to which the current time belongs;

[0045] When the current time is in the peak service time interval, the rounds service corresponding to the waiting room will be controlled to maintain or restore to the default rounds policy;

[0046] When the current time is in the off-peak service time interval, obtain the patient distribution in the waiting room during the off-peak time interval, generate a patient distribution change curve, and based on the patient distribution change curve, determine the concentrated service interval within the off-peak time interval and the average number of patients corresponding to different areas within the concentrated service interval, and select the area with the largest average number of patients as the target area;

[0047] Obtain the average number of patients in the target area, and combine the path length, average movement speed of medical staff, and service start error to obtain the optimal service time for the waiting room.

[0048] Based on the optimal service time, a low-peak service strategy is generated, and the patrol service corresponding to the waiting room is controlled to the path planning mode corresponding to the low-peak service strategy;

[0049] Among them, when the current time is in the off-peak service time interval, it includes:

[0050] When it is detected that a patient needs emergency services, all rounds of medical services in the waiting room corresponding to the patient's area will be used as control targets. Based on the area corresponding to the patient's emergency service needs, service extension control targets and service delay control targets will be determined;

[0051] Based on the preset emergency service time corresponding to the waiting room, the corresponding parameters of the service extension control target and the service delay control target are adjusted respectively, and after the emergency service is completed, the off-peak service strategy is restored;

[0052] The preset emergency service time is less than the optimal service time.

[0053] Based on patient distribution and hospital management system data, the current path planning for waiting room rounds is adjusted to generate a real-time optimization plan, including:

[0054] Based on the patient distribution ratio, determine the relatively concentrated areas and secondary concentrated areas of patients;

[0055] Obtain the length of the first and second rounds of the waiting room's path, and predict the first and second rounds of the waiting room's time based on the average movement speed of the medical staff.

[0056] Obtaining a first growth rate of the number of patients corresponding to the relatively concentrated area, and determining a first service growth amount of the waiting room based on the first growth rate, in combination with the path lengths of each path corresponding to the relatively concentrated area, the first waiting time, and a preset service speed of medical staff corresponding to the current time period;

[0057] According to the first service growth amount, the first round time, the first service time and the service start error of adjacent patients, the first round extension time corresponding to the relatively concentrated area is obtained;

[0058] At the same time, a second growth rate of the number of patients corresponding to the secondary concentrated area is obtained, and a second service growth amount of the waiting room is determined based on the second growth rate, in combination with the path length of each path corresponding to the secondary concentrated area, the second waiting time, and the preset service speed of the medical staff corresponding to the current time period;

[0059] According to the second service growth amount, the second round time, the second service time and the service start error of adjacent patients, the second round extension time corresponding to the secondary concentrated area is obtained;

[0060] The round time corresponding to the current path planning of the waiting room round service is adjusted based on the first round extension time and the second round extension time to generate a real-time optimization plan.

[0061] Among them, generating environment maps and navigation paths includes:

[0062] Obtain the robot's current location information, generate a preliminary map of the environment through the SLAM algorithm based on the environment's feature data, and update the real-time location information;

[0063] Based on real-time location information and path planning information, the autonomous navigation module performs path navigation operations;

[0064] In the event that the target path does not match the predetermined path planning information, the navigation path is readjusted and real-time navigation is performed through the autonomous navigation module.

[0065] Compared with the prior art, the present invention has the following advantages:

[0066] A patrol robot for PET / CT waiting rooms comprises a sensing and monitoring module for real-time monitoring of dynamic data about patients and the environment in the waiting room; a control system for planning the robot's path and assigning task instructions based on this dynamic data; a mobile platform for moving the robot to designated locations within the waiting room based on path planning; an interaction module for providing human-machine interaction and guiding patients through pre-examination preparations; and a task execution module for executing proactive intervention tasks based on task instructions. By leveraging multi-sensor fusion, intelligent control, and human-machine interaction technologies, the robot addresses issues such as patient management, radiation protection, and the waste of medical resources.

[0067] Other features and advantages of the present invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the present invention.

[0068] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0070] Figure 1 This is a structural diagram of a patrol service robot for a PET / CT waiting room according to an embodiment of the present invention;

[0071] Figure 2 This is a structural diagram of the sensing and monitoring module in an embodiment of the present invention;

[0072] Figure 3 This is a structural diagram of a control system in an embodiment of the present invention. DETAILED DESCRIPTION

[0073] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0074] An embodiment of the present invention provides a patrol service robot for a PET / CT waiting room, comprising:

[0075] Sensing and monitoring module, used to monitor the dynamic data of patients and environment in the waiting room in real time;

[0076] The control system is used to plan the robot path and assign task instructions based on dynamic data;

[0077] A mobile platform is used to move the robot to a designated location in the waiting room based on path planning;

[0078] The interactive module is used to provide human-computer interaction functions and guide patients to complete the preparations before the examination;

[0079] The task execution module is used to execute the robot's active intervention task based on the task instructions.

[0080] The working principle of the above technical solution is as follows: the mobile platform is responsible for the autonomous movement of the robot in the waiting room. By integrating lidar and visual sensors, SLAM (simultaneous localization and mapping) technology is realized, which can accurately perceive the environment and autonomously plan the path. SLAM technology combines lidar ranging and visual sensors to provide environmental data. The robot can avoid obstacles in the complex waiting room environment and move along a predetermined path. When the mobile platform is started, it will perform an environmental scan and generate a map of the waiting room in real time. Through SLAM technology, the robot can identify and avoid moving obstacles, such as patients, tables and chairs, etc., to ensure the robot's autonomous movement ability. When the control system issues a path planning task, the robot drives the mobile chassis through the power provided by the battery pack, and moves according to the planned path to ensure the smooth completion of the task.

[0081] The sensing and monitoring module monitors the dynamic status of patients in the waiting room in real time, including movement behavior, biometrics (such as heart rate, body temperature) and behavioral norms. Sensors are used to identify whether the patient maintains the correct posture (such as sitting still) in the waiting area, and whether there are behaviors that are not conducive to PET / CT examinations (such as frequent walking, talking, etc.). The sensor system monitors the patient's physical signs and behavior, and uses the biometric recognition camera to identify whether the patient meets the health standards. If the patient's physical signs (such as heart rate, body temperature) exceed the set normal range, or their behavior does not meet the examination requirements (such as walking or talking), the sensor will send an alarm message to the control system. After receiving the data, the control system will analyze it and decide whether it is necessary to communicate with the patient through the interactive module or notify medical staff.

[0082] The interactive module provides human-computer interaction functions to help patients understand and follow the examination process. The robot can communicate with patients through voice or touch screen interface, provide real-time guidance and examination-related precautions, and reduce patients' anxiety and uneasiness. While patients are waiting, the robot uses the voice recognition system to identify patients' needs or questions and responds through the speech synthesis system. The robot can guide patients to complete pre-examination preparations (such as sitting quietly, avoiding talking, etc.) and provide necessary examination information, such as prompts such as "Please sit down and avoid moving." Through the multi-language support module, the robot can translate and communicate in real time according to the patient's language preference.

[0083] The task execution module performs robot-initiated intervention tasks, such as automatic disinfection, comforting patients, and assisting patients in moving. The robotic arm can perform physical tasks such as cleaning and disinfection, and the disinfection nozzle can disinfect the air or environmental areas to ensure the hygiene of the waiting room. Operation: When the control system issues a task instruction, the task execution module intervenes according to the specific task. For example, if the control system detects that a certain area needs to be disinfected, the robot will spray disinfectant through the disinfection nozzle, or refresh the air through the air purification device; if a patient is anxious, the robotic arm can deliver comforting items (such as water cups, paper towels, etc.). These tasks are scheduled and executed with the support of real-time data.

[0084] The control system integrates the data collected by each sensor module through the central control system, performs real-time analysis and plans robot tasks. The control system supports path planning, task instruction allocation, and synchronizes data with the hospital management system. The edge computing module can process some tasks locally to ensure real-time performance and response speed; the communication module is responsible for data interaction and remote control with other systems. Operation: The control system receives data from the sensor module and adjusts the robot task according to the data content (such as the patient's biometrics and motion status). The control system will optimize the robot's path planning and task allocation based on the current environmental conditions and task priorities. If remote intervention or adjustment is required, hospital managers can also connect with the robot in real time through the communication module.

[0085] The mobile platform provides the robot with mobility in the waiting room and is the basis for other modules to move to their target locations. The sensing and monitoring module monitors the patient's behavior and health status in real time, and provides this data to the control system to help it make intelligent decisions. The control system performs path planning and task allocation based on real-time data, and dispatches the task execution module to complete specific operations. The interactive module communicates directly with patients to reduce waiting anxiety, while guiding patients to comply with examination requirements and improve their cooperation. After receiving instructions from the control system, the task execution module performs specific tasks (such as disinfection, assistance, etc.) and coordinates the work of other modules.

[0086] The beneficial effects of the above technical solution include: the robot can promptly communicate examination procedures and precautions to patients through voice reminders and guidance. The water reminder function not only optimizes patient preparation before the examination, but also, through its intelligent rounds service, reduces patient anxiety and dissatisfaction caused by long wait times or lack of understanding of the process. By providing thoughtful measures such as water service, the patient experience is significantly improved. While waiting for an appointment, improper patient behavior (such as frequent walking or strenuous exercise) can distort examination results. This invention uses a sensing and monitoring module to detect the patient's movement status in real time, and uses voice reminders and human-computer interaction to promptly correct the situation. This significantly reduces the examination failure rate caused by improper behavior, thereby reducing the need for repeated examinations. Traditional waiting rooms require frequent rounds of medical staff, increasing the risk of radiation exposure. Robots can take on tasks such as patient guidance, status monitoring, and task execution, such as measuring blood sugar and blood pressure. This reduces the frequency of direct contact between medical staff and patients, effectively reducing radiation risks while ensuring work quality and improving the occupational safety of medical staff. The robot can autonomously navigate and monitor patient behavior, enabling intelligent management of the waiting room. For example, if a patient fails to sit still as instructed, the robot can promptly remind them and, if necessary, notify medical staff to intervene. This intelligent management approach not only reduces the need for manual intervention but also improves the overall efficiency of waiting room operations.

[0087] In another embodiment, a sensing and monitoring module includes: a multimodal sensor and a patient status monitoring system;

[0088] Multimodal sensors are used to collect the movement status and biometric characteristics of patients in the waiting room in real time and generate dynamic data reports;

[0089] The patient status monitoring submodule is used to identify abnormal patient behavior by analyzing dynamic data reports.

[0090] Among them, identifying abnormal patient behavior includes:

[0091] When the system detects that the patient's dynamic data exceeds the normal range, it will simultaneously generate a patient abnormal behavior report on the medical resource management terminal, and provide detailed abnormal behavior analysis for the medical service personnel based on the patient abnormal behavior report;

[0092] When multiple abnormal behaviors are identified, the medical staff prioritizes the abnormal behaviors based on the patient's specific circumstances, develops the best intervention measures, and submits a treatment plan;

[0093] Provide detailed abnormal behavior analysis to medical personnel based on patients' abnormal behavior reports, including:

[0094] Abnormal behavior recognition rules are set based on dynamic data analysis models and the patient's historical health data. Abnormal behavior recognition rule configuration includes parameter rule settings for motion state thresholds, biometric fluctuation ranges, behavioral norm deviations, and abnormal alarm priorities.

[0095] When the information management terminal in the PET / CT waiting room receives the patient's dynamic data, it performs intelligent analysis based on the data report and the set abnormal behavior identification rules. Among them, the visiting service staff can choose between two modes: manual review of abnormal behavior reports and automatic generation of intervention suggestions.

[0096] The working principle of the above technical solution is as follows: Multimodal sensors are composed of multiple different types of sensors, which are placed in multiple locations in the waiting room to ensure that the status of each patient can be fully and accurately monitored. They work in the following ways:

[0097] Infrared sensors: Used to detect patient movement. Infrared sensors can sense changes in body heat and determine whether a patient is sitting still or moving. For example, if an infrared sensor detects a patient moving around in the waiting area, the system will record their movement trajectory to help determine whether the patient is anxious or uncomfortable. Pressure sensors: Installed on waiting room chairs, they detect whether a patient is sitting down. By monitoring pressure changes, the sensors can determine in real time whether the patient is maintaining a sitting position, which is crucial for assessing patient compliance with waiting rules. Biometric cameras: Using computer vision and biometric technology, they monitor patients' facial expressions, eye movements, posture, and other behavioral characteristics in real time to analyze emotional fluctuations and changes in physical signs. These cameras can also monitor physiological data such as heart rate and body temperature to identify any potential health issues. Integration and data processing: The output data from all sensors is transmitted to a central control system via a wireless communication module. This system processes the raw data collected by the sensors in real time and generates detailed dynamic data reports that include the patient's movement status, physiological parameters (such as heart rate and body temperature), and behavioral performance.

[0098] The patient status monitoring system analyzes the dynamic data collected by sensors and identifies abnormal patient behavior through specialized algorithms (such as anomaly detection algorithms). Its operation steps include:

[0099] Behavioral analysis: The system analyzes patients' behavior patterns in the waiting room to determine whether they meet the examination requirements. For example, PET / CT examinations require patients to remain seated as much as possible before the scan, avoiding strenuous movement or changes in body position. Therefore, the system monitors patients for movements, frequent seat changes, and other unusual behaviors, instantly identifying them.

[0100] Physiological status monitoring: In addition to behavioral monitoring, the system also closely monitors the patient's physiological status, such as heart rate and body temperature. If an abnormal heart rate (such as too fast or too slow) or elevated body temperature is detected, the system will issue an alarm, indicating that there may be health risks or the need to adjust the examination plan.

[0101] Reminders and Notifications: If a patient exhibits unusual behavior or physiological parameters are outside the normal range, the system will issue a notification through intelligent reminders, alerting the patient or notifying the medical staff in the waiting room. For example, the system may remind the patient to remain seated or notify medical staff to come and check on the patient's condition.

[0102] These include: Movement Status: whether the patient has been immobile for extended periods or suddenly engaged in intense movement; Biometrics: fluctuations in physiological parameters such as heart rate, body temperature, and blood pressure; and Behavioral Patterns: for example, whether the patient exhibits anxiety, restlessness, or excessive nervousness. When the system detects these dynamic data outside of pre-set normal ranges, it automatically generates a report on the patient's abnormal behavior. For example, if a patient's heart rate fluctuates significantly over a short period of time, the system will identify and report this as abnormal behavior. To accurately identify abnormal behavior, the system intelligently analyzes the patient's historical health data and pre-set rules. Abnormal behavior identification rules include multiple parameter configurations: Movement Status Threshold: If the patient's movement level exceeds or falls below a certain threshold, the system identifies it as abnormal. For example, if a patient suddenly accelerates in the waiting room, this indicates a change in their psychological or physiological state. Biometric Fluctuation Range: A heart rate fluctuation of more than 10% within a short period of time indicates physical discomfort, and the system will register this fluctuation as an alert. Behavioral Deviation: By observing the patient's behavioral norms (such as walking and sitting posture), any deviations from normal behavior will be flagged as abnormal. Abnormal Alert Priority: The system assigns different priorities to different abnormal behaviors based on their severity. A tachycardia is designated a high-priority alert, requiring immediate attention; a mild case of unsteady walking is designated a low-priority alert, pending further action. These rules are based on a dynamic data analysis model that continuously adjusts these parameters based on various sensor data and the patient's historical records to ensure accurate recognition.

[0103] When the system identifies abnormal behavior, medical staff can adopt different handling modes based on the report: Manual Review Mode: Medical staff review the abnormal behavior report, assess the severity of each abnormal behavior, and manually handle it based on the actual situation. This means that staff can use detailed data analysis to determine whether further intervention is necessary or directly notify the doctor. Automatic Intervention Recommendation Mode: The system automatically generates intervention recommendations based on the abnormal behavior report and identification rules. For example, if the heart rate is too high, the system can automatically recommend lying down, regulating breathing, or taking other mitigating measures, or directly notify the doctor. Medical staff can prioritize multiple abnormal behaviors based on the patient's specific situation, ensuring that the most urgent health issues receive timely intervention. At the information management terminal in the PET / CT waiting room, medical staff can receive dynamic patient data reports. These data reports are generated by the intelligent analysis system, and the system conducts in-depth analysis based on the patient's historical health records, current physiological indicators, and other factors. The information management terminal's functions include: Intelligent Analysis of Abnormal Behavior: Based on pre-set abnormal behavior identification rules, the information management terminal automatically analyzes data and screens for possible abnormal behaviors. Report Generation and Notification: Once abnormal behavior is identified, the system will generate a detailed report showing the abnormal data, analysis results, and possible health risks, and notify the medical staff. Intervention Recommendation Generation: In automatic mode, the system will not only identify abnormal behavior but also provide recommended intervention measures to the medical staff to ensure that the patient's health problems receive timely intervention.

[0104] The beneficial effects of the above technical solution include: through real-time monitoring and automated data processing, waiting room management becomes more efficient. Medical staff no longer need to constantly observe every patient; the system automatically detects abnormalities and sends alerts, reducing workload and ensuring patient safety. During PET / CT examinations, factors such as patient movement and heart rate can affect image quality and examination results. By monitoring the patient's condition in real time, the system ensures that the patient remains seated and quiet before the examination, minimizing unnecessary movement and ensuring accurate examination results. By monitoring the patient's heart rate, body temperature, and other physiological characteristics, the system can identify potential health risks in real time. An elevated temperature indicates a risk of infection; an abnormal heart rate indicates poor health. Timely alerts enable medical staff to respond quickly and conduct further health assessments and interventions. Because patients' behavior and physiological status are continuously monitored, patients maintain a high level of safety and comfort without frequent interaction with medical staff. Furthermore, the system can proactively alert patients to avoid inappropriate behavior, reducing examination issues caused by unawareness.

[0105] In another embodiment, a control system includes: a central control unit, an edge computing module, and a communication module;

[0106] Central control unit, used to support remote control and ensure flexibility of robot operation;

[0107] Edge computing module, used to analyze dynamic data in real time, connect with the hospital management system, and generate optimized path planning and task allocation solutions;

[0108] Communication module, used to transmit dynamic data to the hospital management system in real time.

[0109] The working principle of the above technical solution is as follows: The central control unit is the "brain" of the entire control system, responsible for commanding and coordinating the entire robot. Its main responsibilities include: Remote control support: The central control unit supports remote control functions, allowing medical staff to control the robot through the hospital management system or mobile devices. For example, when special tasks are required (such as transferring a patient or inspecting a device), medical staff can adjust the robot's path, task, or execution status through remote operation. In this way, the robot can maintain flexibility and efficiency without human intervention. Task scheduling and command issuance: The central control unit formulates task scheduling plans based on the robot's work tasks and real-time data, and issues specific operation instructions to each subsystem or execution module (such as the movement module, sensor module, etc.). For example, if abnormal patient behavior is detected during medical rounds, the central control unit will issue instructions to the robot to activate an alarm, play a voice prompt, or notify medical staff.

[0110] The edge computing module resides in the robot's local environment and is responsible for real-time analysis and processing of dynamic data. Its core functions include: Real-time Data Processing: The edge computing module integrates sensor data (such as patient movement, heart rate, and body temperature) for local, real-time processing. This allows the robot to rapidly respond to changes in the patient environment in the waiting room, quickly assessing and reacting to the current situation without having to send all data to a remote server or hospital management system for processing. For example, the edge computing module can locally analyze whether the patient is moving, in an inappropriate position, or has an abnormal heart rate, and immediately issue instructions to adjust accordingly. Path Planning and Task Allocation: The edge computing module optimizes the robot's path planning based on real-time data and task requirements, ensuring it can efficiently complete its rounds. For example, within the waiting room, the robot needs to plan the shortest and safest route based on patient distribution, the spatial layout of the waiting area, and task priorities. The module adjusts the route in real time to avoid collisions and congestion. Interconnection with Hospital Management Systems: The edge computing module not only processes local data but also exchanges data with the hospital management system. For example, the robot can send the patient's health data (such as abnormal heart rate, abnormal body temperature, etc.) to the hospital management system so that medical staff can understand the patient's real-time health status and adjust the diagnosis and treatment plan accordingly.

[0111] The communication module is responsible for data transmission between the robot and the hospital management system, other robots, and external devices. Its main functions include: Real-time data transmission: The communication module transmits the robot's dynamic data, task execution status, and sensor feedback information to the hospital management system in real time through wireless communication technologies (such as Wi-Fi, 5G, or Bluetooth). This ensures that hospital managers can always grasp the robot's operating status, patient monitoring data, and the progress of current tasks. For example, when the robot detects that the patient's body temperature is abnormal, the communication module will immediately transmit the data to the hospital's management system, and medical staff can respond immediately. System docking and information sharing: The communication module not only transmits the robot's status, but also realizes docking with the hospital information system (HIS), patient management system, electronic medical record system (EMR), etc. This enables the robot to automatically share information with other systems in the hospital while performing rounds, ensuring the circulation and timeliness of patient health data.

[0112] The above technical solution has the following beneficial effects: Through the coordinated operation of the central control unit, edge computing module, and communication module, the robot can perform efficient and accurate rounds in complex waiting room environments. Real-time data processing and optimized path planning enable the robot to flexibly adjust to patient needs and environmental changes, ensuring that each task is completed on time and accurately. For example, if a patient's behavior is abnormal, the robot can take timely action, notifying medical staff or automatically adjusting its behavior. Remote control support from the central control unit allows the robot to flexibly respond to various situations based on medical needs without manual intervention, reducing the workload of medical staff. Furthermore, remote control allows hospital administrators to adjust the robot's tasks at any time, ensuring that the robot always aligns with the hospital's diagnosis and treatment plan. The edge computing module optimizes the robot's rounds through real-time data analysis, avoiding congestion in the waiting room and unnecessary route repetition. This not only improves the robot's rounds efficiency, but also reduces battery consumption and device wear, ensuring long-term stable operation. Optimized path planning also allows the robot to adjust the rounds strategy based on specific patient needs (such as a rapid heart rate or high body temperature), improving the targeted execution of tasks.

[0113] In another embodiment, a mobile platform comprises: a tracked or wheeled mobile chassis, a battery pack, and an autonomous navigation module;

[0114] Tracked or wheeled mobile chassis, used to provide stable mobile support for the robot;

[0115] Battery pack, used to adopt a new power management system to ensure long-term stable operation of the robot;

[0116] The autonomous navigation module is used to achieve accurate perception and navigation of the waiting room environment based on SLAM technology combined with lidar and visual sensors, and generate environmental maps and navigation paths.

[0117] The working principle of the above technical solution is that the robot obtains physical support and moves through a crawler or wheeled chassis. Tracked chassis are usually used in environments with uneven ground or many obstacles, and can provide stronger traction and stability, making them suitable for complex venues. Wheeled chassis, on the other hand, are suitable for flat surfaces and can provide higher movement speed and efficiency. In the waiting room, the chassis provides sufficient stability and support, allowing the robot to move smoothly to the location of each patient for rounds of medical services. The chassis movement is driven by an electric motor. By controlling each wheel or track, the robot can smoothly move forward, turn, and bypass obstacles.

[0118] The battery pack is responsible for providing power to the entire robot system, ensuring long-term, stable operation. The battery pack utilizes a novel power management system that efficiently distributes and monitors energy, extending the robot's endurance. In waiting rooms, robots must operate continuously for extended periods, so the battery pack must not only provide sufficient power but also ensure efficient power management to avoid mission interruptions due to battery depletion. The novel power management system intelligently regulates battery usage, optimizing charging and discharging processes, extending battery life, and ensuring a constant charge throughout the entire patient visit.

[0119] Autonomous Navigation Module: LiDAR: LiDAR is a key sensor for autonomous robot navigation, measuring the distance to surrounding objects by emitting lasers and receiving reflected signals. This technology helps robots build accurate environmental maps and detect obstacles and other important features in real time. For example, in a waiting room, LiDAR can scan the surroundings in real time, generating a three-dimensional map of the environment, helping the robot understand the locations of walls, furniture, and patients. Vision Sensor: Vision sensors collect image data through cameras, further supplementing the information obtained by LiDAR. Especially in complex or detailed environments, vision sensors can provide additional image data, helping robots make more precise perceptions and decisions. SLAM (Simultaneous Localization and Mapping): SLAM is a technology that simultaneously performs localization and mapping. Combining LiDAR and vision sensors, robots can simultaneously build a real-time map of their environment and determine their position within it while exploring unknown environments. Specifically, SLAM helps robots determine their current position by fusing sensory data and continuously optimizes map accuracy by continuously scanning and updating environmental information. Navigation and Obstacle Avoidance: Based on the environmental map generated by SLAM, the robot can plan the optimal route for patient visits and, through dynamic obstacle avoidance technology, avoid collisions and obstacles in real time. If it encounters an unexpected obstacle (such as a patient standing up suddenly or furniture shifting), the robot can automatically adjust its path to ensure successful completion of the task.

[0120] The beneficial effects of the above technical solution include: the robot can autonomously move within the PET / CT waiting room, ensuring quick and efficient completion of its rounds through precise environmental perception and intelligent path planning. Requiring no human intervention, the robot can freely navigate along a pre-defined path and reach each patient requiring medical attention, significantly improving the efficiency of medical rounds. By utilizing SLAM technology, which combines lidar and visual sensors, the robot maintains high stability and flexibility in complex and dynamic waiting environments. For example, a waiting room may contain tables and chairs in different positions, patients, and sudden environmental changes (such as people moving around). By updating its map and path in real time, the robot can flexibly avoid obstacles and complete its tasks without interruption. The robot's innovative battery pack and power management system enable it to perform long rounds in the waiting room without frequent recharging. This continuous and stable operation not only improves the robot's efficiency but also allows hospitals to more efficiently utilize the robot for routine rounds without worrying about interruptions due to power outages.

[0121] In another embodiment, the interaction module includes: a touch screen, a speech recognition and synthesis submodule, and a multi-language support submodule;

[0122] Touch screen, used to provide an operation interface to help patients obtain examination-related information;

[0123] The speech recognition and synthesis submodule is used to communicate through voice, play precautions, guide patients to prepare for the examination, and generate voice interaction records;

[0124] The multi-language support sub-module is used to intelligently identify patients' language preferences, provide multi-language switching and personalized services.

[0125] Among them, through voice communication, playing precautions, guiding patients to prepare for the examination, and generating voice interaction records, including:

[0126] Obtaining patient object information, where the object information includes at least one patient object identifier (equivalent to each patient's "identity card number", for example, a patient ID);

[0127] In response to a first patient among the at least one patient satisfying a preset interaction condition (the patient enters a waiting area or enters a specific state, such as waiting for an examination), displaying an interactive guidance element on the touch screen;

[0128] In response to the medical rounds service robot triggering an interactive guidance element (a button or icon appears on the screen, prompting the patient to interact, usually "click here to learn more" or "view examination precautions"), the first patient is played with precautions for preparing for the examination. The precautions are used to guide the patient to understand the examination requirements and procedures;

[0129] The method includes: displaying a voice playback page in response to a triggering operation of the medical rounds service robot on the interactive guidance element; and displaying at least one candidate note in the voice playback page;

[0130] In response to a triggering operation on at least one candidate precaution, target precaution information (referring to the content of a specific precaution selected by the patient, such as "You need to fast for 4 hours before the examination") is obtained;

[0131] Playing voice content matching the target precaution information to the first patient;

[0132] The target precaution information includes the target precaution text, and the voice content includes a voice control for playing the target precaution (a control button for playing sound, such as a "play" button, which the patient can click to listen to relevant voice information) and the first voice message corresponding to the target precaution (when "fasting for 4 hours" is selected, the system will play through voice: "Please note that you need to fast for at least 4 hours before undergoing a PET / CT examination to ensure accurate examination results."), and the voice content matches the target precaution text.

[0133] The working principle of this technical solution is as follows: The touch screen provides an intuitive and easy-to-use interface, allowing patients to view detailed information related to the PET / CT examination, including the examination process, preparation, precautions, etc. The touch screen interface displays a combination of pictures and text, allowing patients to access various information with simple clicks. For example, when a patient selects the "Exam Preparation" module on the touch screen, the system displays specific preparation precautions, such as fasting requirements and whether medication discontinuation is necessary. The touch screen also displays real-time waiting information to help patients understand the examination progress.

[0134] The speech recognition and synthesis submodule interacts with patients through voice, guiding them through pre-examination preparations. Patients can receive real-time feedback by asking questions (e.g., "What preparations do I need for the examination?") or simple instructions (e.g., "Begin the examination process"). The system understands the patient's instructions through speech recognition technology and returns a response to the patient through the speech synthesis module, for example, "You need to fast for 8 hours before the examination." The speech synthesis submodule can also play relevant precautions at specific times to further help patients understand the examination requirements and process. This voice interaction method is particularly suitable for patients with limited mobility or who are not proficient in using touch screens.

[0135] The multilingual support submodule intelligently identifies the patient's language preference and automatically provides multilingual switching. When a patient enters the waiting room, the robot asks for their language preference via voice or touchscreen (for example, "Please select your language") and then provides services in the selected language. This module, based on natural language processing (NLP) technology, automatically switches between different languages through an automated translation system, ensuring that all patients, whether native or foreign-speaking, can clearly understand examination information, enhancing the convenience of cross-lingual communication.

[0136] The beneficial effects of the above technical solution are as follows: The interactive module meets patients' needs through various methods, from touchscreen to voice interaction to multilingual support, providing patients with a comprehensive and convenient examination preparation support system. Patients no longer need to frequently ask medical staff for information such as examination procedures and precautions, reducing the inconvenience caused by language barriers or information asymmetry, thereby effectively improving the overall patient experience. By combining speech synthesis with a touchscreen, patients can choose the most appropriate interaction method based on their preferences, thus avoiding the discomfort caused by operational difficulties. Through the information query and guidance functions provided by the robot, patients can self-service access most examination-related information and instructions, reducing the time medical staff spend on repetitive tasks (such as explaining preparation matters and answering common questions). Medical staff can focus more on professional medical procedures and emergency response, improving overall work efficiency. Because the interactive module can systematically and standardizedly convey examination-related information, patients can more clearly understand the entire examination process and preparation, thereby reducing anxiety or misunderstandings caused by insufficient information. The speech synthesis module can also repeatedly remind patients of precautions, helping them better adhere to pre-examination preparation requirements, improving the accuracy and probability of a smooth examination.

[0137] In another embodiment, the task execution module includes: a robotic arm, a disinfection nozzle or air purification submodule, and an alarm submodule;

[0138] A robotic arm to assist with patient mobility and calm agitation, generating patient comfort assessments;

[0139] Disinfection nozzles or air purification submodules are used to automatically disinfect the area around the patient's seat and generate environmental hygiene status reports;

[0140] The alarm submodule is used to monitor abnormal situations, provide real-time warnings, and generate safety warning information.

[0141] The working principle of the above technical solution is as follows: The robotic arm module is a highly automated device designed to assist patients in moving around the waiting room, relieve anxiety, and provide comfort assessments. Through integrated sensors and control systems, the robotic arm can provide personalized intervention based on the patient's specific needs. For example, when a patient is anxious, the robotic arm can slowly and steadily guide the patient to perform soothing exercises or provide hand massage services to help relieve tension and anxiety. The robotic arm can detect the patient's posture and movements in real time through cameras and sensors, and automatically assess their comfort level. When the system detects signs of discomfort or anxiety in the patient, the robotic arm will activate the corresponding soothing mode (such as gentle arm movements) or provide physical contact to soothe the patient's emotions. In addition, the robotic arm can also help the patient stand up, sit down, or move from the waiting chair based on the patient's mobility, thereby reducing the patient's discomfort.

[0142] Disinfection nozzles or air purification modules are responsible for automatically disinfecting the air or surfaces in the waiting area to ensure environmental hygiene. Disinfection nozzles use aerodynamics or air pressure principles to spray high-efficiency disinfectants to clean patient seats, armrests and the surrounding environment. These nozzles are arranged in a distributed manner to spray disinfectants in multiple key areas of the waiting area to ensure that every corner is covered, thereby effectively killing harmful microorganisms such as pathogens and viruses. The air purification sub-module purifies the air through built-in high-efficiency filters (such as HEPA filters) and negative ion generators, removing bacteria, dust, viruses and other harmful substances in the air, ensuring that patients breathe fresh and harmless air while waiting. The entire disinfection and air purification process is automated and does not require human intervention. The equipment automatically operates according to the timing settings or feedback from environmental sensors, generating real-time environmental hygiene status reports, recording the disinfection area, time and disinfection intensity to ensure that the environment is always in the best hygienic state.

[0143] The alarm submodule provides real-time warnings by monitoring abnormal conditions in the waiting room around the clock. Combining multiple sensors such as infrared sensors, temperature and humidity sensors, and gas detectors, the module constantly monitors environmental changes, such as abnormally high temperatures and leaks of harmful gases in the air. It can analyze abnormal conditions based on real-time detection data and immediately issue an alarm signal when potential risks are detected. Warning information is transmitted to medical staff in real time through sound, light, or notification systems, helping to quickly respond to emergencies. In addition, the alarm submodule also has a linkage function. When a patient is found to be overly excited, physically unwell, or facing other safety risks, the system will automatically activate the corresponding emergency plan, such as calling staff, turning on the comfort mode, and initiating a safe evacuation procedure.

[0144] The beneficial effects of the above technical solution are as follows: the robotic arm module can provide personalized soothing services to anxious patients, helping them remain calm and reduce anxiety. This not only enhances the patient waiting experience, but also reduces physical discomfort and improves their emotional state through soothing measures. By automating tasks (such as patient movement assistance, environmental disinfection, and air purification), the workload of medical staff is significantly reduced. The efficient robotic assistance allows medical staff to focus on higher-priority tasks, reducing repetitive and mechanical labor and improving work efficiency. The disinfection nozzle and air purification module maintain a clean environment and air quality during patient entry and exit, reducing the risk of cross-infection. This highly efficient automated disinfection and air purification technology not only reduces the spread of pathogenic microorganisms such as bacteria and viruses, but also significantly enhances patients' sense of hygiene and safety. The alarm module's real-time monitoring and warning functions ensure a safe waiting environment while enabling timely response to unexpected abnormalities. This is crucial for the safety of patients and medical staff, effectively preventing safety hazards such as fires and gas leaks and triggering emergency response measures in a timely manner.

[0145] In another embodiment, the multimodal sensor includes: an infrared sensor, a pressure sensor, and a biometric recognition camera;

[0146] Infrared sensors are used to accurately locate the patient's movements and posture in the waiting room by detecting changes in the patient's body temperature and heat radiation patterns, and to determine the patient's current state, including stillness, walking, or sitting;

[0147] Pressure sensors to monitor changes in a patient's weight distribution, sitting or lying posture;

[0148] Biometric cameras to monitor patients' facial expressions and physiological responses.

[0149] The working principle of the above technical solution is as follows: An infrared sensor is a device that senses environmental changes by detecting infrared rays (i.e., thermal radiation) emitted by objects. In the PET / CT waiting room patrol service robot, the infrared sensor is mainly used to detect the patient's body temperature distribution and thermal radiation pattern, thereby accurately identifying the patient's position and movement status. The following is its specific working method:

[0150] Body temperature detection: Infrared sensors can capture infrared radiation emitted by the patient's body and accurately measure the patient's surface temperature. For example, if the sensor detects that the patient's body temperature is too high (such as fever symptoms), the system will automatically trigger an alarm or alert medical staff. Motion and posture judgment: The infrared sensor locates the patient's body parts by analyzing the intensity and distribution pattern of thermal radiation, and identifies whether the patient is stationary, walking, or sitting. For example, when sitting, the sensor detects that the thermal radiation is concentrated near the seat, while the thermal radiation area moves dynamically when walking. This non-contact detection method ensures the security and accuracy of data collection, while avoiding the direct contact problem of traditional body temperature measurement.

[0151] Pressure sensors measure the contact pressure between the patient and the surface, providing information about the patient's weight distribution and posture. In mobile medical service robots, pressure sensors are typically embedded in the patient's seat surface or armrests to monitor the following indicators in real time:

[0152] Weight distribution: The pressure sensor can capture the pressure distribution exerted by various parts of the patient's body. For example, when the patient is sitting normally, the seat surface will show a uniform pressure distribution; when the patient is tilted or the center of gravity shifts, the sensor can detect the asymmetric pressure distribution and prompt possible discomfort or physical abnormalities. Changes in sitting or lying posture: By continuously monitoring pressure data, the system can determine whether the patient is sitting normally, semi-lying, or standing up suddenly. For example, when it is detected that the patient suddenly leaves the seat and the pressure distribution changes rapidly, the system can determine that the patient has stood up and perform a comprehensive analysis in combination with other sensors. This real-time pressure data feedback is important for assisting in judging the patient's condition and preventing falls or discomfort caused by prolonged improper posture.

[0153] A biometric recognition camera is a device that combines a regular camera with an artificial intelligence algorithm. It can capture a patient's facial expressions, physiological characteristics, and micro-expression changes to identify their emotions and health status. Here's how it works:

[0154] Facial expression analysis: The camera collects the patient's facial data and uses AI algorithms to analyze subtle changes in facial muscles to determine whether the patient has emotions such as anxiety, anger, or sadness. For example, drooping eyebrows and drooping corners of the mouth may be identified as a state of anxiety or dissatisfaction. Physiological reaction monitoring: In addition to facial expressions, the camera can also capture physiological signals such as changes in skin color and breathing rate. For example, redness of the skin may indicate increased blood pressure, and pale face may be related to low blood pressure or fatigue. Identity confirmation: Combined with biometric recognition technology (such as face recognition), the camera can verify the patient's identity information to ensure that the service robot can provide targeted and personalized services. This module relies on computer vision and machine learning algorithms to efficiently perform non-contact emotion and health monitoring.

[0155] The beneficial effects of the above technical solution are as follows: multimodal sensors (infrared sensors, pressure sensors, biometric recognition cameras) work together to detect the patient's behavior, emotions and health status in real time from multiple dimensions. This comprehensive judgment method enables the patrol robot to accurately understand the patient's dynamic state and avoids the misjudgment that may be caused by a single sensor. For example, by combining the data from infrared sensors and pressure sensors, the robot can more accurately determine whether the patient is standing or adjusting his sitting posture. All sensors use non-contact technology (such as infrared detection and visual recognition) and can complete data collection without disturbing the patient. This method not only improves the patient's comfort, but also reduces the risk of cross-infection. It is very suitable for crowded and mobile environments such as waiting rooms. By monitoring the patient's body temperature, posture and emotions in real time, the patrol robot can quickly identify abnormal situations. For example, when an infrared sensor detects an abnormal patient temperature, it can alert medical staff to check for fever or infection risks. When a pressure sensor detects a patient suddenly standing up and losing their balance, it can trigger an early warning to prevent falls. And when a biometric camera detects an abnormal expression on a patient's face (such as pain or fatigue), it can prompt the robot to proactively comfort the patient or provide assistance. Using the biometric camera, the robot can quickly identify the patient and record their emotional trends, providing more personalized and attentive service.

[0156] In another embodiment, generating an optimized path planning and task allocation solution includes:

[0157] Compare the current patient dynamic data in the waiting room with the preset standards in the hospital management system;

[0158] When the patient's motion state or biometric characteristics in the current dynamic data exceed the corresponding preset standards, it is determined that the service demand in the waiting room has increased, the patient distribution in each area of the waiting room is obtained, and the number of patients in adjacent areas is merged to obtain the regional patient density;

[0159] Compare the patient density in different areas of the waiting room to determine the patient distribution ratio in the waiting room. Based on the patient distribution ratio and data from the hospital management system, adjust the current path planning and generate a real-time optimization plan.

[0160] Among them, dynamic data include the patient's movement status, heart rate, blood oxygen saturation, body temperature and behavioral norms;

[0161] When the patient's motion status and biometric characteristics in the current dynamic data are within the preset standard range, it is determined that the service demand in the waiting room is normal;

[0162] When the patient's motion status and biometrics in the current dynamic data are within the preset standard range, the service demand in the waiting room is determined to be normal, including:

[0163] Get the current time and determine the time interval to which the current time belongs;

[0164] When the current time is in the peak service time interval, the rounds service corresponding to the waiting room will be controlled to maintain or restore to the default rounds policy;

[0165] When the current time is in the off-peak service time interval, obtain the patient distribution in the waiting room during the off-peak time interval, generate a patient distribution change curve, and based on the patient distribution change curve, determine the concentrated service interval within the off-peak time interval and the average number of patients corresponding to different areas within the concentrated service interval, and select the area with the largest average number of patients as the target area;

[0166] Obtain the average number of patients in the target area, and combine the path length, average movement speed of medical staff, and service start error to obtain the optimal service time for the waiting room.

[0167] Based on the optimal service time, a low-peak service strategy is generated, and the patrol service corresponding to the waiting room is controlled to the path planning mode corresponding to the low-peak service strategy;

[0168] Among them, when the current time is in the off-peak service time interval, it includes:

[0169] When it is detected that a patient needs emergency services, all rounds of medical services in the waiting room corresponding to the patient's area will be used as control targets. Based on the area corresponding to the patient's emergency service needs, service extension control targets and service delay control targets will be determined;

[0170] Based on the preset emergency service time corresponding to the waiting room, the corresponding parameters of the service extension control target and the service delay control target are adjusted respectively, and after the emergency service is completed, the off-peak service strategy is restored;

[0171] The preset emergency service time is less than the optimal service time.

[0172] The working principle of the above technical solution is as follows: the patrol service robot is equipped with a sensor and monitoring module in the waiting room, which can collect the following patient information in real time:

[0173] Exercise status: whether there is strenuous exercise or long periods of inactivity;

[0174] Heart rate: monitor heart rate to see if it is too fast or too slow;

[0175] Blood oxygen saturation: whether it is below the healthy standard (e.g. below 95% may indicate health problems);

[0176] Body temperature: whether it exceeds the normal range (e.g., fever exceeding 37.5°C);

[0177] Behavioral norms: Are there any behaviors that are inconsistent with the requirements of the waiting room (such as leaving the area or affecting others).

[0178] For example, if a patient's smart bracelet uploads real-time data showing his or her body temperature as 38.0°C (exceeding the preset standard of 37.5°C), the medical service robot will immediately mark this status as an increased demand for service.

[0179] The robot compares the patient data with pre-set standards to determine the waiting room's service demand: Normal: When all patient data falls within the pre-set standard, the robot determines that service demand is normal. Increased: If any patient's dynamic data exceeds the standard (such as a rapid heart rate or abnormal body temperature), the robot determines that service demand has increased. Once this determination is made, the robot further determines the patient distribution within each area of the waiting room. For example, if the waiting room is divided into four areas, A, B, C, and D, with 12 patients in Area A, 8 in Area B, 5 in Area C, and 15 in Area D, the robot combines the patient counts in adjacent areas and calculates the patient density for each area: A+B: 20, C+D: 20. Based on the patient density, the robot determines the current patient distribution within the waiting room (e.g., 50% in Area A+B, 50% in Area C+D).

[0180] Based on the patient distribution ratio, the patrol robot adjusts its current route planning. For example, in the initial route planning, the robot patrols each area every 10 minutes by default. In the adjusted route planning, if the patient density in areas C+D is higher and service demand increases, the robot may prioritize areas C+D, adjusting the patrol frequency to every 5 minutes while reducing the frequency of coverage of areas A+B. Through dynamic route planning adjustments, the patrol robot achieves efficient allocation of service resources.

[0181] The robot divides the current time into peak service time or off-peak service time: Peak service time (such as 9:00-11:00 am): The patrol robot maintains or restores the default patrol strategy and covers all areas regularly. Off-peak service time (such as 2:00-4:00 pm): The robot monitors the changes in patient distribution, generates a patient distribution change curve, and determines the concentrated service interval and target area. For example: During the off-peak period, the average number of patients in area D is the largest, and the robot sets it as the target area. Based on the path length (such as area D is 50 meters from the center point), the average moving speed of medical staff (such as 1.5 meters / second), and the service startup error (such as 1 second), the robot calculates the optimal service time to be 35 seconds, generates a off-peak service strategy, and optimizes path planning.

[0182] During off-peak service hours, if a patient in a certain area requires emergency services (e.g., sudden fainting), the robot will immediately adjust its strategy: Overall rounds of service target: Concentrate all rounds of service resources on the patient's area; Emergency service time control: Adjust service extension and delay parameters based on the waiting room's preset emergency service time (e.g., a response must be within 20 seconds); Revert to off-peak service strategy: After the emergency service is completed, the robot automatically reverts to the off-peak service strategy. For example, if a patient suddenly falls in area B, the robot will move to area B as quickly as possible, alert medical staff through voice, and notify other robots to temporarily delay patrols in areas A, C, and D.

[0183] The beneficial effects of this technical solution include: by monitoring patients' movement status and biometrics in real time, the system can quickly identify and respond to service needs, preventing patients from missing timely attention due to health issues or behavioral abnormalities. Precise route planning and optimization reduce waste of medical resources while ensuring more appropriate service coverage and frequency. Dynamic adjustment of service routes and patrol frequency ensures that resource allocation during peak and off-peak hours aligns with patient demand. By calculating the optimal service time for target areas, the robot reduces unnecessary patrol time and improves equipment utilization. When patients require emergency services, the robot can immediately dispatch resources and respond, significantly reducing the likelihood of medical errors. After emergency services are completed, the system automatically reverts to off-peak strategies, ensuring continuous and efficient waiting room management. Prioritizing service in crowded areas ensures that patients experience higher-quality medical care during peak hours. Through precise time planning and route optimization, the patrol robot avoids frequent interruptions to patients waiting for care and improves overall waiting room comfort.

[0184] In another embodiment, based on the patient distribution ratio and hospital management system data, the current path planning of the waiting room rounds service is adjusted to generate a real-time optimization plan, including:

[0185] Based on the patient distribution ratio, determine the relatively concentrated areas and secondary concentrated areas of patients;

[0186] Obtain the length of the first and second rounds of the waiting room's path, and predict the first and second rounds of the waiting room's time based on the average movement speed of the medical staff.

[0187] Obtaining a first growth rate of the number of patients corresponding to the relatively concentrated area, and determining a first service growth amount of the waiting room based on the first growth rate, in combination with the path lengths of each path corresponding to the relatively concentrated area, the first waiting time, and a preset service speed of medical staff corresponding to the current time period;

[0188] According to the first service growth amount, the first round time, the first service time and the service start error of adjacent patients, the first round extension time corresponding to the relatively concentrated area is obtained;

[0189] At the same time, a second growth rate of the number of patients corresponding to the secondary concentrated area is obtained, and a second service growth amount of the waiting room is determined based on the second growth rate, in combination with the path length of each path corresponding to the secondary concentrated area, the second waiting time, and the preset service speed of the medical staff corresponding to the current time period;

[0190] According to the second service growth amount, the second round time, the second service time and the service start error of adjacent patients, the second round extension time corresponding to the secondary concentrated area is obtained;

[0191] The round time corresponding to the current path planning of the waiting room round service is adjusted based on the first round extension time and the second round extension time to generate a real-time optimization plan.

[0192] The working principle of the above technical solution is as follows: In hospital waiting rooms, especially those equipped with high-tech equipment such as PET / CT, route planning and time management for rounds are crucial due to factors such as patient volume, waiting times, and rounds of visits. To improve the efficiency of rounds and patient satisfaction, real-time optimization can be achieved by using patient distribution ratios and data from hospital management systems.

[0193] First, we need to determine which areas of the hospital waiting room have a relatively concentrated number of patients and which areas have relatively fewer patients based on the patient distribution ratio. Specifically, assuming there are two main areas in the waiting room (Area A and Area B), we can use data from the hospital management system to determine the number of patients in each area. For example: Area A: There are 40 waiting patients, and Area B: There are 10 waiting patients. Using this data, we can calculate the relatively concentrated area (Area A) and the less concentrated area (Area B). In this case, Area A is the relatively concentrated area, and Area B is the less concentrated area.

[0194] In the waiting room, the patrol robot needs to patrol various areas along a predetermined path. The patrol time varies depending on the path. We can obtain the patrol path length of each area through the hospital management system. For example, the patrol path length of Area A is 100 meters, and the patrol path length of Area B is 50 meters. At the same time, considering the average movement speed of the patrol robot is 1 meter per second, we can predict the first and second patrol times for each area: first patrol time (Area A): 100 meters ÷ 1 meter per second = 100 seconds, second patrol time (Area B): 50 meters ÷ 1 meter per second = 50 seconds.

[0195] Next, we need to consider the rate of patient growth and adjust the routing accordingly. Suppose the number of patients in Area A has increased by 20% over the past hour, while Area B has increased by 10%. Based on this data, we can calculate the patient growth rate, for example: Area A: 20% / hour, Area B: 10% / hour. Using this growth rate, we can further predict the service growth volume for each area. Service growth volume refers to the increase in the number of patients requiring service within a specific timeframe. For example, in Area A, if one new patient joins every minute, the first service growth volume is the number of new patients multiplied by the service duration.

[0196] Based on the service increase and visit duration for each area, we can further calculate the visit extension time. Assume that the service increase in area A requires an additional 20 seconds, while the service increase in area B requires 10 seconds. The visit service time will then be adjusted accordingly. For example, the first visit in area A will be extended by 20 seconds, while the second visit in area B will be extended by 10 seconds.

[0197] After determining the extended visit time, we can optimize the visit route in real time. The adjusted visit time will take into account the number of patients in different areas, waiting times, growth rate, and extended time. For example: the original first visit time: 100 seconds, extended by 20 seconds, the new first visit time: 120 seconds; the original second visit time: 50 seconds, extended by 10 seconds, the new second visit time: 60 seconds. Through these adjustments, the visit route can be flexibly adjusted according to actual conditions, thereby improving work efficiency and optimizing the patient service experience.

[0198] The beneficial effects of the above technical solution are as follows: by making real-time adjustments based on the patient distribution ratio, growth rate, and path length, the patrol robot can plan routes more efficiently, avoid invalid or repeated patrols, and thus reduce invalid time. By optimizing path planning, it is possible to more accurately predict which areas of patients require more attention, reduce delays in patrol time, effectively control patients' waiting time, and improve patients' medical experience. Through the robot's intelligent patrols, medical staff can reduce unnecessary patrol work, thereby focusing more on links that require manual intervention, improving the work efficiency of the entire waiting room and the quality of medical services. As the number of patients increases or decreases, the system can automatically adjust the patrol route based on real-time data to cope with changes in patient distribution in different situations, thereby improving the flexibility of the system.

[0199] In another embodiment, generating an environment map and a navigation path includes:

[0200] Obtain the robot's current location information, generate a preliminary map of the environment through the SLAM algorithm based on the environment's feature data, and update the real-time location information;

[0201] Based on real-time location information and path planning information, the autonomous navigation module performs path navigation operations;

[0202] In the event that the target path does not match the predetermined path planning information, the navigation path is readjusted and real-time navigation is performed through the autonomous navigation module.

[0203] The working principle of the above technical solution is: when constructing the environmental map and navigation path for the PET / CT waiting room patrol service robot, it is first necessary to generate a preliminary map of the environment based on the robot's current position information and the characteristic data of the surrounding environment, combined with the SLAM (Simultaneous Localization and Mapping) algorithm, and continuously update it during real-time operation.

[0204] The robot's positioning information is obtained by internal sensors. These sensors include laser radar (LiDAR), visual cameras, ultrasonic sensors, and more. The robot uses these sensors to perceive the physical features of its surroundings, such as walls, obstacles, and spatial layout. In the PET / CT waiting room scenario, the robot uses LiDAR to scan the entire waiting area, obtain distance information, and form point cloud data of the environment (i.e., mapping the position of objects in space by measuring the distance between points). This sensor data helps the robot determine its own position and surrounding obstacles.

[0205] The core of the SLAM algorithm is to enable robots to simultaneously localize and map an unknown environment. Through the SLAM algorithm, the robot can gradually build a complete map of the initially unknown environment and update it based on real-time data. During the robot's actual operation, SLAM continuously determines the robot's current position based on sensor data and simultaneously generates or updates a map of the current environment. In a PET / CT waiting room, this map includes the waiting room's seats, corridors, walls, doors, and other facilities. The map is continuously updated as the robot moves to adapt to dynamic changes in the environment.

[0206] Once the robot knows the current environmental map and its own position, it can start path planning. The path planning module will calculate an optimal path based on the target location (such as the area where a patient is located or the equipment). Commonly used path planning algorithms include the A algorithm, the Dijkstra algorithm, etc., which can help the robot find the shortest or safest path from the current location to the target location. Assuming that the target location is a specific area in the PET / CT waiting room, the path planning will take into account factors such as obstacles and channel width to plan a suitable path. As the robot continues to move forward in the environment, the real-time position information will be continuously fed back to the navigation system. The navigation module will adjust the robot's route according to the path planning results and control the robot's movement in real time.

[0207] In actual operation, the robot may encounter some unexpected obstacles or path changes. For example, if a patient suddenly walks into the aisle or other objects are mistakenly placed in the aisle, the robot will find that the actual path is inconsistent with the planned path. At this time, the robot will recalculate the path and adjust its driving route. For example, the robot may automatically bypass the obstacle, choose an alternative path, or re-plan the optimal path to ensure that it can reach the destination on time. Through this real-time path adjustment, the robot can dynamically adapt to changes in the environment and continuously optimize its navigation process to ensure that its medical services in the waiting room are not affected.

[0208] The beneficial effects of the above technical solution are as follows: By introducing the SLAM algorithm, the robot can efficiently and autonomously navigate complex environments such as waiting rooms and generate accurate environmental maps. Real-time updated maps and path planning ensure that the robot always finds the optimal path, thereby reducing patient rounds and improving service efficiency. In environments like PET / CT waiting rooms, where patient wait times are often long, the robot can provide scheduled rounds or provide necessary services to patients (such as inquiring about medical history and providing comfort advice), effectively improving service quality. The robot can obtain real-time information about environmental changes and respond promptly (such as avoiding temporary obstacles and adjusting its route). In the complex and ever-changing waiting room environment, the robot can respond to various emergencies and ensure uninterrupted rounds. This adaptive capability enhances the robot's intelligence, enabling it to provide patients with more personalized and attentive service. Automated rounds can significantly enhance the patient experience. The robot can regularly patrol the waiting room according to a predetermined route, not only providing patients with quick reception and guidance, but also alleviating their anxiety through continuous interaction and improving their satisfaction during the waiting period. Through accurate positioning and navigation, the robot can also avoid collisions or entering restricted areas, potentially causing physical damage or disrupting patients. The robot can autonomously complete medical rounds and tasks, reducing the hospital's reliance on manual rounds. This not only saves labor costs but also reduces the risks associated with negligence that can occur during manual work.

[0209] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A patrol service robot for PET / CT waiting room, characterized in that: include: Sensing and monitoring module, used to monitor the dynamic data of patients and environment in the waiting room in real time; The control system is used to plan the robot path and assign task instructions based on dynamic data; A mobile platform is used to move the robot to a designated location in the waiting room based on path planning; The interactive module is used to provide human-computer interaction functions and guide patients to complete the preparations before the examination; The task execution module is used to execute the robot's active intervention task based on the task instructions; The control system includes: a central control unit, an edge computing module and a communication module; Central control unit, used to support remote control and ensure flexibility of robot operation; Edge computing module, used to analyze dynamic data in real time, connect with the hospital management system, and generate optimized path planning and task allocation solutions; Communication module, used to transmit dynamic data to the hospital management system in real time; Generate optimized path planning and task allocation solutions, including: Compare the current patient dynamic data in the waiting room with the preset standards in the hospital management system; When the patient's motion state or biometric characteristics in the current dynamic data exceed the corresponding preset standards, it is determined that the service demand in the waiting room has increased, the patient distribution in each area of the waiting room is obtained, and the number of patients in adjacent areas is merged to obtain the regional patient density; Compare the patient density in different areas of the waiting room to determine the patient distribution ratio in the waiting room. Based on the patient distribution ratio and data from the hospital management system, adjust the current path planning and generate a real-time optimization plan. Among them, dynamic data include the patient's movement status, heart rate, blood oxygen saturation, body temperature and behavioral norms; When the patient's motion status and biometric characteristics in the current dynamic data are within the preset standard range, it is determined that the service demand in the waiting room is normal; Based on patient distribution and hospital management system data, the current routing plan for waiting room rounds is adjusted to generate a real-time optimization plan, including: Based on the patient distribution ratio, determine the relatively concentrated areas and secondary concentrated areas of patients; Obtain the length of the first and second rounds of the waiting room's path, and predict the first and second rounds of the waiting room's time based on the average movement speed of the medical staff. Obtaining a first growth rate of the number of patients corresponding to the relatively concentrated area, and determining a first service growth amount of the waiting room based on the first growth rate, in combination with the path lengths of each path corresponding to the relatively concentrated area, the first waiting time, and a preset service speed of medical staff corresponding to the current time period; According to the first service growth amount, the first round time, the first service time and the service start error of adjacent patients, the first round extension time corresponding to the relatively concentrated area is obtained; At the same time, a second growth rate of the number of patients corresponding to the secondary concentrated area is obtained, and a second service growth amount of the waiting room is determined based on the second growth rate, in combination with the path length of each path corresponding to the secondary concentrated area, the second waiting time, and the preset service speed of the medical staff corresponding to the current time period; According to the second service growth amount, the second round time, the second service time and the service start error of adjacent patients, the second round extension time corresponding to the secondary concentrated area is obtained; The round time corresponding to the current path planning of the waiting room round service is adjusted based on the first round extension time and the second round extension time to generate a real-time optimization plan.

2. A patrol service robot for PET / CT waiting room according to claim 1, characterized in that: The sensing and monitoring module includes: multimodal sensors and patient status monitoring system; Multimodal sensors are used to collect the movement status and biometric characteristics of patients in the waiting room in real time and generate dynamic data reports; The patient status monitoring submodule is used to identify abnormal patient behavior by analyzing dynamic data reports.

3. The robot for PET / CT waiting room patrol service according to claim 1, characterized in that: The mobile platform includes: a tracked or wheeled mobile chassis, a battery pack, and an autonomous navigation module; Tracked or wheeled mobile chassis, used to provide stable mobile support for the robot; Battery pack, using a power management system to ensure long-term stable operation of the robot; The autonomous navigation module is used to achieve accurate perception and navigation of the waiting room environment based on SLAM technology combined with lidar and visual sensors, and generate environmental maps and navigation paths.

4. The robot for PET / CT waiting room patrol service according to claim 1, characterized in that: The interactive module includes: touch screen, speech recognition and synthesis submodule and multi-language support submodule; Touch screen, used to provide an operation interface to help patients obtain examination-related information; The speech recognition and synthesis submodule is used to communicate through voice, play precautions, guide patients to prepare for the examination, and generate voice interaction records; The multi-language support sub-module is used to intelligently identify patients' language preferences, provide multi-language switching and personalized services.

5. The robot for PET / CT waiting room patrol service according to claim 1, characterized in that: The task execution module includes: a robotic arm, a disinfection nozzle or air purification submodule, and an alarm submodule; A robotic arm to assist with patient mobility and calm agitation, generating patient comfort assessments; Disinfection nozzles or air purification submodules are used to automatically disinfect the area around the patient's seat and generate environmental hygiene status reports; The alarm submodule is used to monitor abnormal situations, provide real-time warnings, and generate safety warning information.

6. The patrol service robot for PET / CT waiting room according to claim 2, characterized in that: Multimodal sensors include: infrared sensors, pressure sensors, and biometric recognition cameras; Infrared sensors are used to accurately locate the patient's movements and posture in the waiting room by detecting changes in the patient's body temperature and heat radiation patterns, and to determine the patient's current state, including stillness, walking, or sitting; Pressure sensors to monitor changes in a patient's weight distribution, sitting or lying posture; Biometric cameras to monitor patients' facial expressions and physiological responses.

7. The patrol service robot for PET / CT waiting room according to claim 3, characterized in that: Generates environment maps and navigation paths, including: Obtain the robot's current location information, generate a preliminary map of the environment through the SLAM algorithm based on the environment's feature data, and update the real-time location information; Based on real-time location information and path planning information, the autonomous navigation module performs path navigation operations; In the event that the target path does not match the predetermined path planning information, the navigation path is readjusted and real-time navigation is performed through the autonomous navigation module.

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