Subject function-based meal care robot selection support system for independent eating

Abstract

A subject function-based meal care robot selection support system for independent eating is disclosed. A meal care robot selection support system according to one embodiment comprises: a memory; and a processor connected to the memory and configured to execute at least one instruction stored in the memory. The processor may store function information of each meal care robot including a function and a use environment of the meal care robot in a database, and recommend a meal care robot supporting independent eating corresponding to a function level of a subject requiring meal care from the function information of each meal care robot stored in the database through evaluation of physical and cognitive function levels of the subject.

Description

User Function-Based Meal Care Robot Selection Support System for Independent Meals

[0001] The following description concerns technology that supports the selection of meal care robots that assist with independent eating based on the functional level of individuals requiring meal care.

[0002] As global aging accelerates, the shortage of care workers is becoming severe, and the need for technological solutions that support independent living is increasing. In particular, meal care plays a crucial role in maintaining the daily independence of individuals. Since physical and cognitive functional levels vary from person to person, a customized approach is required. Through function-based, customized solutions, it is possible to promote the independence and improve the quality of life of these individuals.

[0003] With the rapid advancement of robotics technology, the potential for utilizing robots in the care sector is increasing. In particular, meal assistance robots can serve as a strategy to reduce dependency and enhance the autonomy of recipients.

[0004] However, there is no systematically organized meal care robot system based on the user's capabilities, making it difficult to receive meal-related assistance tailored to one's abilities. Consequently, existing meal care robots offer only a limited range of functions, and there is a lack of a systematic system that allows for the selection of the optimal robot based on the user's specific skill level.

[0005] We can provide a method and system for selecting the optimal meal care robot that supports independent eating through a decision-making process based on the functional level of the subject requiring meal care.

[0006] Customized meal care robots capable of supporting independent meals can be provided according to the functional level of individuals requiring meal care.

[0007] We aim to contribute to increasing the efficiency of care services and improving the quality of life of the subjects by evaluating the physical and cognitive functions of the subjects and recommending the optimal meal care robot.

[0008] A meal care robot selection support system comprises: a memory; and a processor connected to the memory and configured to execute at least one command stored in the memory, wherein the processor stores functional information of each meal care robot, including the function and usage environment of the meal care robot, in a database, and can recommend a meal care robot that supports independent meals corresponding to the functional level of the subject through an evaluation of the physical and cognitive functional levels of the subject requiring meal care, based on the functional information of each meal care robot stored in the database.

[0009] The processor identifies a patient requiring dietary care, evaluates the swallowing function of the identified patient requiring dietary care to determine whether oral intake is possible, identifies the type of diet if oral intake is possible based on the determination, performs an evaluation of the eating and drinking function of the identified type of diet, and if oral intake is not possible based on the determination, follows the instructions of medical staff or selects enteral nutrition or total parenteral nutrition.

[0010] The processor may evaluate arm strength if the result of the eating and drinking function evaluation performed is equal to or greater than a preset score, and may select the use of a special eating tool or a manual arm support if the result of the eating and drinking function evaluation performed is less than a preset score.

[0011] The processor may select to use a fully automatic meal care robot if the result of the evaluated arm strength is below a preset grade, and select to use a partial meal assistance device or a manual / semi-automatic meal care robot depending on the arm strength if the result of the evaluated arm strength is above a preset grade.

[0012] The above processor may instruct the user to stop oral intake and consult a medical professional if phlegm and coughing occur during a meal.

[0013] The above processor includes classifying the functions of the meal care robot into automatic meal care robots, manual meal care robots, and special eating tools and storing them in a database; the automatic meal care robot includes a fully automatic meal care robot and a semi-automatic arm support; the electronic meal care robot includes CareMeal, Bestic, Meal Buddy, Mealtime Partner, My spoon, Obi, and Neater Eater Robotic; the manual meal care robot includes a manual meal care robot and a manual arm support; the manual meal care robot includes Neater Eater; the manual arm support includes a slide-type arm support, a shoulder / elbow support, an armrest support, and a spring arm support; and the special eating tools may include an inclined plate, a plate guard, a thermal plate, a special cup, specially designed tableware, and anti-shake tableware.

[0014] The above processor can utilize the International Standardized Dietary Framework for Dysphagia to classify the characteristics and types of Korean food into multiple stages and store them in a database for the selection of food for independent eating of the subject requiring dietary care.

[0015] The above multiple stages are classified into stages 1 through 8, wherein stage 1 refers to a degree of flow like water and includes water, beverages, clear juices, and teas; stage 2 refers to a level of thickness that flows easily and has a viscosity slightly higher than water and includes clear fresh fruit juice, sungnyung, clear gruel, and clear broth; stage 3 refers to a slightly thick level that flows off a spoon and includes thick fresh fruit juice, gruel / grain beverages, milkshakes, and thin soups; stage 4 refers to a medium-thick level that can be drunk from a cup and includes honey, clear porridge, and thick sauces / soups; stage 5 refers to a very thick level that cannot be drunk from a cup or straw and includes steamed eggs, pudding, thick porridges, and yogurt; stage 6 refers to a level that is chopped or ground and includes porridges; and stage 7 refers to a level that can be chewed softly and requires chewing before swallowing. It includes soft rice, curry or stews, and steamed fish, and the 8th stage refers to a degree where crispy, dry, and chewy textures are all possible, and may include soft and easily digestible regular food.

[0016] The above processor can quantitatively measure the Activities of Daily Living (ADL) and Cognitive Ability of the subject requiring meal care and store them in a database.

[0017] The processor can re-evaluate the suitability of the recommended meal care robot for the subject requiring meal care and change the meal care robot through the re-evaluation.

[0018] The above processor can store strategies for independent eating for subjects requiring meal care in a database, taking into account physical, psychological, social, and cultural factors.

[0019] The above processor can provide the recommended meal care robot and detailed information about the recommended meal care robot.

[0020] The processor can provide a list of recommended meal care robots and guide the user on the detailed functions and usage of the recommended meal care robots to select a meal care robot for independent eating for a subject requiring meal care from the list of recommended meal care robots.

[0021] A method for supporting the selection of a meal care robot performed by a meal care robot selection support system may include: a step of storing functional information of each meal care robot, including the functions and usage environment of the meal care robot, in a database; and a step of recommending a meal care robot that supports independent meals corresponding to the functional level of the subject from the functional information of each meal care robot stored in the database through an evaluation of the physical and cognitive functional levels of the subject requiring meal care.

[0022] In a computer program stored on a computer-readable storage medium to execute a meal care robot selection support method performed by a meal care robot selection support system, the meal care robot selection support method may execute the step of storing functional information of each meal care robot, including the function and usage environment of the meal care robot, in a database; and the step of recommending a meal care robot that supports independent meals corresponding to the functional level of the subject from the functional information of each meal care robot stored in the database through an evaluation of the physical and cognitive functional levels of the subject requiring meal care.

[0023] Provision of customized services for the subject: By selecting a meal care robot optimized for the subject's functional level, the subject's ability to eat independently can be enhanced.

[0024] Improved care efficiency: Selecting a suitable meal care robot can reduce the burden on care providers and improve the quality of care services.

[0025] Increased technology utilization: Maximizes the utilization of meal care robots and can promote the practical adoption of robot technology.

[0026] Improvement of the subject's quality of life: Independent meal support can enhance the subject's autonomy and psychological stability.

[0027] FIG. 1 is a diagram illustrating an example of a network environment in one embodiment.

[0028] FIG. 2 is a diagram illustrating a strategy for independent eating for a person requiring meal care in one embodiment.

[0029] FIG. 3 is a flowchart illustrating a function-based meal care robot algorithm in one embodiment.

[0030] FIG. 4 is a diagram illustrating the operation of storing a meal care robot in one embodiment.

[0031] FIG. 5 is a diagram illustrating the operation of storing the characteristics and types of Korean food in a database using a dysphagia diet standardization system in one embodiment.

[0032] FIG. 6 is a block diagram illustrating a meal care robot selection support system in one embodiment.

[0033] FIG. 7 is a flowchart illustrating a method for supporting the selection of a meal care robot in one embodiment.

[0034] Hereinafter, embodiments will be described in detail with reference to the attached drawings.

[0035]

[0036] In the embodiments, we will describe an operation that systematically supports the selection of a meal care robot that supports independent eating based on the functional level of a person requiring meal care. By evaluating the physical and cognitive functions of a person requiring meal care and recommending the optimal meal care robot, it is possible to increase the efficiency of care services and contribute to improving the quality of life of the person.

[0037] FIG. 1 is a diagram illustrating an example of a network environment in one embodiment.

[0038] The network environment of FIG. 1 illustrates an example including a server (100), an electronic device (110), and a network (130). FIG. 1 is merely an example for explaining the invention, and the number of electronic devices or servers is not limited. Furthermore, the network environment of FIG. 1 illustrates only one example of environments applicable to the embodiments, and the environments applicable to the embodiments are not limited to the network environment of FIG. 1.

[0039] The electronic device (110) may be a fixed terminal or a mobile terminal implemented as a computer device. Examples of the electronic device (110) include a smartphone, a mobile phone, a navigation system, a computer, a laptop, a digital broadcasting terminal, a PDA (Personal Digital Assistants), a PMP (Portable Multimedia Player), a tablet PC, etc. For example, in FIG. 1, the electronic device (110) is described as a smartphone, but in the embodiments, the electronic device (110) may refer to one of various physical computer devices capable of communicating with other electronic devices and / or a server (100) via a network (130) using a wireless or wired communication method.

[0040] The communication method is not limited and may include not only communication methods utilizing communication networks (e.g., mobile communication networks, wired internet, wireless internet, broadcasting networks) that the network (130) may include, but also short-range wireless communication between devices. For example, the network (130) may include any one or more networks such as a PAN (personal area network), LAN (local area network), CAN (campus area network), MAN (metropolitan area network), WAN (wide area network), BBN (broadband network), and the Internet. Additionally, the network (130) may include any one or more network topologies such as a bus network, a star network, a ring network, a mesh network, a star-bus network, a tree or hierarchical network, but is not limited thereto.

[0041] The server (100) may be implemented as a computer device or a plurality of computer devices that communicate with an electronic device (110) and a network (130) to provide commands, code, files, content, services, etc. For example, the server (100) may be a system that provides services (e.g., a meal care robot selection support service, etc.) to a plurality of electronic devices connected through the network (130). In an embodiment, the server (100) may be a meal care robot selection support system.

[0042] The database (120) can store functional information of each meal care robot, including the functions and usage environment of the meal care robot. The database (120) can periodically or non-periodically update functional information of the care recipient and functional information of the meal care robot.

[0043] FIG. 2 is a diagram illustrating a strategy for independent eating for a person requiring meal care in one embodiment.

[0044] The meal care robot selection support system can establish strategies for independent eating for individuals requiring meal care. The system can formulate strategies for independent eating by incorporating physical, psychological, social, and cultural factors. Strategies for independent eating for individuals requiring meal care can be categorized into ensuring meal times, creating a conducive dining environment, promoting social interaction, maintaining proper posture during meals, providing meal assistance, oral hygiene, and considering religious, cultural, and spiritual backgrounds.

[0045] Guaranteeing meal times may include flexibility in meal times, ensuring sufficient time for meals, and appropriate intervals between each meal.

[0046] The creation of a dining environment may include appropriate colors and lighting, temperature and comfort, removal of distractions, adequate space and comfortable furniture, and suitable types of food and tableware. In this case, suitable types of food and tableware may include food consistency, food size, and the chewing and swallowing functions of the individual requiring meal assistance.

[0047] Promoting social interaction may include selecting dining locations based on preference, regularly planned gathering activities, and ensuring sufficient spacing between tables and chairs. In this case, selecting dining locations based on preference may include providing communal dining spaces and guaranteeing private meal times.

[0048] The correct posture during meals may include the posture for eating in a chair or wheelchair, the posture for eating in bed, and the posture after eating. In this case, the posture for eating in a chair or wheelchair may include bending the hips and knees to a 90-degree angle, supporting the lower back with a pillow, and keeping the back straight or slightly forward. The posture for eating in bed may include raising the head of the bed to a 90-degree angle and keeping the head upright or slightly bent forward. The posture after eating may include maintaining a comfortable, upright sitting posture for at least one hour and lowering the head of the bed to 60 degrees or less.

[0049] Meal assistance may include verbal encouragement and instructions, physical support, and staffing during meal times. In this case, physical support may include spoon-feeding and the use of meal aids.

[0050] Oral hygiene may include controlling food texture, controlling meal frequency, regular brushing, and denture care.

[0051] FIG. 3 is a flowchart illustrating a function-based meal care robot algorithm in one embodiment.

[0052] Figure 3 describes the step-by-step process for selecting a meal care robot based on the patient's function for independent eating. The meal care robot selection support system can identify a patient requiring meal care (301). The meal care robot selection support system can evaluate the swallowing function of the identified patient requiring meal care to determine whether oral intake is possible (302, 303). If oral intake is possible based on the determination, the meal care robot selection support system can identify the type of food (305) and perform an evaluation of eating and drinking functions for the identified type of food (306). Eating refers to performing coordination tasks and behaviors such as bringing food to the mouth and eating, cutting or breaking food into pieces, opening bottles or cans, using eating utensils, and eating banquet-style, formal, or regular meals according to culturally acceptable methods. Drinking refers to picking up a beverage and bringing it to the mouth to drink, mixing and shaking a beverage to drink, opening a bottle or can, drinking with a straw, or drinking running water such as from a faucet, depending on culturally accepted methods. These eating and drinking function evaluation criteria can be classified as follows: 0 points indicate no problem, 1 point indicates mild difficulty (bearable), 2 points indicates moderate difficulty (causes disruption to daily life), 3 points indicates severe difficulty (partially disrupts daily life), and 4 points indicates extreme difficulty (completely disrupts daily life). The meal care robot selection support system can determine, through judgment, whether oral intake is impossible, to follow the instructions of medical staff or to select tube feeding or total parenteral nutrition (304). Additionally, the meal care robot selection support system can instruct the user to stop oral intake and consult with medical staff if phlegm and coughing occur during a meal.

[0053] The meal care robot selection support system can evaluate arm strength if the result of the performed eating and drinking function evaluation is higher than a preset score (e.g., 2 to 4 points) (307, 309). Arm strength can be evaluated based on the arm primarily used during eating, and can be classified into Grade 0 (no muscle contraction is observed (complete paralysis)), Grade 1 (arm cannot be moved but muscle contraction is observed), Grade 2 (arm can be dragged on the floor but cannot be lifted), Grade 3 (arm can be lifted on the floor), Grade 4 (lifted arm can withstand pushing by another person to some extent), and Grade 5 (muscle strength is complete). If the result of the performed eating and drinking function evaluation is lower than a preset score, the meal care robot selection support system can select the use of a special eating tool or a manual arm support (308).

[0054] The meal care robot selection support system can select the use of a fully automatic meal care robot if the result of the evaluated arm strength is below a preset grade (e.g., grade 3) (310, 311). If the result of the evaluated arm strength is above a preset grade, the meal care robot selection support system can select the use of a partial meal assistive device or a manual / semi-automatic meal care robot depending on the arm strength (312).

[0055] FIG. 4 is a diagram illustrating the operation of storing a meal care robot in one embodiment.

[0056] The meal care robot selection support system can classify meal care robots and devices into automatic meal care robots, manual meal care robots, and special eating tools, and store them in a database.

[0057] The automatic meal care robot may include a fully automatic meal care robot and a semi-automatic arm support.

[0058] Electronic meal assistance robots may include CareMeal, Bestic, Meal Buddy, Mealtime Partner, My Spoon, Obi, and Neater Eater Robotic. CareMeal, developed by the National Rehabilitation Center and manufactured by NT Robot, was designed to handle rice, soup, and various side dishes including kimchi and vegetables. In particular, it was developed to have two robotic arms to handle rice effectively. One is a spoon-equipped robotic arm that transfers food to the user's mouth, and the other is equipped with a gripper to effectively scoop up rice or side dishes, transferring food to the spoon of the spoon-equipped robotic arm. It can handle Korean cuisine, such as rice and vegetables, better than other systems. Bestic (Rahana Life, UK) consists of a 4-degree-of-freedom robotic arm in a single rotating bowl, and a spoon is used as the eating tool. The movement of the arms can be controlled via any switch the user can press, such as the hands, knees, feet, chin, or shoulders. Bestic offers various control methods that allow users to change how they use a spoon on a plate. Caregivers can set and adjust the distance between the spoon and the mouth. Bestic fits into a compact backpack and has a battery life of approximately 5 hours. Meal Buddy (performance health, USA) is specially designed to enable patients to eat independently. With just the press of a button, users can control when to take a bite and which bowl to use. There are also various options to turn the device on and off at set times. Using the included blue button switch, it can be connected to various types of interface devices depending on the situation. Mealtime Partner (Mealtime Partners LLC, USA) is a battery-operated robotic assistive eating device that helps users eat independently without using their arms or hands.Food is served in three separate bowls. The bowls rotate until the desired food is positioned beneath the spoon. Then, the spoon is dipped into the bowl to scoop up the food and serve it right near the user's lips. The user must lean slightly forward to eat the food on the spoon. This requires a slight movement of the neck or upper body. Depending on functional or cognitive needs, the user can control the robotic eater using two adaptive switches, one adaptive switch, or fully automatic mode (no adaptive switches). Adaptive switches are selected and positioned to suit each user's needs. Let's describe My Spoon (SECOM, Japan). Food is cut into bite-sized pieces and placed on a partitioned tray. The joystick can be controlled by moving the jaw. The user controls the fork or spoon with the joystick. When the first signal sounds, My Spoon operates the fork and spoon together to move between the partitions of the tray and pick up the food. The fork supports the food on the spoon to prevent it from spilling but does not crush it. As the spoon turns toward the user's mouth, it maintains a horizontal position. The spoon stops at a preset position and waits until the user touches it with their mouth. Because the robot arm moves very smoothly and precisely, it can grasp small and delicate foods like rolled omelets or soft foods like tofu. My Spoon can be used for solid foods of a suitable bite size or smaller. Soups and beverages are served in mugs with straws. Obi (DESIN, LLC, USA) allows users to select from four food compartments and decide when to scoop and deliver food to their mouth with just a single touch of a customizable switch. Learning modes can be set, and switch control is customizable. The switch can be controlled using body parts other than the hand.The Neater Eater Robotic (Neater, UK) features a portable design that allows for convenient use in various environments, including restaurants, creating an environment where the whole family can dine together. It offers customizable settings based on personal preferences and provides various control methods, such as a touchscreen and switches. Users can select options like mouth position settings, automatic spoon cleaning, and plate rotation via the touchscreen menu and help guide. It includes fork and snack holder modes, as well as a routine to scrape the plate at the end of a meal. A high-capacity battery allows for extended use without interrupting meals.

[0059] The manual meal care robot may include a manual meal care robot and a manual arm support.

[0060] Manual meal assistance robots may include the Neater Eater. The Neater Eater (Neater, UK) is an innovative meal assistance device designed to enhance the independence of individuals with various disabilities, such as cerebral palsy and multiple sclerosis.

[0061] Passive arm supports may include sliding arm supports, shoulder / elbow supports, arm sling supports, and spring arm supports. Sliding arm supports facilitate easy movement of the arm when transferring it from a plate to the mouth. Using a roof attachment allows the arm to maintain its position on the slide and provides additional control during meals. Shoulder / elbow supports are used for individuals with mild to moderate ataxia, spasms, tremors, or ataxia, and friction bands at four joints help control horizontal abduction and adduction of the shoulder, as well as flexion and extension of the elbow. Arm sling supports are arm slings that support the arm and provide functional assistance and muscle retraining for individuals with shoulder muscle paralysis, cervical spine injury, hemiplegia, multiple sclerosis, or certain forms of rheumatoid arthritis. Spring arm supports are arm supports specifically designed for individuals with limited arm and hand strength or those who can use muscle strength for only a limited amount of time.

[0062] Special dining utensils may include inclined plates, plate guards, thermal plates, special cups, specially designed tableware, and anti-shake tableware. A plate guard is a metal or plastic rim attached to a plate to prevent food from sliding out of the plate. Thermal plates are used for caregivers who take a long time to eat. Special cups may include cups shaped to make drinking easy, cups with lids, cups with straws, cups with cup holders, etc. Specially designed tableware is designed to make it easy to hold, pick up, and cut food, and may include curved spoons, forks, curved knives, rolling knives, etc. Anti-shake tableware may include weight-adjustable tableware and spoons that detect hand tremors and maintain balance.

[0063] FIG. 5 is a diagram illustrating the operation of storing the characteristics and types of Korean food in a database using a dysphagia diet standardization system in one embodiment.

[0064] The meal care robot selection support system can utilize the International Standardized Framework for Dysphagia to classify the characteristics and types of Korean food into multiple stages and store them in a database for the purpose of food selection for independent meals of individuals requiring meal care. In this case, the multiple stages can be divided into stages 1 through 8. Stage 1 refers to a consistency that flows like water and may include water, beverages, clear juices, and teas. Stage 2 refers to a consistency that is thick enough to flow easily and has a viscosity slightly higher than water, and may include clear fresh fruit juice, sungnyung (rice water), clear gruel, and clear broth. Stage 3 refers to a slightly thick consistency that flows off a spoon and may include thick fresh fruit juice, gruel / grain beverages, milkshakes, and thin soups. Stage 4 refers to a medium-thick consistency that can be drunk from a cup and may include honey, clear porridge, and thick sauces / soups. Stage 5 refers to a very thick consistency that cannot be drunk with a cup or straw, and may include steamed eggs, pudding, thick porridge, and yogurt. Stage 6 refers to a chopped or ground consistency and may include porridge. Stage 7 refers to a soft texture that requires chewing before swallowing, and may include soft rice, curry or stew, and steamed fish. Stage 8 refers to a consistency where crispy, dry, and chewy textures are all possible, and may include soft and easily digestible regular food.

[0065] FIG. 6 is a block diagram illustrating a meal care robot selection support system in one embodiment.

[0066] The meal care robot selection support system (600) may include at least one of an interface module (610), a memory (620), or a processor (630). In some embodiments, at least one of the components of the meal care robot selection support system (600) may be omitted, and at least one other component may be added. In some embodiments, at least two of the components of the meal care robot selection support system (600) may be implemented as a single integrated circuit.

[0067] The interface module (610) may provide an interface for the meal care robot selection support system (600). According to one embodiment, the interface module (610) includes a communication module, and the communication module may communicate with an external device. The communication module may establish a communication channel between the meal care robot selection support system (600) and the external device and may communicate with the external device through the communication channel. The communication module may include at least one of a wired communication module or a wireless communication module. The wired communication module may be connected to the external device via a wire and may communicate via a wire. The wireless communication module may include at least one of a short-range communication module or a long-range communication module. The short-range communication module may communicate with the external device using a short-range communication method. The long-range communication module may communicate with the external device using a long-range communication method. Here, the long-range communication module may communicate with the external device via a wireless network. According to another embodiment, the interface module (610) may include at least one of an input module or an output module. The input module can input a signal to be used in at least one component of the meal care robot selection support system (600). The input module may include at least one of an input device configured to allow a user to directly input a signal to the meal care robot selection support system (600), a sensor device configured to detect the surrounding environment and generate a signal, or a camera module configured to capture an image and generate image data. The output module may include at least one of a display module for visually displaying information or an audio module for outputting information as an audio signal.

[0068] The memory (620) can store various data used by at least one component of the meal care robot selection support system (600). For example, the memory (620) may include at least one of volatile memory or non-volatile memory. The data may include at least one program and related input data or output data. The program may be stored in the memory (620) as software containing at least one instruction.

[0069] The processor (630) can control at least one component of the meal care robot selection support system (600) by executing a program in memory (620). Through this, the processor (630) can perform data processing or calculations. At this time, the processor (630) can execute commands stored in memory (620).

[0070] The processor (630) can store functional information of each meal care robot, including the functions and usage environment of the meal care robot, in a database. The processor (630) can recommend a meal care robot that supports independent meals corresponding to the functional level of the subject requiring meal care, based on the functional information of each meal care robot stored in the database, by evaluating the physical and cognitive functional levels of the subject requiring meal care. The processor (630) can recommend an optimal meal care robot by comparing and analyzing the functional level data of the subject requiring meal care with the functional information of the meal care robot.

[0071] For example, we will explain a specific case of support for selecting a meal care robot based on the recipient's function for independent eating according to the recipient's functional level.

[0072] Case 1. A 70-year-old male with hemiplegia due to a stroke

[0073] Health Status: Bedridden due to reduced muscle strength and function on the right side caused by a disability. Swallowing function is good, and oral intake is possible.

[0074] Level of daily activities: Moderate to severe difficulty with independent eating

[0075] Assessment Result: Eating / Drinking Function Assessment: 3 (Severe difficulty, partially interfering with daily life)

[0076] Upper Extremity Strength Assessment: Grade III; able to lift arms against gravity but unable to overcome resistance.

[0077] Recommended Meal Robots: Depending on arm strength, the use of partial meal assistance devices (e.g., spring arm supports) or manual / semi-automatic meal care robots is recommended. Information on selecting the optimal meal care robot considering the subject's functional level is provided, along with descriptions of each robot.

[0078] Case 2. A 35-year-old woman with impaired muscle function due to ALS.

[0079] Health Status: General upper limb muscle strength is weakened due to ALS, and the patient uses a wheelchair with assistance. Frequently complains of fatigue. Swallowing function is good but requires caution.

[0080] Level of daily activities: Primarily confined to bed, and sits or moves to a chair with assistance for rehabilitation therapy.

[0081] Assessment Result: Eating / Drinking Function Assessment: 4 Severe difficulty (completely interfering with daily life)

[0082] Upper Extremity Strength Assessment: Grade II; can drag arms off the floor but cannot lift them.

[0083] Recommendation: Recommendation of fully automatic meal care robots. Provides information on meal care robots tailored to the functional level of the subject through the algorithm of Fig. 2 and a database including the characteristics, functions, and usage environments of various meal care robots of Fig. 3.

[0084] FIG. 7 is a flowchart illustrating a method for supporting the selection of a meal care robot in one embodiment.

[0085] In step (710), the meal care robot selection support system can store functional information of each meal care robot, including its functions and usage environment, in a database. The meal care robot selection support system can store strategies for independent eating for subjects requiring meal care in a database by considering physical, psychological, social, and cultural factors. To facilitate food selection for independent eating for subjects requiring meal care, the meal care robot selection support system can store Korean food characteristics and types classified into multiple stages in a database by utilizing the International Dietary Standards for Dysphagia. The meal care robot selection support system can quantitatively measure the Activities of Daily Living (ADL) and Cognitive Ability of subjects requiring meal care and store them in a database. For example, the subjects' Activities of Daily Living and Cognitive Ability can be evaluated through responses to questions by a caregiver to assess the subjects' ADL and Cognitive Ability. The meal care robot selection support system can link the functional information and food selection information of each meal care robot stored in the database.

[0086] In step (720), the meal care robot selection support system can recommend a meal care robot that supports independent eating corresponding to the functional level of the subject by evaluating the physical and cognitive functional levels of the subject requiring meal care and from the functional information of each meal care robot stored in the database. The meal care robot selection support system can identify the subject requiring meal care, evaluate the swallowing function of the identified subject requiring meal care to determine whether oral intake is possible, and if oral intake is possible based on the determination, identify the type of food, perform an eating and drinking function evaluation of the identified type of food, and if oral intake is not possible based on the determination, follow the instructions of medical staff or select tube nutrition or total parenteral nutrition. If the result of the performed eating and drinking function evaluation is higher than a preset score, the meal care robot selection support system evaluates the muscle strength of the arm, and if the result of the performed eating and drinking function evaluation is lower than a preset score, select the use of a special eating tool or a manual arm support. The meal care robot selection support system allows for the selection of a fully automatic meal care robot if the evaluated arm strength result is below a preset grade, and the selection of a partial meal assistive device or a manual / semi-automatic meal care robot depending on arm strength if the evaluated arm strength result is above the preset grade. The system can also instruct the user to stop oral intake and consult with medical staff if phlegm or coughing occurs during meals. The system not only recommends the optimal meal care robot by comparing and analyzing the subject's functional level data with the robot's functional information, but also re-evaluates the suitability of the recommended robot for subjects requiring meal care and provides a customized solution by changing the robot based on the re-evaluation.

[0087] In step (730), the meal care robot selection support system can provide a recommended meal care robot and detailed information about the recommended meal care robot. The meal care robot selection support system can provide a list of recommended meal care robots and detailed functions and usage methods of the recommended meal care robots to help the recipient who requires meal care select a meal care robot for independent eating from the list of recommended meal care robots. The meal care robot selection support system can provide the recommended meal care robots, as well as the roles, advantages, disadvantages, precautions, drawings, and operation methods performed by the recommended meal care robots. Accordingly, a care environment centered on the recipient can ultimately be established. The meal care robot selection support system can visually provide the selected meal care robot and provide the main features of the recommended meal care robot and the reason for matching.

[0088] According to one embodiment, by systematically supporting the selection of a meal care robot that supports independent eating based on the functional level of the subject, the quality of care services can be improved, and the subject's independence and autonomy can be enhanced.

[0089] According to one embodiment, decision-making can be supported by visually providing evaluation results and recommended meal care robot information through an intuitive interface that is easy for caregivers and recipients to use.

[0090] The device described above may be implemented as a hardware component, a software component, and / or a combination of a hardware component and a software component. For example, the device and components described in the embodiments may be implemented using one or more general-purpose or special-purpose computers, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing unit may execute an operating system (OS) and one or more software applications executed on said operating system. Additionally, the processing unit may access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing unit may be described as being used as a single unit, but those skilled in the art will understand that the processing unit may include a plurality of processing elements and / or a plurality of types of processing elements. For example, the processing unit may include multiple processors or one processor and one controller. Additionally, other processing configurations, such as parallel processors, are also possible.

[0091] Software may include computer programs, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired or instruct the processing unit independently or collectively. Software and / or data may be embodied in any type of machine, component, physical device, virtual equipment, computer storage medium, or device so as to be interpreted by the processing unit or to provide instructions or data to the processing unit. Software may be distributed over networked computer systems and may be stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

[0092] The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., either alone or in combination. The program instructions recorded on the medium may be those specifically designed and configured for the embodiment, or they may be those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc.

[0093] Although the embodiments have been described above with reference to limited examples and drawings, those skilled in the art can make various modifications and variations from the description above. For example, suitable results can be achieved even if the described techniques are performed in a different order than described, and / or the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0094] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims set forth below.

Claims

In the meal care robot selection support system, Memory; and A processor connected to the memory and configured to execute at least one instruction stored in the memory, and The above processor is, Function information of each meal care robot, including its functions and usage environment, is stored in a database, and By evaluating the physical and cognitive functional levels of subjects requiring meal care, recommending a meal care robot that supports independent meals corresponding to the subject's functional level from the functional information of each meal care robot stored in the aforementioned database. A meal care robot selection support system characterized by the following. In paragraph 1, The above processor is, Identify subjects requiring dietary assistance, evaluate the swallowing function of the identified subjects to determine whether oral intake is possible, identify the type of diet if oral intake is possible, perform eating and drinking function evaluations for the identified diet type, and if oral intake is not possible, follow the instructions of the medical staff or select enteral nutrition or total parenteral nutrition. A meal care robot selection support system characterized by the following. In paragraph 2, The above processor is, If the result of the eating and drinking function assessment performed above is equal to or greater than a preset score, arm muscle strength is evaluated, and if the result of the eating and drinking function assessment performed above is less than a preset score, the use of a special eating aid or a manual arm support is selected. A meal care robot selection support system characterized by the following. In paragraph 3, The above processor is, If the result of the arm strength evaluated above is below a preset grade, select the use of a fully automatic meal care robot; if the result of the arm strength evaluated above is above a preset grade, select the use of a partial meal assistance device or a manual / semi-automatic meal care robot according to the arm strength. A meal care robot selection support system characterized by the following. In paragraph 2, The above processor is, If phlegm and coughing occur during meals, stop oral intake and consult a medical professional. A meal care robot selection support system characterized by the following. In paragraph 1, The above processor is, It includes classifying the functions of meal care robots into automatic meal care robots, manual meal care robots, and special meal tools and storing them in a database, and The above automatic meal care robot includes a fully automatic meal care robot and a semi-automatic arm support, and The above electronic meal care robots include CareMeal, Bestic, Meal Buddy, Mealtime Partner, My spoon, Obi, and Neater Eater Robotic. The above manual meal care robot includes a manual meal care robot and a manual arm support, and The above-mentioned manual meal care robot includes a Neater Eater, and The above manual arm support includes a slide-type arm support, a shoulder / elbow support, an armrest support, and a spring arm support. The above-mentioned special dining utensils include inclined plates, plate guards, thermal plates, special cups, specially designed tableware, and anti-shake tableware. A meal care robot selection support system characterized by the following. In paragraph 1, The above processor is, To facilitate independent eating for the aforementioned subjects requiring dietary care, the characteristics and types of Korean food are classified into multiple levels and stored in a database using the International Dietary Standards for Dysphagia. A meal care robot selection support system characterized by the following. In Paragraph 7, The above plurality of steps are divided into steps 1 through 8, and Stage 1 refers to a degree of water-like flow, and includes water, beverages, clear juices, and teas. The second stage refers to a consistency that is thick enough to flow easily, with a viscosity slightly greater than water, and includes clear fresh fruit juice, rice water, clear gruel, and clear broth. Stage 3 refers to a slightly thick consistency that flows easily from a spoon, and includes thick fresh fruit juice, gruel / grain drinks, milkshakes, and thin soups. Stage 4 refers to a medium-thick consistency suitable for drinking from a cup, and includes honey, clear porridge, and thick sauces / soups, Stage 5 refers to a very thick level that cannot be drunk with a cup or straw, and includes steamed eggs, pudding, thick porridge, and yogurt. Stage 6 refers to the degree of mincing or grinding, and includes porridges, Stage 7 refers to a level where chewing is required before swallowing, allowing for soft chewing; this includes soft rice, curry or stews, and steamed fish. Stage 8 refers to a degree where crispy, dry, and chewy textures are all possible, including soft and easily digestible regular foods. A meal care robot selection support system characterized by the following. In paragraph 1, The above processor is, Quantitatively measuring the Activities of Daily Living (ADL) and Cognitive Ability of the aforementioned subjects requiring meal care and storing them in a database A meal care robot selection support system characterized by the following. In paragraph 1, The above processor is, Re-evaluating the suitability of the recommended meal care robot for the subject requiring meal care, and changing the meal care robot through the re-evaluation A meal care robot selection support system characterized by the following. In paragraph 1, The above processor is, Storing strategies for independent eating for the aforementioned subjects requiring meal care in a database, taking into account physical, psychological, social, and cultural factors. A meal care robot selection support system characterized by the following. In paragraph 1, The above processor is, Providing information on the above-recommended meal care robot and details regarding the above-recommended meal care robot A meal care robot selection support system characterized by the following. In Paragraph 12, The above processor is, The list of the recommended meal care robots above, and guidance on the detailed functions and usage of the recommended meal care robots to select a meal care robot for independent eating for a subject requiring meal care from the list of recommended meal care robots above. A meal care robot selection support system characterized by the following. In a method for supporting the selection of a meal care robot performed by a meal care robot selection support system, A step of storing functional information of each meal care robot, including the functions and usage environment of the meal care robot, in a database; and A step of recommending a meal care robot that supports independent meals corresponding to the subject's functional level from the functional information of each meal care robot stored in the database, by evaluating the physical and cognitive functional levels of the subject requiring meal care. A method for supporting the selection of a meal care robot including In a computer program stored on a computer-readable storage medium for executing a meal care robot selection support method performed by a meal care robot selection support system, The above method for supporting the selection of the meal care robot is, A step of storing functional information of each meal care robot, including the functions and usage environment of the meal care robot, in a database; and A step of recommending a meal care robot that supports independent meals corresponding to the subject's functional level from the functional information of each meal care robot stored in the database, by evaluating the physical and cognitive functional levels of the subject requiring meal care. A computer program stored on a computer-readable storage medium that executes.

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