Posture correction and musculoskeletal health management methods

Abstract

There is a lack of technology that utilizes sensor technology capable of detecting and correcting a user's posture in real time to analyze incorrect posture and provide notifications. Therefore, there is a need for multi-purpose posture correction technology applicable in various fields, such as rehabilitation therapy and sports analysis, through such real-time analysis. To this end, a musculoskeletal health management method is presented comprising: a step of collecting data from a sensor pad including an accelerometer that detects the user's movement and tilt, a gyroscope that measures changes in posture, and a pressure sensor that measures pressure applied to a specific part; a normalization step of removing outliers from the information obtained in the step of collecting data; a step of performing an evaluation of posture by comparing the data collected from the sensor pad attached to each part based on sensor position values; and a step of warning the user based on the evaluation of posture or prescribing exercise through the evaluation.

Description

Technology Field

[0001] The present invention relates to a method of attaching a sticker equipped with a sensor to each part of the body to detect whether a posture is causing stress to the spine, and notifying a smartwatch or smart tone if the posture is misaligned. Background Technology

[0002] Spinal and joint diseases are rapidly increasing among modern people due to sedentary lifestyles, poor posture, and excessive use of smart devices. Most existing posture correction devices have limitations, such as being uncomfortable to wear or unable to correct posture in real time.

[0003] As the number of people sitting for long periods or using electronic devices increases, musculoskeletal disorders such as back pain, forward head posture, and herniated discs related to poor posture are emerging as major health problems. Accordingly, various advanced technologies focused on prevention and management are being developed. However, despite the growth of the wearable healthcare market, the technology for real-time posture correction devices integrated with smartphones and smartwatches remains in the early stages.

[0004] As a technology related to wearable devices, smart posture correctors are wearable devices attached to the back, waist, or neck that monitor posture in real time and provide feedback to the user through vibrations or notifications if an incorrect posture is maintained; these devices utilize accelerometers, gyroscopes, and pressure sensors to measure the user's spinal angle and movement.

[0005] Smart clothing equipped with built-in posture correction sensors provides a comfortable fit while continuously collecting posture data; it is utilized for sports and rehabilitation therapy and helps prevent musculoskeletal injuries during exercise.

[0006] Recently, artificial intelligence data analysis technology is being applied to analyze data collected from the aforementioned devices. For personalized posture correction, AI algorithms analyze user data—such as body structure, lifestyle habits, and musculoskeletal conditions—to provide personalized posture correction solutions. This involves learning incorrect posture patterns based on past data and recommending correction methods suitable for the user. Furthermore, deep learning models analyze the user's daily data to predict the likelihood of musculoskeletal disorders, enabling the user to take preventive measures before the disease develops. This is integrated into a health management platform and links with other health management devices, such as smartwatches and fitness trackers, to manage other health data including heart rate, activity levels, and calorie expenditure.

[0007] Recently, as a technology supporting VR and AR-based rehabilitation therapy, posture correction and rehabilitation training are being provided in a more immersive way. This involves visually displaying the correct posture to the user in real time, providing feedback, and motivating the user by converting posture correction and musculoskeletal health management into a game format where points increase when the correct posture is maintained. Additionally, research is being discussed on rehabilitation robots that help patients with musculoskeletal disorders recover spinal and joint mobility, smart chairs or desks that automatically adjust to help users maintain the correct posture for extended periods, technologies that design customized corrective devices by precisely measuring the user's body structure through 3D scanning, and telemedicine technologies that analyze the user's posture data in real time to allow physical therapists or doctors to provide correction guidelines remotely. The problem to be solved

[0008] Due to changes in modern lifestyles and advancements in digital technology, posture correction and musculoskeletal health management technologies are rapidly evolving. However, there is a lack of technology that utilizes sensor technology to detect and correct user posture in real time, analyzing incorrect postures and providing notifications. Therefore, there is a need for multi-purpose posture correction technology applicable in various fields, such as rehabilitation and sports analysis, based on such real-time analysis.

[0009] The problems solved by the present invention are not limited to those mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the description below. means of solving the problem

[0010] According to an embodiment of the present invention as a means to solve the aforementioned technical problem, the method comprises: a step of collecting data from a sensor pad including an accelerometer that detects the movement and tilt of a user, a gyroscope that measures changes in posture, and a pressure sensor that measures pressure applied to a specific part; a normalization step of removing outliers from the information obtained in the step of collecting data; a step of performing an evaluation of posture by comparing the data collected from the sensor pad attached to each part based on sensor position values; and a step of warning the user or prescribing exercise through the evaluation based on the evaluation of posture.

[0011] After the step of performing an evaluation of the above posture, it further includes a step of evaluating whether there is a disease in the spine based on the data.

[0012] The sensor pad is characterized by transmitting data using one of the wireless communication technologies among Bluetooth, Wi-Fi, or LoRa, and the sensor pad is attached to the user's body and is characterized by being attached to the apex, acromion, hip joint, knee joint, and ankle joint.

[0013] The exercise prescription step described above is characterized by collecting user data to provide an exercise prescription, analyzing the collected data through machine learning, and then presenting a customized exercise prescription to the user.

[0014] In the step of determining the presence of the disease mentioned above, the collected data is transmitted to a physical therapist or doctor's terminal to determine the presence of the disease. Effects of the invention

[0015] According to the present invention, the approach is expanding beyond simple disease treatment to a preventive approach. A program connected to a wearable device continuously provides feedback to the user and supports the formation of correct posture habits.

[0016] Data collected from sensors is transmitted to smartphones, tablets, or cloud servers via wireless communication technologies such as Bluetooth, Wi-Fi, or LoRa. This data transmission occurs in real time, allowing users to check their posture information through an app or web interface. The system provides analyzed data to aid in posture correction and offers real-time feedback via vibration, audible alerts, or a smartphone app when an incorrect posture is maintained. For example, if a user is hunched over, the device can detect this and send a notification to maintain the correct posture. Consequently, it provides a customized correction plan that takes into account the user's body type, lifestyle habits, and health status. Brief explanation of the drawing

[0017] FIG. 1 is a figure showing the attachment location of the sensor pad according to the present invention. FIG. 2 is a spinal posture management method according to the present invention. Specific details for implementing the invention

[0018] Further objects, features, and advantages of the present invention can be more clearly understood from the following detailed description and the accompanying drawings.

[0019] Before providing a detailed description of the present invention, it should be understood that the present invention is capable of various modifications and may have various embodiments, and that the examples described below and illustrated in the drawings are not intended to limit the present invention to specific embodiments, but rather include all modifications, equivalents, and substitutions that fall within the spirit and scope of the present invention.

[0020] IoT (Internet of Things) technology related to spinal posture correction is a technology developed to support modern health management, consisting of devices and systems that monitor a user's spinal posture in real time and help correct incorrect posture.

[0021] Sensors and wearable devices are the core of spinal posture correction IoT technology. These are typically worn or attached to the user's back, and the sensors utilized include accelerometers that detect user movement and tilt, gyroscopes that measure spinal angles and changes in posture, and pressure sensors that identify changes in posture by checking pressure applied to specific areas.

[0022] Regarding data collection and transmission technology, data collected from sensors is transmitted to smartphones, tablets, or cloud servers via wireless communication technologies such as Bluetooth, Wi-Fi, or LoRa. This data transmission takes place in real time, allowing users to check their posture information through an app or web interface.

[0023] Technologies applied to artificial intelligence and data analysis evaluate a user's posture by analyzing collected data. Technologies are being presented in which AI algorithms perform tasks such as determining whether a user's posture is correct, learning patterns of incorrect posture to suggest directions for improvement, or generating predictive models based on the user's daily activity data.

[0024] Real-time feedback and correction notifications allow the system to provide real-time feedback via vibration, audible alerts, or a smartphone app when a user maintains an incorrect posture. For example, if a user is hunched over, the device detects this and sends a notification to maintain the correct posture. Recently, personalized IoT technology has been providing customized correction plans that take into account the user's body type, lifestyle, and health status; this feature is particularly useful for office workers and students who sit for long periods, or for patients with spinal disorders. Furthermore, this technology integrates with other health management devices and systems to function as a health management platform. For instance, it can link with smartwatches or fitness trackers to monitor overall health status, or connect with physical therapists or doctors to share the user's posture data and provide professional feedback.

[0025] Hereinafter, specific technical details to be implemented in the present invention will be described in detail with reference to the attached drawings.

[0026] FIG. 1 shows the area where the sensor pad is attached according to the present invention. The mastoid process refers to a part of the temporal bone that extends downward in a mastoid shape at the bottom of the back of the earlobe, and the acromion refers to the acromion, which is the highest part of the shoulder and is the joint where the pelvis and femur on the right and left sides of the hip joint are connected. Sensor pads are attached to the knee joint and ankle joint areas. The sensor pad has a built-in high-sensitivity sensor, allowing posture data to be collected using sensor values. Here, each sensor transmits and receives position values ​​to each other to obtain more accurate data.

[0027] In designing the sensor pad, a high-sensitivity sensor is embedded within it, responsible for collecting posture data and converting it into a digital signal. The exterior of the pad is covered with a waterproof cover to prevent damage from water or sweat and to safely protect the internal sensor, while the adhesive is composed of a hypoallergenic material that minimizes skin irritation, preventing skin damage even during prolonged attachment. Additionally, the pad can be designed to possess both flexibility and durability to accurately detect joint movements.

[0028] During the process of collecting and processing data from the sensor pad, the sensor detects the user's joint movements and changes in posture in real time and transmits this to a smart device via a wireless communication module. The collected data is then processed by an algorithm that analyzes abnormal changes in posture. Based on factors such as joint angles and movement patterns, the algorithm identifies incorrect posture and provides feedback to correct it.

[0029] FIG. 2 illustrates a method for managing posture correction and musculoskeletal health by attaching sensor pads according to the present invention. Sensor pads are attached to the previously mentioned acromion, acromion, hip joint, knee joint, and ankle joint, respectively. Here, sensor pads can be attached to both the left and right sides, in which case up to 10 pads are attached. Data collected from these attached sensors undergoes a normalization process. Normalization is a process of converting data values ​​of various sizes and ranges into a fixed range to improve the efficiency of analysis, learning, and processing. When values ​​obtained from various sensors or data sources have different ranges, normalization adjusts the values ​​to the same range to prevent the model from being biased toward specific values. Furthermore, numerical stability can be provided through filtering to remove data with overflow or underflow, as well as missing values ​​or outliers in sensor data or measurement data. By comparing the position values ​​that have undergone normalization, angles can be evaluated, and the necessity of posture correction or the level of disease can be determined accordingly. By accumulating this data, it is possible to build personalized data for each individual, thereby enabling the provision of information regarding customized exercise prescriptions or posture adjustments.

[0030] Smartphone or smartwatch apps provide an intuitive interface that allows users to check posture data in real time and learn correction methods. The apps offer data customized for each user and support various functions, such as setting posture correction goals, adjusting alert frequency, and reviewing historical data. Additionally, data is stored on a cloud server to analyze long-term trends in posture changes.

[0031] In analyzing the data, the collected data is used to compare the user's body type with general posture standards to distinguish between normal and abnormal postures; if an abnormal posture persists, the user is warned via vibration or notification on a smartphone or smartwatch, and user data learns over time to establish personalized, optimized correction standards.

[0032] To measure spinal posture, sensors detect changes in spinal curvature in real time based on angle and curvature data between joints, including the major neck, thoracic, and lumbar vertebrae. Through this, they determine the correct alignment as well as abnormal bending and twisting states, and the measurement data visually represents changes in spinal posture over time, warning the user of stress caused by persistent poor posture.

[0033] As data accumulates, measurement data can be analyzed using machine learning; this analysis is carried out through systematic steps ranging from data preprocessing and model training to result interpretation and distribution.

[0034] Real-time data collected from sensor pads undergoes a preprocessing stage, which involves handling missing values, detecting and filtering outliers, and performing data scaling, normalization, and transformation. Subsequently, the measurement data is partitioned for use in training and evaluation, and a machine learning model is selected. Generally, continuous data is analyzed using regression models such as linear regression, decision trees, random forests, XGBoost, and deep learning (ANN). The model is trained using the training data, evaluated to determine if the model applied to machine learning is appropriate, and the results are interpreted.

[0035] When using such machine learning, the results of analyzing measurement data vary depending on various factors, such as data quality, model selection, and performance evaluation. By utilizing measurement data through proper data preprocessing and model design, it is possible to discover complex patterns and enhance predictive capabilities. Explanation of the symbols

[0036] 110: Mastoid process region 120: Peak area 130: Hip joint area 140: Knee joint area 150: Ankle joint area

Claims

Claim 1 A method for posture correction and musculoskeletal health management comprising: a step of collecting data from a sensor pad including an accelerometer that detects a user's movement and tilt, a gyroscope that measures changes in posture, and a pressure sensor that measures pressure applied to a specific part; a normalization step of removing outliers from information obtained in the step of collecting data; a step of performing an evaluation of posture by comparing the data collected from the sensor pads attached to each part based on sensor position values; and a step of warning the user based on the evaluation of posture or prescribing exercise through the evaluation. Claim 2 A musculoskeletal health management method using a sensor pad according to claim 1, further comprising the step of evaluating the presence of spinal disease based on data after the step of performing an evaluation of the posture. Claim 3 A method for managing musculoskeletal health using a sensor pad according to claim 1, wherein the sensor pad transmits data using one of the wireless communication technologies of Bluetooth, Wi-Fi, or LoRa. Claim 4 A method for managing musculoskeletal health using a sensor pad according to claim 1, characterized in that the sensor pad is attached to the user's body and is attached to the apex, acromion, hip joint, knee joint, and ankle joint. Claim 5 A musculoskeletal health management method using a sensor pad according to claim 1, characterized in that, in the step of performing the exercise prescription, user data is collected to perform the exercise prescription, the collected data is analyzed through machine learning, and a customized exercise prescription is presented to the user. Claim 6 In paragraph 2, a musculoskeletal health management method using a sensor pad, characterized in that, in the step of determining the presence of disease, the collected data is transmitted to a physical therapist or doctor's terminal to determine the presence of disease.

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