RFID EMBEDDED SMART BED THAT CAN TRACK HEALTH, POSTURE, AND SLEEP.

Abstract

The invention is a smart bed system that can monitor body posture, movements, pressure distribution, temperature changes, and general health indicators during rest and sleep via sensors. RFID sensors and biometric sensors (optional) embedded in the bed measure sleeping positions, movement frequency, heart rate, breathing patterns, temperature changes, and pressure points. The collected data is analyzed using machine learning algorithms to provide detailed information about health status.

Description

RFID EMBEDDED SMART BED THAT CAN TRACK HEALTH, POSTURE, AND SLEEP. TECHNICAL FIELD The invention analyzes body posture, movements, and pressure during rest and sleep. distribution, temperature changes and general health indicators via sensors It is a smart bed system that can track. RFID sensors and biometric data are embedded in the bed. Sensors (optional) monitor sleep positions, movement frequency, heart rate, and respiration. By measuring the pattern, temperature variations, and pressure points, the collected data is used by the machine. Detailed information about health status is obtained by analyzing it with learning algorithms. It provides. PREVIOUS TECHNIQUE Current sleep tracking systems are generally based solely on motion sensors. It works by detecting changes in the user's position while sleeping. However, these systems focus on body temperature, heart rhythm, respiratory pattern, or It is unable to measure comprehensive biophysical parameters such as pressure distribution. Therefore The data obtained only provides a limited sleep analysis and does not offer insight into the user's overall health. It does not allow for meaningful inferences to be made about the situation. Especially for the detection of conditions such as sleep apnea, circulatory disorders, or night sweats. More multi-dimensional and integrated sensor data is needed. This deficiency, There are serious obstacles to conducting continuous and in-depth analysis in the health monitoring of individuals. It constitutes an obstacle. The patient beds currently used in hospitals are generally only basic. They are mechanical structures capable of adjusting position, and are sensor-supported and data-driven. Their ability to provide health monitoring is quite limited. Some advanced models have weight or... Although these systems also have in-bed pressure sensors, they do not continuously provide dynamic health data. It lacks integrated AI-powered systems that can monitor and analyze. This The situation is particularly lacking in long-term health monitoring of hospitalized patients, according to nurses. or it increases the need for manual observations by healthcare personnel and early This limits the possibilities for intervention. It is directly related to the sleep quality of individuals. Many parameters are ignored in these systems. 1 Sleep tracking carried out using methods such as cameras and microphones constitutes a privacy violation. This carries serious risks in terms of user experience. Such solutions require users to constantly... This constitutes a violation of privacy because it involves their being viewed or their voices being recorded. and raises serious questions regarding data security. Furthermore, these methods... Poor image quality in dark environments, microphone affected by ambient noise. They also face technical challenges, such as those encountered at home or outside of a hospital. In applications, users do not prefer these methods; they work more secretly and passively. Sensor-based systems are needed. THE PURPOSE OF THE INVENTION The invention aims to improve rest and sleep quality, monitor health, and provide care for the elderly and sick. facilitating, providing comfort for disabled individuals and ensuring the safety of newborns It includes objectives of increasing... These objectives include: - Sleep disorders such as sleep apnea, insomnia, restless legs syndrome, etc. early diagnosis - Health monitoring through data such as heart rate, respiration, movement analysis, and blood circulation. - Sleep position monitoring, respiratory analysis, tracking of sudden movements in newborns. security, - Posture and spine support with ergonomic fit and automatic support mechanisms. protecting health - Supporting blood circulation through temperature variations in specific regions, - Caused by inactivity in individuals who spend a long time in bed It has technical effects such as increasing comfort by preventing problems. Another technical impact of our invention is that the RFID readers and sensors it contains allow humans to interact with it. enabling them to work in a safe environment that will not threaten their health, It offers a structure based on the principles of electromagnetic isolation and signal accuracy. In this context, RFID components and sensors are positioned within a conductive cage. This prevents signal leakage to the external environment and also protects users from electromagnetic interference. Direct contact with the waves is prevented. Based on the Faraday cage principle. Thanks to this design, external electromagnetic interferences are protected from the system. Data reliability is increased by eliminating its negative effects. Furthermore... Signals from the sensors are transmitted via a special non-conductive top surface using RFID. 2 The signal is directed to the reader, thereby minimizing signal loss and improving the system's performance. Accuracy is maximized. DETAILED DESCRIPTION OF THE INVENTION The patient bed system described in the invention aims to increase patient comfort and improve health monitoring. Integrated sensor network and intelligent control to ensure uninterrupted operation. It is equipped with modules. The system allows the user to both rest or treat during the treatment process. by analyzing both their physical movements and basic biometric indicators, It offers personalized health management. This structure is particularly suitable for long-term hospitalization. It provides continuous monitoring opportunities for patients who require it and for healthcare personnel. It supports the intervention process. RFID sensors were used in the invention. RFID (Radio Frequency) (Identification) The sensor, thanks to its integrated circuit and antenna, detects information from a reader. Passive RFID is an electronic tag that can detect and respond to incoming radio waves. The sensors do not have their own power sources; they get their energy solely from RFID. It operates by receiving the electromagnetic field from the reader. The transmitted signal is received by the antenna in the sensor, and this energy is transmitted inside the sensor. by activating the circuit, it transmits the sensor's identity or environmental information back. RFID sensors operating in the UHF (Ultra High Frequency) band provide low-frequency solutions. It can exchange data over long distances using energy. On the bed surface The installed RFID sensor network tracks the user's sleeping position and movements. It detects and thus tracks the frequency of a person's position changes throughout the day. These RFID sensors are located on the surface of the bed and are passive. It is based on UHF RFID technology. The sensors detect the user's body pressure. They are strategically located in areas where they can be applied. When the patient lies down in bed... or when changing position, the pressure exerted by body weight on different points Due to this, the activity status of certain RFID sensors changes. This change is related to RFID. The reader detects the active / passive status of each sensor, and the sensor amplitude is also detected. And phase information, along with a timestamp, is recorded. Thus, the user When and how often did they change positions during the day, and in which areas did they exert their weight? data such as concentrated areas and regions that have remained inactive for a long time are systematically organized. These sensors collect information while the patient is bedridden. Early detection of complications that may arise from immobility becomes possible. This is happening. Position data from RFID sensors are continuously analyzed on a time-based basis. 3 This is done when certain sensors are found to remain in the same state for an extended period of time. The system classifies this data as risky immobility. This allows, in particular, pressure... wounds (decubitus ulcers), circulatory disorders, and musculoskeletal weaknesses, etc. Complications can be identified before they even occur. Microcontroller The machine learning algorithms included analyze past data patterns. learning user-specific immobility thresholds and early detection in unusual situations It generates warnings. This way, both caregivers are informed and... User-specific preventive position adjustments are made by the system. It can be automated. In addition to the comfort layer of the bed, it takes into account human posture and A sensor layer was created to enable precise detection of their movements. It is supported by a specially designed conductive textile layer. This special conductive layer is RF. from a textile material that will block and trap the signals It is manufactured with a conductive textile layer placed at a specific distance from the sensor layer. It consists of two layers with a soft, insulating intermediate layer between them. Thanks to this arrangement, the electronic components in the sensor layer are connected to the conductive layer. It does not make any physical contact, thus preventing unwanted electrical interactions. This prevents the transmission of RFID signals through the conductive layer inside the mattress. Signal loss is minimized by limiting it, and signal reading performance is improved. is enhanced. In addition, thanks to the Faraday effect, the user's electromagnetic field is amplified. It provides effective protection from radiation. The conductive textile cover is larger than the bed. It is designed in dimensions that, when placed on the bed, depend on the user's posture. As a result, the conductive surface of the coating will approach the sensor layer. During this approach... User posture and movements are determined through changes in information occurring in the sensor. It is detected with high precision. This sensor is designed to be removable. layer and integrated conductive textile layer, for different beds or as needed. It can be easily adapted to similar furniture, offering flexibility and functionality in use. is being enhanced. Signals from RFID sensors are transmitted to devices positioned under the bed. Detected by the RFID reader module and prioritized as an RFID signal. The components are assembled in an intermediate hardware unit called the Collection Unit. This unit collects data from the sensors. Converting the incoming signals into digital format and the activity status of each RFID sensor. It associates time information with this. This process requires a fact from the system. A real-time clock (RTC) module is used, and all data is displayed as date and time. It is processed along with its stamp. This sensor data, labeled with time information, The data is transferred directly to an integrated module called the Data Recording and Management Unit. This unit, 4 It consists of a microprocessor and a data storage unit, and RFID sensors. Analyzing incoming data at regular intervals, position changes and stagnation their periods systematically stored in a permanent memory (e.g., embedded SD card, flash memory) (or an external data server) records the data. This recording process allows the user to access and record the data. Daily movement profile, sensor activity map, and position times retrospectively. This can be examined using a Machine Learning Software Module included in the invention. These data are collected at regular intervals, and sleep positions and inactivity thresholds are measured. It performs analyses on the system. The software detects abnormalities based on the system's training data. to identify situations and provide early warnings to the user or healthcare professional when needed. It can send warnings. Biosensor structures integrated into the bed system monitor the user's heartbeat, Continuously monitoring basic health indicators such as respiratory pattern and body temperature These sensors are designed for the purpose of direct contact with the bed surface layer. It is located underneath and can operate without requiring physical contact with the user. It is structured in such a way that each sensor group precisely captures a specific biometric data. It measures in this way and converts the obtained data into digital signals, creating a central data center. It transmits it to the collection unit. Heart rate is measured by piezoelectric-based vibration sensors used in the system. It is perceived through this. When the user is in a supine or side-lying position, the body Microscopic vibrations emanating from its surface are detected by these sensors, The vibrations are interpreted as pulse signals and the number of pulses per minute is calculated. The sensors are being transformed using algorithms that filter out environmental noise. This is supported, thus enabling the identification of vibrations of cardiac origin only. is provided. The respiratory pattern is monitored using the same piezoelectric sensors or flexible piezoresistive sensors. It is detected by low-frequency signal variations obtained from the films. Breath resulting from the rising and falling of the chest and abdominal area during shopping Pressure changes create stress on the sensor surface, and these changes transmit the signal. This allows both respiratory rate and regularity (apnea, Conditions such as hypopnea can be analyzed. Body temperature is measured using a contactless IR (infrared) sensor placed on the inner surface of the mattress. Temperature is measured via temperature sensors or NTC / PTC thermistors. These sensors, It detects heat radiating from the skin surface without direct contact with the user. and calculates average body temperature. Data from all these sensors is collected as analog signals. and the signal is transmitted to the RFID Signal Acquisition Unit integrated into the sensors. This unit, As mentioned earlier, the signals from the sensors are converted into digital format. converting and analyzing the time information along with the activity status of each RFID sensor. It provides a continuous link between the user's real-time health status. It is being monitored in some way, and the system is continuously evaluated through analysis software. These measures are implemented and interventions such as early warning or automatic bed adjustment are made if necessary. It is triggered. Another feature of the invention is the automatic bed adjustment mechanism, which allows the user based on data such as body position, weight distribution, and immobility status Multi-zone system capable of making height and tilt changes in specific areas of the bed. It consists of a movable structure. This mechanism is integrated into the bed frame using a low-profile design. It operates using noisy electric linear actuators or servo motors. Each The motor is positioned to correspond to a specific area of ​​the bed, and It precisely performs the required regional height adjustment. The motors operate within a defined range of motion (e.g., 0–15 cm), and each is separate. They can be controlled separately. The main set of sensors that provide data to this mechanism is RFID-based positioning. It consists of sensing sensors and pressure sensors integrated into the bed. RFID sensors track the user's position and movement on the bed. In addition, piezoresistive pressure sensors determine the position of body weight on the mattress. It numerically measures which areas the concentration is high in. This allows both the user... Which region is under the most pressure, and for how long? Information such as the person remaining motionless in that position is obtained. Data from the sensors is first transmitted to the Signal Acquisition Unit. This As mentioned earlier, the unit converts the signals from the sensors into a digital format. converting and analyzing the time information along with the activity status of each RFID sensor. It correlates them. Subsequently, the data is transmitted to a microcontroller located within the bed system. The data is collected and processed by the unit. This microcontroller is typically an ARM. It is a Cortex-based, low-power processor that processes RFID signals and pressure signals. multiple such as analog data from sensors and, if necessary, biometric sensor outputs It can evaluate data sources simultaneously. The microcontroller, It analyzes position data and determines that the user has remained in the same position for a long time. 6 detecting that excessive pressure is being applied to a specific area or that the body's balance is disrupted When this happens, it triggers the corresponding motor, repositioning the relevant section of the bed. During this process, the microcontroller uses predefined threshold values ​​and user-specific settings. It operates according to a comfort profile; for example, the pressure applied to the hip area is specific. If the pressure has been high for some time, this area will be automatically increased by a certain amount. is balanced. Similarly, respiratory support or balance can be achieved by changing the upper body tilt. The appropriate position for blood circulation can be provided. All these procedures are quiet and controlled. and is carried out continuously, every movement of the system is reproduced with sensor data. It is optimized through monitoring. Another feature of the invention is its modulus of temperature change, which varies in specific regions. It supports blood circulation by providing localized heating. This module, in particular... Patients who remain immobile may experience problems such as a feeling of coldness and impaired circulation. It contributes to prevention. Heating elements are made of flexible and safe materials. It is integrated and temperature-sensitively controlled. Bed The temperature change module integrated into the system continuously monitors the user's body temperature. a smart building that automatically provides heating in the areas where it is needed by monitoring This module has local anomalies, particularly seen in users who remain inactive for extended periods. to prevent cooling, slowed blood circulation and related discomforts It was developed for this purpose. The main objective of the system is to increase user comfort and improve circulation. The aim is to create a supportive effect on the system. In this context, body temperature, Non-contact IR (infrared) placed just below the upper contact surface of the bed Measurements are taken via sensors or NTC / PTC thermistors. IR sensors, It detects the heat radiating from the user's skin and provides temperature data non-contactly. They produce thermistors, which precisely measure the ambient temperature in the area where they are located. These sensors measure temperature data that is updated in seconds using analog signals. It produces signals, and this data is collected by the Signal Acquisition unit located within the bed. It is transmitted to the unit. This unit, as mentioned earlier, receives information from the sensors. converting the signals into digital format and the activity status of each RFID sensor They associate time information together. Then the microcontroller, this analog It continuously evaluates the data. The processed data is based on a predetermined temperature. It is compared with a threshold; for example, the minimum comfort temperature that needs to be heated is 30 °C. If this is determined, and the temperature measured by the sensor is below this value, then the system... It detects the heating need. At this point, the microcontroller determines the heating requirement in the relevant area. The elements are activated and temperature adjustment is initiated in this module. 7 Heating is provided via flexible carbon fiber heaters or low-voltage resistance strips. These elements are provided inside the bed, without direct contact with the user. integrated into its layers and electrically insulated for safety reasons They are positioned in such a way that heating elements are only located where they are needed. It is activated in a controlled manner, thus preventing unnecessary energy consumption. The microcontroller continuously monitors the heating time and temperature increase with an accuracy of ±1 °C. It performs temperature control. When the relevant area reaches the target temperature, the system It automatically switches off the heating element, thus ensuring both safety and... Comfort is maintained. The entire process is enclosed with real-time temperature feedback. It operates on a feedback principle, and the system uses the user's body data when needed. By analyzing the temperature profile, we can learn about regional heating trends and It can create personalized comfort settings. Thus, the temperature change module It functions not only as a reactive but also as a proactive health support tool. He sees. Machine learning software analyzes data from RFID sensors and biosensors. By analyzing the data, the patient's sleep patterns, movement habits, and health indicators can be determined. It produces comprehensive results on Gaussian Process Regression and Linear. Data analysis performed using algorithms such as regression analysis is patient-specific. It produces detailed reports. The software has the ability to learn from historical data. This allows us to identify trends and make comparisons with real-time data. It can foresee potentially risky situations. This system is limited to traditional machine learning algorithms only. not only that, but it also includes advanced technologies such as deep learning, pattern recognition, and natural language processing. It also uses advanced artificial intelligence approaches, particularly neural networks. Meaningful patterns are extracted from complex biological data with the help of (networks), Potential health risks can be identified in advance using anomaly detection algorithms. This can be determined through time series analysis and predictive modeling. (by modeling) techniques, scenarios regarding the patient's future health status can be created. This can be done, which increases the effectiveness of preventive health services. In addition, by integrating with Big Data technologies, it becomes even more... Large datasets and information from different sources can also be processed. Cloud-based. By using data storage solutions and real-time analytics infrastructure, the system is large. efficiently managing data volumes and thus data mining With these techniques, the behavioral and physiological patterns of patients can be examined in more detail. 8 can be examined. The microcontroller uses at least one of these technologies. It includes. 9

Claims

1. This is an RFID-embedded smart bed that can track health, posture, and sleep; its features include: - consisting of passive UHF RFID sensors placed on the bed surface; position to detect the user's body position and movements sensors, infrared (IR) sensors to monitor body temperature, NTC / PTC thermistors use piezoelectric technology to measure heart rate. sensors, piezoresistive film to monitor respiratory patterns a sensor network consisting of sensors, - collects signals from these sensors and determines whether each sensor is active or inactive. a system that correlates the state of a sensor with amplitude and phase information, and time information. RFID signal acquisition unit, - analyzes and sustains the data coming from the signal acquisition unit in question. a device that stores data in memory and can trigger hardware based on analysis results microcontroller unit - Height adjustment of the bed in sections according to the user's position. an automated system that can do this, containing an electric linear actuator and a servo motor. position adjustment mechanism, - and integrated into the bed structure, according to the user's temperature requirements. by including a temperature variation module that provides district heating It is characteristic.

2. It is a smart bed system according to claim 1, and its feature is that it receives data from position sensors. by analyzing the data, if the user remains in the same position for a long time a position adjustment mechanism that triggers the pressure ulcer risk It is characterized by containing a microcontroller.

3. Smart bed system according to claim 1, whose feature is; RFID sensors detecting the external environment. to prevent the user from being affected by incoming signals and electromagnetic a conductive textile layer and a Faraday cage to provide protection against radiation It is characterized by having this structure.

4. It is a smart bed system according to claim 1, and its feature is that it receives sensor data in real time. Processing and saving data by adding a date and time stamp with the support of the Time Module (RTC). It is characterized by containing a microcontroller.

5. According to Claim 1, it is a smart bed system whose feature is; past data patterns. by examining user-specific immobility thresholds and unusual to generate early warnings in situations, to inform caregivers and user-specific preventive position adjustments are made by the system. Machine learning and deep learning configured for automation, Pattern recognition and natural language processing, neural networks, anomaly detection, time series Analysis and predictive modeling algorithms are among the most important big data technologies. It is characterized by containing a microcontroller, of which at least one is included. 11