Artificial intelligence-assisted personalized sleep optimization system

Abstract

The invention relates to a system that provides a personalized sleep experience through biometric data collection, artificial intelligence-assisted analysis and loT-based environmental optimization technologies.

Description

[0001] ARTIFICIAL INTELLIGENCE-ASSISTED PERSONALIZED SLEEP OPTIMIZATION SYSTEM

[0002] Technical Field of the Invention

[0003] The invention relates to a system that provides a personalized sleep experience through biometric data collection, artificial intelligence-assisted analysis and loT-based environmental optimization technologies.

[0004] State of the Art

[0005] Technologies developed to improve sleep quality often focus on facilitating the process of falling asleep or improving the waking experience. The systems developed in this field utilize biometric data to manage environmental factors (light, temperature, sound, etc.) and aim to make the sleep process more comfortable. However, existing solutions are limited in many respects and fall short of offering dynamic and proactive optimization that suits the individual physiological and psychological needs of users.

[0006] Existing technologies include sleep monitoring devices, smart bed systems, and environmental control mechanisms. For example, some systems analyze sleep stages with pressure sensors or EEG-based measurements, but they only use these analyses reactively to instantly change environmental conditions. Such solutions do not offer specific optimization based on users' stress, anxiety-related stress or anxiety levels, but work based on general healing principles.

[0007] Some advanced systems determine specific sleep parameters by monitoring pulse, respiration and body movements. However, the vast majority of these systems use basic algorithms that do not analyze biometric data in depth and operate based on certain thresholds. Therefore, personalized and time-based learning artificial intelligence-assisted intervention mechanisms are not included in these systems.

[0008] Solutions that offer interventions for all phases of the sleep process, not just falling asleep and waking up, are not yet sufficiently developed. In particular, systems that analyze the impact of factors such as stress, anxiety-related stress and anxiety onsleep quality and offer an integrated optimization to manage these conditions are very limited. Although anxiety-related stress and stress are known to increase heart rate during sleep, disrupt breathing patterns and cause a more superficial sleep, current systems lack the ability to analyze these physiological changes and dynamically adjust environmental factors.

[0009] In addition, existing technologies often consist of devices that operate independently of each other. Many users have to use different systems separately, such as sleep monitoring wristbands, smart thermostats, or sound machines. However, since these systems are usually not operate in an integrated manner, they are unable provide a holistic sleep optimization by establishing a link between data. There is not yet a system that analyzes the relationship between the user's pulse, respiratory rate and movement data and the temperature, light and sound level of the environment, and accordingly offers a fully integrated sleep experience.

[0010] Summary and Objects of the Invention

[0011] The invention relates to a system that provides a personalized sleep experience through biometric data collection, artificial intelligence-assisted analysis and loT-based environmental optimization technologies.

[0012] The object of the invention is to provide a system that integrates biometric data (heart rate, heart rate variability, respiration rate, body temperature, blood oxygen level, movement, etc.) and environmental data (temperature, humidity, light, sound, smell) during sleep.

[0013] Another object of the invention is to learn the user's sleep habits through artificial intelligence-based data analysis and to make a personalized and proactive sleep optimization over time.

[0014] Another object of the invention is that, unlike existing systems, to analyze not only the processes of falling asleep and waking up, but all sleep stages (light sleep, deep sleep, REM, etc.) and provide specific optimization for each stage.Another object of the invention is to detect psychological states such as stress, anxiety-related stress, fear and anxiety, and to manage these states with user-specific environmental adjustments (aromatherapy, white noise, light and temperature adjustments) and improve sleep quality.

[0015] Another object of the invention is to take early precautions against possible health risks during sleep by analyzing physiological responses such as breathing irregularity patterns and heart rate variability.

[0016] Another object of the invention is to provide a mobile interface (Persephone) that analyzes users' sleep history and helps them improve their sleep habits by comparison with different users.

[0017] Description of the Drawings

[0018] Fig. 1. Drawing showing a schematic view of the system of the invention.

[0019] Fig. 2. Drawing showing an image of the sleep assistance device of the invention.

[0020] Description of the References in the Drawings

[0021] a. light sensor

[0022] b. temperature sensor

[0023] c. noise sensor

[0024] d. sleep assistance device

[0025] e. wearable device

[0026] f. application

[0027] g. server

[0028] h. electronic device

[0029] Detailed Description of the Invention

[0030] This invention is an loT-based artificial intelligence system that collects the user's biometric data during sleep and provides personalized optimization by analyzing this data.The sleep assistance device included in the invention comprises a scent module, a light module, and a sound module.

[0031] The scent module relaxes the user by diffusing certain essential oils into the sleep environment depending on the user's biometric data and environmental factors. The temperature sensor (b), which measures the ambient temperature, is integrated in the scent module. For example, when the ambient temperature rises and the user falls into deep sleep, cool and refreshing essential oils (e.g. peppermint, eucalyptus) are activated. If stress or anxiety-related stress is detected before sleep, calming essences such as lavender and chamomile are diffused. Scent diffusion is carried out in a controlled manner thanks to the micro diffuser system.

[0032] The light module adjusts the ambient lighting according to the user's sleep phase. The light module adjusts the ambient lighting in accordance with the user's biological clock. In the process of falling asleep, it emits warm, low-intensity light to promote melatonin production. During the morning waking process, it supports the user to wake up more comfortably by providing lighting in bright and natural tones that mimic sunlight. The light sensor (a), which regulates the ambient light during the night, is integrated in the light module. For example, when a sudden change in light (phone screen, car headlights, etc.) is detected during sleep, the light module automatically adjusts its settings to maintain the balance of the environment.

[0033] The sound module detects the ambient sound level during sleep and makes the necessary sound adjustments to improve the user's sleep quality. It generates relaxing sounds such as white noise, nature sounds, and respiratory rhythm, allowing the user to experience a comfortable sleep. When the ambient noise level rises, the system automatically emits white noise to mask external sounds. The noise sensor (c), which measures the ambient noise level, is integrated in the sound module. For example, when a sudden noise from the outside environment is detected, the device immediately reduces the impact by emitting white noise or calming nature sounds.

[0034] The sleep assistance device (d) continuously measures the temperature, light, and noise levels of the environment. The user's pulse, respiratory rate and movement data are collected from wearable devices (e) (e.g. smart bracelet) to determine the sleep phase. The collected biometric and environmental data is processed by the server (g)with the assistance of artificial intelligence. Stress, anxiety-related stress, relaxation or deep sleep phases of the user are analyzed and the environment is arranged accordingly. The scent module promotes relaxation by emitting a calming essence when stress is detected. The light module automatically adjusts the light color and intensity according to the sleep phase. The sound module, on the other hand, emits white noise according to the noise level to mask external sounds.

[0035] The wearable device (e) is equipped with various sensors to analyze the user's physiological data during the sleep process. These sensors continuously monitor the physical and biological state of the user and provide data flow to the artificial intelligence-assisted analysis system.

[0036] The PPG (Photoplethysmography) sensor determines heart rate by measuring changes in the user's blood flow, respiratory rate by analyzing the synchronization between respiration and pulse, signs of breathing irregularity patterns by tracking changes in respiratory rhythm, and heart rate variability by analyzing changes between pulse signals. It is directly related to the user's heart rate, stress, anxiety-related stress and sleep patterns. When anxiety-related stress and stress levels rise, the heart rate increases and becomes irregular. Heart rate variability is the time difference between heartbeats and indicates the activity of the autonomic nervous system (sympathetic and parasympathetic nervous system). HRV decreases in high stress and anxiety-related stress states.

[0037] The thermal sensor measures temperature changes at the user's skin contact points. Stress and anxiety-related stress can cause the body temperature to increase or show sudden changes.

[0038] The accelerometer sensor detects the amount and direction of movement of the user during sleep. The gyroscope sensor detects the user's rotational movements during sleep. Excessive activity during sleep can be a sign of superficial sleep and stress. More frequent awakenings and restless sleep can indicate high stress levels.

[0039] The SpO2 Sensor (Infrared LED and Photodiode Sensor) measures the amount of oxygen in the blood using infrared lightwaves.The wearable device (e) continuously monitors the user's heart rate, heart rate variability, respiration rate, body temperature, movement status and blood oxygen saturation, recording real-time data through advanced sensors. This collected biometric data is processed on the server (g) by artificial intelligence-assisted analysis algorithms to determine the user's stress, anxiety-related stress and other physiological states during sleep. Based on the analyzed data, the necessary optimization information is transferred to the sleep assistance device (d). The device transmits this obtained information to the sleep assistance device (d) via a wireless connection (Wi-Fi, Bluetooth or other communication protocols) to ensure integrated operation of the system. For example, if the user's stress level is high, the sleep assistance device (d) can emit a calming scent or play white noise to regulate the sleep environment in a relaxing way. In this way, the aim is to provide the user with a healthier, uninterrupted, and comfortable sleep experience. In the preferred embodiment of the invention, the wearable device (e) is in the form of a wristband.

[0040] The wearable device (e) collects biometric data in real time and transmits it to the server (g) via the electronic device (h) through a wireless connection (Wi-Fi / Bluetooth). The artificial intelligence algorithm running on the server (g) analyzes the incoming data and extracts information about the user's sleep phase and stress level. The artificial intelligence algorithm running on the server (g) analyzes incoming biometric data and environmental factors to extract detailed sleep data, including not only sleep stage, stress level and anxiety-related stress state, but also sleep quality score, total sleep time, time to fall asleep and number of sleep interruptions. It identifies possible sleep-related irregularities by monitoring the user's pulse and respiratory fluctuations, breathing irregularity patterns. Additionally, chronic stress and anxiety tendencies, as well as, through body movement analysis, signs of restlessness during sleep can be identified. Analyzing the impact of environmental factors on sleep, the algorithm determines the optimal sleep environment by evaluating the role of temperature, humidity, light level, and noise levels on sleep quality. By estimating the user's circadian rhythm and melatonin production, sleep can be planned according to their biological clock. Long-term analysis can identify the early risk indicators of sleep-related irregularities such as sleep-related breathing irregularity patterns, restlessness-related movement patterns, etc. Artificial intelligence processes the user's historical and current sleep data to provide personalized sleep recommendations and proactivelyintervenes by dynamically adjusting the ambient light, temperature, and scent levels. This provides a personalized sleep experience that maximizes the user's sleep quality.

[0041] On the server (g), artificial intelligence generates appropriate environment optimization decisions based on the user's current sleep state and stress level. The server (g) sends these decisions to the sleep assistance device (d) to change the light, sound, and odor settings of the environment.

[0042] The mobile application (f) provides an interface that allows the user to track sleep data, view analysis results, and manage sleep environment optimizations. The data from the wearable device (e) and the sleep assistance device (d) are processed with artificial intelligence algorithms on the server (g) and presented to the user in a visualized form via the mobile application (f). The user can review historical sleep data, track critical information such as sleep duration, deep sleep rate, stress and anxiety-related stress levels, and learn recommended improvement strategies. Furthermore, the application (f) provides the user with personalized sleep recommendations, helping them to improve their sleep habits. The user can manually adjust the light, scent, and sound settings of the sleep assistance device (d) or leave it in fully automatic mode. In addition, the application (f) offers the possibility to compare sleep quality by comparative analysis with other users. Thanks to all these functionalities, the mobile application (f) enables a personalized sleep experience by making the sleep process trackable and manageable.

Claims

CLAIMS1. A sleep optimization system, characterized by comprising:- at least one sleep assistance device (d) that continuously measures the temperature, light and noise levels of the environment in communication with the server (g) and adjusts them according to the parameters set by the server (g), comprising at least one scent module including a temperature sensor (b) that measures the ambient temperature, which enables the diffusion of essential oils into the environment according to the information received from the server (g); at least one light module including a light sensor (a) that detects the ambient light, which adjusts the ambient lighting according to the user's sleep phase; at least one sound module including a noise sensor (c) that measures the ambient noise level, which detects the ambient sound level during sleep and makes sound adjustments to improve the user's sleep quality,- at least one wearable device (e) that continuously monitors the user's heart rate, heart rate variability metrics, respiration pattern features, body temperature, movement status and blood oxygen saturation, records realtime data and transmits this collected biometric data to the server (g) through wireless connection via electronic device (h), comprising at least one PPG sensor that determines the user's heart rate by measuring changes in blood flow, respiratory rate by analyzing the synchronization between respiration and pulse, signs of breathing irregularity patterns by tracking changes in respiratory rhythm, and heart rate variability by analyzing changes between pulse signals; at least one thermal sensor that measures temperature changes at the user's skin contact points; at least one gyroscope sensor that detects the amount and direction of movement of the user during sleep; at least one SpO2 Sensor that measures the amount of oxygen in the blood using infrared lightwaves,- at least one server (g) which identifies with artificial intelligence the sleep stage, stress level, anxiety-related stress status, sleep quality score, total sleep duration, sleep onset time, and number of sleep disruptions by analyzing biometric data from the wearable device (e) and environmental factors from the sleep assistance device (d), determines optimal sleep environment parameters by evaluating the role of temperature, humidity,light level, scent, and noise level on sleep quality, predicts the user's circadian rhythm and melatonin production to plan sleep according to their biological clock, and processes the user's past and current sleep data to provide personalized sleep recommendations,- at least one mobile application (f) executed on an electronic device (h) that includes interfaces that enable the user to review historical sleep data calculated by the server (g), track sleep duration, deep sleep rate, stress and anxiety-related stress levels, and see recommended improvement strategies.

2. The sleep optimization system according to claim 1, characterized in that it comprises a scent module that activates cooling-effect essential oils when the ambient temperature increases and the user goes into deep sleep.

3. The sleep optimization system according to claim 1, characterized in that it comprises a scent module that enables the activation of calming essential oils if stress or anxiety-related stress is detected by the server (g) prior to sleep.

4. The sleep optimization system according to claim 1, characterized in that it comprises a light module that automatically adjusts the light to maintain the balance of the environment when a light change is detected during sleep.

5. The sleep optimization system according to claim 1, characterized in that it comprises a sound module that masks external sounds by emitting white noise when the environmental noise level increases.

6. The sleep optimization system according to claim 1, characterized in that it comprises a server (g) that determines, with artificial intelligence, chronic stress and anxiety tendencies and symptoms of restlessness during sleep by body mobility analysis.

7. The sleep optimization system according to claim 1, characterized in that it comprises a server (g) that identifies possible sleep malfunctions or irregularities by monitoring the user's pulse and respiratory fluctuations, breathing irregularity patterns, and respiratory irregularities.

8. The sleep optimization system according to claim 1, characterized in that it comprises an application (f) that enables the user to manually adjust the light, scent, and sound settings of the sleep assistance device (d) or to set it to operate in fully automatic mode.

9. The sleep optimization system according to claim 1, characterized in that it comprises an application (f) that enables the user to compare sleep quality by comparative analysis with other users.

10. The sleep optimization system according to claim 1, characterized in that it comprises a wearable device (e) in the form of a wristband, watch, ring, glasses, headphones, body band.

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