System and method for monitoring physiological stress of users

Abstract

A system and method for assessing stress levels in real-time is described The stress level is assessed based on circadian rhythms, using a wearable device. The wearable device measures Resting Heart Rate (RHR) of a user and correlates changes in the RHR with circadian zones to evaluate the stress. Stress information along with sleep, activity, and nap zones is visually represented on an interface of the wearable device. A scoring mechanism is used for adjusting the user's stress score based on a time of day and physiological data, for enhancing personal management of health and stress.

Description

[0001] SYSTEM AND METHOD FOR MONITORING PHYSIOLOGICAL STRESS OF USERS

[0002] FIELD OF INVENTION

[0003] [1] The present invention relates to a wearable device, and specifically relates to a wearable device for monitoring stress of a user.

[0004] BACKGROUND

[0005] [2] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.

[0006] [3] In general, human body exhibits a natural circadian rhythm, influencing various physiological states, including stress and activity levels. Circadian rhythm is a cycle in the body that occurs roughly across 24 hours. In humans, circadian rhythms cause physical and mental changes in the body, including feelings of wakefulness and sleep.

[0007] [4] The Phase Response Curve (PRC) describes how various stimuli — such as light exposure, physical activity, and food intake — can shift the body’s internal circadian rhythm, either advancing it (causing earlier sleep and wake times) or delaying it (resulting in later sleep and wake times). These shifts are measured relative to the body’s temperature minima, the point during sleep when core body temperature reaches its lowest level, serving as a biological reference for circadian alignment.

[0008] [5] A phase advance occurs when stimuli like light or exercise promote an earlier circadian phase — meaning the body becomes primed to fall asleep and wake up earlier. In contrast, a phase delay results when the same stimuli push the circadian phase later, making the body more inclined to sleep and wake later. The temperature minima zone marks the period of deepest biological night, when the body is most vulnerable to external disruptions; light and activity during this window can impair sleep quality and recovery processes. The circadian dead zone refers to a phase when the body’s internal clock is relatively unresponsive to light exposure — stimuli during this period have minimal or no effect on circadian timing. These biochemical shifts underscore the importance of aligning lifestyle habits with circadian biology to optimize sleep, alertness, and overall well-being.

[0009] [6] Stress is a response of a living being to a change in environment which can be beneficial or threatening / challenging situation. The strength of the body to buffer dis-stress and resolve the same before it’s impact on underlying circadian rhythm is well established to form the basis of wellness and longevity. Managing stress effectively requires understanding of its interplay with body's internal clock. For example, s tress physical or mental when presented in a circadian phase where the individual is alert causes the activation of biochemical pathways that can be effectively handled by the body. The same stress when presented when the body is normally in rest, causes a much larger biochemical disruption. Conventional health monitoring devices track various health metrics, such as heart rate, Heart Rate Variability (HRV), body temperature, and movement. For example, the HRV is used for determining stress level of an individual in acute and chronic scenarios, where a lower HRV is usually an indication of fatigue and stress. However, the conventional health monitoring devices do not typically interpret these signals (health metrics) in the context of an individual's circadian rhythm to assess stress. The lack of contextual stress assessment can lead to provide misleading health advice, as the physiological state varies significantly with circadian phases.

[0010] [7] Thus, there is a need of a device and a method of accurately determining real-time physiological data in synchrony with the circadian phases.

[0011] OBJECT OF THE INVENTION

[0012] [8] A general objective of the present invention is to provide a smart wearable capable of monitoring stress of a user.

[0013] [9] Another objective of the invention is to provide a smart wearable capable of monitoring stress in correlation with the circadian rhythm of the user.

[0014]

[0010] Another objective of the invention is to provide a smart wearable that maps the stress equilibrium rhythm of the user over time, rather than merely detecting isolated stress episodes. This involves capturing patterns, trends, and habitual responses in relation to the user's daily lifestyle and biological rhythms. By identifying deviations from expected circadian-aligned stress rhythms, the system can offer deeper insights into long-term wellness and health. This capability is critical to understanding how consistent misalignment or erratic stress patterns contribute to overall physiological and psychological deterioration.

[0015] SUMMARY OF THE INVENTION

[0016]

[0011] The summary is provided to introduce aspects related to monitoring physiological stress cadence of a user using a wearable device, and the aspects are further described below in the description. This summary is not intended to identify essential features of the claimed subject matter nor is it intended for use in determining or limiting the scope of the claimed subject matter.

[0017]

[0012] The present disclosure provides a method for monitoring daily and long-term physiological stress profile of a user based on his / her habits and lifestyle using a wearable device. According to an embodiment, the method comprises receiving physiological data associated with the user from a plurality of sensors and a user input, where the physiological data includes at least one of a resting heart rate (RHR) value, a heart rate variability (HRV) value, a temperature value, movement information, sleeping pattern information, and cortisol levels. Further, the method includes detecting one or more stress events associated with the user based on a processing of the physiological data and a correlation of a circadian cycle of the user with respect to the RHR value, the HRV value, and activity. Further, the method includes a methodology to identify the stress episode as a beneficial physiological challenge as that involving body movements and exercise which release beneficial chemicals in the body and episodes of stress which occur when the user is likely to be initiating rest and recovery and which disrupts their circadian rhythm by changing biochemical balance. The method also includes assigning an overall dynamic stress score to each of the one or more stress events by continuously analyzing physiological signals — such as resting heart rate (RHR), heart rate variability (HRV), and respiratory patterns — and correlating them with the user’s circadian rhythm profile. This score adapts in real time to reflect changing states of autonomic balance, with breathwork interventions factored in as modulators that can actively shift stress physiology by enhancing parasympathetic activation.

[0018]

[0013] Further, the method includes analyzing the stress score corresponding to each of the one or more stress events with respect to the user’s circadian rhythm by evaluating it against predefined threshold values. This enables the determination of a user’s stress level over a predefined time interval, while aligning the analysis with the body's natural biochemical fluctuations and daily resilience cycles.

[0019]

[0014] Further, the method includes analyzing the stress score corresponding to each of the one or more stress events with respect to the user’s circadian rhythm by evaluating it against predefined threshold values. This enables the determination of a user’s stress level over a predefined time interval, while aligning the analysis with the body's natural biochemical fluctuations and daily recovery cycles.

[0020]

[0015] In an embodiment, the stress score is computed using the Ultrahuman Stress Rhythm (SR) model, which initiates each day with a baseline value of 100. This value dynamically decreases in response to heart rate elevations detected outside of logged physical activity — indicative of psychological or environmental stressors. Importantly, the system differentiates between eu-stress (performance-related based on movement or activity) and di-stress (anxiety- related) based on heart rate variability signatures, intensity, and time of day.

[0021]

[0016] In an embodiment, the SR algorithm is time-weighted and follows time sensitive scoring. Thus, any change in the circadian rhythm of a person, impacts the scoring. For example, a person with night shift will have a different circadian rhythm than a person with morning shift. Thus, stress occurring for a night person may vary as compared to the morning person. For example, the stress occurring of a morning person may result in a smaller deduction from the stress score compared to similar events happening in the evening or night, when the body is less primed to handle stress and more susceptible to recovery disruption. On the other hand, the stress occurring of a night person may result in a smaller deduction from the stress score compared to similar events happening in the day time or morning, when the body is less primed to handle stress and more susceptible to recovery disruption. This time- sensitive scoring approach accounts for the elevated impact of late-day stressors on sleep quality and recovery, as evidenced by reductions in nocturnal heart rate variability (HRV). By modelling stress in alignment with the body’s internal clock, the method provides a more precise and personalized assessment of daily stress exposure.

[0022]

[0017] Further, these signals are continuously analyzed and interpreted through the lens of circadian biology, aligning the output with the user’s individual cortisol rhythm, sleep-wake cycle, and core body temperature fluctuations. The invention recognizes that the interpretation of stress signals is highly time-sensitive, as the body’s natural stress response systems follow a diurnal pattern, with cortisol typically peaking in the early morning and tapering toward evening. By mapping stress-related physiological changes against these circadian-informed baselines, the system ensures that a rise in physiological arousal during the natural cortisol peak is not misclassified as abnormal stress, while similar patterns during rest phases (e.g., late evening) are flagged with greater sensitivity.

[0023]

[0018] Further, the method includes displaying, via a user interface (UI), the level of stress along with the stress score and an observation on the level of stress for the user.

[0024]

[0019] A key innovation of this system lies in its ability to not only detect and contextualize stress states, but also to proactively engage the user in regulation via biofeedback -based interventions. When stress levels exceed circadian-adjusted thresholds, the system can recommend or tag evidence-based interventions such as breathwork sessions. These sessions may include paced breathing, resonance frequency breathing, or guided diaphragmatic breathing, with the goal of activating the parasympathetic nervous system and modulating autonomic balance.

[0025]

[0020] According to some embodiments, a system for monitoring physiological stress of a user is disclosed. In an embodiment, the system comprises one or more processors configured to receive physiological data associated with the user from a plurality of sensors and a user input, wherein the physiological data includes at least one of a resting heart rate (RHR) value, a heart rate variability (HRV) value, a temperature value, movement information, sleeping pattern information. Further, the one or more processors are configured to identify the circadian cycle of the user based on an analysis of the physiological data. Further, the one or more processors are configured to detect one or more stress events associated with the user based on a processing of the physiological data and a correlation of the circadian cycle of the user with respect to the RHR value and the HRV value. Further, the one or more processors are configured to assign a stress score to each of the one or more stress events based on a result of the processing of the physiological data and a result of the correlation of the circadian rhythm of the user with respect to the RHR value and the HRV value. Further, the one or more processors analyzes the aggregate stress score corresponding to each of the one or more stress events with respect to at least one of a predefined threshold values to determine a level of stress the user is experiencing in a predefined period of time. In an embodiment, the aggregate stress score is calculated on a daily basis. Accordingly, the aggregate stress score is reset daily. Further, the one or more processors are configured to display, via a user interface (UI), the level of stress along with the stress score and an observation on the level of stress for the user. According to some embodiment, the one or more processors are configured to provide notification to the user for example, the user may receive notification regarding the best practices the user is adapting to control the stress within the limit, suggestions to perform or modify any activity to control the stress and the like.

[0026]

[0021] Other aspects and advantages of the invention will become apparent from the following description, taken in conjunction with the accompanying drawings, illustrating by way of example the principles of the invention.

[0027] BRIEF DESCRIPTION OF THE DRAWINGS

[0028]

[0022] The accompanying drawings constitute a part of the description and are used to provide further understanding of the present invention. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0029]

[0023] FIG. 1 illustrates an exemplary environment 100 of a wearable device according to an embodiment of the present disclosure.

[0030]

[0024] FIG. 2 illustrates a block diagram of various components of the smart ring, according to an embodiment of the present disclosure.

[0031]

[0025] FIG. 3 illustrates a method for monitoring physiological stress of a user by the wearable device, according to an embodiment of the present disclosure.

[0032]

[0026] FIGs. 4-7 illustrate example User Interfaces (UIs) for displaying physiological stress in correlation with circadian rhythms, in accordance with an embodiment of the present invention.

[0033]

[0027] FIG. 8 illustrates a general block diagram of the wearable device 101, according to an embodiment of the present disclosure.

[0034] DESCRIPTION OF THE INVENTION

[0035]

[0028] The description set forth below in connection with the appended drawings is intended as a description of various embodiments of the present invention and is not intended to represent the only embodiments in which the present invention may be practiced.

[0029] Each embodiment described in this invention is provided merely as an example or illustration of the present invention, and should not necessarily be construed as preferred or advantageous over other embodiments. The description includes specific details for the purpose of providing a thorough understanding of the present invention. However, it will be apparent to those skilled in the art that the present disclosure may be practiced without these specific details.

[0036]

[0030] The present disclosure provides a system and method for monitoring physiological data from a wearable device. In an embodiment, the system interprets the physiological signals to assess stress levels, and displays the stress levels in correlation with the wearer's (i.e. users) circadian rhythms. The present disclosure uniquely integrates detection of physiological stress markers with natural cortisol cycles and circadian phases of an individual, enhancing the accuracy and usefulness of stress assessments.

[0037]

[0031] According to an embodiment, a wearable device for monitoring physiological stress in correlation with circadian rhythms is disclosed. In a non-limiting example, the wearable device may be a smart watch, a smart band, or an electronic ring. Although the details have been provided successively with reference to a smart ring merely for the sake of explanation, it must be understood that the invention could be fairly implemented in a similar manner using any other wearable device, such as the ones listed above.

[0038]

[0032] FIG. 1 illustrates an exemplary environment 100 of a wearable device according to an embodiment of the present disclosure. According to an embodiment, the exemplary environment 100 includes the wearable device 101 used for monitoring physiological stress in correlation with a circadian cycle of the user. In a non-limiting example, the wearable device 101 may corresponds to a smart ring, a smart wrist band, or any smart gadget that is in contact with the skin of the user. Further, an explanation has been made with respect to the smart ring. However, the same shall not be construed as limiting the scope of the invention.

[0039]

[0033] In an embodiment, the smart ring 101 may be made using a hypoallergenic material for allowing comfortable and continuous wear by the user. In an embodiment, the smart ring 101 may include one or more sensors to receive physiological data of the user. In a non-limiting example, the one or more sensors include a photoplethysmography (PPG) sensor, a motion sensor, a gyro sensor, a temperature sensor, and the like. Further, as an example, the physiological data includes at least one of a resting heart rate (RHR) value, a heart rate variability (HRV) value, a temperature value, movement information, sleeping pattern information. In an embodiment, the wearable device 101 processes the physiological data for determining insights related to health of the user.

[0040]

[0034] According to a further embodiment, the smart ring 101 is wirelessly coupled with a smartphone 103 and may transfer the data to a server 105 for storage and / or further processing. End-to-end encryption may be implemented for data transmission from the smart ring 101 to the smartphone 103 and / or the server 105, thereby maintaining data privacy and security.

[0041]

[0035] FIG. 2 illustrates a block diagram of various components of the smart ring, according to an embodiment of the present disclosure. According to an embodiment, the smart ring 101 includes various components such as, but are not limited to, a processing unit 201, a sensor unit 203, a display 205, a data projection element 207, a wireless module 209, and a battery module (not illustrated).

[0042]

[0036] According to an embodiment, the sensor unit 203 includes all the sensors as explained above. In an embodiment, the sensor unit 203 receives the physiological data associated with the user from the sensors in the sensor unit 203. For example, the PPG sensor collects the RHR value and the HRV value of the user. According to a further example, the temperature value and the movement information may be received by the temperature sensor and the gyro sensor. In a further embodiment, the processing unit 201 may receive the user input. The user input may be the sleeping pattern information of the user. The sleeping pattern information relates to the sleeping style of the user. For example, the user can be an early morning person or a late night person. The details of such inputs are provided by the user while creating a user profile.

[0043]

[0037] According to an example embodiment, the aggregated physiological measures such as resting heart rate, average heart rate variability, average temperature and so on can be collected during night time and used as baseline information. Further, the changes in the baseline information may correspond to stress. Further, the processing unit 201 may process physiological data to detect stress events. In an embodiment, parameters indicative of the stress events include increase in heart rate, reduced heart rate variability, elevated body temperature, and excessive or abrupt movements.

[0038] According to an embodiment, the processing unit 201 further tracks the circadian cycle of the user, by processing the movement information, the body temperature value, and sleeping information of the user. Further, the processing unit 201 identifies a chronotype and the circadian cycle of the user based on the analysis of the physiological data. In an embodiment, the processing unit 201 correlates the circadian cycle of the user with respect to the RHR value and the HRV value for detecting the stress events. According to some embodiment, the processing unit 201 also determines the cortisol levels and considers the same in determining the stress events. According to some embodiment, the cortisol levels may be obtained from cortisol sensors or any other external sources.

[0044]

[0039] According to a further embodiment, the processing unit 201 determines an aggregate stress score periodically by assigning points based on a result of the processing of the physiological data and a result of the correlation of the circadian rhythm of the user with respect to the RHR value and the HRV value.

[0045]

[0040] According to some embodiment, the processing unit 201 analyzes the aggregate stress score corresponding to each of the one or more stress events with respect to at least one of a predefined threshold values to determine a level of stress the user is experiencing in a predefined period of time. For example, the user may experience elevated stress (increased heart rate and decreased HRV) at 10 AM (phase advance). The processing unit 201 may log this as a stress event. If a similar stress event occurs at 8 PM (phase delay). This reflects the natural biological expectation of lower stress towards the end of the day.

[0046]

[0041] According to an embodiment, the display 205 or the data projection element 207 displays, via a user interface (UI), the level of stress along with the aggregate stress score and an observation on the level of stress for the user. According to an embodiment, the level of stress showing overlapping zones of sleep, activity, nap, and stress breakdown may be displayed to the user via the display 205 or the data projection element 207. Alternatively, or additionally, the stress information may be communicated for display to the smartphone 103 via the wireless module 209. The smart ring 101 allows the user to observe variation in his stress levels throughout the day in relation to their biological clock, thereby facilitating more informed lifestyle choices.

[0042] FIG. 3 illustrates a method for monitoring physiological stress of a user by the wearable device, according to an embodiment of the present disclosure. According to an embodiment, the method 300 is implemented in the smart ring 101.

[0047]

[0043] According to an embodiment, at step 301, the sensor unit 203 and the processing unit 201 periodically monitors and receives the physiological data associated with the user from the sensors and the user input.

[0048]

[0044] In an embodiment, at step 303, the processing unit 201 identifies a circadian cycle of the user based on an analysis of the physiological data. For doing so, the a pre-classified circadian zones are used for personalized profiling of the user to analyze circadian rhythm of each user by first identifying their chronotype, or body rhythm type, through the detection of the most frequent sleep and wake times based on the physiological data. The processing data is then used to differentiate between waking and sleeping hours to determine whether the user’s circadian cycle is phase-advanced or delayed.

[0049]

[0045] Accordingly , the processing unit 201 processes and analyzes the physiological data to detect a change in a stress rhythm equilibrium for determining the stress events. In an embodiment, the processing unit 201 processes and analysis the physiological data of the user with respect to the pre-classified circadian zones. The pre-classified circadian zones are time segments aligned with an individual's biological clock. In an embodiment, the pre-classified circadian zones are defined as advance, dead zone, delay, and minima corresponding to specific times of a day. For example, an acceptable stress are falls under an advance or dead zone. Further, less stress under fall under delay zone, and least stress fall under minima zone.

[0050]

[0046] According to an embodiment, based on analysis of the physiological data, processing unit 201 identifies the circadian cycle of the user.

[0051]

[0047] Individualized circadian phases represent a user-specific refinement of these general zones, dynamically adjusted based on a person’s lifestyle, behavioral patterns, sleep-wake cycles, and other habitual cues. This differentiation is critical and forms a core aspect of the innovation, moving beyond static scientific models to a personalized interpretation of circadian alignment. By integrating both established circadian zones and individualized circadian phases, the system ensures a more accurate and context-aware stress assessment for each user.

[0048] In an embodiment, the processing unit 201 generate the personal profile of the user having a chronotype of the user by using the circadian cycle of the user. In an embodiment, the processing unit 201 further calibrate the personal profile of the user as when the wearable device detects a change in the circadian cycle.

[0052]

[0049] In particular, the processing unit 201 analyzes the circadian cycle for profiling of the user to identify their chronotype, or body rhythm type, through the detection of the most frequent sleep and wake times. The processing unit 201 then differentiates between waking and sleeping hours to determine whether the user’s circadian cycle is phase-advanced or delayed.

[0053]

[0050] For example, the processing unit 201 identifies the most frequent sleep and wake patterns to establish a baseline chronotype using the circadian cycle.

[0054]

[0051] In an embodiment, the processing unit 201 further correlates the RHR value and the HRV value of the user with the pre-classified circadian zones based on the analysis of the physiological data. According to some embodiments the processing unit 201 correlates the cortisol levels with the pre-classified circadian zones. The cortisol level mapping plays a vital role in understanding and validating stress assessment, as cortisol is the body’s primary stress hormone and a key regulator of the circadian rhythm. Typically, cortisol levels follow a diurnal pattern. The cortisol level peaks in the morning with the cortisol awakening response to support the transition from sleep to wakefulness, and gradually declining throughout the day to facilitate melatonin release and sleep initiation. Disruptions to this rhythm, such as prolonged elevation of cortisol levels, are linked to poor sleep quality and impaired recovery.

[0055]

[0052] In stress assessment models, mapping cortisol levels helps differentiate between healthy, adaptive stress responses and prolonged, harmful stress states. It provides a biological context for interpreting heart rate variations and improves the precision of stress scores. By incorporating insights from cortisol rhythms, stress detection algorithms can more accurately identify stress episodes that are likely to impact sleep and recovery, making the overall assessment more personalized and physiologically meaningful.

[0056]

[0053] Over time, the processing unit 201 establishes an anchor pattern based on consistent historical data, enabling it to recognize and adapt to significant shifts in routine, such as those resulting from international travel or shift work. When sleep patterns become highly irregular, these periods are labeled as “disturbed sleep” to maintain the accuracy of the model and ensure reliable stress assessments despite temporary disruptions in the circadian rhythm. Building upon this individualized profiling, the system delivers precise circadian modeling, which significantly enhances the accuracy of stress interpretation and overall physiological insights. Additionally, during phases of significant routine variation, the system provides real-time notifications and adaptive guidance to help users cope with these departures from their normal rhythm. These notifications may include personalized suggestions for light exposure, optimal nap times, or modified activity and recovery plans — enabling users to better manage the physiological effects of schedule shifts and maintain resilience. Further, the notification may be regarding the best practices the user is adapting to control the stress within the limit, suggestions to perform or modify any activity to control the stress and the like

[0057]

[0054] Further, at step 305, the processing unit 201 detects the one or more stress events associated with the user based on the processing of the physiological data and the correlation of the circadian cycle of the user with respect to the RHR value and the HRV value. In particular, to detect the stress events, the processing unit 201 determines a change in in at least one of the RHR value and the HRV value. The processing unit 201 determines the change is due to associated activity of the user based on the result of the processing of the physiological data and the result of the correlation of the circadian rhythm of the user with respect to the RHR value and the HRV value.

[0058]

[0055] In an embodiment, the processing unit 201 detects the change in the stress rhythm equilibrium based on the determination of the change in the RHR value and the HRV value. For example, in certain activities like user performing yoga the RHR value is low and HRV value is high. However, in such a scenario the user is not experiencing any stress. Thus, in such a scenario also the user is not experiencing any stress. Thus, the stress rhythm equilibrium improves. However, if the user is in a stressful workplace meeting, even though there is no movement, RHR increases and HRV decreases which is then identified as a stressful event and the stress rhythm score is adjusted accordingly.

[0059]

[0056] Accordingly, the processing unit 201 determines the one or more stress events associated with the user based on the determination of the change in at least one of the RHR value and the HRV value is not due to the associated activity of the user. The one or more such stress events indicates a non-exercise-related stress.

[0057] Further, at step 307, the processing unit 201 assigns an aggregate stress score to each of the one or more stress events based on a result of the processing of the physiological data and a result of the correlation of the circadian rhythm of the user with respect to the RHR value and the HRV value. In particular, the processing unit 201 determines a time of occurrence of the stress events. Further, the processing unit 201 deduct a predefined value from a preliminary value based on the determination that the increase in at least one of the RHR value and the HRV value is not due to the increase in the movement of the user and the time of occurrence of the one or more stress events.

[0060]

[0058] Further, the processing unit 201 obtains the aggregate stress score based on the deduction of the predefined value from the preliminary value. Calculation of the stress score involves assigning of “Points” to each data point detected by the smart ring. Each “Point” is curated by multiple bio-signals including heart rate. Heart Rate Variability, body temperature, motion and steps. “Point” curation also involves its presence in the circadian phase, for example high stress in Phase Advance get less points as compared to Phase Delay. After curation of Points, an overall stress score is generated from a fixed value, such as 100.

[0061]

[0059] Thus, according to an embodiment, the processing unit 200 may determine an overall stress score by assigning points based on the correlation between the stress level and the circadian zone overlap, subtracting from 100 to derive a final score. In an embodiment, the processing unit 201 calculates the stress score on a daily cycle, starting at midnight with an initial value of 100, and follows a negative scoring model. Throughout the day, points are deducted when elevated heart rate is detected without a corresponding increase in movement, which typically indicates non-exercise-related stress. However, if an elevated heart rate is accompanied by movement, such as during physical activity or exercise, no deduction occurs, as this is categorized as “good stress” or eustress. The processing unit 201 integrates the user’s circadian rhythm into its analysis, applying time-of-day sensitivity to score deductions. For instance, stress experienced in the evening results in a greater reduction in score due to its potential to negatively impact sleep and recovery. This dynamic approach allows the system to differentiate between performance-related eustress and anxiety-related distress, resulting in a more personalized and context-aware assessment of daily stress.

[0062]

[0060] For example, a stress score of 100 may be set at midnight (12 AM) each day. The stress score is decreased with each detected stress event. Decrement in the stress score is weighted by timing of the stress event relative to the user's circadian cycle. The stress events during the phase advance have less impact on the stress score compared to those occurring during the phase delay. In an embodiment, the stress score is calculated on a daily basis and hence gets reset daily.

[0063]

[0061] Thus, the aggregated stress score is a rhythm-driven output that offers an aggregated view of the individual's event profile throughout the day. It is dynamic and captures how effectively the user manages or responds to stressors. Thus, the aggregated stress score provides details about but how stress patterns change in relation to the user’s circadian rhythm and daily habits. This rhythmic mapping is unique, as it reveals how misalignment or harmony with natural cycles directly affects long-term wellness and health outcomes.

[0064]

[0062] Upon assigning the aggregate stress score, the processing unit 201, at step 309, analyzes the stress score corresponding to each of the one or more stress events with respect to at least one of a predefined threshold values to determine a level of stress the user is experiencing in a predefined period of time. For example, consider that a user has the following stress scores corresponding to various events over a week or a day :

[0065] Monday: Stress Event (High-pressure meeting) - Score: 10-15

[0066] Tuesday: Stress Event (Family argument) - Score: 15

[0067] Wednesday: Stress Event (Work deadline) - Score: 15

[0068] Thursday: Relaxation Day - Score: >90

[0069] Friday: Stress Event (Project presentation) - Score: 10

[0070] Saturday: Stress Event (Personal issues) - Score: 12

[0071] Sunday: Low activity day - Score: 60-70

[0072] Predefined Thresholds:

[0073] High Stress: Score < 40

[0074] Moderate Stress: 40 > Score > 70

[0075] Low Stress: Score > 70

[0063] Accordingly, throughout the week, the processing unit 201 identifies events with stress scores that exceed the thresholds. The level of stress experienced by the user can be obtain below:

[0076] Monday: 10-15 (High)

[0077] Tuesday: 15 (High)

[0078] Wednesday: 15 (Boundary case; can be interpreted as High depending on definitions)

[0079] Thursday: > 90 (Low)

[0080] Friday: 10 (High)

[0081] Saturday: 12 (High)

[0082] Sunday: 60-70 (Low)

[0083] Determine the Level of Stress: During the week analyzed:

[0084] High Stress Events: 5 (Monday, Tuesday, Wednesday, Friday, Saturday)

[0085] Low Stress Events: 2 (Thursday, Sunday)

[0086]

[0064] According to the example, scenario, it can be seen that the user experienced mostly high stress throughout the week with only two days of low stress. Depending on this analysis, recommendations could be made for stress management techniques or lifestyle changes, such as relaxation exercises, meditation, scheduling time off, or seeking professional help if necessary.

[0087]

[0065] In certain implementations, one or more machine learning techniques may be utilized to adapt and predict stress patterns based on long-term data collection, for improving the system's accuracy over time. According to some embodiment, the wearable device may be coupled with other devices for example, home environment, blood test biomarkers for displaying the notification, user profile details for monitoring wellness. Thus, the wearable device provide a longitudinal profiling and the generation of wellness insights over time. In an embodiment, at step 311, the display 205 or the data projection element 207 displays via a user interface (UI) the level of stress along with the stress score and an observation on the level of stress for the user.

[0088]

[0066] FIGs. 4-7 illustrate example User Interfaces (UIs) for displaying physiological stress in correlation with circadian rhythms, in accordance with an embodiment of the present invention.

[0089]

[0067] FIG. 8 illustrates a general block diagram of the wearable device 101, according to an embodiment of the present disclosure.

[0090]

[0068] In an example, the MCU 801 may be a single processing unit or a number of units, all of which could include multiple computing units. The MCU 801 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logical processors, virtual processors, state machines, logic circuitries, and / or any devices that manipulate signals based on operational instructions. Among other capabilities, MCU 801 is configured to fetch and execute computer-readable instructions and data stored in a memory 803.

[0091]

[0069] The memory 803 may include any non-transitory computer-readable medium known in the art including, for example, volatile memory, such as static random-access memory (SRAM) and dynamic random-access memory (DRAM), and / or non-volatile memory, such as read-only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes.

[0092]

[0070] In an example, the unit(s) 807 may include a program, a subroutine, a portion of a program, a software component or a hardware component capable of performing a stated task or function. As used herein, the unit(s) 807 may be implemented on a hardware component such as a server independently of other modules, or a module can exist with other modules on the same server, or within the same program. The unit(s) 807 may be implemented on a hardware component such as processor one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and / or any devices that manipulate signals based on operational instructions. The unit(s) 807 when executed by the MCU 801 may be configured to perform any of the described functionalities.

[0071] As a further example, the database 805 may be implemented with integrated hardware and software. The hardware may include a hardware disk controller with programmable search capabilities or a software system running on general-purpose hardware. Examples of databases are but are not limited to, in-memory databases, cloud databases, distributed databases, embedded databases, and the like. The database amongst other things, serves as a repository for storing data processed, received, and generated by one or more of the MCU 801.

[0093]

[0072] As an example, the display unit 809 includes a computer monitor, a touch screen, an output device capable of displaying the graphics, and the like. The display unit 809 is configured to display visual output in desktops, laptops, and workstations. The display unit 809 may come in different sizes, resolutions, and types (such as LCD, LED, or OLED).

[0094]

[0073] As a further example, the network interface 811 is configured to provide and establish communication with any electronic device via a public network, private network, or any wireless communication technology.

[0095]

[0074] Above proposed system offers the benefit of providing real-time and longitudinal personalized stress profiling and management insights to users. Present invention assesses stress in the context of user's biological clock, providing more accurate and actionable insights. The system also encourages behavioral adjustments based on circadian health insights. The system could be implemented as a smart wearable device such as smart ring and thus integrates seamlessly in daily life of users.

[0096]

[0075] The figures of the disclosure are provided to illustrate some examples of the invention described. The figures are not to limit the scope of the depicted embodiments or the appended claims. Aspects of the disclosure are described herein with reference to the invention to example embodiments for illustration. It should be understood that specific details, relationships, and method are set forth to provide a full understanding of the example embodiments. One of ordinary skill in the art recognize the example embodiments can be practiced without one or more specific details and / or with other methods.

[0097]

[0076] Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0098]

[0077] While this specification contains many specific implementation details, these should not be construed as limitations on the scope of any disclosures or of what may be claimed, but rather as descriptions of features specific to particular embodiments of particular disclosures. Certain features that are described herein in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable sub combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a sub combination or variation of a sub combination.

[0099]

[0078] Thus, particular embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In certain implementations, multitasking and parallel processing may be advantageous.

[0100]

[0079] It is to be understood that the disclosure is not to be limited to the specific embodiments disclosed, and that modifications and other embodiments are intended to be included within the scope of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation, unless described otherwise.

[0101]

[0080] The terms “or” and “and / or” as used herein are to be interpreted as inclusive or meaning any one or any combination. Therefore, “A, B or C” or “A, B and / or C” mean “any of the following: A; B; C; A and B; A and C; B and C; A, B and C.” An exception to this definition will occur only when a combination of elements, functions, steps or acts are in some way inherently mutually exclusive.

[0081] Any combination of the above features and functionalities may be used in accordance with one or more embodiments. In the foregoing specification, embodiments have been described with reference to numerous specific details that may vary from implementation to implementation. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense. The sole and exclusive indicator of the scope of the invention, and what is intended by the applicants to be the scope of the invention, is the literal and equivalent scope of the set as claimed in claims that issue from this application, in the specific form in which such claims issue, including any subsequent correction.

Claims

AMENDED CLAIMS received by the International Bureau on 22 August 2025 (22.08.2025)We Claim:

1. A method for monitoring physiological stress of a user, the method comprises: receiving physiological data associated with the user from a plurality of sensors and a user input, wherein the physiological data includes at least one of a resting heart rate (RHR) value, a heart rate variability (HRV) value, a temperature value, movement information, cortisol levels, and sleeping pattern information; identifying a circadian cycle of the user based on an analysis of the physiological data; determining a change in at least one of the RHR value and the HRV value is due to an associated activity of the user based on the result of the analysis of the physiological data and a correlation of the circadian cycle of the user with respect to the RHR value and the HRV value; detecting one or more stress events associated with the user based on the determination that the change in at least one of the RHR value and the HRV value is not due to the associated activity of the user; deducting a predefined value from a preliminary value based on the determination that the increase in at least one of the RHR value and the HRV value is not due to the associated activity of the user and a time of occurrence of the one or more stress events; obtaining the aggregate stress score based on a deduction of the predefined value from a preliminary value; assigning an aggregate stress score to each of the one or more stress events based on a result of a processing of the physiological data and a result of the correlation of the circadian cycle of the user with respect to the RHR value and the HRV value; analyzing the stress score corresponding to each of the one or more stress events with respect to at least one of a predefined threshold values to determine a level of stress the user is experiencing in a predefined period of time; anddisplaying, via a user interface (UI), the level of stress along with the stress score and an observation on the level of stress for the user.

2. The method as claimed in claim 1, further comprising: analysing the physiological data of the user with respect to pre-classified circadian zones; and generating a personal profile of the user having a chronotype based on the circadian cycle of the user.

3. The method as claimed in claim 2, further comprising correlating the RHR value, the HRV value, and cortisol levels of the user with the pre-classified circadian zones based on the analysis of the physiological data.

4. The method as claimed in claim 1, further comprising detecting a change in a stress rhythm equilibrium to detect the one or more stress events for a period of time comprises: detecting the change in the stress rhythm equilibrium based on the determination of the change in the RHR value and the HRV value.

5. The method as claimed in claim 1, wherein the one or more stress events indicates a nonexercise-related stress.

6. The method as claimed in claim 1, further comprises: determining a time of occurrence of the one or more stress events for obtaining the aggregate stress score.

7. The method as claimed in claim 1, wherein the preliminary value is indicative of a maximum score derived from various data points associated with the physiological data collected by a wearable device.

8. The method as claimed in claim 1, wherein the predefined value is obtained based on the correlation of the circadian cycle of the user with respect to the RHR value and the HRV value.

9. The method as claimed in claim 1, wherein the aggregate stress score that is obtained based on the deduction of the predefined value from the preliminary value follows a negative scoring model.

10. The method as claimed in claim 7, wherein the wearable device (101) corresponds to one of a smart watch, a smart band, or an electronic ring.

11. A system for monitoring physiological stress of a user, the system comprises one or more processors (801) configured to: receive physiological data associated with the user from a plurality of sensors and a user input, wherein the physiological data includes at least one of a resting heart rate (RHR) value, a heart rate variability (HRV) value, a temperature value, movement information, sleeping pattern information; identify a circadian cycle of the user based on an analysis of the physiological data; determine a change in at least one of the RHR value and the HRV value is due to an associated activity of the user based on the result of the analysis of the physiological data and a correlation of the circadian cycle of the user with respect to the RHR value and the HRV value; detect one or more stress events associated with the user based on the determination that the change in at least one of the RHR value and the HRV value is not due to the associated activity of the user; deduct a predefined value from a preliminary value based on the determination that the increase in at least one of the RHR value and the HRV value is not due to the associated activity of the user and a time of occurrence of the one or more stress events; obtain the aggregate stress score based on a deduction of the predefined value from a preliminary value;assign a stress score to each of the one or more stress events based on a result of a processing of the physiological data and a result of the correlation of the circadian cycle of the user with respect to the RHR value and the HRV value; analyze the stress score corresponding to each of the one or more stress events with respect to at least one of a predefined threshold values to determine a level of stress the user is experiencing in a predefined period of time; and display, via a user interface (UI), the level of stress along with the stress score and an observation on the level of stress for the user.

12. The system as claimed in claim 6, wherein the one or more processors (801) are configured to: analyse the physiological data of the user with respect to a pre-classified circadian zones; and generate a personal profile of the user having a chronotype based on the circadian cycle of the user.

13. The system as claimed in claim 7, further comprising correlating the RHR value, the HRV value, and cortisol levels of the user with the pre-classified circadian zones based on the analysis of the physiological data.

14. The system as claimed in claim 1, wherein the one or more processors (801) are configured to: detect the change in the stress rhythm equilibrium based on the determination of the change in the RHR value and the HRV value.

15. The system as claimed in claim 11, wherein the one or more stress events indicates a nonexercise-related stress.

16. The system as claimed in claim 11, wherein the one or more processors (801) are configured to:determine a time of occurrence of the one or more stress events for obtaining the aggregate stress score.

17. The system as claimed in claim 11, wherein the preliminary value is indicative of a maximum score derived from various data points associated with the physiological data collected by a wearable device (101).

18. The system as claimed in claim 11, wherein the predefined value is obtained based on the correlation of the circadian cycle of the user with respect to the RHR value and the HRV value.

19. The system as claimed in claim 11, wherein the aggregate stress score that is obtained based on the deduction of the predefined value from the preliminary value follows a negative scoring model.

20. The system as claimed in claim 17, wherein the wearable device (101) corresponds to one of a smart watch, a smart band, or an electronic ring.

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