DEVICE AND METHOD FOR STRESS ASSESSMENT USING PHYSIOLOGICAL DATA - Patent application

Abstract

The present disclosure generally relates to a measurement device (110) and method (200 / 300) for assessing a user's stress. The measurement device (110) includes a sensor module for measuring several physiological data sets, each measured over a time period, a database (112) for storing the data, and a display module (116) for displaying visual information (400 / 420 / 440). The method (200 / 300) includes the steps of: determining a stress parameter for each data set for comparison with a predetermined stress criterion; identifying a first stress parameter for a current time period; generating a stress alert when a predetermined stress condition is determined to be met based on at least the first stress parameter; and displaying visual information (400 / 420 / 440) corresponding to the stress alert, the visual information assisting in alleviating the stress state, where the stress condition is met when the first stress parameter indicates the user's stress state relative to the predetermined stress criterion. [Selected Figure] Figure 1A

Description

[Technical field]

[0001] (CROSS REFERENCE TO RELATED APPLICATIONS) This disclosure claims the benefit of Singapore Patent Application No. 10201801851S, filed March 2, 2018, which is incorporated herein by reference in its entirety.

[0002] The present disclosure relates generally to devices and methods for stress assessment. More specifically, the present disclosure describes various embodiments of devices and methods for performing stress assessment on a user or human being using physiological data measured from the user. [Background technology]

[0003] Various kinds of measuring or sensing devices have emerged to help people self-monitor their health by measuring physiological data from their bodies, such as blood pressure, heart rate, and heart rate variability. Summary of the Invention [Problem to be solved by the invention]

[0004] However, these devices may not provide sufficiently accurate self-monitoring of health conditions, e.g., with regard to stress assessment, etc. Furthermore, many measurement or detection devices do not provide people with useful feedback regarding their own stress management.

[0005] Therefore, there is a need to provide improved devices and methods for stress assessment to address or mitigate at least one of the above-mentioned problems and / or shortcomings. [Means for solving the problem]

[0006] According to a first aspect of the present disclosure, there is a measurement device for stress assessment of a user. The measurement device comprises a sensor module with a photoplethysmography (PPG) sensor for measuring several physiological data sets from a user, each measured during a separate time period, a database for storing the physiological data, a display module with a set of graphical user interface (GUI) portions for displaying visual information from the stress assessment based on the physiological data, and a processor. The processor is configured to determine stress parameters for each physiological data set for comparison with a predetermined stress criterion, identify a first stress parameter for a current time period, generate a stress alert when a predetermined stress condition is determined to be met based on at least the first stress parameter, and communicate the stress alert to the display module for displaying visual information corresponding to the stress alert, the visual information being helpful to the user in alleviating a stress state, on at least one of the GUI portions, the stress condition being met when the first stress parameter indicates a stress state of the user compared to the predetermined stress criterion.

[0007] According to a second aspect of the present disclosure, there is a computerized method executed by a measurement device for stress assessment of a user and a non-transitory computer readable storage medium having instructions stored thereon that, when executed, cause a processor of the measurement device to execute the method, the method comprising: retrieving from a database of the measurement device several physiological data sets measured from a user, each physiological data set being measured during a distinct time period, determining a stress parameter for each physiological data set for comparison with a predefined stress criterion, identifying a first stress parameter for a current time period, generating a stress alert when a predefined stress condition is determined to be met based on at least the first stress parameter, and displaying visual information corresponding to the stress alert in at least one graphical user interface (GUI) portion, the visual information being useful in aiding a user in alleviating a stress condition, the stress condition being met if the first stress parameter is indicative of a stress state of the user compared to the predefined stress criterion.

[0008] According to a third aspect of the present disclosure, there is a computerized method executed by an electronic device for stress assessment of a user and a non-transitory computer readable storage medium having instructions stored thereon that, when executed, cause a processor of the electronic device to execute the method, the method comprising: receiving from a measurement device a measurement dataset including several physiological datasets measured from a user, each physiological dataset being measured during a distinct time period; storing the measurement dataset in a database of the electronic device; determining a stress parameter for each physiological dataset to compare with a predefined stress criterion; identifying a first stress parameter for a current time period; generating a stress alert when a predefined stress condition is determined to be met based on at least the first stress parameter; and displaying visual information corresponding to the stress alert in at least one graphical user interface (GUI) portion to aid a user in alleviating a stress condition, the stress condition being met if the first stress parameter is indicative of a stress state of the user compared to the predefined stress criterion.

[0009] Thus, devices and methods for stress assessment according to the present disclosure are disclosed herein. Various features, aspects, and advantages of the present disclosure will become more apparent from the following detailed description of embodiments thereof, by way of non-limiting examples only, taken in conjunction with the accompanying drawings. [Brief description of the drawings]

[0010] [Figure 1A] FIG. 1 is a schematic diagram of a system including a measurement device, an electronic device, and a remote server for stress assessment of a user according to an embodiment of the present disclosure. [Figure 1B] FIG. 1 is a schematic diagram of a measurement device according to an embodiment of the present disclosure. [Figure 1C]1 is a schematic diagram of an electronic device according to an embodiment of the present disclosure. [Diagram 2] 1 is a flowchart of a computerized method performed by a measurement device for stress assessment of a user according to an embodiment of the present disclosure. [Diagram 3] 1 is a flowchart of a computerized method performed by an electronic device for stress assessment of a user according to an embodiment of the present disclosure. [Figure 4A] FIG. 1 is a diagram of a graphic / screen displayed on a measurement device / electronic device for visual information according to an embodiment of the present disclosure. [Figure 4B] FIG. 1 is a diagram of a graphic / screen displayed on a measurement device / electronic device for visual information according to an embodiment of the present disclosure. [Figure 4C] FIG. 1 is a diagram of a graphic / screen displayed on a measurement device / electronic device for visual information according to an embodiment of the present disclosure. [Figure 5A] FIG. 1 is a diagram of a time space having multiple consecutive and discrete time periods for determining stress parameters to generate a stress alert according to an embodiment of the present disclosure. [Figure 5B] FIG. 1 is a diagram of a time space having multiple consecutive and discrete time periods for determining stress parameters to generate a stress alert according to an embodiment of the present disclosure. [Figure 5C] FIG. 1 is a diagram of a time space having multiple consecutive and discrete time periods for determining stress parameters to generate a stress alert according to an embodiment of the present disclosure. [Figure 6] FIG. 1 is a general time-space diagram for determining stress parameters to generate a stress alert according to an embodiment of the present disclosure. [Figure 7A] FIG. 13 is an illustration of a histogram graphic / screen displayed on an electronic device for visualizing a user's cumulative stress pattern according to an embodiment of the present disclosure. [Figure 7B]FIG. 13 is an illustration of a histogram graphic / screen displayed on an electronic device for visualizing a user's cumulative stress pattern according to an embodiment of the present disclosure. [Figure 8] FIG. 1 is a block diagram of the technical architecture of a computer according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] For brevity and clarity, the description of the embodiments of the present disclosure relates to a system and method for securing data communication between computers according to the drawings. It will be understood that although aspects of the present disclosure are described in conjunction with the embodiments presented herein, they are not intended to limit the present disclosure to these embodiments. Rather, the present disclosure is intended to encompass alternatives, modifications, and equivalents of the embodiments described herein that fall within the scope of the present disclosure as defined by the appended claims. Furthermore, in the following detailed description, specific details are described to provide a thorough understanding of the present disclosure. However, individuals of ordinary skill in the art, i.e., those skilled in the art, will appreciate that the present disclosure can be practiced without the specific details and / or with numerous details resulting from combinations of aspects of the specific embodiments. In some cases, well-known systems, methods, procedures, and components have not been described in detail so as not to unnecessarily obscure aspects of the embodiments of the present disclosure.

[0012] In embodiments of the present disclosure, the depiction of a given element or consideration or the use of a particular element number in a particular figure or corresponding explanatory material in reference to that figure can encompass the same, equivalent, or similar element or element number identified in another figure or explanatory material associated therewith.

[0013] References to an "embodiment / example," "another embodiment / example," "some embodiments / examples," "some other embodiments / examples," etc. mean that the embodiment / example so described may include a particular feature, structure, characteristic, attribute, element, or limitation, but not all embodiments / examples necessarily include that particular feature, structure, characteristic, attribute, element, or limitation. Furthermore, repeated use of the phrase "in an embodiment / example" or "in another embodiment / example" do not necessarily refer to the same embodiment / example.

[0014] The terms "comprising...", "including...", "having...", etc. do not exclude the presence of other features / elements / steps than those listed in an embodiment. Even if certain features / elements / steps are described in different embodiments, it does not mean that these features / elements / steps cannot be used in combination in an embodiment.

[0015] As used herein, the terms "a" and "an" are defined as one or more than one. The use of " / " in the figures or related text is understood to mean "and / or" unless otherwise specified. The term "set" is defined as a non-empty, finite organization of elements that mathematically exhibits a cardinality of at least 1 according to known mathematical definitions (e.g., a set as defined herein can correspond to a set of units, singlets, or single elements, or a set of multiple elements). Recitation of a particular numerical value or range of values ​​herein is understood to include or be a recitation of an approximate numerical value or range of values.

[0016] As used herein, the terms "component," "module," "system," "interface," and the like are intended to generally refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution. For example, a component or module may be, but is not limited to, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and / or a computer. As examples, both an application running on a controller and a controller may be a component / module. One or more components / modules may reside within a process and / or thread of execution. A component / module may be centralized on one computer or further / or distributed across multiple computers.

[0017] In an exemplary or representative embodiment of the present disclosure, as shown in FIG. 1A, there is a system 100 comprising a measurement or detection device 110, an electronic device 130, and a remote server 150 communicatively connected via a communication network 170. The measurement device 110 is configured to measure physiological data from a user and to perform a stress assessment of the user based on the physiological data. The electronic device 130 is configured to perform a stress assessment of the user based on the physiological data received from the measurement device 110 via the communication network 170. The remote server 150 is configured to assess the user's stress, in particular a long-term or chronic stress state, based on the physiological data received from the measurement device 110 and / or the electronic device 130, as well as the user's historical physiological data.

[0018] The measuring device 110 comprises a first database 112 that resides on-site at the measuring device 110. The electronic device 130 comprises a second database 132 that resides on-site at the electronic device 130. The remote server 150 comprises a third database 152 that resides on-site at the remote server 150. The databases 112, 132, and 152 can comprise data storage devices, flash storage memory, hard drives, etc. for storing the physiological data.

[0019] The measuring device 110 is a physiological monitor that is connected or connectable to a user to measure and collect physiological data of the user. The physiological data is then used for stress assessment of the user. The physiological data is related to or derived from the user's vascular activity, such as volume changes resulting from fluctuations in blood flow in blood vessels in the area where the measuring device 110 is attached. The measuring device 110 may be in the form of a wearable device that is worn or attached to the user, such as on a fingertip, on the wrist, any part of the arm, or any part of the neck. For example, the measuring device 110 is in the form of a watch that can be worn on the user's wrist. The measuring device 110 may be configured to measure physiological data only if battery power is sufficient.

[0020] Physiological data includes data regarding a user's vital signs measurable from vascular activity, such as, but not limited to, heart rate, heart rate variability, blood pressure, pulse shape variability, and any combination thereof. Pulse shape variability may be referred to as the standard deviation of a vital sign feature derived from the pulse shape of an input physiological signal (e.g., a PPG signal) and may be calculated, for example, based on pulse time interval information, skewness, magnitude, integral and derivative information, frequency content, or derivatives thereof.

[0021] The measuring device 110 comprises a sensor module for measuring physiological data. In particular, the sensor module includes a photoplethysmography (PPG) sensor for measuring several physiological data sets (i.e., at least one physiological data set) from the user, each physiological data set being measured in a separate time period. For example, the physiological data sets can be measured in a time period ranging from 1 minute to 5 minutes, although other time periods are possible. In some embodiments, the PPG sensor is a pulse oximeter sensor having an illumination element, e.g., a light emitting diode (LED), and at least two photodetectors / photodiodes for measuring physiological data resulting from the user's vascular activity. The illumination element may be located between the two photodetectors or adjacent to the two photodetectors.

[0022] In each cardiac cycle, the heart pumps blood to the body's extremities (e.g., wrist and fingers) through pressure pulses. The pressure pulses are sufficient to dilate blood vessels in the subcutaneous tissue within the body's skin, thus changing the blood volume in the subcutaneous tissue within the body's skin. The pulse oximeter sensor measures the vascular activity resulting from blood circulation in the body. Specifically, the pulse oximeter sensor indirectly measures the amount of oxygen in the blood by revealing the oxygen saturation level (SO2) of hemoglobin in the blood, and also measures the change in blood volume within the body's skin. The change in volume caused by the pressure pulse is detectable by illuminating the skin with the illumination element of the pulse oximeter sensor and measuring the amount of light transmitted or reflected to the photodetector / photodiode. The measurement device 110 is worn or attached near the skin of the user's body so that the PPG or pulse oximeter sensor can measure physiological data by illuminating the skin and detecting changes in light absorption. The physiological data is measured as at least one set of data signals or waveforms, i.e., a photoplethysmogram, having a series of physiological data.

[0023] The electronic device 130 is a computer or computing device operated by a user. Some examples of the electronic device 130 include, but are not limited to, desktop devices, mobile devices, personal digital assistants (PDAs), mobile phones, tablets, phablets, laptop computers, and any other electronic communication that may have a processor, microprocessor, central processing unit, or controller. The electronic device 130 can communicate with the measurement device 110 and the remote server 150 via a communication network 170, for example, to share physiological data.

[0024] The remote server 150 is a computer server that is located remotely from the electronic device 130, i.e., does not share the same local network of the electronic device 130. The remote server 150 is a physical data processing system or a cloud data processing system that runs a server program. The server can be implemented in hardware or software, or a combination thereof. Servers include computers, laptops, minicomputers, mainframe computers, any non-transient and tangible machine capable of executing machine-readable code, cloud-based servers, distributed server networks, and networks of computer systems.

[0025] The communication network 170 is a medium or environment for communicating content, notifications, and / or messages between various entities including the measurement device 110, the electronic device 130, and the remote server 150. Some examples of the communication network 170 include, but are not limited to, a virtual private network (VPN), a wireless fidelity (Wi-Fi) network, a light fidelity (Li-Fi) network, a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a satellite network, the Internet, a fiber optic network, a coaxial cable network, an infrared (IR) network, a radio frequency (RF) network, and any combination thereof. Connections to the communication network 170 can be by various wired and wireless communication protocols such as Transmission Control Protocol / Internet Protocol (TCP / IP), User Datagram Protocol (UDP), 2nd-5th Generation (2G-5G), Long Term Evolution (LTE), Long Range (LoRa), and any combination thereof. Each of the measurement device 110, the electronic device 130, and the remote server 150 includes a data communication or transceiver module for communication and transmission / reception of data over the communication network 170. Some examples of transceiver modules include, but are not limited to, an antenna module, a radio frequency transceiver module, a wireless transceiver module, a Bluetooth transceiver module, an Ethernet port, a Universal Serial Bus (USB) port, or any combination thereof. Furthermore, communication over the communication network 170 can be secured by protocols such as Hypertext Transfer Protocol Secure (HTTPS) and / or implemented with a network security system such as a computing firewall, as would be readily understood by one of ordinary skill in the art.

[0026] In some embodiments, the measuring device 110 can communicate with the electronic device 130 via wireless / contactless communication protocols such as Bluetooth, Wi-Fi, and Near Field Communication (NFC) communication protocols. For example, the measuring device 110 and the electronic device 130 can share the same Wi-Fi network and can communicate data between them. Furthermore, the measuring device 110 may be able to communicate with the electronic device 130 via wired communication such as USB. The electronic device 130 can communicate with the remote server 150 via the Internet, etc. Thus, the electronic device 130 acts as an intermediate device between the measuring device 110 and the remote server 150 so that the measuring device 110 can communicate with the remote server 150 via the electronic device 130. For example, the measuring device 110 measures physiological data and stores the physiological data in the first database 112. The measuring device 110 can automatically communicate the physiological data to the electronic device 130 and thereby communicate to the remote server 150. Alternatively, the measuring device 110 can first communicate the physiological data to the electronic device 130 for storage in the second database 132, and then the electronic device 130 communicates the physiological data at a later point in time to the remote server 150 for storage in the third database 152. This may occur when a user is being measured by the measuring device 110 and has zero or limited network connectivity. In some other embodiments, the measuring device 110 can communicate directly with the remote server 150, for example over the internet, to share the physiological data directly.

[0027] 1B, the measurement device 110 includes a device body 114 and a display module 116. The display module 116 includes a graphical user interface (GUI) 118 having a set of graphical user interface (GUI) portions 120 for displaying visual information from a user's stress assessment based on physiological data. The visual information may be derived from processing of the physiological data and displayed in one or more of the GUI portions 120 or throughout the GUI 118. In some embodiments, the GUI 118 includes a first GUI portion 120a, a second GUI portion 120b, and a third GUI portion 120c. It will be appreciated that each of the GUI portions 120a-c may be repositioned anywhere on the GUI 118.

[0028] 1C, electronic device 130 includes device body 134 and display module 136. Display module 136 includes GUI 138 having a set of GUI portions 140 for displaying visual information from a user's stress assessment based on physiological data. The visual information may be derived from processing of the physiological data and displayed in one or more of GUI portions 140 or throughout GUI 138. In some embodiments, GUI 138 includes first GUI portion 140a, second GUI portion 140b, and third GUI portion 140c. It will be appreciated that each of GUI portions 140a-c may be repositioned anywhere on GUI 138.

[0029] In one embodiment, a user downloads a software application, such as a mobile app, and installs it on an electronic device 130, such as a mobile phone. In another embodiment, the software application is a web application or web-based application accessible using a browser running on the electronic device 130. The web application or web-based application may be hosted on a remote server 150 such that it may be accessed by multiple users using multiple electronic devices 130. The software application may operate on a subscription basis such that a user is required to pay a subscription fee to use the stress assessment functionality utilized by the software application.

[0030] A software application is executable on the electronic device 130 to perform a stress assessment of the user. The user may be asked to set up his / her profile when using the software application for the first time. During this set-up or registration procedure, the user inputs a set of relevant personal information, including gender, date of birth, weight, height, occupation, and a set of physiological information such as health conditions. The personal information and physiological information are used to determine a baseline state for the user's stress assessment, e.g., a normal / non-stress state for reference.

[0031] After the registration procedure, the user sets the measuring device 110 to associate with the electronic device 130, for example by Bluetooth pairing. The association between the measuring device 110 and the electronic device 130 allows the measuring device 110 to communicate measured physiological data to the electronic device 130. Personal information and physiological information may be communicated from the electronic device 130 to the measuring device 110, along with baseline conditions.

[0032] 2, there is shown a computer-implemented or computerized method 200 for stress assessment of a user. The method 200 is implemented on or performed by a measurement device 110 that comprises various modules / components for performing the various steps of the method 200, such as a processor for executing program instructions.

[0033] The method 200 includes retrieving 202 several physiological data sets (i.e., at least one physiological data set) measured from the user from the first database 112, each physiological data set measured at a separate time period. The method 200 includes determining 204 a stress parameter of each physiological data set for comparison with a predefined stress criterion. The method 200 includes identifying 206 a first stress parameter for a current time period. The method 200 includes generating 208 a stress alert when it is determined that a predefined stress condition is met based on at least the first stress parameter. In particular, the stress condition is met if the first stress parameter is indicative of the user's stress state relative to the predefined stress criterion. The method 200 includes displaying 210 visual information corresponding to the stress alert on at least one GUI portion 120 of the measuring device 110, the visual information assisting the user in alleviating the stress state.

[0034] In some embodiments, the measuring device 110 shares the physiological data with the electronic device 130 so that the electronic device 130 performs a stress assessment of the user. In one embodiment, the physiological data is measured and stored in the first database 112 before communicating the physiological data to the electronic device 130, e.g., upon request by the user. In another embodiment, there is an active communication link between the measuring device 110 and the electronic device 130 so that the physiological data is automatically shared with the electronic device 130 immediately or a short time after the measurement. Similarly, there may be an active communication link between the electronic device 130 and the remote server 150 so that the physiological data is automatically shared with the remote server 150.

[0035] 3, there is shown a computer-implemented or computerized method 300 for stress assessment of a user. The method 300 is implemented on or performed by an electronic device 130 that comprises various modules / components for performing the various steps of the method 300, such as a processor for executing program instructions.

[0036] The method 300 includes receiving 302 a measurement dataset from the measurement device 110, the measurement dataset including several physiological datasets (i.e., at least one physiological dataset) measured from a user, each physiological dataset being measured at a separate time period. The method 300 includes storing 304 the measurement dataset on the second database 132. The method 300 includes determining 306 a stress parameter of each physiological dataset for comparison with a predefined stress criterion. The method 300 includes identifying 308 a first stress parameter for the current time period. The method 300 includes generating 310 a stress alert when it is determined that a predefined stress condition is met based on at least the first stress parameter. In particular, the stress condition is met if the first stress parameter is indicative of the user's stress state relative to the predefined stress criterion. The method 300 includes displaying 312 visual information corresponding to the stress alert on at least one GUI portion 140 of the electronic device 130, the visual information assisting the user in alleviating the stress state.

[0037] In steps 202 and 302, physiological data sets are measured from the user using the measurement device 110 prior to the determination of the stress parameters. Each physiological data set is measured for a distinct time period that may range from 1 minute to 5 minutes, although other time periods such as 10 minutes, 30 minutes, 1 hour, etc. are possible. The duration of the distinct time periods may be adjustable by the user using a software application on the electronic device 130 or by using the measurement device 110. The physiological data sets are collected to form a series of physiological data. For example, the series of physiological data includes 12 physiological data sets, each set measured for a distinct time period of 5 minutes, such that the series of physiological data is measured in a time space of 1 hour. It will be appreciated that the distinct time periods and number of physiological data sets in the series of physiological data are adjustable to customize the measurement of the physiological data to the user's preferences.

[0038] In steps 204 and 306, stress parameters are determined for each physiological data set at each time period for comparison with a predefined stress criterion. The stress parameters may include a stress score or index calculated using a predefined algorithm applied to physiological data such as heart rate, heart rate variability, blood pressure, pulse shape variability, and any combination thereof. The predefined stress criterion may be a baseline stress score or index derived from the user's baseline condition determined during the enrollment procedure. Additionally, the user's stress criterion may be further determined based on national average stress patterns and / or stress parameters and stress criteria from a user population.

[0039] Steps 206 and 308 identify a first stress parameter for the current time period. The first stress parameter may indicate a user's stress state relative to a predetermined stress criterion. For example, if the first stress parameter is equal to or greater than the stress criterion, the user may be in a stressed state. Conversely, if the first stress parameter is lower than the stress criterion, the user may be in a normal / non-stressed state.

[0040] The predetermined stress criterion may be adjustable by the user to vary the sensitivity of the stress state indication. For example, the user may increase the stress criterion so that the stress parameter is less likely to indicate a stress state. The software application may present several levels of the predetermined stress criterion for selection by the user.

[0041] In some embodiments of the method 200 / 300, the predetermined stress condition is met based on the first stress parameter and the second stress parameter. In one embodiment, the method 200 / 300 optionally includes identifying a second stress parameter for a second time period preceding the current time period. Thus, the current time period is consecutive to the second time period. If the second stress parameter also indicates a stress state of the user relative to the predetermined stress criteria, the stress condition is met.

[0042] In another embodiment, the method 200 / 300 optionally includes identifying a recent stress state of the user based on stress parameters for earlier time periods prior to the current time period, the recent stress state being indicated by the second stress parameter for the earliest of the earlier time periods. The earliest time period for which the second stress parameter indicates a stress state may be immediately before or before the current time period. Furthermore, if the second stress parameter indicates a recent stress state of the user and none of the stress parameters for the other earlier time periods indicates a normal state of the user, the stress condition is met.

[0043] In some embodiments of the method 200 / 300, the predetermined stress condition is met based on the first stress parameter, the second stress parameter, and the third stress parameter. In one embodiment, the method 200 / 300 optionally includes identifying a second stress parameter for a second time period preceding the current time period and identifying a third stress parameter for a third time period preceding the second time period. Thus, the current time period, the second time period, and the third time period are consecutive time periods. The stress condition is met if both the second and third stress parameters are also indicative of the user's stress state relative to the predetermined stress criteria.

[0044] In another embodiment, the method 200 / 300 optionally includes identifying two most recent stress states of the user based on stress parameters for earlier time periods prior to the current time period, the most recent stress states being indicated by second and third stress parameters for second and third respective ones of the earlier time periods, the third time period being the earliest one of the earlier time periods. Further, if both the second and third stress parameters indicate a most recent stress state of the user and none of the stress parameters of the other earlier time periods indicate a normal state of the user, the stress condition is met.

[0045] In some embodiments of the method 200 / 300, the predetermined stress condition is met based on the first stress parameter and a plurality of recent stress parameters. The method 200 / 300 optionally includes identifying a plurality of recent stress states of the user based on stress parameters for earlier time periods prior to the current time period, the recent stress state being indicated by the plurality of recent stress parameters for the plurality of recent ones of the earlier time periods, the plurality of recent stress parameters including an earliest stress parameter for an earliest one of the earlier time periods. Furthermore, the stress condition is met if all of the plurality of recent stress parameters indicate a recent stress state of the user and none of the stress parameters for the other earlier time periods indicate a normal state of the user.

[0046] By matching two or more stress parameters indicative of a stressed state for two or more separate time periods, e.g., consecutive time periods, a stress pattern can be established that improves accuracy in determining whether the user is in a stressed state. However, this chain of stress parameters may be broken if one of the stress parameters indicates a normal state for the user, and the earlier stress parameters may be ignored. For example, stress parameters for all time periods prior to the current time period are ignored for a stressed condition if the first stress parameter indicates a normal state for the user.

[0047] The measuring device 110 can determine the measurement conditions for each physiological data set. The measurement conditions may affect the accuracy of the measured physiological data. If the measurement conditions are determined to be insufficient, such as not meeting the user's criteria conditions determined during the registration procedure or some other set of common criteria conditions applicable for all measuring devices 110, the physiological data sets measured under these insufficient measurement conditions are discarded. In one embodiment, discarding the physiological data may mean permanently deleting the physiological data. In another embodiment, the physiological data may still be stored in the first database 112 for later communication to the electronic device 130 and the remote server 150, but will not be considered for stress assessment. Since the physiological data for this time period is discarded, it is not possible to determine the stress parameters for this time period. This is considered to indicate an invalid or null state, since it is not possible to determine whether the user is in a stressed state or a normal state. If there is no physiological data for a time period, the result is also considered to be null.

[0048] Each of the measuring device 110 and the electronic device 130 is configured to display various graphics / screens on the respective GUIs 118 and 138 during measurement of physiological data from the user and / or during processing of the physiological data for stress assessment. With reference to Figs. 4A to 4C, there is a first graphic 400, a second graphic 420, and a third graphic 440 that can be displayed on the GUIs 118 and 138. The graphics 400 / 420 / 440 display visual information related to stress assessment to the user. In the measuring device 110, the graphics 400 / 420 / 440 can be displayed on any of the GUI portions 120. Similarly, in the electronic device 130, the graphics 400 / 420 / 440 can be displayed on any of the GUI portions 140.

[0049] Visual information from the stress assessment can be presented to the user on the GUI 118 / 138. The visual information can include a color indicator in monochrome (black and white), grayscale, and / or a color palette. During the measurement of the physiological data in each time period, the visual information can be presented to the user in the form of a first graphic 400 and / or a second graphic 420. The first graphic 400 can be presented in a monochrome or grayscale palette. The first graphic 400 as shown in FIG. 4A includes a normal icon 402 representing a normal / non-stressed state, a stress icon 404 representing a stressed state, and a null icon 406 representing a null state. The second graphic 420 can be presented in a monochrome, grayscale, or color palette. The second graphic 420 as shown in FIG. 4B includes a normal icon 422 representing a normal / non-stressed state when no stress alert is generated, a stress icon 424 representing a stressed state when a stress alert is generated, and a null icon 426 representing a null state. The normal, stress, or null state for each time period is determined from processing of the physiological data as described above.

[0050] FIG. 5A illustrates an example of a time space 510 having multiple consecutive and distinct time periods for which stress parameters have been determined. A series of stress parameters in the time space 510 can be displayed on the measurement device 110. In particular, the first to last time periods are arranged from right to left, with the first time period referring to the current time period. Each stress parameter is represented by a normal icon 402, a stress icon 404, or a null icon 406. A stress alert 500 is generated when it is determined that a predetermined stress condition is met based on at least the first stress parameter or the current stress parameter. In particular, if the first stress parameter, which may be for any current time period, indicates a stress state, the stress condition is met. If the first stress parameter indicates a normal or null state, the stress alert 500 is not generated.

[0051] 5B shows another example of a time space 520 having multiple consecutive and distinct time periods for which a stress parameter was determined. The series of stress parameters in the time space 520 can be displayed on the measurement device 110. In the time space 520, two stress parameters indicative of a stress condition are generally required for a stress alert 500 to be generated, for example when a stress condition exists in two consecutive time periods. In a first group 522 of a first and second time period in the time space 520, both the first and second stress parameters are indicative of a stress condition. A stress condition is met and a stress alert 500 is generated.

[0052] In the second group 524, the first stress parameter for the first time period indicates a stressed state, while the second stress parameter for the second time period indicates a null state. Thus, the user's recent stress state is identified based on the stress parameters for the earlier time periods before the first time period. The recent stress state is indicated by the recent stress parameter for the earliest of the earlier time periods. In the second group 524, the recent stress parameter is a third stress parameter for a third time period, which is indicative of a stressed state. None of the stress parameters for the other earlier time periods (i.e., the second stress parameter for the second time period) indicates a normal state. The stress condition is met and a stress alert 500 is generated. In particular, if the first and last stress parameters indicate a stressed state and the intervening stress parameters do not indicate a normal state (may indicate a null state), the stress condition is met and a stress alert 500 is generated.

[0053] If a normal state is indicated in any time period, the chain of stress parameters of all earlier time periods up to that time period is "broken" and the stress parameters of all earlier time periods are ignored. As an illustrative example, in the third group 526, the first and third stress parameters indicate a stressed state and the second stress parameter indicates a normal state. There are two stress parameters indicating a stressed state, but the second stress parameter indicating a normal state "breaks" the chain of stress parameters. Thus, the third stress parameter, as well as the earlier stress parameters, are ignored in determining whether the stress condition is met. Because only the first stress parameter indicates a stressed state, no stress alert 500 is generated, i.e., it is considered a non-alert 500'. If the next stress parameter for the next time period indicates a stressed state, the stress alert 500 is generated later in the next period.

[0054] 5C shows another example of a time space 530 having multiple consecutive distinct time periods for which stress parameters have been determined. The set of stress parameters in the time space 530 can be displayed on the measurement device 110. In the time space 530, three stress parameters indicative of a stress state are typically required for a stress alert 500 to be generated, e.g., if a stress state is present in three consecutive time periods. In a first group 532 of first to third time periods in the time space 530, all the first to third stress parameters are indicative of a stress state. The stress condition is met and a stress alert 500 is generated.

[0055] In the second group 534, the first and second stress parameters for the first and second time periods indicate a stressed state, while the third stress parameter for the third time period indicates a null state. Thus, the user's two most recent stress states are identified based on the stress parameters for an earlier time period before the first time period. The most recent stress state is indicated by the two most recent stress parameters for the two most recent time periods within the earlier time period, one of the two most recent time periods being the earliest of the earlier time periods. In the second group 534, the two most recent stress parameters are the second and fourth stress parameters for the second and fourth time periods, both of which indicate a stressed state. The fourth time period is also referred to as the one of the two most recent time periods that is the earliest of the earlier time periods. None of the stress parameters for the other earlier time periods (i.e., the third stress parameter for the third time period) indicate a normal state. The stress condition is met and a stress alert 500 is generated. In particular, if the first and last stress parameters indicate a stressed state and the intervening stress parameters include a stress parameter indicating a stressed state and do not include a stress parameter indicating a normal state (which may indicate a null state), then the stress condition is met and a stress alert 500 is generated.

[0056] Similar to the time space 520 of FIG. 5B, when a normal state is indicated in any time period, the chain of stress parameters of all earlier time periods up to that time period is broken and the stress parameters of all earlier time periods are ignored. As an illustrative example, in the third group 536, the first, third, and fourth stress parameters indicate a stress state and the second stress parameter indicates a normal state. There are three stress parameters indicating a stress state, but the second stress parameter indicating a normal state breaks the chain of stress parameters. Thus, the third and fourth stress parameters, as well as the earlier stress parameters, are ignored in determining whether the stress condition is met. Because only the first stress parameter indicates a stress state, no stress alert 500 is generated, i.e., it is considered to be a non-alert 500'. If the two next stress parameters for the two next time periods indicate a stress state, the stress alert 500 is later considered to be generated in the second next time period.

[0057] It will be appreciated that the user may set / adjust the predetermined stress conditions such that the stress alert 500 is generated based on various combinations / permutations of the various stress parameters for different time periods. To illustrate that this is a general example, there is a general time space having multiple consecutive, distinct time periods for which stress parameters have been determined. In this general time space, multiple stress parameters indicative of a stress state are generally required for the stress alert 500 to be generated, such as when a stress state exists in multiple consecutive time periods. If there is no continuity of stress states and the first stress parameter is indicative of a stress state, multiple recent stress states of the user are identified based on stress parameters for earlier time periods prior to the first time period. The recent stress state is indicated by multiple recent stress parameters for multiple recent time periods within the earlier time period. The multiple recent stress parameters include the earliest stress parameter for the earliest of the earlier time periods. Because a normal state breaks the chain of stress parameters, the stress condition is met if the first stress parameter and all of the multiple recent stress parameters indicate the user's recent stress state, and none of the stress parameters for other earlier time periods indicate the user's normal state.

[0058] With reference to the general time space 600 of FIG. 6 as an illustrative example, if a total of three stress parameters (including the first stress parameter for the current time period) indicative of a stressed state are required to satisfy the stress condition and generate the stress alert 500, the stress alert 500 is generated in the current time period 602, 604, and 606. If a total of four stress parameters indicative of a stressed state are required, the stress alert 500 is generated in the current time period 604 and 606. If a total of five stress parameters indicative of a stressed state are required, the stress alert 500 is not generated in any time period of the time space 600. Notably, the stress parameter for time period 608 (indicative of a normal state) breaks the chain of stress parameters and ignores the stress parameter for time period 602 (indicative of a stressed state). However, if the stress parameter for time period 608 indicates a stressed state or a null state, the stress alert 500 is generated in the current time period 606.

[0059] Considering stress parameters for multiple time periods in time space helps to establish a user's stress or mood pattern and more accurately inform the user of the user's overall stress state. It will be appreciated that additional stress parameters for additional preceding time periods may be considered collectively with stress parameters for subsequent time periods to establish the user's long-term or chronic stress pattern.

[0060] In steps 210 and 312, visual information corresponding to the stress alert 500 is displayed in at least one GUI portion 120 / 140. The visual information may be presented to the user in the form of a third graphic 440. The third graphic 440 may be presented in a color palette. The third graphic 440 includes a set of lighting elements (e.g., LEDs) 442. The third graphic 440 as shown in FIG. 4C includes three LEDs 442 arranged in a row, which are configured to illuminate a color indicator. When the stress alert 500 has not occurred, the color indicator is green, indicating that the user is in a normal state or mood. Conversely, when the stress alert 500 has occurred, the color indicator of the visual information corresponding to the stress alert 500 is purple. Surprisingly, the purple color indicator is helpful in calming the user's mood. Therefore, when the stress alert 500 occurs because the user is in a stressed state, it is believed that the visual information corresponding to the stress alert 500 is helpful in alleviating the user's stressed state.

[0061] The third graphic 440 and / or another graphic containing visual information corresponding to the stress alert 500 may appear as a visual pop-up notification on the GUI 118 / 138 to draw the user's attention. In some embodiments, the measuring device 110 includes a haptic module for generating haptic feedback corresponding to the stress alert 500. The haptic feedback may be in the form of a vibration that can be felt by a user wearing the measuring device 110, thus alerting the user to the stress condition. The software application may provide the user with the ability to configure the visual pop-up notification and the haptic feedback, such as the visual appearance and vibration intensity.

[0062] The visual information is presented to the user in real time based on live measurements of physiological data. Because stress states can change constantly and depend on the user's physiological responses, visual information can be displayed quickly to assist the user in combating and managing stress. The visual information and optional haptic feedback resulting from the stress alert 500 helps the user recognize his or her stress state and encourages the user to take action to reduce his or her stress state.

[0063] As described above, a time space, such as time spaces 510 / 520 / 530 shown in Figures 5A-5C, has a number of consecutive individual time periods. Each time period is the same, ranging from 1 minute to 5 minutes, although other ranges are possible. The various individual time periods may have the same duration, but may alternatively differ from one another. A series of physiological data is measured during the time space, and the series of physiological data is collectively considered in determining the user's stress state. The measurement of a series of physiological data by the measurement device 110 during a single time space may be known as a spot stress measurement.

[0064] When the measurement device 110 performs a new spot stress measurement, the new physiological data is stored as a first series of physiological data in the first database 112. The first series of physiological data can be shared with the electronic device 130 and / or the remote server 150 for further processing. For example, the first series of physiological data is communicated to the electronic device 130 for further processing, such as archiving, since the first database 112 cannot store more than one series of physiological data. The first series of physiological data can then be stored in the second database 132. The second database 132 may already have previous series of physiological data previously measured, such as second and third series of physiological data. The multiple series of physiological data can be collectively processed by the electronic device 130 to determine intermediate stress measurements and cumulative stress patterns.

[0065] In one embodiment as shown in FIG. 7A, the electronic device 130 may display a histogram graphic / screen 700 on the GUI 138 to visualize a user's cumulative stress pattern 702. The cumulative stress pattern 702 is formed from several time spaces. Each time space is associated with a cumulative stress parameter determined from a series of physiological data measured in that time space. The cumulative stress parameter for a time space may be determined based on an average or median value of the stress parameter for a time period within that time space. Thus, the cumulative stress pattern 702 as shown in the histogram graphic 700 is determined from the cumulative stress parameters and provides the user with visual information or feedback of the user's median stress measurement. The histogram graphic 700 helps the user to further recognize his mood and stress pattern.

[0066] In Figure 7A, a histogram graphic 700 shows a cumulative stress pattern 702 for a 12-hour time space. Each bar or section 704 of the cumulative stress pattern 702 represents or spans a one-hour time space. In another embodiment, as shown in Figure 7B, the electronic device 130 can display an alternative histogram graphic / screen 710 on the GUI 138 to visualize a user's cumulative stress pattern 712. Instead of the bars 704 of the histogram graphic 700, the histogram graphic 710 shows chart lines 714 across columns representing the 12-hour time space.

[0067] It will be appreciated that the cumulative stress pattern 702 / 712 may be displayed for any duration between 1 hour and 24 hours or longer. The cumulative stress pattern 702 / 712 may be updated with cumulative stress parameters for the new time space. In that case, the leftmost or rightmost time space may be removed from view (i.e., moved out of the GUI 138), the new time space may be added, and the cumulative stress pattern 702 / 712 may be updated. For example, the cumulative stress pattern 702 may be displayed for a 12 hour time space from 0600 to 1800 hours. As the next hour's set of physiological data is received, the cumulative stress parameters are determined and updated into the cumulative stress pattern 702 / 712. Specifically, the cumulative stress pattern 702 / 712 may be moved to display a 12 hour time space from 0700 to 1900 hours. Thus, the cumulative stress pattern 702 / 712 and histogram graphic 700 / 710 may be updated hourly (or at any other time interval).

[0068] A user can configure the cumulative stress pattern 702 / 712 to display a time space shorter than 12 hours or longer than 12 hours. For example, the cumulative stress pattern 702 / 712 can be displayed for a time space of one week or 168 hours. Each bar or section 704 of the cumulative stress pattern 702 or each column of the chart line 714 can represent or span a time space of one hour. A user can adjust the visualization of the cumulative stress pattern 702 / 712 on the histogram graphic 700 / 710, for example, by adjusting each bar or section 704 of the cumulative stress pattern 702 or each column of the chart line 714. For example, each bar or section 704 or each column may span 12-14 hours instead of one hour. Additionally, the user may reset the intermediate stress measurements and cumulative stress patterns 702 / 712 at any given time / interval, such as daily or weekly, a predefined number of days, or at a predefined time such as the end of each day.

[0069] In some embodiments, the user can set the measuring device 110 to reset, for example, daily or weekly, since the first database 112 may not be able to store further physiological data. The measured physiological data can be transferred to the electronic device 130 and / or the remote server 150 for further processing and for storage / archiving in the second database 132 and / or the third database 152, respectively. In particular, the remote server 150 can store the user's historical physiological data in the third database 152 to perform long-term stress measurements, for example to reveal long-term or chronic stress patterns.

[0070] In one embodiment, the remote server 150 receives a measurement dataset from the measurement device 110 or the electronic device 130. The measurement dataset includes multiple physiological datasets measured from the user. The measurement dataset is stored in a third database 152 together with the user's previously acquired historical measurement datasets. The user's measurement datasets can be collectively used to derive various information of the user. For example, the remote server 150 can apply algorithms to the measurement datasets to calculate the user's activity, the user's sleep activity, the user's stress parameters, etc. The total period of the long-term measurement, i.e. the total period of all time spaces from all measurement datasets, can range from a few days to several years, as can be adjusted by the user. Various algorithms and statistical methods can be implemented to perform a long-term stress measurement based on all measurement datasets. The user can request a periodic summary of the measurement datasets and the long-term stress pattern, for example in a daily, weekly or monthly format. The periodic summary can be communicated to the measurement device 110 / electronic device 130 and displayed on the respective GUI 118 / 138.

[0071] In some embodiments, the remote server 150 determines the user's long-term or chronic stress state from the long-term stress measurements against a reference data set. The reference data set can be derived from the user, national averages, and / or user population reference conditions. Additionally, the remote server 150 generates recommended content to alleviate the user's chronic stress state. The recommended content may be provided by a third-party service provider and shared with the remote server 150. Based on a particular user's measurement data set, the remote server 150 generates and distributes curated recommended content to the user. Some examples of recommended content include, but are not limited to, relaxation techniques (e.g., breathing exercises and mindfulness training), stress relief images / videos / audio, interactive information, exercise / fitness information (e.g., yoga or pilates), and recommended foods / supplements for stress relief. The recommended content can be communicated to the measurement device 110 / electronic device 130 and displayed on the respective GUIs 118 / 138.

[0072] In some embodiments, there is an active communication link between the measuring device 110, the electronic device 130 and the remote server 150 via the communication network 170. The active communication link facilitates automatic sharing of physiological data immediately or shortly after a measurement by the measuring device 110. In this way, a stress assessment of the user based on the physiological data is performed in real time by the measuring device 110, the electronic device 130 and the remote server 150. Similarly, the user can obtain visual information from the stress assessment in real time.

[0073] In one embodiment, a clinician can communicate with the remote server 150 to access stress assessments of a particular user, for example, who has previously been assessed by the clinician as being at risk for chronic stress. The long-term stress measurements performed by the remote server 150 provide the clinician with a more accurate and insightful long-term stress pattern of the user. The long-term stress pattern helps the clinician check the mental state of the user and allows the clinician to review the user's stress pattern over time. The clinician can provide the user with appropriate stress-relieving exercises and administer medication in very serious situations. Furthermore, the clinician can take the long-term stress pattern into account when assessing other health conditions of the user, such as high blood pressure and sleep-related conditions.

[0074] As mentioned above, the absence of physiological data for a period of time is considered to be a null state. In one embodiment, the null state results in the communication of a null signal from the measuring device 110 to the electronic device 130 / remote server 150. The null signal alerts the clinician to a state where no physiological data is available for that period of time. The remote server 150 can track the measurement of physiological data in real time, and if no physiological data is received for a certain period of time, the clinician can infer an untoward condition for the user. For example, some users may face extreme stress conditions, and the clinician can infer that the user is in a state of distress, such as a state of desperation or a situation that leads to self-harm or harm to others. In a more specific example, the user may be wearing the measuring device 110 (in the form of a watch) on the wrist, and the measuring device 110 is continuously measuring physiological data. However, in the next period of time, a null signal is provided, which may mean that a change in the measurement of physiological data has occurred, such as the user cutting their wrist, causing profuse bleeding from the wrist and abruptly ending the measurement. The null signal aids the clinician in assessing whether the user is in distress and whether immediate remedial action is required.

[0075] 8 is a block diagram illustrating the technical architecture of a computer 800 according to an embodiment of the present disclosure. Some non-limiting examples of the computer 800 are the measurement device 110, the electronic device 130, and the remote server 150. The computer 800 includes a processor / central processing unit (CPU) 802, a memory device 804, a database 806, a data communication module 808, and a physiological data module 810.

[0076] The processor 802 accesses and executes instructions, code, computer programs, and / or scripts from the memory device 804. The processor 802 includes appropriate logic, circuitry, and / or interfaces for performing such operations or steps. Some examples of the processor 802 include, but are not limited to, an application specific integrated circuit (ASIC) processor, a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a field programmable gate array (FPGA), and the like. Although only one processor 802 is shown, there may be multiple processors 802. Thus, although instructions may be discussed as being executed by the processor 802, the instructions may be executed simultaneously, sequentially, or otherwise by one or more processors 802 (e.g., in a multi-core configuration).

[0077] The memory device 804 may comprise a storage device (such as a flash memory, disk drive, or memory card), a read-only memory (ROM), and a random access memory (RAM). The memory device 804 stores non-transitory instructions operated by the processor 802 to perform various operations or steps of the method 200 / 300 according to various embodiments of the present disclosure. The memory device 804 may also be referred to as a computer-readable storage medium and / or a non-transitory computer-readable medium. A non-transitory computer-readable medium includes all computer-readable media, with the only exception being a transitory propagating signal itself.

[0078] The database 806 is any computer-operated hardware suitable for storing and / or retrieving data. Some examples of the database 806 are, but are not limited to, databases 112, 132, and 152. The database 806 can include multiple storage units, such as hard disks and / or solid state disks in a redundant array of independent disks (RAID) configuration. The database 806 can include, but is not limited to, a storage area network (SAN) and / or a network attached storage (NAS) system. The data communications module 808 is configured to communicate with other computers 800.

[0079] The physiological data module 810 is configured to process the physiological data and perform a stress assessment based on the physiological data. Various algorithms can be implemented in the physiological data module 810 to perform said processing of the physiological data and said stress assessment.

[0080] In the above detailed description, embodiments of the present disclosure relating to a device and method for stress assessment are described with reference to the accompanying drawings. The description of various embodiments herein is not intended to call out or limit to specific or particular expressions of the present disclosure, but is intended to merely provide non-limiting examples of the present disclosure. The present disclosure helps to address at least one of the above-mentioned problems and issues related to the prior art. Although only some embodiments of the present disclosure have been disclosed herein, in light of this disclosure, it will be apparent to those skilled in the art that various changes and / or modifications can be made to the disclosed embodiments without departing from the scope of the present disclosure. Therefore, the scope of the present disclosure and the scope of the following claims are not limited to the embodiments described herein.

Claims

1. A wearable measurement device for evaluating a user's stress, comprising: a sensor module including a photoplethysmography (PPG) sensor for measuring several physiological data sets from the user, each data set being measured during a distinct period of time; a database for storing said physiological data; a display module having a set of graphical user interface (GUI) portions for displaying visual information from the physiological data-based stress assessment; Processor and It is equipped with The processor, determining a stress parameter from each physiological data set for comparison to a predetermined stress criterion; identifying a plurality of stress parameters in a time space having a plurality of consecutive, distinct time periods, each for a time period of the time periods, the plurality of stress parameters including a first stress parameter for a current time period at an end of the time space and one or more earlier stress parameters for one or more earlier time periods prior to the current time period; generating a stress alert when a predetermined stress condition is determined to be satisfied based on a plurality of consecutive stress parameters, the predetermined stress condition including the first stress parameter and a second stress parameter for a second time period immediately preceding the current time period, the predetermined stress condition being satisfied when each of the first stress parameter and the second stress parameter are each indicative of a stress state of the user relative to the predetermined stress criteria; configured to communicate the stress alert to the display module for displaying visual information corresponding to the stress alert in at least one of the GUI portions, the visual information assisting the user in alleviating the stress condition; The stress condition relates to a stress pattern of the user formed by the plurality of stress parameters in the time space.

2. the consecutive plurality of stress parameters includes an earliest stress parameter for an earliest time period at a beginning of the time space; 2. The device of claim 1, wherein the stress condition is met when each of the first and earliest stress parameters indicates a stressed state of the user and none of the remaining ones of the earlier stress parameters indicates a normal state of the user.

3. the successive plurality of stress parameters further includes a third stress parameter for a third time period preceding the second time period; The device of claim 1 , wherein the stress condition is met when each of the first, second, and third stress parameters indicate a stress state of the user relative to the predetermined stress criterion.

4. A device according to any one of claims 1 to 3, wherein stress parameters for all time periods prior to the current time period are ignored with respect to the stress condition if the first stress parameter indicates a normal state of the user.

5. 5. The device of claim 1, wherein the processor is further configured to communicate the physiological dataset to an electronic device and / or a remote server for processing by the electronic device and / or the remote server, respectively.

6. 1. A computerized method for stress assessment of a user, comprising: carried out by wearable measurement devices, retrieving from a database of the wearable measurement device a number of physiological data sets measured from the user, each physiological data set being measured during a distinct time period; determining a stress parameter from each physiological data set for comparison with a predetermined stress criterion; identifying a plurality of stress parameters in a time space having a plurality of consecutive, distinct time periods, each for a time period of the time periods, the plurality of stress parameters including a first stress parameter for a current time period at an end of the time space and one or more earlier stress parameters for one or more earlier time periods prior to the current time period; generating a stress alert when it is determined that a predetermined stress condition is met based on a plurality of consecutive stress parameters, the predetermined stress condition including the first stress parameter and a second stress parameter for a second time period immediately preceding the current time period, the predetermined stress condition being met when each of the first stress parameter and the second stress parameter are each indicative of a stress state of the user relative to the predetermined stress criteria; displaying visual information in at least one graphical user interface (GUI) portion corresponding to the stress alert, the visual information assisting the user in alleviating the stress condition. Contains The method, wherein the stress condition relates to a stress pattern of the user formed by the plurality of stress parameters in the time space.

7. the consecutive plurality of stress parameters includes an earliest stress parameter for an earliest time period at a beginning of the time space; 7. The method of claim 6, wherein the stress condition is met when each of the first and earliest stress parameters indicates a stressed state of the user and none of the remaining ones of the earlier stress parameters indicates a normal state of the user.

8. the successive plurality of stress parameters further includes a third stress parameter for a third time period preceding the second time period; The method of claim 6 , wherein the stress condition is met if each of the first, second, and third stress parameters are indicative of a stress state of the user relative to the predetermined stress criteria.

9. 9. The method of claim 6, wherein stress parameters for all time periods prior to the current time period are ignored with respect to the stress condition if the first stress parameter indicates a normal state of the user.

10. 10. The method according to any one of claims 6 to 9, further comprising communicating the physiological dataset to an electronic device and / or a remote server for processing by the electronic device and / or the remote server, respectively.

11. 1. A computerized method for stress assessment of a user, comprising: performed by an electronic device, receiving a measurement dataset from a wearable measurement device, the measurement dataset including several physiological datasets measured from the user, each physiological dataset being measured during a distinct time period; storing said measurement data set in a database on said electronic device; determining a stress parameter from each physiological data set for comparison with a predetermined stress criterion; identifying a plurality of stress parameters in a time space having a plurality of consecutive, distinct time periods, each for a time period of the time periods, the plurality of stress parameters including a first stress parameter for a current time period at an end of the time space and one or more earlier stress parameters for one or more earlier time periods prior to the current time period; generating a stress alert when a predetermined stress condition is determined to be satisfied based on a plurality of consecutive stress parameters including the first stress parameter and a second stress parameter for a second time period immediately preceding the current time period, the predetermined stress condition being satisfied when each of the first stress parameter and the second stress parameter are each indicative of a stress state of the user relative to the predetermined stress criteria; displaying visual information in at least one graphical user interface (GUI) portion corresponding to the stress alert, the visual information assisting the user in alleviating the stress condition. Contains The method, wherein the stress condition relates to a stress pattern of the user formed by the plurality of stress parameters in the time space.

12. the consecutive plurality of parameters includes an earliest stress parameter for an earliest time period at a beginning of the time space; 12. The method of claim 11, wherein the stress condition is met if each of the first and earliest stress parameters indicates a stressed state of the user and none of the remaining ones of the earlier stress parameters indicates a normal state of the user.

13. the successive plurality of stress parameters further includes a third stress parameter for a third time period preceding the second time period; The method of claim 11 , wherein the stress condition is met if each of the first, second, and third stress parameters are indicative of a stress state of the user relative to the predetermined stress criterion.

14. 14. The method according to claim 11, wherein stress parameters for all time periods prior to the current time period are ignored with respect to the stress condition if the first stress parameter indicates a normal state of the user.

15. 15. The method according to any one of claims 11 to 14, further comprising the step of communicating the stress alert to the wearable measurement device for displaying corresponding visual information on the wearable measurement device.

16. The method of any one of claims 11 to 15, further comprising communicating the measurement data set to a remote server for processing by the remote server.

17. receiving, from the remote server, recommended content for alleviating the chronic stress state of the user; The method of claim 16 , wherein the generation of the recommended content and the determination of the chronic stress state are performed by the remote server based on the measurement dataset and a historical measurement dataset of the user relative to a reference dataset.

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