SYSTEM AND METHOD TO DETECT FATIGUE CONDITION
TECHNICAL FIELD
The present disclosure relates generally to data processing and more specifically, systems and methods for detection of fatigue condition in humans. BACKGROUND
Generally, users, such as humans perform one or more physical activities to keep the body fit and healthy. The physical activities include but not limited to walking, jogging, running, exercising or involving in an indoor/outdoor sport. The users take adequate amount of food which is further consumed during such physical activities and day today activities. The users may come across one or more physical and mental conditions while performing such physical activities, which may have a considerable effect on performance. Further, these physical and mental conditions can be directly related to the physical and mental wellbeing of the user.
Typically, the conditions that a user may come across includes, fatigue, stress, anxiety, depression, sleeplessness, obesity and so forth. These conditions directly impact on the performance of the user in physical activities. While performing the physical activities, the entire body including heart, muscles, lungs and the like are purposefully trained. Out of which, fatigue is one of interrelated condition which involves both mind and body. Fatigue is a feeling of constant tiredness or weakness which may be physical, mental or a combination of both. Fatigue is also a symptom, caused by a combination of lifestyle, social, psychological and general wellbeing issues rather than an underlying medical condition.
Notably, fatigue may cause chronic tiredness or sleepiness, headache, dizziness, sore or aching muscles, muscle weakness, slowed reflexes and responses, impaired decision-making and judgement, moodiness, such as irritability, impaired hand-to-eye coordination, appetite loss, reduced immune system function, blurry vision, short-term memory problems, poor concentration, hallucinations, reduced ability to pay attention to the situation, low motivation and the like. Thus, fatigue may seriously impact safety of the users and lead to increase in accidents. A user who is experiencing fatigue may not be able to react or communicate effectively, thereby causing a threat to its life or others. In a prior art solution, disclosed is a utility model that relates to a kind of wearable muscular fatigue detection devices, specifically include adjustable frequency signal source, signal regulation and control unit, phase discriminator, input electrode, receiving electrode, differential amplifier circuit, filter circuit, shaping reduction unit, microprocessor and display module. The utility model structure simply minimizes, and acquisition mode is non-invasive, harmless and easy to operate.
Therefore, in light of the foregoing discussion, there exists a need to overcome various problems associated with conventional methods to detect fatigue condition in a user.
SUMMARY
The present disclosure seeks to provide a system to detect fatigue condition in a user. The present disclosure also seeks to provide a method to detect fatigue condition in a user.
According to an aspect, an embodiment of the present disclosure provides a system to detect fatigue condition, the system comprising:
- a wearable unit, when in operation, is configured to generate a first data, wherein the first data comprises a plurality of parameters associated with a user;
- an electronic device communicatively coupled to the wearable unit, wherein the electronic device is configured to:
- analyze each parameter of the plurality of parameters in the first data;
- detect a deviation in a value of at least one of the parameters of the plurality of parameters from a predefined range of each parameter; and
- alert the user of detected abrupt deviation in the value of at least one of the parameters, indicative of a level of fatigue;
- a first communication network communicatively coupled to the electronic device through the wearable unit, wherein the first communication network is configured to receive a second data from the electronic device, and wherein the second data comprises a partially processed first data and a Global Positioning System (GPS) value associated with the GPS location of the user;
- a server communicatively coupled to the first communication network, wherein the server is configured to:
- analyse the second data received from the first communication network; - invoke a critical status associated with the user, if the level of fatigue exceeds a threshold limit; and
- generate an alert notification for at least one care personnel based on the critical status of the user; and
- a database communicatively coupled to the server, wherein the database is configured to store at least one of: the first data, the second data, contact information of the at least one care personnel.
Optionally, the electronic device analyses each parameter of the plurality of parameters in the first data and detect the deviation by identifying an increase or a decrease in the value of at least one of the parameters from the predefined range of the parameter.
Optionally, the plurality of parameters of the first data includes at least one of: a heart rate exertion of the user, a pace and steps of the user,
Optionally, the electronic device is configured to determine the pace of the user by calculation of an average length of stride of the user and a number of steps covered by the user in a specific time period.
Optionally, the database is further configured to store a profile of the user, and wherein the profile of the user comprises at least one of: a wearable unit identifier (ID), a name of the user, an age of the user, a location of the user, a height of the user, a weight of the user a mobile number, an emergency contact number and a blood group.
Optionally, the electronic device is configured to determine the heart rate exertion of the user by using an average heart rate of the user and the age of the user.
Optionally, the server compares the second data with the threshold limit for determination of the critical status of the user and provide the GPS value associated with the user to the at least one care personnel based on the determined critical status of the user.
Optionally, the server is further configured to monitor a plurality of users, and wherein the monitoring of each user of the plurality of users is based on at least one of: an age, a health history, a type of activity performed by a user at a moment of monitoring, a level of fatigue, a heart rate, a location of each user. According to another aspect, an embodiment of the present disclosure provides a method for detecting fatigue condition, the method comprises:
- generating a first data, wherein the first data comprises a plurality of parameters associated with a user;
- analysing each parameter of the plurality of parameters in the first data;
- detecting a deviation in a value of at least one of the parameters of the plurality of parameters from a predefined range of each parameter;
- alerting the user of detected abrupt deviation in the value of at least one of the parameters, indicative of a level of fatigue;
- receiving a second data, wherein the second data comprises a partially processed first data and a Global Positioning System (GPS) value associated with the GPS location of the user;
- analysing the second data;
- invoking a critical status associated with the user, if the level of fatigue exceeds a threshold limit;
- generating an alert notification for at least one care personnel based on the critical status of the user; and
- storing at least one of: the first data, the second data, contact information of the at least one care personnel.
Optionally, the method further comprising monitoring each user of a plurality of users based on at least one of: an age, a health history, a type of activity performed by a user at a moment of monitoring, a level of fatigue, a heart rate, a location of each user.
It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.
DESCRIPTION OF THE DRAWINGS
The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.
Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein:
FIG. 1 is a schematic diagram of a system to detect fatigue condition, in accordance with an embodiment of the present disclosure;
FIG. 2 is a block diagram of a wearable unit and an electronic device in communication, in accordance with an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of exemplary system to detect fatigue condition, in accordance with an embodiment of the present disclosure;
FIG. 4 is a flowchart illustrating the steps of a method to determine a pace of the user, in accordance with an embodiment of the present disclosure;
FIG. 5 is a flowchart illustrating the steps of a method to determine a heart rate exertion of a user, in accordance with an embodiment of the present disclosure;
FIG. 6 is a flowchart illustrating the steps of a first method to determine a level of fatigue, in accordance with an embodiment of the present disclosure;
FIG. 7 is a flowchart illustrating the steps of a second method to determine a level of fatigue, in accordance with an embodiment of the present disclosure;
FIG. 8 is a flowchart illustrating the steps of a third method to determine a level of fatigue, in accordance with an embodiment of the present disclosure;
FIG. 9 is a flowchart illustrating the steps of an exemplary method to detect fatigue condition, in accordance with an embodiment of the present disclosure;
FIG. 10 is an example fatigue detection module or ECG module or wearable unit in an aspect of the present invention;
FIG. 11A and 11B illustrates another example wearable unit with belt strap embedded in a T-shirt; FIG. 12A, 12B and 12C, illustrates different views of belt strap; and
FIG. 13A through 13F illustrates various components of ECG module and belt strap in an embodiment of the present invention.
In the accompanying drawings, an underlined number is employed to represent an item over which the underlined number is positioned or an item to which the underlined number is adjacent. A non-underlined number relates to an item identified by a line linking the non- underlined number to the item. When a number is non-underlined and accompanied by an associated arrow, the non-underlined number is used to identify a general item at which the arrow is pointing.
DETAILED DESCRIPTION
In overview, embodiments of the present disclosure are concerned with systems and methods to detect fatigue condition in users.
According to an aspect, an embodiment of the present disclosure provides a system to detect fatigue condition, the system comprising:
- a wearable unit, when in operation, is configured to generate a first data, wherein the first data comprises a plurality of parameters associated with a user;
- an electronic device communicatively coupled to the wearable unit, wherein the electronic device is configured to:
- analyse each parameter of the plurality of parameters in the first data;
- detect a deviation in a value of at least one of the parameters of the plurality of parameters from a predefined range of each parameter; and
- alert the user of detected abrupt deviation in the value of at least one of the parameters, indicative of a level of fatigue;
- a first communication network communicatively coupled to the electronic device, wherein the first communication network is configured to receive a second data from the electronic device, and wherein the second data comprises a partially processed first data and a Global Positioning System (GPS) value associated with the GPS location of the user;
- a server communicatively coupled to the first communication network, wherein the server is configured to:
- analyse the second data received from the first communication network; - invoke a critical status associated with the user, if the level of fatigue exceeds a threshold limit; and
- generate an alert notification for at least one care personnel based on the critical status of the user; and
- a database communicatively coupled to the server, wherein the database is configured to store at least one of: the first data, the second data, contact information of the at least one care personnel.
According to another aspect, an embodiment of the present disclosure provides a method for detecting fatigue condition, the method comprises:
- generating a first data, wherein the first data comprises a plurality of parameters associated with a user;
- analysing each parameter of the plurality of parameters in the first data;
- detecting a deviation in a value of at least one of the parameters of the plurality of parameters from a predefined range of each parameter;
- alerting the user of detected abrupt deviation in the value of at least one of the parameters, indicative of a level of fatigue;
- receiving a second data, wherein the second data comprises a partially processed first data and a Global Positioning System (GPS) value associated with the GPS location of the user;
- analysing the second data;
- invoking a critical status associated with the user, if the level of fatigue exceeds a threshold limit;
- generating an alert notification for at least one care personnel based on the critical status of the user; and
- storing at least one of: the first data, the second data, contact information of the at least one care personnel.
The fatigue in a user is due to chronic tiredness or sleepiness, headache, dizziness, sore or aching muscles, muscle weakness, slowed reflexes and responses, impaired decision-making and judgement, moodiness, such as irritability, impaired hand-to-eye coordination, appetite loss, reduced immune system function, blurry vision, short-term memory problems, poor concentration, hallucinations, reduced ability to pay attention to the situation at hand, low motivation etc. Some of the above symptoms can be identified by a heart rate, blood pressure and amount of breathing.
Further, to address the above symptoms of fatigue in a person, it is crucial to analyse the heart rate and detect a fatigue condition in a person, especially while performing physical activities, since the heart rate may be volatile and considerable rate of change in fatigue may be observed. The following invention describe a method to analyse the heart rate in a particular manner and formulate an algorithm to detect the fatigue condition in a user.
Referring to FIG. 1, there is shown a system 100 for detection of fatigue condition, in accordance with an embodiment of the present disclosure. The figure is shown comprising components that include a wearable unit (or vest) 110, an electronic device 120 such as a mobile device, a first communication network 130, a server 140 and a database 150. The following paragraphs describe the above components in detail. The wearable unit 110, when in operation, is configured to generate a first data. The first data comprises a plurality of parameters associated with the user. The wearable or vest 110 which is worn by the user is connected to the electronic device 120, through a second communication network (not shown), for example, Bluetooth or BLE. The wearable unit 110 covers the chest portion wherein which consists of one or more sensors to primarily monitor the heart rate and other activities of the user. The sensors include heart rate monitoring sensor, an accelerometer or pedometer, and a gyroscope. In an embodiment, one or more similar type of sensors is used to accurately detect any movement, and appropriately capture and record the variation during the activities. The heart rate monitoring sensor records the heart rate of the user, during any activity such as walking, running, jogging and so forth. In another embodiment, the wearable unit 110 transmits the first data from one or more sensors to the electronic device 120 for further processing. The first data includes heart rate, accelerometer data and gyroscope data. The electronic device 120 communicatively coupled to the wearable unit is configured to analyse each parameter of the plurality of parameters in the first data. Optionally, the plurality of parameters of the first data includes at least one of: a heart rate exertion of the user, a pace of the user, the GPS location of the user. The plurality of parameters includes, a heart rate, blood pressure and breathing pattern of a person, and the like. Moreover, the electronic device 120 detects a deviation in a value of at least one of the parameters of the plurality of parameters from a predefined range of each parameter. The predefined range of each parameter may be standard range of parameters in accordance with medical norms. For example, a predefined range for heart rate of a person may be 60 to 100 beats per minute. Furthermore, the electronic device 120 alert the user in reference to the detected abrupt deviation in the value of at least one of the said parameters, indicative of a level of fatigue. The electronic device 120 is configured with an application to receive and read the first data from the wearable unit 110. The mobile application process and analyse the first data with one or more algorithms and methods to find any change in pattern.
The heart rate of the user is typically analysed to determine average heart rate and number of beats per minute. The heart rate may vary person to person, and activity to activity. The variation in heart rate is due to one or more internal or external parameters that include, stress, fatigue, anxiety, walking, jogging, running, or any physical activity or mental state of the user. Further, heart rate sensor is used to identify any abrupt variation in the heart rate and further helps to alert the user or share the information with the network through the electronic device 120, immediately.
In an embodiment, the algorithms of subject invention are primarily capable of identifying pace of user, determine heart rate exertion and fatigue in a user, while performing any activity. Any abrupt value in fatigue level is immediately identified and user is alerted to pause or stop the ongoing task.
The electronic device 120 further adds a GPS location value to the first data and prepares the second data. The electronic device 120 (for example, a mobile device) transmits the second data to the server 140, through a first communication network 130. The first communication network 130 communicatively coupled to the server 140 configured to receive a second data from the electronic device 120, Notably, the second data comprises a partially processed first data and a Global Positioning System (GPS) value associated with the GPS location of the user. The first and second data which is being captured by the wearable unit 110 and electronic device 120 are transmitted to the server 140 for additional processing, wherein the server 140 is configured to analyse the second data received from the first communication network. The server 140 further invoke a critical status associated with the user, if the level of fatigue exceeds a threshold limit and generate an alert notification for at least one care personnel based on the critical status of the user. The one or more adverse heart rate conditions of one or more users are shared in a safety network or groups or closed contacts or hospitals for identification of adverse condition, monitoring of user and to provide timely assistance. Optionally, the server compares the second data with the threshold limit for determination of the critical status of the user and provide the GPS value associated with the user to the at least one care personnel based on the determined critical status of the user. The threshold limit may be a minimum or a maximum value associated with each parameter, such that if any parameter of the user falls below the minimum value or rise above the maximum value generates a critical status, so the user may receive medical assistance. For example, if a heart rate of a person rises to 130 beats per minute, which is one of the indications of fatigue, the server invokes the critical status and alerts the user and at least one care personnel. The server 140 manages all data in the network, process them in a particular manner with the help of one or more algorithms and ultimately analyse health data to invoke a critical status with alert notifications. The server 140 stores all such processed data in the database 150. The database 150 maintains all data related to users, connected devices, emergency contact details in one or more tables. The database 150 is configured to store the first data, the second data, contact information of the at least one care personnel.
Optionally, the database 150 is further configured to store a profile of the user, and wherein the profile of the user comprises at least one of: a wearable unit identifier (ID), a name of the user, an age of the user, a location of the user, a height of the user, a weight of the user, a mobile number, an emergency contact number and a blood group. The database 150 further indexes the data for faster retrieval, and revert when requested by the server 140. Optionally, the server is further configured to monitor a plurality of users, and wherein the monitoring of each user of the plurality of users is based on at least one of: an age, a health history, a type of activity performed by a user at a moment of monitoring, a level of fatigue, a heart rate, a location of each user.
Referring to FIG. 2, illustrated is a block diagram of a wearable unit 110 and an electronic device 120 in communication, in accordance with an embodiment of the present disclosure. The figure is shown comprising the components of wearable unit 110 and the electronic device 120. As shown there, the components of wearable unit 110 include a micro controller unit 205, a battery unit 210, a second communication module 215 and sensor modules 220. The sensor modules further include, an accelerometer or a pedometer 225, a gyroscope 230, and a heart rate monitor (HRM) 235. The components of electronic device 120 include, a first communication module 255, a GPS module 265 and primary controller unit 260. The first communication module 255 of the electronic device 120 and the second communication module 215 of wearable unit 110 are connected through a second communication network (not shown). The first data from wearable unit 110 is transmitted through the second communication network, to the electronic device 120.
Referring to FIG. 3, shown is a schematic diagram of exemplary system to detect fatigue condition, in accordance with an embodiment of the present disclosure. As shown there, the server 140 is connected with one or more user groups through one or more network, including first communication networks. The one or more user groups may include, users preparing for marathon in different range (5K, 10K, half marathon and a full marathon), users under coaching for one or more sport or sport related activities, or any activity. In an embodiment, the group of users may not be in a same place. The server 140 may also monitor the activities of every user in the network. The server 140 may also be configured to monitor a specific set of users based on their age, health history, type of activity, pace, fatigue level, Heart rate, distance covered, location, regularity (in doing an activity) and so forth.
Referring to FIG. 4, shown is a flowchart 400 illustrating the steps of a method to determine a pace of the user, in accordance with an embodiment of the present disclosure. Optionally, the electronic device is configured to determine the pace of the user by calculation of an average length of stride of the user and number of steps covered by the user in a specific time period. Herein, the electronic device is referred to as a mobile device. In step 410, the server or mobile device monitor the movement of the user and count the steps of a first course or current activity through the wearable unit. The mobile device is also capable of recording the each and every activity with a start and end time. In an embodiment, each activity may have one or more courses. A course is a part of an activity wherein which the starting step count is being recorded and continuously monitoring the activity of the user and ends when user stops the recording or pauses the recordation of step count over a period of time and distance. The wearable unit transmits the step data to mobile device. In step 420, the mobile device is configured to determine the total number of steps taken by the user in a first course from first location to second location. In an embodiment, the mobile device also uses GPS data to approximate the total steps between first and second location. In step 430, the mobile device simultaneously identifies the stride length of the user, based on average step count and total distance or from the current step values. In step 440, the mobile device determines the pace of the user with average stride length and current step values. In an example, the pace of the user is determined as follows,
PACE = ((Stride length * total number of steps)/total time taken) )/60
Referring to FIG. 5, shown is a flowchart 500 depicting steps of a method to determine a heart rate exertion of a user, in accordance with an embodiment of the present disclosure. Optionally, the electronic device is configured to determine the heart rate exertion of the user by using an average heart rate of the user and the age of the user. In step 505, the server or mobile device identifies the profile of the user when the user wears the wearable (or wearable unit) and pairs with the mobile device. The profile of the user is created at least with wearable device ID, name, age, location, height, weight, total number of steps to be covered in a day by user, mobile number, blood group, emergency contact number etc. If user profile is already available, the mobile device is capable of retrieving the total steps taken by user over a period of time, heart rate values at various occasions, stride length, total distance covered, fatigue level of the user etc, from the database. In step 510, the wearable configured with the heart rate sensor which records heart rate of user every second and transmits the same to the mobile device in equal interval, for example, every 5 minutes. In step 515, the mobile device identifies the average heart value per minute of the user. In step 520, the mobile device determines the heart exertion rate in reference to user’s age. In one example, heart rate exertion is determined as follows,
HEART RATE EXERTION = ((average heart rate exertion)) / (220-age of the user)
In step 525, the mobile device compares and checks the heart exertion rate with that of default set of rates configured with respect to age and past performances of the user. When the heart exertion rate is less than 0.8, then the control is transferred to step 530, otherwise, the control is transferred to 535. In step 530, the mobile device assigns the heart rate exertion value as ‘ G . In step 535, the mobile device again checks exertion rate, when exertion rate is between 0.8 and 0.9, the control is transferred to step 540, otherwise, the control is transferred to step 545. In step 540, the mobile device assigns the heart rate exertion value as ‘2’. In step 545, the mobile device again checks exertion rate, and finds when exertion rate is more than 0.9, the control is transferred to step 550, otherwise, the control is transferred to step 555. In step 550, the mobile device assigns the heart rate exertion value as ‘3’. In step 555, the mobile device cannot determine the heart rate exertion value and the control is transferred to step 520, and again the process continues till exertion rate is determined.
Referring to FIG. 6, shown is a flowchart 600 illustrating the steps of a first method to determine a level of fatigue, in accordance with an embodiment of the present disclosure. In step 605, the mobile device monitors the pace and heart rate value of the user through the wearable. In step 610, the mobile device checks whether the heart rate value is monitored for at least 300 seconds. If the heart rate is being monitored more than 300 seconds, then the control is transferred to step 615, otherwise the control is transferred to step 605. In an embodiment, the mobile device frequently monitors the heart rate value of user. In step 615, the primary controller unit in the mobile device (through a mobile application) may obtain last three computed heart rate exertion values which are being represented by v[0], v[l] and v[2].
In step 620, the primary controller unit checks the condition of the current exertion values of the user. When the exertion values v[0]=l & v[l]=2 & v[2]=2, then the control is transferred to step 625, otherwise the control is transferred to step 630. In step 625, the primary controller unit identifies and assigns a fatigue level 0.4 for the subject exertion. In step 630, when the primary controller unit checks the current exertion values with v[0]=l & v[l]=2 & v[2]=3, then the control is transferred to step 635, otherwise the control is transferred to step 640. In step 635, the primary controller unit identifies and assigns a fatigue level 0.5 for the subject exertion. In step 640, when the primary controller unit further checks the current exertion values with v[0]=l & v[l]=3 & v[2]=3, then the control is transferred to step 645, otherwise the control is transferred to step 650. In step 645, the primary controller unit identifies and assigns a fatigue level 0.6 for the subject exertion. In step 650, when the primary controller unit further checks the current exertion values with v[0]=2 & v[l]=3 & v[2]=3, then the control is transferred to step 655, otherwise the control is transferred to step 660. In step 655, the primary controller unit identifies and assigns a fatigue level 0.65 for the subject exertion. In step 660, when the primary controller unit further checks the current exertion values with v[0]=3 & v[l]=3 & v[2]=3, then the control is transferred to step 665, otherwise the control is transferred to step 670. In step 665, the primary controller unit identifies and assigns a fatigue level 0.75 for the subject exertion. In step 670, the primary controller unit cannot determine the heart rate exertion value and the control is transferred to step 615 and further the primary controller unit is configured to determine the fatigue level from the last three exertion values.
Referring to FIG. 7, illustrated is a flowchart 700 illustrating the steps of a second method to determine a level of fatigue, in accordance with an embodiment of the present disclosure. In step 705, the mobile device monitors the pace and heart rate value of the user through the wearable, beyond 300 seconds. In step 710, the primary controller unit of mobile device checks the current pace value of the user. The last three pace values per second are identified and analysed. The last pace value (first value) is pacevalfO], second pace value is identified as paccval| 1 1 and third pace value is identified as paceval[2]. When the pace values (paccval|0| > paceval[2]) & (paccval| 11 > paceval[2]), then the control is transferred to step 715, otherwise the control is transferred to step 705.
In step 715, the primary controller unit further checks for the condition, if ((paceval [2] - pace val 101 ) >15) & ((paceval[2] > paccval 101 ) <25), then the control is transferred to step 720, otherwise the control is transferred to step 710. In step 720, the primary controller unit checks the result of step 715 with that of identified current heart rate exertion values. When, current exertion values with v[0]=l & v[l]=3 & v[2]=3, then the control is transferred to step 725, otherwise the control is transferred to step 730. Further, in step 725, the primary controller unit identifies and assigns a fatigue level 0.65 for the subject exertion. In step 730, the primary controller unit checks current exertion values with v[0]=2 & v[l]=3 & v[2]=3, then the control is transferred to step 735, otherwise the control is transferred to step 740. In step 735, the primary controller unit identifies and assigns a fatigue level 0.7 for the subject exertion. In step 740, the primary controller unit checks current exertion values with v[0]=3 & v[l]=3 & v[2]=3, then the control is transferred to step 745, otherwise the control is transferred to step 740. In step 745, the primary controller unit identifies and assigns a fatigue level 0.8 for the subject exertion. In step 750, the primary controller unit cannot determine the heart rate exertion value and fatigue level and the control is transferred to step 705 and the primary controller unit monitors the pace and heart rate value beyond 300 seconds.
Referring to FIG. 8, shown is a flowchart 800 illustrating the steps of a third method to determine a level of fatigue, in accordance with an embodiment of the present disclosure. In step 805, the mobile device monitors the pace and heart rate value of the user through the wearable, beyond 300 seconds. In step 810, the primary controller unit of mobile device checks the current pace value of the user. The last three pace values per second are identified and analyzed. The last pace value (first value) is paceval [0], second pace value is identified as pacevall 1 1 and third pace value is identified as paceval[2]. When the pace values (paceval 101 > paceval[2]) & (paceval| 1 1 > paceval[2]), then the control is transferred to step 815, otherwise the control is transferred to step 805. In step 815, the primary controller unit further checks for the condition, if ((paceval [2] - paceval [0]) / paceval [2]) * 100 is greater than 25), then the control is transferred to step 820, otherwise the control is transferred to step 810. In step 820, the primary controller unit checks the result of step 815 with that of identified current heart rate exertion values. When, current exertion values with v[0]=l & v[l]=3 & v[2]=3, then the control is transferred to step 825, otherwise the control is transferred to step 830. Further, in step 825, the primary controller unit identifies and assigns a fatigue level 0.75 for the subject exertion. In step 830, the primary controller unit again checks current exertion values with v[0]=2 & v[l]=3 & v[2]=3, then the control is transferred to step 835, otherwise the control is transferred to step 845. In step 835, the primary controller unit identifies and assigns a fatigue level 0.8 for the subject exertion and user is moderately critical. In step 840, the primary controller unit, immediately alert the user with the increased fatigue level and also notify the other users in a network. In step 845, the primary controller unit checks current exertion values with v[0]=3 & v[l]=3 & v[2]=3, then the control is transferred to step 850, otherwise the control is transferred to step 860. In step 850, the primary controller unit immediately alert the user with the extreme fatigue level and critical, advise the user to take a rest and further notify the other users in a network to provide a medical assistance to the subject user. In step 860, the primary controller unit cannot determine the heart rate exertion value and fatigue level and the control is transferred to step 805, and the primary controller unit monitors the pace and heart rate value beyond 300 seconds.
The present disclosure provides a method to detect fatigue condition. Referring to FIG.9, there is shown a method 900 to detect fatigue condition, in accordance with an embodiment of the present disclosure. At a step 902, the method comprises generating a first data, wherein the first data comprises a plurality of parameters associated with a user. At a step 904, the method comprises analysing each parameter of the plurality of parameters in the first data. At a step 906, the method comprises detecting a deviation in a value of at least one of the parameters of the plurality of parameters from a predefined range of each parameter. At a step 908, the method comprises alerting the user of detected abrupt deviation in the value of at least one of the parameters, indicative of a level of fatigue. At a step 910, the method comprises receiving a second data, wherein the second data comprises a partially processed first data and a Global Positioning System (GPS) value associated with the GPS location of the user. At a step 912, the method comprises analysing the second data. At a step 914, the method comprises invoking a critical status associated with the user, if the level of fatigue exceeds a threshold limit. At a step 916, the method comprises generating an alert notification for at least one care personnel based on the critical status of the user. At a step 918, the method comprises storing at least one of: the first data, the second data, contact information of the at least one care personnel.
Referring to FIG. 10, shown is an example fatigue detection module or ECG module or wearable unit 1000 in an aspect of the present invention. The ECG module 1000 has a flexible belt like structure providing a snug fit to the abdomen (chest or heart portion) of the user. In an embodiment, the belt strap and ECG module are enclosed in a vest and which is further knitted within a T-shirt. Thus, a smart t-shirt is made which is capable of detecting a heart rate of user. In another embodiment, the rear side of belt which touches the skin of user has a two or more electrodes to detect heart signal and the module detecting and transmitting the heart rate.
Referring to FIG. 11A and 11B, shown is another example wearable unit or ECG module with belt strap 1120 embedded in a T-shirt 1110. The figures also show respective front and back portion of T-shirt 1110. In an embodiment, the belt strap 1120 having the ECG module is particularly placed or positioned at the chest portion or upper abdomen of the user to sense and monitor the heart rate and heart rate exertion of the user in real-time.
FIG. 12A, 12B and 12C, illustrates different views of belt strap 1120. In an embodiment, the ECG module 1210 has two main components namely, a module and an ECG base. The ECG base is knitted or sewed on the belt strap 1120. In another embodiment, the module is coupled with the ECG base. In yet another embodiment, the module is detachable from the ECG base, and which firmly sits within the slot provided in ECG base, when attached, with the help of the sliding mechanism constructed on the ECG base and back side of the module. The ECG base supports the vertical insertion and removal of module from the ECG base. FIG. 12B illustrates the example belt strap 1120 and ECG module 1210 in an embodiment of the present invention, wherein the two ends of belt strap 1120 are attached and weaved together at 1220 to form an elastic belt like structure. This elastic nature of belt strap 1120 further provides a snug fit to the user. FIG. 12C illustrates the example belt strap 1120, wherein, the ends of belt strap 1120 are attached together through a button mechanism, or hook mechanism or any adhesion technique to keep belt strap snug fit for the user.
FIG. 13A through 13F illustrates various components of ECG module 1210 and belt strap 1120 in an embodiment of the present invention. FIG. 13A illustrates the position and arrangement of ECG base 1310, on the first side (or front side) of the belt strap 1120. In an embodiment, the ECG base 1310 is made of ABS and PU material and is attached to the belt strap 1120 through a pair of nickel-plated rivets. Whereas, on the second side (or rear side) of the belt strap 1120, the nickel-plated rivets are attached to the pair of nickel -plated washers and electrodes. In an embodiment, the pair of electrodes are arranged above the belt strap surface. In another embodiment, these pair of electrodes are supported by two more electrodes to absorb better heart readings and to receive improved signal quality at the nickel- plated rivets. The pair of electrodes in combination of nickel-plated washers are directly in contact with the skin of user and further transmits the heart rate signals to the ECG base and ECG module.
FIG. 13B and 13C is the rear side of belt strap 1120 illustrating the position and placement of pair of electrodes 1330, nickel-plated washers 1340, and a first sensor layer 1350. In an embodiment, the first sensor layer 1350 and pair of electrodes 1330 are arranged on the belt strap 1120 one above the another. In other words, a first sensor layer 1350 is placed between the pair of electrodes 1330 and the belt strap 1120 to improve the quality of signal. The nickel-plated washers 1340 are used to transmit the electrical signals, which are captured by the pair of electrodes 1330, to the module, through nickel-plated rivets. In an embodiment, one or more sensor layers may be placed between the pair of electrodes 1330 and belt strap 1120 to improve the signal quality. In an embodiment, the nickel-plated washers 1340 and rivets are made up of stainless steel and copper respectively. In another embodiment, the pair of electrodes 1330 are primarily made up of carbon or conductive carbon/rubber combination. In yet another embodiment, the electrodes 1330 becomes conductive and transmit electrical signals, when comes in contact with water or saline or sweat or gel. In yet another embodiment, the belt strap 1120 is combination of is spandex fabric and cotton material. In yet another embodiment, the module is made up of ABS and PC material.
FIG. 13D is an ECG base 1310 in an embodiment of the present invention. The figure also shows the position and arrangement of nickel-plated rivets (1360 and 1370) which are capable of transmitting the electrical signals from the pair of electrodes 1330 to the module. FIG. 13E and 13F is an example front side and rear side view of the module in an embodiment of the present invention. In one aspect, the module comprises a controller unit, a power supply unit, a pair of signal units, a pair of pins and a communication module. Further, the communication module, pair of signal units and power supply unit are connected to the controller unit. In an embodiment, the pair of pins (ex: pogo pins) are internally connected with the pair of signal units. When the module is placed in the ECG base, the nickel-plated rivets and a pair of pins comes to direct contact and electrical signals generated from pair of electrodes are transmitted to the pair of signal units of the module, for processing. The signals at signal units are further transferred to the controller unit. The controller unit receives the signals from the pair of signal units, process, integrate and prepare the heart signals for transmission. The power supply unit provides electrical supply to the controller unit, communication module and other components of module. In an embodiment, the power supply unit is a rechargeable battery and a port is provided in the module to increase the battery level time to time. The communication module transmits the data processed by the controller unit to the mobile device. And, the mobile application configured in the mobile device is capable of analysing the heart rate value exertion rate, fatigue condition of user. FIG. 13F is an example rear side view of the module, illustrating the position and arrangement of pogo pins in an embodiment of the present invention. These pogo pins (1380 and 1390) are used to transmit the electrical signals from nickel-plated rivets to the pair of signal units.
Optionally, the method further comprising monitoring each user of a plurality of users based on at least one of: an age, a health history, a type of activity performed by a user at a moment of monitoring, a level of fatigue, a heart rate, a location of each user.
Modifications to embodiments of the invention described in the foregoing are possible without departing from the scope of the invention as defined by the accompanying claims. Expressions such as “including”, “comprising”, “incorporating”, “consisting of’, “have”, “is” used to describe and claim the present invention are intended to be construed in a non exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural. Numerals included within parentheses in the accompanying claims are intended to assist understanding of the claims and should not be construed in any way to limit subject matter claimed by these claims.