Claims:WE CLAIM:
1. A system for performance evaluation of an exercise performed by a user comprising:
one or more processors;
an input subsystem operable by the one or more processors, and configured to receive user data from the user;
a calibration subsystem operable by the one or more processors, and configured to:
calibrate an exercise mat for the corresponding user based on received user data using a calibration technique, wherein the exercise mat comprises one or more sensors configured to sense one or more exercise parameters for the exercise performed by the user on the exercise mat;
to generate calibration data upon calibrating the exercise mat;
a monitoring subsystem operable by the one or more processors, and configured to:
receive one or more exercise parameters from the exercise mat, wherein the one or more exercise parameters are associated with the exercise performed by the user on the exercise mat;
compute the one or more exercise parameters and a pre-defined set of parameters using a computation technique for generating a computed result;
an evaluation subsystem operable by the one or more processors, and configured to evaluate the exercise performed by the user in real time upon receiving the computed result for generating evaluated parameters associated with at least one of the user data, the one or more exercise parameters, the calibration data or a combination thereof; and
a training subsystem operable by the one or more processors, and configured to provide assistive feedback for the exercise performed by the user on the exercise mat in real time based on the evaluated parameters.
2. The system as claimed in claim 1, wherein the user data comprises height, weight, gender, body mass index, associated with the user and type of one or more exercises to be performed by the user.
3. The system as claimed in claim 1, wherein the calibration technique comprises one of a machine learning technique and an artificial intelligence technique.
4. The system as claimed in claim 1, wherein the one or more exercise parameters comprises at least one of flexibility, balance, strength and physiological parameters of the user while performing the exercise on the exercise mat.
5. The system as claimed in claim 1, comprises a score generation subsystem operable by the one or more processors, and configured to generate one or more scores representative of the corresponding one or more aspects associated with the exercise performed by the user on the exercise mat.
6. The system as claimed in claim 1, comprises a correction subsystem operable by the one or more processors, and configured to compute a tolerance value representative of correction of the exercise performed by the user on the exercise mat.
7. A method (120) for performance evaluation of an exercise performed by a user comprising:
receiving, by an input subsystem, user data from the user; (130)
calibrating, by a calibration subsystem, an exercise mat for the corresponding user based on received user data using a calibration technique for generating calibration data upon calibrating the exercise mat; (140)
receiving, by a monitoring subsystem, one or more exercise parameters from the exercise mat, wherein the one or more exercise parameters are associated with the exercise performed by the user on the exercise mat; (150)
computing, by the monitoring subsystem, the one or more exercise parameters and a pre-defined set of parameters using a computation technique for generating a computed result; (160)
evaluating, by an evaluation subsystem, the exercise performed by the user in real time upon receiving the computed result for generating evaluated parameters associated with at least one of the user data, the one or more exercise parameters, the calibration data or a combination thereof; and (170)
training, by a training subsystem, the user for the exercise performed by the user on the exercise mat in real time based on based on the evaluated parameters. (180)
8. The method (120) as claimed in claim 7, wherein receiving the user data from the user comprises receiving height, weight, gender, body mass index associated with the user, and type of exercise to be performed by the user.
9. The method (120) as claimed in claim 7, comprising generating, by a score generation subsystem, one or more scores representative of the corresponding one or more aspects associated with the exercise performed by the user on the exercise mat.
10. The method (120) as claimed in claim 7, comprising computing, by a correction subsystem a tolerance value representative of correction of the exercise performed by the user on the exercise mat.

Dated this 7th day of January 2020

Vidya Bhaskar Singh Nandiyal
(IN/PA-2912)
Authorized Signatory

, Description:FIELD OF INVENTION
Embodiments of a present disclosure relate to performance evaluation of exercise performed by a user, and more particularly to system and method for performance evaluation of an exercise performed by the user on an exercise mat.
BACKGROUND
Physical exercise is any kind of bodily activity which enhances or maintains physical fitness and overall wellness of a body. One such widely popular type of exercise is yoga which is considered as a next generation therapy for health and wellness. Further, modern technologies provide an interactive platform for enhancing the physical exercise of a user with the help of multimedia. Different approaches are being implemented to monitor and enhance the performance of the exercise performed by the user.
In one conventional approach, the performance of the exercise of the user is evaluated using equipment such as treadmill and the like to monitor certain parameters such as calories burnt, duration of exercise, number of repetitions and so on performed by the user. Furthermore, different types of exercises are evaluated through different means. One such means includes an exercise mat which is used to perform different types of floor exercises. The system provides graphical illustrations on the exercise mat for the user to perform the exercise based on the graphical illustrations provided by the system on the exercise mat. However, such system the exercise done by the user is not monitored. In addition, parameters associated with the corresponding user while performing the exercise varies, such varying parameters are not calibrated initially with the exercise mat for better usage of the exercise mat. Henceforth such limitations make such an approach less reliable and less accurate in terms of performance evaluation.
Hence, there is a need for an improved system and method for performance evaluation of an exercise performed by the user to address the aforementioned issues.
BRIEF DESCRIPTION
In accordance with one embodiment of the disclosure, a system for performance evaluation of an exercise performed by a user is provided. The system includes one or more processors. The system also includes an input subsystem configured to receive user data from the user. The system also includes a calibration subsystem configured to calibrate an exercise mat for the corresponding user based on received user data using a calibration technique and to generate calibration data upon calibrating the exercise mat. The system also includes a monitoring subsystem configured to receive one or more exercise parameters from the exercise mat, wherein the exercise parameters are associated with the exercise performed by the user on the exercise mat. The monitoring subsystem is also configured to compute the one or more exercise parameters and a pre-defined set of parameters using a computation technique for generating a computed result. The system includes an evaluation subsystem configured to evaluate the exercise performed by the user in real time upon receiving the computed result to generate evaluated parameters associated with at least one of the user data, the one or more exercise parameters, the calibration data or a combination thereof. The system also includes a training subsystem configured to provide assistive feedback for the exercise performed by the user on the exercise mat in real time based on based on the evaluated parameters.
In accordance with another embodiment of the disclosure, a method for performance evaluation of an exercise performed by a user is provided. The method includes receiving user data from the user. The method also includes calibrating an exercise mat for the corresponding user based on received user data using a calibration technique for generating calibration data. The method also includes receiving one or more exercise parameters from the exercise mat, wherein the exercise parameters are associated with the exercise performed by the user on the exercise mat. The method also includes computing the one or more exercise parameters with a pre-defined set of parameters using a computation technique for generating a computed result. The method also includes evaluating the exercise performed by the user in real time upon receiving computed result to generate evaluated parameters associated with at least one of the user data, the one or more exercise parameters, the calibration data or a combination thereof. The method also includes training the exercise performed by the user on the exercise mat in real time based on based on the evaluated parameters.
To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.
BRIEF DESCRIPTION OF THE DRAWINGS
The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which:
FIG. 1 is a block diagram representation of a system for performance evaluation of an exercise performed by a user in accordance with an embodiment of the present disclosure;
FIG. 2 is a block diagram representation of a computer or a server in accordance with an embodiment of the present disclosure; and
FIG. 3 is a flow chart representing steps involved in a method for performance evaluation of an exercise performed by a user in accordance with an embodiment of the present disclosure.
Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.
DETAILED DESCRIPTION
For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure.
The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more devices or sub-systems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.
Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.
In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.
Embodiments of the present disclosure relate to a system and method for performance evaluation of an exercise performed by a user. The system includes one or more processors. The system also includes an input subsystem configured to receive user data from the user. The system also includes a calibration subsystem configured to calibrate an exercise mat for the corresponding user based on received user data using a calibration technique to generate calibration data. The system also includes a monitoring subsystem configured to receive one or more exercise parameters from the exercise mat, wherein the exercise parameters are associated with the exercise performed by the user on the exercise mat. The monitoring subsystem is also configured to compute the one or more exercise parameters with a pre-defined set of parameters using a computation technique. The system includes an evaluation subsystem configured to evaluate the exercise performed by the user in real time upon receiving computed result to generate evaluated parameters associated with at least one of the user data, the one or more exercise parameters, the calibration data or a combination thereof. The system also includes a training subsystem configured to provide assistive feedback for the exercise performed by the user on the exercise mat in real time based on based on the evaluated parameters.
FIG. 1 is a block diagram representation of a system (10) for performance evaluation of an exercise performed by a user. As used herein, the term “exercise” is defined as is any bodily activity that enhances or maintains physical fitness and overall health and wellness of the user. In one embodiment, the exercise may include one of Pilate, yoga, floor exercise and the like. The system (10) includes one or more processors (20). The system (10) also includes an input subsystem (30) configured to receive user data from the user. In one embodiment, the user data may include at least one of height, weight, gender, body mass index, type of exercise associated with the user.
The system (10) also includes a calibration subsystem (40) operatively coupled to the input subsystem (20). The Calibration subsystem (40) is configured to calibrate an exercise mat for the corresponding user based on received user data using a calibration technique to generate calibration data. In one embodiment, exercise mat may include one of a Pilate mat, a yoga mat, a fitness mat, a wellness mat and the like. In one exemplary embodiment, the calibration technique may include one of a machine learning technique and an artificial intelligence technique. As used herein the term “artificial intelligence” refers to sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals, such as visual perception, speech recognition, decision-making, and translation between languages. Also, the term “machine learning” refers to an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programme.
Furthermore, the system (10) includes a monitoring subsystem (50) operatively coupled to the calibration subsystem (40). The monitoring subsystem (50) is configured to receive one or more exercise parameters from the exercise mat, wherein the exercise parameters are associated with the exercise performed by the user on the exercise mat. In one embodiment, the one or more exercise parameters may be received by at least one sensor matrix which may comprise one or more sensors, wherein the at least one sensor matrix may be operatively coupled to the exercise mat. In such embodiment, the one or more sensors may include at least one of a pressure sensor, a contact sensor, a touch sensor, a stability sensor, a temperature sensor, a proximity sensor and the like.
In one exemplary embodiment, the one or more exercise parameters may include data associated to at least one of pressure, weight, distance between user’s hands and legs, and the like upon performing the exercise on the mat upon making a contact with a body of the user with the mat. In such embodiment, the one or more exercise parameters may be monitored to determine at least one of flexibility, balance, strength, physiological parameters and the like of the user while performing the exercise on the exercise mat.
The monitoring subsystem (50) is also configured to compute the one or more exercise parameters with a pre-defined set of parameters using a computation technique. In one embodiment, the computation technique may include one of the machine learning technique and the artificial intelligence distance. In one specific embodiment, the system (10) may further include a mat training subsystem (not shown in FIG. 1) which may be operatively coupled to the calibration subsystem (40). The training subsystem may include training data for different personas which is possible through a crowd-sourcing platform for one or more exercise experts for the training of the corresponding one or more exercises. In such embodiment, the training of the one or more exercise experts may be done using one of an artificial intelligence technique or a machine learning technique.
The system (10) also includes an evaluation subsystem (60) operatively coupled to the monitoring subsystem (50). The evaluation subsystem (60) is configured to evaluate the exercise performed by the user in real time upon receiving computed result to generate evaluated parameters associated with at least one of the user data, the one or more exercise parameters, the calibration data or a combination thereof. In one embodiment, the exercise may be evaluated upon comparing the computed result with a pre-defined set of data, wherein the pre-defined set of data may be associated with the one or more exercise experts which may be calibrated with the corresponding user and the corresponding exercise mat prior to initiate the monitoring of the exercise being performed by the user on the exercise mat in real time.
In one exemplary embodiment, upon calibrating the exercise mat with the corresponding user and the user details, the exercise which is performed by the user on the exercise mat is monitored in real time to guide and train the user. In order to achieve the same, the one or more exercise parameters is compared with the pre-defined set of data which may be configured at the time of calibration of the exercise mat.
Furthermore, the system (10) includes a training subsystem (70) operatively coupled to the evaluation subsystem (60). The training subsystem (70) is configured to train and guide the exercise performed by the user on the exercise mat in real time based on the evaluated parameters. In one specific embodiment, the training subsystem (70) may generate the notification to the user based on the evaluated result.
In one specific embodiment, the system (10) may further include a correction subsystem (not shown in FIG. 1) operatively coupled to the evaluation subsystem (60). The correction subsystem may be configured to compute a tolerance value representative of correction of the exercise performed by the user on the exercise mat. In such embodiment, the tolerance value for correction of the exercise may be defined based on type of the user, wherein the type of the user may be one or more exercise experts, a practitioner, a student, or the like.
In one exemplary embodiment, the system (10) may further include a feedback subsystem (not shown in FIG. 1) which may be operatively coupled to the training subsystem (70). The feedback subsystem may be configured to generate a feedback for the user based on the performance of the exercise being performed by the user on the exercise mat. In such embodiment, the feedback may be generated based on a computed value of the evaluation output and the tolerance level for correction of the exercise performed by the user. In one specific embodiment, the feedback may be in a form of message, wherein the message may be a text message, a voice message, a multimedia message, or the like.
In another exemplary embodiment, the system (10) may further include a score generation subsystem (not shown in FIG. 1) which may be operatively coupled to the evaluation subsystem. The score generation subsystem may be configured to generate one or more scores representative of the corresponding one or more aspects associated with the exercise performed by the user on the exercise mat. In one embodiment, each of the one or more scores may be associated with a corresponding one or more exercise parameters. More specifically, each of the one or more exercise parameters may be assigned with the corresponding one or more scores. The one or more scores may be generated for at least one of flexibility, balance, strength, physiological parameters and the like of the user while performing the exercise on the exercise mat. In such embodiment, the one or more scores may be generated based on the evaluated result. In one specific embodiment, the score generation subsystem may be configured to generate relative performance which may be in a form of percentage improvement or a percentage degradation with respect to the performance parameters at the calibration phase.
Referring back to the above-mentioned embodiment, the calibration subsystem may be further configured to re-calibre the exercise mat upon identifying a significant performance change in the exercise performed by the user on the exercise mat. In such embodiment, the calibration subsystem may use one or more calibration tests such as posture test for flexibility and balance which are based only on plantar pressure measurement using the exercise mat.
In one specific embodiment, the performance of exercise performed by the user on the exercise mat may be computed by one of a Center of Plantar Pressure (COP) or a Center of Plantar Pressure Displacement (COPD). As used herein the term “Center of Plantar Pressure (COP)” is defined as a pressure field that acts between the foot and the support surface during everyday locomotor activities. In such embodiment, the COP of the user may be calibrated with normal standing pose of the user on the exercise mat. In such another embodiment, the COP displacement may be computed while the user is performing the exercise on the exercise mat.
In one specific example, a time for holding a pose of the exercise on the exercise mat may be Tref . Further the COPD which may be obtained during calibration may be used as a reference for strength and flexibility computation. In one exemplary embodiment, Forward bend test gives balance as well as strength using COPD and COPV (COP mean Velocity) whereas bending down to touch the palms while standing, provides COPD reference for flexibility, called as ?COPD?_ref^bal , , ?COPV?_ref^str, ?COPD?_ref^flex respectively.
Furthermore, the ?COPV?^str may be computed using the equation:
?COPV?^str = (?_(i=1)^q¦?COPD?_i^bal )/q ,
Where, q is the quotient of T_hold/T_ref for observations and for calibration, q = T_ref as COPD is computed for every pre-defined time interval. In one specific embodiment, the pre-defined time interval may be one of seconds, minutes or the like.
In another specific embodiment, the performance of exercise performed by the user on the exercise mat may be computed by Posture Perfection Score. For example, Score for a yoga asana k performed N times may be given by
P^k=100 x (1- (?_(i=1)^N¦?x_i X E_i^k ?)/N)
E_i^k= v(?_(i=1)^nP¦?w_l^k X ((a_(P )^l- µ_P^l)/(µ_P^l ))^2+ ?_(m=1)^nPr¦?w_m^k X ((a_Pr^m- µ_Pr^m)/(µ_Pr^m ))^2 ??)
Where, x_i is an indicator variable, x_i = 1 if the asana k is performed with error (i.e., with at least one correction) and zero otherwise.
E_i^k is the total error computed for asana k when performed i^th time.
nP, nPr, nOr denote the number of position, pressure and orientation points on the exercise mat, respectively.
w_j^k denotes weight for the error at point j (for position, pressure or orientation) in asana k.
a_(P ), a_(Pr ), a_(Or )denote actual test values for position, pressure or orientation for i^th time and µ_(P ), µ_(Pr ), µ_(Or )are the mean values from training data, respectively.
In yet another specific embodiment, the performance of exercise performed by the user on the exercise mat may be computed by strength improvement. For example, hoe steady and for how long the user can balance the posture may be measured using the equation:
?BLS?^k = 100 X w_bal^k X ((?COPD?_(T_ref)^bal- ?COPD?_ref^bal )/(?COPD?_ref^bal )+ (?COPV?_(T_hold)^str- ?COPD?_ref^str )/(?COPD?_ref^str )+ w_hold X (T_(hold )- T_ref )/T_ref )
Where, w_bal may be 1 whenever asana k involves balancing and is zero otherwise.
T_(hold ) is the time for which yoga asana may be maintained.
w_hold varies based on inputs like teacher or student or practitioner from the one or more user or the one or more expert users and the corresponding lifestyle.
In yet another specific embodiment, the performance of exercise performed by the user on the exercise mat may be computed by flexibility improvement. For example, for every attempt of the yoga asana k, flexibility score ?FL?^k may be computed as follows:
?FL?^k=100 X w_flex^k X (?COPD?_obs^flex- ?COPD?_ref^flex )/(?COPD?_ref^flex )
Where, w_flex may be 1 whenever asana k involves stretching and flexibility and may be zero otherwise. Henceforth, the above parameters are computed to analyse, train and guide the user for the exercise performed by the ser on the exercise mat.
FIG. 2 is a block diagram representation of a computer (80) or a server (80) in accordance with an embodiment of the present disclosure. The server (80) includes processor(s) (90), and memory (100) coupled to the processor(s) (90) through a bus (110).
The processor(s) (90), as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a digital signal processor, or any other type of processing circuit, or a combination thereof.
The memory (80) includes a plurality of subsystems stored in the form of executable program which instructs the processor (90) to perform the method steps illustrated in FIG. 3. The memory has following subsystems: an input subsystem (30), a calibration subsystem (40), a monitoring subsystem (50), an evaluation subsystem (60) and a training subsystem (70).
The input subsystem (30) is configured to receive user data from the user.
The calibration subsystem (40) is configured to calibrate an exercise mat for the corresponding user based on received user data using a calibration technique to generate calibration data.
The monitoring subsystem (50) is configured to receive one or more exercise parameters from the exercise mat, wherein the exercise parameters are associated with the exercise performed by the user on the exercise mat and to compute the one or more exercise parameters with a pre-defined set of parameters using a computation technique.
The evaluation subsystem (60) is configured to evaluate the exercise performed by the user in real time upon receiving computed result to generate evaluated parameters associated with at least one of the user data, the one or more exercise parameters, the calibration data or a combination thereof.
The training subsystem (70) is configured to provide assistive feedback for the exercise performed by the user on the exercise mat in real time based on the evaluated parameters.
Computer memory elements may include any suitable memory device(s) for storing data and executable program, such as read only memory, random access memory, erasable programmable read only memory, electrically erasable programmable read only memory, hard drive, removable media drive for handling memory cards and the like. Embodiments of the present subject matter may be implemented in conjunction with program modules, including functions, procedures, data structures, and application programs, for performing tasks, or defining abstract data types or low-level hardware contexts. Executable program stored on any of the above-mentioned storage media may be executable by the processor(s).
FIG. 3 is a flow chart representing steps involved in a method (120) for performance evaluation of an exercise performed by a user. The method (120) includes receiving user data from the user in step 130. In one exemplary embodiment, receiving the user data may include receiving the user data by an input subsystem. In one embodiment receiving the user data may include receiving the user data from a computing device, wherein the computing device may include one of a laptop, a mobile phone, a tablet or the like. In such embodiment, receiving the user data may include receiving at least one of height, weight, gender, body mass index, type of exercise associated with the user. In such embodiment, wherein receiving the user data from the user may include receiving height, weight, gender, body mass index, type of exercise associated with the user
The method (120) also includes calibrating an exercise mat for the corresponding user based on received user data using a calibration technique to generate calibration data in step 140. In one exemplary embodiment, calibrating the exercise mat may include calibrating the exercise mat by a calibration subsystem. In one embodiment, calibrating the exercise mat may include calibrating the exercise mat based on received user data using one of a machine learning technique and an artificial intelligence technique.
Furthermore, the method (120) includes receiving one or more exercise parameters from the exercise mat, wherein the exercise parameters are associated with the exercise performed by the user on the exercise mat in step 150. In one exemplary embodiment, receiving the one or more exercise parameters may include receiving the one or more exercise parameters by a monitoring subsystem. In one embodiment, receiving the one or more exercise parameters may include receiving at least one of flexibility, balance, strength and physiological parameters of the user while performing the exercise on the exercise mat.
The method (120) also includes computing the one or more exercise parameters with a pre-defined set of parameters using a computation technique in step 160. In one exemplary embodiment, computing the one or more exercise may include computing the one or more exercise parameters by the monitoring subsystem. In such embodiment, computing the one or more exercise parameters may include computing the one or more exercise parameters using one of the artificial intelligence technique and the machine learning technique.
The method (120) also includes evaluating the exercise performed by the user in real time upon receiving computed result to generate evaluated parameters associated with at least one of the user data, the one or more exercise parameters, the calibration data or a combination thereof in step 170. In one exemplary embodiment, evaluating the exercise may include evaluating the exercise by an evaluation subsystem. In one embodiment, evaluating the exercise performed by the user upon comparing the computed result with a pre-defined set of data, wherein the pre-defined set of data may be associated with the one or more exercise experts which may be calibrated with the corresponding user and the corresponding exercise mat prior to initiate the monitoring of the exercise being performed by the user on the exercise mat in real time.
Furthermore, the method (120) includes training the user for the exercise performed by the user on the exercise mat in real time based on based on the evaluated parameters in step 180. In one exemplary embodiment, training the exercise performed by the user may include training the user by a training subsystem. In one specific embodiment, the method (120) may include generating a notification to the user based on the evaluated result.
In another exemplary embodiment, the method (120) may further include computing a tolerance value representative of correction of the exercise performed by the user on the exercise mat. In such embodiment, the tolerance value for correction of the exercise may be defined based on type of the user, wherein the type of the user may be one or more exercise experts, a practitioner, a student, or the like.
In yet another exemplary embodiment, the method (120) may further include generate a feedback for the user based on the performance of the exercise being performed by the user on the exercise mat. In such embodiment, the feedback may be generated based on a computed value of the evaluation output and the tolerance level for correction of the exercise performed by the user.
In yet another embodiment, the method (120) may further include generating one or more scores representative of the corresponding one or more aspects associated with the exercise performed by the user on the exercise mat. In such embodiment, generating the score may include generating the score by a score generation subsystem. The one or more scores may be generated for at least one of flexibility, balance, strength, physiological parameters and the like of the user while performing the exercise on the exercise mat. In such embodiment, generating the one or more scores may include generating the one or more scores based on the evaluated result. In one specific embodiment, the method (120) may further include generating relative performance which may be in a form of percentage improvement or a percentage degradation with respect to the performance parameters at the calibration phase.
Referring back to the above-mentioned embodiment, the method (120) may include re-calibrating the exercise mat upon identifying a significant performance change in the exercise performed by the user on the exercise mat. In such embodiment, re-calibrating the exercise mat may include re-calibrating the exercise mat by using one or more calibration tests such as posture test for flexibility and balance which are based only on plantar pressure measurement using the exercise mat.
In one specific embodiment, the performance of exercise performed by the user on the exercise mat may be computed by one of a Center of Plantar Pressure (COP) or a Center of Plantar Pressure Displacement (COPD). In another specific embodiment, the performance of exercise performed by the user on the exercise mat may be computed by one of a Posture Perfection Score, flexibility improvement, strength improvement or the like for analysing, training and guiding the user for the exercise performed by the ser on the exercise mat.
Various embodiments of the present disclosure enable the system to monitor, train, guide and provide assistive feedback for the user for the exercise being performed on the exercise mat. In addition, the system will enable the calibration of the exercise mat before the exercise is performed by the user. Also, the system monitors the varying parameters of the user while performing the exercise on the exercise mat, which makes the system more accurate and more reliable.
While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.
The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependant on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples.