Validation, and Method thereof

FIELD OF THE INVENTION

The present invention relates to a system and workout clotting intended for personalized exercise monitoring in conjunction with the system, and method for personalized physical exercise monitoring and validation. More specifically, it relates to a system based on personalized physical exercise guidance tailored to individual fitness level of the exerciser or respectively to individual physical rehabilitation exercises. Furthermore, it relates to a method for training and validation of motion tasks of a person, wherein the tasks are structured according to the individually tailored exercises.

BACKGROUND OF THE INVENTION

Various electronic apparatus and devices are used for automatically tracking and recording the movements of a human body during a physical activity such as a sporting activity or other health-related activity. The purpose of such apparatus and devices can be to eliminate the need of the person performing the activity or another person to manually track and record the accomplishment of a particular physical activity, such as the completion of an exercise. Another example of physical activity tracking and recording devices are those that are worn directly on the body of the exerciser. Such devices may include sensors, heart-rate monitors, GPS units or watches, and like electronics and may be used alone or in connection with other apparatus to automatically track and record parameters such as distance traversed, elapsed time, pace, amount of calories burned, heart rate, and the like of the user relative to a known exercise. Wearable computing systems are an emerging category of devices. These devices enable users to perform a variety of tasks. For example, users may virtually interact with online accounts; record and/or observe information such as videos, images, and sounds; control other computing systems and other connected appliance; interact with other people; and in some instances monitor the current conditions, state and performance of an individual's body. Devices capable of monitoring an individual's fitness have become increasingly popular. Monitoring and maintaining physical fitness is an ongoing concern for individuals with busy lifestyles, and this concern is becoming more pronounced with an aging population. Despite this effort there still exists a need in the art for an improved home rehabilitation or training system that can track physical activities progression of the patient physical rehabilitation, or to track individual fitness.

The system and method according to present invention aims to enable knowledge based personalized supervised physical exercise guidance tailored to individual fitness level of the exerciser and matched to exerciser's needs in terms of fulfilling the tasks of the exercising (e.g. training or rehabilitation). The system also uses tools to add to sustainability of rehabilitation and to increase the motivation to exercise of vulnerable groups of patients, e.g. persons in physical rehabilitation or diabetics, and has added value to pre-diabetes conditions handling by preventing obesity.

The objectives off or such a system and method are following:

• improving health and wellbeing of individuals who do not have a possibility to regularly participate in individual or group physical activities in fitness centre due to long working hours, busy working schedule, frequent travelling, distant housing or own finances,

· enabling rehabilitation at home in order to extend the time of rehabilitation (stay in rehabilitation centre is usually short and extension is recommended in most cases to patients),

• to provide workout clothing and charging device for the same,

• to optimize battery discharge, and

· to enable validation of each training session in order to improve exercising accuracy. The system according to present invention enables work with multiple users at the same time. Further system and method according to the present invention consists essentially of the wireless body sensor network (WBSN) comprising multiple sensor nodes (SN), each of which is switchable (on - off). Sensor nodes are embedded into workout clothing consisting of several parts, where each part can be worn separately or individually depending on the training plan and exercises. For each exercise an optimal number of sensor nodes is active in order to monitor the person exercising and measure the movement data. In the objective of minimizing the SN battery power consumption, for each exercise only the optimal set of SNs is switched on. Accordingly each part of the workout clothing comprises main sensor node (MSN) which performs wirelessly transferring of the sensor data to the e-platform in the cloud. E-platform comprises database and software with tools designed for creating personal training exercise record, and performing qualitative and quantitative validation of each the training session. Further according present invention recharging of batteries of the sensor nodes embedded into of the workout clothing is performed simultaneously and wirelessly in the new charging device. BRIEF DESCRIPTION OF THE DRAWINGS

Figs. 1 and 2 illustrate a system according to the present invention,

Fig. 3 illustrates a workout clotting according to the present invention,

Fig. 4 illustrates a charging device intended for charging of the workout clothing according to the present invention;

Figs. 5a - 5c illustrate training session over time, where in 5a) the wake-up session on SNs (2) is shown, in 5b) setting of optimal configuration for exercise 1 is shown and in 5c) detailed time diagram of training session and functionalities of the parallel processes are shown, Fig. 6 illustrates interactive screen of the exerciser's device of motional exercise in 2D presenting virtual trainer and virtual character of the exerciser, and

Fig. 7 shows a flow diagram illustrating process of a training session.

DETAILED DESCRIPTION OF THE INVENTION

Before the invention is described in detail it is to be understood that this invention is not limited to the particular component parts of the devices described or process steps of the methods described as such devices and methods may vary. It is also to be understood that the terminology used herein is for purposes of describing particular embodiments only and is not intended to be limiting. It must be noted that as used in the specification and the appended claims the singular forms "a," "an", and "the" include singular and/or plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a sensor" may include several sensors, and the like.

The system according present invention may be used for:

1 ) assigning personalized set(s) of exercises by trainer to exerciser,

2) assigning personalized set(s) of exercises by physical therapist to patient in rehabilitation,

3) monitoring of exercising process,

4) visualization of motional exercise 2D or 3D pattern on a part of a screen of a mobile device or a personal computer in the shape of a virtual trainer,

5) visualization of own individual exercising in real time on a screen in the shape of a virtual character whose appearance may be modified according to own preference, and

6) qualitative and quantitative validation of the exercising process. The system, as illustrated in figs. 1 and 2, consisting essentially of a wireless body sensor network (WBSN), a set of workout clothing 1 which serves as the carrier of the WBSN sensor nodes 2, one or more access points 4a connected to the Internet and/or a smart mobile phone 4, or a computer 6a, and an e-platform 5 in the cloud 7 with the supporting software for personalized physical exercise monitoring and validation.

A wireless body sensor network (WBSN) comprises multiple sensor nodes 2 powered by rechargeable batteries, each sensor node 2 being embedded into workout clothing 1 wearable of an exerciser during performance of a plurality of exercises, where each of the sensor nodes 2 is switchable and for each exercise only optimal number of sensor nodes is switched on and are communicating sensor data 106 through a wireless communication channel to the selected main sensor node 3. An e-platform 5 in the cloud 7 comprises supporting software with e-platform tools.

Exerciser's device (4, 6a) and virtual trainer device (4b, 6b) are in communication over Internet connection with the e-platform 5, wherein selected main sensor node 3 is wirelessly connected to said exerciser's device for transferring the sensor data 106 to the e-platform 5, where the e-platform 5 is configured to communicate said data to the virtual trainer device (4b, 6b) in regular time intervals.

The system according to present invention is configured to:

- input and store personalized training exercise plan, the pace of the exercising and exercising process into personal exerciser's record in the database arranged in e- platform (5),

- perform configuration of the operation of sensor nodes 2 and selection of main sensor node 3 according to performance of each particular exercise stored in personalized training exercising plan,

- create and store movement record selected form the sets of exercises performed by virtual trainer, and create and store referent movement record selected form the sets of exercises performed by exerciser consisting of an array of orientations sampled from sensor nodes 2 during one repetition of an exercise, where the stored exerciser's referent movement record from the said array is the one with at least deviation in comparison with the movement record performed by virtual trainer,

- measure the exerciser's movements performed in each exercise and process the data obtained from said movements performed in each exercise and perform visualization of motional exercise in 2D or 3D pattern on a part of a screen of the exerciser's device (4, 6a) in the form of a virtual character, and simultaneously visualization of referent movements of the virtual trainer in real time on the adjacent part of the screen,

- qualitatively and quantitatively validate the training session using referent movement record selected form the sets of exercises performed by the exerciser in respect of movements records associated to the said set of exercises performed by the virtual trainer, and

- store all data into the exerciser's personal record in e-platform (5).

The qualitative validation of the training session enables that the best ranged exerciser's movement record is stored as referent for further training sessions and each correctly performed exercise movement is used for subsequent quantitative validation and continuously comparing the exerciser's performance with the referent movement records. The qualitative validation of the training session is based on qualitative validation of each exerciser's movement by determining whether the deviation of exerciser's movement is within the limits of error predetermined by the training plan, and in case it is within the said limits, the quantitative score is increased by one point. Further, on the exerciser's device (4, 6a) and trainer device (4b, 6b) screens interactive user interface is displayed comprising the database with personalized exerciser's data on performed exercises, the information on exercise characteristics and data comprising each exercise visualization and result of the qualitative and quantitative validation. The database in the cloud is configured to comprise sub-database comprising plurality of different exercises from which specifically tailored exercises according to the user needs can be selected to create training exercising plan. Visualization of performance of each exercise in said sub-database in the form of virtual trainer is enabled. Further the database is configured to include for each user private record to which are associated selected exercises to be performed in each training session.

The supporting software comprises e-platform tools enabling definition of the training exercising plan consisting essentially of: the duration of the each training session (TS), exercises to be performed in a training session (TS) selected from the sub-database, the number of sets of a particular exercise which the exerciser is imposed to repeat during the training session (TS), the number of repetitions of the exercise during each set for a particular exercise, the pace of exercising including duration of inter-set pauses (ISP) between sets of exercises, and pauses between the repetitions (IRP) within the set; wherein the training plan is stored into the exerciser's private record in the database in e-platform (5), and the exerciser can access to the training plan at any time. Each sensor node 2 is assigned to a particular exerciser body part by arranged position on the workout clothing 1. Sensor data 106 is, after processing by the processing unit of the sensor node 2, transmitted by the communication circuit through a wireless communication channel to the main sensor node 3 which in turn organizes the dataflow from the wireless body sensor network to the e- platform 5. Further advantage of present invention is that any sensor node 2 of the wireless body sensor network can be configured as the main sensor node 3, so that any of the workout clothing 1 parts may be worn alone and independently, without the need to wear the other parts of workout clothing 1 .

The WBSN is organized in such a way that individual sensor nodes 2 communicate with the main sensor node 3 according to a pre-set schedule illustrated in Fig 5a. At the beginning of each training, before the exercise sessions start, during the sensor node 2 wake up period, the main sensor node 3 sends a synchronization pulse in order to synchronize local processor units of the sensor nodes 2. Each sensor node 2 responds to the synchronization pulse by sending an acknowledgment message where the sensor nodes 2 organized in the WBSN respond with the acknowledgment message in a predefined order, each with a predefined delay ΔΤ. Each sensor node 2 is configurable for optimizing battery energy consumption in a way that each sensor node 2 may be switched on and off. The configuration of the operation of sensor nodes 2, e.g. data on which sensor node 2 is switched on and which sensor node 2 is switched off on particular workout clothing part 1 , for a particular exercise is programmed for each exercise and stored in the e-platform 5. The configuration of sensor nodes 2 is depending on which part or parts of the body are exercising targets. In that way, in addition to optimization of the battery energy consumption of each sensor node 2, also the need for frequent recharging of the sensor nodes 2 is reduced. There are two possibilities for transfer of the data from the main sensor node 3 to the e-platform 5 in the cloud 7. Main sensor node3 device is connected to a mobile communication device 4 and transfers the data to the e-platform 5 in the cloud 7 in regular intervals. Alternatively, main sensor node 3 device is connected to an access point 4a to Internet and transfers the data to the e-platform 5 in the cloud 7 in regular intervals. The users have access to the e-platform 5 via a personal computer 6a, 6b and/or 6c where under personal computer either desk-top or laptop configurations are considered connected to the Internet, or via their smart mobile phones 4, 4b and/or 4c, or respectively Internet access point. The e-platform 5 has an interactive user interface displayed on the screen of abovementioned devices, the database with user's data on performed exercises, the database with information on exercise characteristics and data comprising each exercise visualization.

The workout clothingl and charging device 9 for the same according to the present invention is now described with further reference to Figs. 3 and 4. The workout clothing 1 consists of a cap, a long sleeve T - shirt, gloves and trousers with the leg prolonged opening, where the sensor nodes 2 are hermetically sealed and waterproof. Each of the sensors nodes 2 comprises a set of inertial sensors configured to measure a parameter selected from a group consisting of motion, acceleration, position relative to one or more others sensor nodes 2. Exerciser's device (4, 6a) and trainer device (4b, 6b) are selected from the group consisting of the smart mobile communication device (4, 4b, 4c), personal computer device (6a, 6b, 6c) or laptop device. Further each sensor node 2 is powered by a rechargeable battery, wherein battery charging is provided by a wireless battery charging device 9. The wireless body sensor network (WBSN) consists of multiple sensor nodes 2 where each sensor node 2 is assigned to a particular body part by arranged position on the set of workout clothing 1 . The sensor nodes 2 are of the same, small size and have the same functionalities but are positioned to different body parts by means of their fixed position on workout clothing 1 . The sensor nodes 2 are hermetically sealed and therefore waterproof. In some examples, a form- fitting sensor workout clothing may include at least one sensor node 2 and associated processing and communications electronics. In other examples, the one or more sensors may be washable sensors that may be borne or otherwise coupled with a workout clothing 1 and configured to be unaffected and/or undamaged by washing or otherwise cleaning or maintaining the said clothing. One or more form-fitting sensor workout clothing may be made to be conformal to any part of the human body as desired. Each sensor node 2 comprises a set of inertial sensors, circuits for sensor signal processing, analogue to digital conversion of the sensor signals into sensors data, a sensor data processing unit and a communication circuit. Each sensor node 2 is capable of measuring its position, acceleration and rotational motion provided by the sensor signals. Sensor data 106 is, after processing by the processing unit on the sensor node 2, transmitted by the communication circuit through a wireless communication channel to the main sensor node (MSN) 3 which in turn organizes the dataflow from the WBSN to the e-platform 5 by wireless communication with an access point 4a or a mobile communication device 4. Any sensor node 2 of the WBSN can be configured as the main sensor node 3, so that any of the workout clothing 1 parts may be worn alone and independently, without the need to wear the other parts of workout clothing 1 and to switch the sensor nodes 2 from those, unused workout clothing parts, on. Each sensor node 2 is powered by a rechargeable battery, wherein battery charging is provided by a wireless battery charging device 9.

The sensor nodes 2 are embedded into the workout clothing 1 . The set of workout clothingl comprises of a cap (similar to monkey cap or skiing mask), of a long sleeve T - shirt with gloves and trousers where the leg opening is prolonged allowing sensor embedding on the top of the foot. Workout clothing 1 parts are elastic and enable fitting to the body part which the clothing covers. On the workout clothing 1 , small pockets are made to accommodate the sensor nodes 2. The sensor nodes 2 are embedded in such a way that each pocket is hermetically enclosed to prevent displacement or falling out of the sensor node 2.

For the purpose of rechargeable batteries charging, a special charging device is used 9. The charging device 9 comprises of a housing produced out of insulating material where in the bottom 9a and on the top 9b of the housing, a set of high frequency antennas 10 is built in. The power supply 8 supplies the antennas 10 with high frequency energy which in turn is emitted through the charging device and through each of sensor nodes 2 for sensor node 2 embedded rechargeable batteries charging. The workout clothing 1 part or parts which is the carrier of the sensor nodes are put into the charging device through an opening 9c of appropriate size. In such a way, all rechargeable batteries embedded in sensor nodes 2 are recharged at the same time which adds to the usability of the system as a whole.

The trainer and the exerciser establish a contact in order to plan the training plan for the exerciser. The function of the trainer is to gather information relevant for health status, health needs and training expectations of the exerciser. The relevant data is entered into the users (exercisers) personal data in the user's database in the e-platform 5.

The planning tools enable the trainer to make a training plan. Establishing of a training plan starts with assigning personalized set(s) of exercises to the exerciser/patient by the trainer/therapist. Such a personalized set of exercises performed in a series within a limited prescribed period of time is referred to as a training session. Each training session consists of one or more exercises where an exercise is defined as a physical effort performed in a determined, repeatable fashion. Each exercise may be repeated in one or several sets, and each set consists of one or several repetitions. The trainer uses the e-platform tools to compose the training sessions. In a training plan the trainer:

1. determines the duration of the each training session,

2. selects exercises to be performed in an each training session from the sub- database,

3. assigns the number of sets of a particular exercise which the exerciser is supposed to repeat during the training session,

4. assigns the number of repetitions of the particular exercise during each set,

5. determines the pace of exercising (including duration of pauses between sets of exercises ISP and pauses between the repetitions of within the set), and 6. saves the training plan into the exercisers private record in the database, wherefrom the exerciser can access the training plan any time connected to the cloud 7.

For every exercise a trainer assigns to an exerciser, there is a referent movement record that precisely describes how the exerciser should perform the exercise. This referent movement record consists of an array of orientations sampled from all sensor nodes 2 during one repetition of an exercise. This record is obtained while the exerciser performs the desired exercise under the immediate supervision of a trainer. Referent movement record is then used to guide the exerciser in correctly performing the assigned exercises and to qualitatively and quantitatively validate the training session. Using own correct referent movements to validate the training session enables personalization of each exercise for a particular user. Whenever the exerciser performs a particular exercise for the first time, the exercising is performed under the supervision of the trainer. The trainer teaches the exerciser how to perform the exercise correctly. After the exerciser has adopted the correct way of performing the exercise, the trainer stores the data on his correct movements as the personal reference data for that particular exercise for a particular exerciser. Whenever exerciser performs the particular exercise again, the calculation of deviations will be referred to his own data on movements during exercising. The quantitative and qualitative evaluation of an exercise being performed is done by comparing the appropriate member of the referent orientation array and the current orientations measured by sensor nodes 2 on the exercisers body. Larger differences or deviations between these orientations mean a poorer performance. A score is assigned to every exercise repetition performed. The score is directly proportional to the amount of difference between the actual and referent orientation. If the score of a repetition is smaller than a threshold set for that particular exercise and that particular exerciser, then the repetition is not counted or ranged as successful. The exerciser's performance is validated as successful only if the repetition is correctly performed within the limits of error defined by the reference movement recorded for the particular exerciser under previous supervision of the trainer.

Regular procedure during exercising is described by the following process:

1 . the exerciser puts appropriate part or complete workout clothing 1 before starting the training session,

2. opens the personalized training plan designed for him,

3. the exerciser switches the sensor nodes 2 on and synchronizes it with the platform through the access point 4a or through a smart mobile phone 4, 4. the exerciser starts the training session by switching on the training program on the e-platform 5,

5. the exerciser can follow the instructions given to him by the virtual trainer on the screen of a computer 6a or smart mobile phone 4a,

6. the sensor nodes 2 sense and measure the movements the exerciser performs and sends the movement data to the e-platform 5 where the data is stored in an organized way into the private record of the database on the exerciser,

7. the software in e-platform 5 calculates the deviations of the movements from the referent movements data of the performed exercise which is stored in the exercise database in the e-platform 5,

8. the platform calculates the movements of the exerciser from the data received from the sensor nodes 2 through main sensor node 3 and displays exerciser movements in a window next to the window with the virtual trainer,

9. the exerciser can see own movements and compare it with the displayed movements of the virtual trainer in real time,

10. the results of the comparison of the personal referent movements from the database and the movements performed by exerciser are validated and displayed in the interactive window,

1 1 . the software calculates the number of movements which are considered to be within the allowed limits of error as compared to the referent movement and displays results to the exerciser in the form of an accomplished number of repetitions / default number of repetitions, and

12. at the end of the exercise session, the overall effort and success rate of the performance is displayed and stored in the database in personal exerciser's record.

Each training 100 is initiated by a start training 101 command transferred from the e-platform 5 to exercisers mobile communication device 4 or through an access point 4a that proceeds to the main sensor node 3. During subsequent wake up period the main sensor nodes 3 fetch exercise data 102 for the training 100 from the database in the e-platform 5 and according to the exercise session data selected main sensor node 3 associated to the excise data for particular body part establishes communication with each sensor node 2 in the WBSN in a predetermined sequence and with a predefined delay ΔΤ between the exchange of communication messages between the sensor nodes 2 and the main sensor node 3 (Fig 5a). The selected main sensor node 3 remains in communication only with those sensor nodes 2 which were switched on in a predetermined sequence and with a predefined delay ΔΤ between the exchanges of communication messages (Fig. 5b).

At the beginning of each exercise (e.g. EX. 1 in Fig 5b) the initial sensor nodes 2 position 103 is defined by switching on appropriate sensor nodes 2 for that particular exercise. After the start of the exercise set 104 and also the start of first repetition 105 which comprises of k repetitions, the visualization of virtual trainer exercise movements on the screen of the exerciser's device is initiated and the measurement of exerciser's movements as well as the processing of exerciser's movement data as well as the visualization of the own virtual character's movements (Fig 5c and 6). This process enables getting data on exerciser's movements 106 which are compared with personal reference data for the exercise 107 and the loop is continued as long the repetition is not finished 108. After each repetition the data is qualitatively and quantitatively evaluated and the scoring result of each repetition movement is displayed on the screen and stored 109. This process continues as long as all prescribed repetitions of a set are not finished 1 10 after which the exercise set is evaluated 1 1 1 and the set score displayed on screen and stored (Fig. 5 c).

The set loops are following each other with a pause period 1 13 until the exercise is finished, i.e. all sets of the exercise performed 1 12.

After finishing the particular exercise 1 12, the proscribed training session is continued 1 14 with initiation of a pause 1 16 between the exercises in a loop until the training session is finished 1 15. At the signal level, the main sensor node 3 sends to the mobile communication device 4 or the access point 4a and through said devices also to the e-platform 5 a signal to declare end of communication and check out of the WBSN.

Scoring of the exerciser's performance is illustrated in table in continuation and carried out by calculating each training session where SE refers to particular exercise average score, and C refers to the complexity index associated to particular exercise.

Sji refers to the rate between number of correctly performed repetitions and number of prescribed repetitions in one set of particular exercise, and is presented by formulae [1 ]. [1 ]

itzji

where /¾, is number of correctly performed repetitions, and n _z y/ is number of prescribed repetitions. Each particular exercise may be repeated in one or several sets (i = 1 - k), where each set consists of one or several repetitions. Overall training session consist of N particular exercises (j = 1— N).

For each particular exercise (j ⁼ \ - N) from the sets of repetitions of exercises (/ ^' =1 - k) average score SEj is calculated according to formulae [2].

To each particular exercise =\ - N) complexity index Q is assigned. Overall training session score Sre is calculated according formulae [3].

Calculated overall training session average score (Sre), for each performed training session, is equal to the sum of the products of complexity indexes Cy and average score SEy for each particular exercise, divided with number N of particular exercises performed in one training session.

Method for personalized physical exercise monitoring and validation including multi part workout clothing (1 ) wearable of an exerciser during performance of a plurality of exercises, where each of workout clothing (1 ) parts consisting essentially of the wireless body sensor network (WBSN) comprising multiple sensor nodes (2) where processed sensor data (106) is transmitted through a wireless communication channel to the selected main sensor node (3) which further provides the sensors dataflow from the wireless body sensor network WBSN to the database in e-platform (5) arranged at cloud (7) by wireless communication consisting essentially of the following steps:

a. selecting from database reference virtual trainer movement data for each particular exercise according to the exerciser's training plan, where each particular exercise has assigned complexity indexes Cy, b. inputting and storing personalized training exercising plan into personal exerciser's record in the database arranged in e-platform (5) in the cloud (7), c. wirelessly transferring the personalized training plan to the exerciser's device (4, 6a),

d. configuring the operation of sensor nodes (2) and selecting the main sensor node (3) for wirelessly transferring the sensor data (106) to the e-platform (5) according to performance of each particular exercise stored in personalized training exercising plan,

e. creating and storing each exerciser's repetition movement record of each particular exercise during the training session,

f. qualitatively and quantitatively validating the performance of each training session in real time, expressed as overall training session average score (Sre), and

g. storing the data on the qualitative and quantitative validation into the exerciser's personal record in e-platform (5) database, and updating the personal reference movement data (106) for each performed particular exercise during training session.

Configuring the operation of sensor nodes (2) and selecting the main sensor node (3) is performed during subsequent wakening up period of the main sensor nodes (3) and loading exercise data (102) from the database in the e-platform (5), and according to the exercise session data selecting the main sensor node (3) associated to the excise data for particular body, and establishing communication with each sensor node (2) in the WBSN in a predetermined sequence and with a predefined delay ΔΤ between the exchange of communication messages between the sensor nodes (2) and the main sensor node (3), where the selected main sensor node (3) is communicating with sensor nodes (2) which are switched on in a predetermined sequence and with a predefined delay ΔΤ between the exchanges of communication messages. Qualitative and quantitative validation of the performance of each training session is performed by calculating the rate Sji between number Πψ of correctly performed exerciser's repetitions movement data measured by the sensor nodes 2 and number η _Ζ of prescribed repetitions in one set of particular exercise, where number of particular exercises is y=1 - N and number of sets of repetitions of the particular exercise is / =1 - k; wherein number /¾, of correctly performed repetitions movement data is established by comparing said data with the reference virtual trainer movement data of the same particular exercise stored in database, where the qualitative validation is continuously determining whether the deviation of exerciser's movement data is within the limits of error predetermined by the training plan for particular exercise. For each particular exercise y=1 - Λ/ from the sets of repetitions of exercises / =1 - k, average score SEj is calculated as sum of Sji divided with number of sets of repetitions k. Qualitative and quantitative validation of the performance of each particular exercise is performed by calculating the product of average score SEj and complexity index Cj. Overall training session average score STS, for each performed training session, is equal to the sum of the products of complexity indexes Cj and average score SEj for each particular exercise, divided with number N of particular exercises performed in one training session. Upon finishing training session displaying on the exerciser's device (4, 6a) and trainer device (4b, 6b) screens interactive user interface comprising the database with personalized exerciser's data on performed exercises, the information on exercise characteristics and data comprising each exercise visualization and result of the qualitative and quantitative validation expressed as qualitative and quantitative validation of the performance of each particular exercise and overall training session average score {STS).