WO2020221905A1

WO2020221905A1 - Method and device for processing sensor data of an exercise activity

Info

Publication number: WO2020221905A1
Application number: PCT/EP2020/062154
Authority: WO
Inventors: Daniel Sulser
Original assignee: Daniel Sulser
Priority date: 2019-04-30
Filing date: 2020-04-30
Publication date: 2020-11-05

Abstract

A method of processing sensor data of an exercise activity by a computing device is proposed, the method comprising the steps of generating instructions (S1) for an exercise activity based on a user profile of a user, generating a target activity score (S2), recording exercise data (S7) of the exercise activity being performed by the user, calculating (S9), by the processor (21), a normalized activity score y, and indicating (S10), by the display (22), to the user, to stop performing the exercise activity, once the normalized activity score y has reached the maximum value y0.

Description

METHOD AN D DEVICE FOR PROCESSING SENSOR DATA OF AN EXERCISE ACTIVITY

FIELD OF THE INVENTION

The present invention relates to a method and a device for processing sensor data of an exercise activity. Specifically, the present invention relates to a method and a computing device for processing sensor data of an exercise activity.

BACKGROU N D OF THE INVENTION

Software applications and devices for tracking exercise are well-known. These software applications are often executed on general mobile computing devices, such as smart phones, or executed in close conjunction with a dedicated device, often worn on the body of a user, such as a smart watch. Additional hardware modules for tracking specific parameters about the user, such as heart rate or step counts, are also well-known. Collectively, these exercise trackers, implemented either on a smart phone carried by a user, or implemented on a dedicated device worn on the wrist, for example, serve to gather data about the exercise activity of the user and display the gathered data while the user is performing the exercise activity. After the user has completed the exercise activity these exercise trackers often further provide a summary of the completed exercise activity, such that the user knows how much exercise they have performed. However, the data presented to the user is often not very useful for a novice user, as the user cannot easily judge if they have performed the exercise activity correctly, if they are undertraining, or if they are overtraining. Furthermore, it is often very difficult for a user to compare their effort to previous efforts, once the effects of a gradually increasing level of fitness are taken into account. The user does not know if their most recently completed exercise activity, such as going for a run, was completed better or worse than an exercise activity of six weeks past. It is therefore difficult for a user to judge whether their fitness is progressing as it should. Furthermore, it is difficult for a user to compare their efforts across different types of exercise activity. For example, a user cannot easily compare whether a completed strength training session, or a completed run, were performed with the same quality. Therefore, it is difficult for a user to know where their weak-spots are, or where the user might focus 5 their attention, as each type of exercise activity has its own specific metrics and parameters which are used for assessing the quality of a training session.

Other applications are known which will set a training plan for the user, and provide prompts or alerts to the user as to when and how the user should perform a certain activity, such as going for a run. These training plans will include a typical progression, for example0 for endurance activities the progression will often be in length and/or intensity of the session, with strength-type activities it will be with number of repetitions, difficulty of the types of exercises, or weight used during the exercises. However, these applications are often inflexible as they do not account for different types of exercise activities and allow the user to track many different kinds of exercise activity at once. For example, the user5 who performs both strength training and endurance training will not know when and exactly how much to train such that the strength training does not hinder his endurance training, and vice versa. Further, the user cannot easily comparethe quality of each exercise activity, or training session, between the different types of training.

Furthermore, applications exist which can be used in a group setting, such that a group of0 users can form a team. For example, in cycling, applications exist which provide the group of users with parameters such as aggregate distance covered for all group members. However, these applications, when they provide features which allow one group to compare themselves to another group, make it difficult for each user to contribute equally to the group success, and also make it difficult for groups to compare themselves to each other on the basis of effort.

SUMMARY OF THE INVENTION

It is an object of this invention to provide a method and a device for processing sensor data of an exercise activity that improves the state of the art. Favorably, it does not have at least some of the disadvantages of the prior art.

According to the present invention, these objects are achieved through the features of the independent claims. In addition, further advantageous embodiments follow from the dependent claims and the description. According to the present invention, the above-mentioned objects are particularly achieved by a method of processing sensor data of an exercise activity, by a computing device comprising a processor and a display, the method comprising a number of steps. According to the method, the processor first generates instructions for an exercise activity. The exercise activity is based on a user profile assigned to a user. The instructions provide information to the user on which type of exercise activity to perform, along with additional information about how the exercise activity is to be performed. For endurance-type exercise activities such as running or cycling, such additional information may instruct the user on the planned duration of the exercise activity (such as the time in minutes), the planned length of the exercise activity (such as the distance in kilometers), the planned intensity of the exercise activity (based on perceived exertion of the user, such as easy tempo, moderate tempo, fast tempo, recovery pace, endurance pace, race pace, etc.). The exercise activity may also be a strength-type activity, in which case the instructions for the exercise activity could comprise a number of repetitions to perform, a number of sets of repetitions to perform, along with scheduled rest breaks in between sets. The exercise activity may also be of other types, such as flexibility-type exercises, mobility-type exercises, etc. In a subsequent step according to the method, the processor generates a target activity score xO, based on the user profile. The target activity score may be based on data used for generating the instructions for the exercise activity. For an endurance- type exercise activity, the target activity score xO may, for example, be a distance in km . In a subsequent step according to the method, the display indicates to the user to begin performing the exercise activity, according to instructions for the exercise activity. The user then begins performing the indicated exercise activity. According to the method, the subsequent sequence of steps is then repeatedly performed. First, exercise data, of the exercise being performed by the user, from a sensor module is recorded by the processor. Next, the processor generates an activity score x using the recorded exercise data. The processor then calculates a normalized activity score y, using a function whose inputs are the activity score xand the target activity score xO. The function has a maximum value of yO when the activity score x is equal to the target activity score xO. The display then indicates the normalized activity score y as the user performs the exercise activity. The display then indicates to the user to stop performing the exercise activity, once the normalized activity score y has reached the maximum value yO.

In an alternative, instead of, or in addition to the sensor module providing exercise data, the exercise data is entered into the computer device 2 by the user. In one way of carrying out the invention, the function has a lower value than the maximum value when the activity score x is lower than or higher than the target activity score xO. In this embodiment, the function is a Gaussian function centered around xO, such that x has a maximum value when x is equal to xO. In an exemplary arrangement, the function has a maximum value ywhen is equal to xO, and the value y does not increase further when is greater than xO. In this arrangement, the function used may be a piece-wise linear function, or a Gaussian function, or a combination thereof.

5 In one way of carrying out the invention, the processor records, from the sensor module, exercise data, and this recording of exercise data comprises the sensor module transmitting one or more of the following types of data of the exercise activity from one or more of the following types of hardware modules, respectively: time data, received from a timing module; distance data, received from a GPS module; step count data, received from0 a step count module; video data, received from a camera module; heart rate data, received from a heart rate module; movement data, received from a movement module; and power data, received from a power module.

In a variation, the hardware modules are integrated in the computing device and/or integrated into a separate tracking device. In a variation, the method further comprises:5 analyzing, by the processor, video data provided by the camera module. Further, the video data is then compared, by the processor, to a predetermined execution of the exercise. The predetermined execution of the exercise comprises, for example, movement information about an individual performing the exercise. The processor then determines whether the user is performing the exercise activity according to the predetermined execution of the0 exercise and then the display indicates whether the user is performing the exercise activity correctly.

In an exemplary arrangement, the user profile comprises one or more of thefollowing: user parameters, user preferences, user physiological parameters, and exercise data of completed exercise activities. The user parameters comprise parameters such as age, gender, height, and weight. The user preferences comprise preferences such as which type of exercise activities the user prefers, whether the user prefers to place a focus on a particular type of exercise activity group, such as endurance-type exercise activities or strength-type activity exercises. The user preferences may further comprise information relating to how many times per week the user wishes to exercise, how much time the user has to dedicate to exercise per week, what intensity level the user has to dedicate to the exercises planned in the training, etc. Use physiological parameters relate to the user's physiological ability to perform exercises. These physiological parameters may be independent of exercise activity, such as a user's lactate threshold values (measured or estimated), V02-max value (measured or estimated), and/or heart rate zones (measured or estimated) . The physiological parameters may also be related to a particular exercise activity, such as a cycling functional threshold power, a cycling critical power curve, heart rate zone data for running, or maximum weights and/or number of repetitions for strength exercises. Exercise data of completed exercise activities comprises data logs of completed exercise activities, along with metadata of the completed exercise activities which may summarize the exercise activity or place it into a specific context.

In an exemplary arrangement, the method further comprises the computing device updating the user profile using the exercise data and/or the normalized activity score. Specifically, the physiological parameters, and the exercise data of completed exercise activities is updated using the exercise data and/or normalized activity score. If the user is able to complete the exercise activity easily then the related physiological parameters are updated to reflect this. Similarly, if the user is unable to complete the exercise activity then the physiological parameters may also be updated to take this into account. In an embodiment, the method of claims further comprises the processor carrying out the following steps. First the processor, using a communication module, transmits to a server device one or more normalized activity scores of the user from one or more exercise activities, enabling the server device to generate a cumulative score using one or more 5 normalized activity scores and/or a group score using a plurality of cumulative scores from a plurality of users. The processor then receives, from the server device, using the communication module, the cumulative score and/or the group score.

Specifically, the exercise activity may be one or more of the following types of exercise activity: walking, hiking, jogging, running, cycling, swimming, rowing, aerobics,0 calisthenics, yoga, gymnastics, and exercising with fitness machines/devices.

In addition to a method of processing sensor data of an exercise activity, by a computing device comprising a processor and a display, the present invention also relates to a computing device for processing sensor data of an exercise activity, the computing device comprising a processor and a display, the processor being configured to generate5 instructions for an exercise activity, which exercise activity is based on a user profile assigned to a user. The processor is configured to generate a target activity score xO, based on the user profile, and then indicate, via the display, to the user, to begin performing the exercise activity, according to instructions for the exercise activity. The processor then configured to repeatedly executing the following sequence of steps. First, record, from a0 sensor module, exercise data of the exercise activity being performed by the user. Then, generate an activity score x using the exercise data. Then, calculate a normalized activity score y, using a function whose inputs are the activity score xand the target activity score xO, wherein the function has a maximum yOwhen the activity score x is equal to the target activity score xO. Then, indicate, via the display, the normalized activity score y as the user performs the exercise activity, and then indicate, via the display, to the user, to stop performing the exercise activity, once the normalized activity score y has reached the maximum value yO.

In an exemplary arrangement, the processor is further configured to record, from the sensor module, one or more of the following types of data of the exercise activity from one or more of the following types of hardware modules, respectively: time data, received from a timing module; distance data, received from a GPS module; step count data, received from a step count module; video data, received from a camera module; heart rate data, received from a heart rate module; movement data, received from a movement module; and power data, received from a power module.

In a variation, the processor is further configured to analyze video data, provided by the camera module. The analyzed video data is then compared to a predetermined execution of the exercise. The processor then determines whether the user is performing the exercise activity according to the predetermined execution of the exercise. The processor then indicates, via the display, whether the user is performing the exercise activity correctly.

In a variation, the hardware modules are integrated in the computing device or, in another variation, integrated into a separate tracking device.

In an embodiment, the user profile comprises one or more of the following: user parameters, user preferences, user physiological parameters, and exercise data of completed exercise activities.

In a variation, the processor is further configured to update the user profile using the normalized activity score y. In addition to a method of processing sensor data of an exercise activity and a computing device for processing sensor data of an exercise activity, the present invention also relates to a system for processing sensor data of an exercise activity. In a preferred arrangement, the system comprises the computing device and a server device, which computing device is detailed above and further comprises a communication module, and which processor of the computing device is further configured to transmit to the server device, using the communication module, one or more normalized activity scores of the user from one or more exercise activities. The server device then generates a cumulative score using the one or more normalized activity scores and/or a group score using a plurality of cumulative scores from a plurality of users. Then, the computing device receives from the server device, using the communication module, the cumulative score and/or the group score.

In an embodiment, the exercise activity is one or more of the following types of exercise activity: walking, hiking, jogging, running, cycling, swimming, rowing, aerobics, calisthenics, yoga, gymnastics, and exercising with fitness machines/devices. In a variation, the exercise activity may further comprise one or more of the following types of activity: team-sports, such as football, hockey, basketball, volleyball, cricket and shooting sports, such as archery, darts, and target shooting and sports such as tennis, badminton, golf, miniature golf, athletics disciplines, climbing.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be explained in more detail, by way of example, with reference to the drawings in which:

Figure 1 : shows a block diagram of a user ( 1 ), a computing device (2), and a tracking device (3); Figure 2: shows a block diagram of the computing device (2) and the tracking device (3);

Figure 3: shows a flow diagram related to processing data of an exercise activity according to the invention; Figure 4: shows a flow diagram related to generating a user profile according;

Figure 5: shows a block diagram related to a sensor module; and

Figure 6: shows a flow diagram related to generating a cumulative user and/or group score.

Detailed Description of the Preferred Embodiments

In Figure 1 , reference numeral 1 relates to a user. The user is a person who carries out an exercise activity and may be of any age, gender, or physical ability. Further, a computing device 2 comprising a display 22 is shown. The computing device 2 is a stationary device or mobile device, such as a desktop computer, laptop computer, tablet computer, smart phone, mobile phone, smart watch, bicycle computer, swimming computer or rowing computer. The computing device 2 is be worn on the body of the user 1 or carried by the user 1 . Alternatively, the computing device 2 is stationary. A tracking device 3 is shown. The tracking device may be worn on the body of the user 1 . The tracking device 3 may be connected to a piece of equipment used by the user 1 during the exercise activity, such as an exercise device. The exercise device may be a bicycle, a rowing machine, or a weight- training device. The tracking device 3 may, in an alternative, be separate from the user 1 and configured to record data of the user during the exercise activity. In Figure 2, the computing device 2 and some of the components are illustrated. The computing device 2 comprises a processor 21 . The processor 21 may be a general purpose processor such as a CPU or a SoC, or a processor configured for specific types of workloads, tasks, and/or computations such as an ASIC. The computing device 2 comprises a display 22, such as a LCD, OLED, or e-ink display. The computing device 2 comprises a communications module 23 which is configured for wired and/or wireless data communication over a wired network and/or wireless network respectively. The wired network could comprise a LAN network, the internet, etc. The wireless network may be a WLAN . The communications module 23 is further configured to communicate using other wireless standards and/or protocols, such as Bluetooth, Bluetooth Low Energy, ANT, ANT+, Zigbee, etc. The computing device 2 further comprises a memory module 24. The memory module 24 comprises exercise software, such as a computer program or an application, which is configured to control the processor 21 to execute the steps according to the invention. The computer program or application may be pre-compiled or interpreted at run-time. The exercise software may be downloaded from a remote server over the internet using a service such as the Apple App Store, or the Google Play digital distribution service. The memory module 24, in particular a logical part of the memory module 24 relating to the exercise software, comprises data related to a user profile 241 and completed exercise activities. The tracking device 3 comprises a sensor module 31 and a communication module 32. The communication module 32 is configured for wired or wireless communication. The wireless communication of the communication module 32 preferably communicates with one or more of the same wireless standards and/or protocols as the communications module 23 of the computing device 2, such as WLAN, Bluetooth, Bluetooth Low Energy, ANT, ANT+, Zigbee, etc. In an embodiment, the sensor module 31 is arranged in, or physically connected to, the computing device 2, instead of being part of the tracking device 3.

In Figure 3, reference numeral 31 refers to the sensor module of the tracking device 3. The sensor module 31 may comprise one or more of the following hardware modules, a timing module 31 1 , a GPS module 31 2, a step count module 31 3, a camera module 31 4, a heart rate module 31 5, a movement module 31 6, and a power module 31 7. The timing module 31 1 is configured for measuring a time or a time difference, such as the time taken to complete the exercise activity or a part of the exercise activity. The GPS module 31 2 is configured for determining position/location data of the user 1 and thereby determining the speed and/or velocity of the user 1 , i.e. how far the user has moved in a given time. The step count module 31 3 is configured for counting the number of steps the user 1 has taken during the exercise activity, for example through the use of one or more accelerometers. The camera module 31 4 is configured for recording still images or video images of the user 1 performing the exercise activity. The heart rate module 31 5, embodied as a device worn on the chest or on the wrist, is configured for determining a heart rate of the user 1 . The movement module 31 6, worn on the body, for example on the chest or on the wrist of the user 1 , comprising accelerometers, is configured for determining the motion of the user 1 during the exercise activity. Based on the motion of the user 1 , the sensor module 31 , tracking device 3, or computing device 2 can determine exercise data of the exercise activity, for example the number of repetitions of an exercise, such as a push-up or a pull- up, or if the exercise activity is being completed correctly, i.e. throughout the prescribed range of motion. The power module 31 7 is configured for determining the power output of the user 1 , for example on a rowing machine or on a bicycle. The hardware modules may be integrated into the sensor module 31 , or connected to the sensor module 31 either wired or wirelessly for wired or wireless data communication, respectively. For example, the GPS module 31 2 may be integrated into the sensor module 31 of the tracking device 3, while the power module 31 7 is arranged in the drive train of a bicycle or on a rowing machine and connects wirelessly for wireless data communication with the sensor module 31 . Figure 4 shows a flow diagram illustrating a sequence of steps performed by the processor 21 , the display 22, and the user 1 , for generating the user profile 241 . After launching the exercise software for the first time, or after registering for the first time, or upon demand, the user 1 can generate or update the user profile 241 . In step S20, the display 22 of the computing device 2 displays a questionnaire or activity programs based on user profiles. The questionnaire and/or activity programs are designed to determine which fitness category the user 1 is assigned to. The questionnaire comprises multiple questions, each with multiple possible answers. In step S21 , the user 1 completes the questionnaire by selecting those answers to the questions which are most appropriate, or selects the activity program, which matches best to the user's profile. In step S22, the processor 21 records the answers selected by the user 1 in response to the questions and/or activity program selection. In Step S23, the processor 21 , using the recorded answers and/or activity program selection, generates or updates the user profile 241 of the user based on the selected answers and/or activity program selection. The example, if one or more answers to the questions indicate that the user 1 is largely non-active and sedentary, the processor 21 updates the user profile 241 to indicate that prescribed exercise activities should be of a low intensity and duration. Based on the answers to the questions, the processor 21 can further determine which types of exercise equipment the user 1 has at his or her disposal, for example a bicycle or a rowing machine. Similarly, questions designed to assess the strength or flexibility of the user 1 can enable the processor 21 to generate or update the user profile 241 to indicate which exercises, and at what level, intensity, and/or duration, would be most appropriate.

Figure 5 shows a sequence of steps executed by the processor 21 and display 22 of the co puting device 2, and the sensor module 31 , for generating instructions for the exercise activity. After launching the application on the computing device 2, the user 1 selects an option for performing the exercise activity. In step S 1 , the processor 21 generates instructions for the exercise activity. The instructions are generated based on the user profile 241 . The instructions for the exercise activity, which may be understood to be analogous to a cooking recipe for cooking a dish, indicate to the user 1 how the exercise activity is to be performed. The instructions may comprise the type of exercise activity to perform, for example endurance-type activities such as running, walking, hiking, or strength-type activities such as body-weight exercises like Pilates, push-ups or pull-ups, weighted exercises such as deadlifts or bench-presses, or flexibility-type exercises such as stretching or yoga. The exercise activity may comprise several sub-activities, such as running and walking, or doing different types of strength exercises, stretches, yoga poses, etc. The instructions may further indicate the equipment needed, for example a floor mat, an elastic band, a bicycle, etc. The instructions further indicate to the user 1 for how long the exercise activity is to be performed (e.g. 1 0 seconds, 1 minute, 1 0 minutes, 40 minutes), how intensely it is to be performed (e.g. comfortably such that a conversation is possible, fast such that breath becomes labored, or all-out maximal effort), and how the exercise activity is to be structured, such as active periods, rest periods, warm-up and cool down periods. Depending on the user profile 241 , parameters of the instructions for the exercise activity, such as its length, distance, and intensity, may be adjusted by the processor 21 . For example, if the user profile 241 indicates that the user 1 is very athletic, the processor 21 may increase the parameters of intensity and/or duration of the exercise activity.

The processor 21 , in Step S2, generates a target activity score xO based on the user profile 241 and/or the instructions for the exercise activity. For example, if the exercise type of the exercise activity is endurance-type and the activity is running, the instructions may indicate to the user 1 that they are to run 6 km at a comfortable pace. In this example, the target activity score xO would be generated using the value of 6 km . In another example, if the instructions indicate to the user 1 that they should perform 1 5 push-up repetitions, the target activity score xO is based on the number 1 5. The target activity score xO may be based on only one factor, as in the above examples, or the target activity score xO may be based on multiple factors. For example, the instructions may indicate that the user 1 is to perform the exercise activity of running for 30 minutes or 5 km, whichever is achieved first. The target activity score xO would then comprise both a time value and a distance value.

In Step S3, the display 22 of the computing device 2 indicates to the user 1 that the user 1 is to begin performing the exercise activity. The user 1 commences performing the exercise activity, for instance the user 1 begins to run or to perform the sequence of sub-activities as indicated by the instructions for the exercise activity.

In Step S4, the sensor module 31 acquires exercise data. The acquired exercise data is data relating to physical variables/parameters of the user 1 performing the exercise activity. The physical variables the sensor module 31 measures are those which are changed or affected as the user 1 performs the exercise activity and/or those physical variables which describe or parametrize the exercise activity. These may be physical variables relating to the start time of the exercise activity, the duration of the exercise activity, the motion of the user 1 during the exercise activity, such as the distance covered by the user 1 , as well as physiological variables of the user 1 , such as heart-rate, V02 rate, lactate levels, power developed, etc. The sensor module 31 automatically acquires exercise data with no input or further steps required from the user 1 . The sensor module 31 of the tracking device 3 acquires exercise data continuously, i.e. as quickly as the respective hardware module can provide data, or discretely, such as in 1 second time intervals. The exercise data which is acquired is then, in Step S5, transmitted from the communication module 32 of the tracking device 3, via the communication module 23 of the computing device 2, and received in Step S6 by the processor 21 of the computing device 2. The exercise data can be transmitted in a wired or wireless manner, according to the specific hardware configuration of the communication modules 23, 32 of the computing device 2 and the tracking device 3, respectively. In Step S7, the exercise data is recorded by the processor 21 to the memory module 24. Using the exercise data, the processor 21 generates an activity score x. The activity score x relates to the physical variables recorded by the sensor module 31 , and the specific physical variables which are used by the processor 21 for generating an activity score depends on the specific type of exercise activity being performed. For example, if the exercise activity is running, then the activity score x could be the distance which the user 1 has covered during the exercise activity, or the length of time which the user 1 has spent exercising, or the length of time which the heart rate of the user 1 has exceeded a specific heart rate threshold. The activity score x is continuously updated by the processor 21 as new exercise data is received from the sensor module 31 . The updated value may be presented to the user 1 on the display 22, so that the user 1 may have an up-to-date representation of how far, or for how long, or how intense, the exercise activity has been performed.

As the different types of exercise activities are tracked via different physical variables and parameters, and as the fitness and capability of the user 1 for performing the exercise activity will increase as the body of the user 1 adapts to the exercises, it can become difficult for the user 1 to co pare efforts, not only between different types of exercise activity, but also to compare efforts between the current exercise activity and past exercise activities. Using the activity score xalone, the user 1 cannot easily determine how close the exercise activity is to completion, and how this relates to past efforts of the same activity type, or efforts of different types of activity. For example, if the user 1 has been currently instructed to perform a 23 minute run at a moderate pace, and the user is currently at minute 1 3, it is difficult for the user 1 to determine what proportion of exercise activity remains to be performed. Only the absolute value, i.e. 1 0 minutes remaining, is easily determined. Therefore, it is difficult for the user 1 to compare current performance with past performance, where, for example, a 1 7 minute long run may have been instructed. Similarly, if the user 1 was, on a different day, instructed to cycle for 1 hour 1 2 minutes, and had currently completed 47 minutes, it is difficult for the user 1 to know which proportion of the exercise activity remains, to properly gauge their effort to ensure that the quality of the exercise activity being performed, and the enjoyment thereof, remains high. For these reasons and more, as will be explained below, the present invention proposes normalizing the activity score x such that exercise activity performance is simple and intuitive for the user 1 to compare between different types of exercise activities and past exercise activities. In Step S9, the processor 21 calculates a normalized activity score y using the activity score . The normalized activity score y is a value which represents the degree to which the user 1 is performing the exercise activity in accordance with the instructions. The normalized activity score y is zero at the start of the exercise activity, and increases as the user 1 performs the exercise activity. When the activity score x has reached the target activity score xO, the normalized activity score y reaches a maximum value. If the user 1 continues to perform the exercise activity, the activity score xwill continue to increase, however the normalized activity score y will decrease. The processor 21 uses a function to calculate the normalized activity score y has inputs comprising the activity score xand the target activity score xO. Additional inputs to the function are taken from the user profile 241 which relate to the ability of the user 1 to perform the exercise activity. Further inputs to the function relate to the type of exercise activity being performed. In one embodiment, the following piece-wise linear function can be used as a function:

X

y = yO x— , 0 < x < xO

7⁷ xO

The above piece-wise linear function increases linearly from O to a value of yO as the activity score increases from 0 to xO. After reaching yO, the function decreases linearly to 0 as the activity score increases from xO to 2x0. In the above function, the value of xO was determined by the processor 21 using the user profile 241 of the user 1 . Figure 7 shows an example of a graph where the piece-wise linear function has a yO value of 1 00 and an xO value of 23. The normalized activity score y linearly increases up to a maximum normalized activity score y value of 1 00 when x is equal to 23. For higher values of x, the normalized activity score y decreases linearly. For example, if the user 1 is currently performing the exercise activity and has a current activity score x equal to 1 3, their normalized activity score y would have a value of 56. In another embodiment, the following Gaussian function can be used as a normalizing function:

(x-xO)²

y = yO X e 2s² The above Gaussian function has the shape of a bell-curve centered around the value xO where the value of the Gaussian function has a maximum value of yO. The variance of the Gaussian function is s². The variance, which relates to the width of the bell-curve, can be adjusted as necessary. Figure 8 shows an example of a graph where the Gaussian Function has a yO value of 1 00 and an xO value of 23. The normalized activity score / increases up to a maximum normalized activity score y value of 1 00 when x is equal to 23. For higher values of x, the normalized activity score /decreases. For example, if the user 1 is currently performing the exercise activity and has a current activity score x equal to 1 3, their normalized activity score /would have a value of 4.4. The benefit of using a piece-wise linear function as the function is that the normalized activity score y is directly proportional to the activity score x, which makes it simple and efficient for the user to gauge and manage their efforts and adjust their tempo during the exercise activity such that they can complete the exercise activity according to the instructions. The benefit of using a Gaussian function is that the normalized activity score y is far lower at the beginning, indicating to the user 1 that the benefits of prolonged exercise come only after the user 1 has completed a certain proportion of the exercise activity. A further benefit is that the Gaussian Function is relatively flat in a region near the maximum of the Gaussian function, such that if the user 1 doesn't quite complete the exercise activity according to the instructions, or if the user 1 performs slightly more exercise than the instructions have prescribed, their normalized activity score / does not change significantly. The function chosen can also be a combination of the above piece- wise linear function and the Gaussian function, such as a linear combination. The person skilled in the art will understand that there are other similar functions which have similar properties as the above two identified and detailed examples and that, depending on the specifics of the implementation, other similar functions could be chosen. In Step S1 0, the normalized activity score y is indicated to the user 1 on the display 22. The normalized activity score y is continuously updated as more exercise data is received by the processor 21 . By providing the user 1 with the normalized activity score y while the user 1 is performing the exercise activity, the user 1 is able to simply, easily, and without mental effort, know which proportion of the exercise activity remains to be completed. Using a previously mentioned example, if the user has completed 1 3 minutes of a 23-minute run, the normalized activity score, using the piece-wise linear function above, would be 57 (rounding up to the nearest whole number) . The user 1 is then easily able to gauge their relative effort to complete the run according to the exercise instructions. Further, as the function reaches a maximum value of yO when the value of the activity score x is equal to the target activity score xO, the user 1 has an immediate indication when the exercise activity has been performed according to the instructions. The user 1 is also incentivized to stop performing the exercise activity once the activity score x is equal to the target activity score xO, because the normalized activity score y then begins to decrease from yO back down to 0. This is to ensure that the user 1 performs the exercise activity according to the instructions and does not perform additional exercise, as this could be detrimental to the user 1 . The user 1 performing additional exercise beyond the prescribed amount of exercise according to the instructions could lead the user 1 to over-training, which can increase the risk of sub-optimal fitness progression as accumulated fatigue will reduce the quality of exercise of subsequent exercise activities. Furthermore, the user 1 , through overtraining, can increase the likelihood of injury or illness. Through indicating the normalized activity score yon the display 22, the computing device 2 enables the user 1 to perform an optimal amount of exercise according to the instructions. Further, the user 1 can easily compare their progress on the current exercise activity with the prescribed instructions and can easily compare their progress on the current exercise activity with past completed exercise activities of the same type as well as of other types. In Step S1 1 , the processor 21 checks whetherthe activity score is equal to or greaterthan the target activity score xO, and/or whether the normalized activity score y is greater than or equal to 1 00. If this is not the case, then the processor 21 continues receiving exercise data being acquired and transmitted from the sensor module 31 , as detailed above. If it is the case, then in Step S1 2 the display 22 indicates to the user 1 that they should stop performing the exercise activity, as the prescribed amount of exercise according to the instructions has been performed. If the user 1 continues performing the exercise activity, contrary to the instructions and the indication on the display 22, then the normalized activity score y will begin decreasing from a value of 1 00. This is to indicate to the user 1 that the optimal amount of exercise has been exceeded.

After completing the exercise activity, the display 22 displays to the user 1 a summary of the exercise activity comprising the normalized activity score y, the activity score , and/or the target activity score xO. The processor 21 may calculate further data based on the exercise data, such as average values of speed, heart rate, etc. The summary of the exercise activity is stored in the memory module 23.

In an embodiment, the processor 21 updates the user profile 241 using the summary of the exercise activity. This allows the user profile 241 to reflect the current capabilities of the user 1 and therefore prescribe more appropriate instructions for future exercise activities to be completed. For example, if yO is set at 1 00, and the user 1 consistently achieves a normalized activity score yof between 95 and 1 00 for one week, the processor 21 updates the user profile 241 to indicate that future instructions for exercise plans are to be more challenging, for example by increasing a running distance or duration. Likewise, if the user 1 consistently doesn't achieve a normalized activity score yin the range of 95 to 1 00 for a certain time range, the processor 21 updates the user profile 241 to indicate that future instructions for exercise plans are to be less challenging, for example by decreasing a running distance or duration.

In an embodiment, the exercise software is further configured to control the processor 21 to generate cumulative scores using the normalized activity score y of the most recent completed exercise activity, as well as other past completed exercise activities. For example, the display 22 may indicate the cumulative weekly normalized activity scores for the past weeks/months. This allows the user 1 to easily see and evaluate how well they are training according to the instructions across a large number of activities, both of a similar type and of a dissimilar type, as all types of activity can generate normalized activity scores of the same, or similar, value.

Figure 6 shows a flow diagram illustrating an exemplary sequence of steps for receiving a cumulative user score and/or group score in a computing device 2. In Step S41 , the computing device 2 transmits one or more normalized activity scores to a server device 4. The normalized activity scores each correspond to a completed exercise activity. The server device 4 receives the normalized activity scores in Step S42. Using the normalized activity score of the user 1 , the server device 4 generates a cumulative score. The cumulative score is a sum of normalized activity scores across a range of dates. A distinct cumulative score may be generated for each week or month or any other time period, such as in the period of the entire activity program, activity event, season, etc. Further, the server device 4 may receive normalized activity scores from a group of users. The group of users might be a group of friends or a group of work-colleagues. The server device 4 generates a group score based on the normalized activity scores of the users comprising the group. Generating a group score based on the normalized activity scores of the users allows different groups composed of different individuals of different abilities to compare efforts and compete with each other on a fair basis, as each individual will be able to contribute equally to the group score on the basis of effort, and not on the basis of ability. Further, the group score may be calculated using an average value of the normalization scores of the individuals, so that the group score is independent of the number of individuals of the group. This makes it simpler for an organization, such as a corporation, to create groups for a competition, as the corporation does not need to ensure that each group has a similar overall average athletic ability, for example.

In Step S44, the server device 4 transmits the cumulative user and/or individual group scores to the computing device 2, which, in a Step S45, receives the cumulative user and/or individual group scores. The computing device 2 may then display the cumulative scores on the display 22, allowing the user 1 to compare their efforts to themselves at earlier dates performing the same or different activities, allowing the user 1 to see the group score and how it is increasing, and allowing the user 1 to compare group scores between their group and other groups. It should be noted that, in the description, the sequence of the steps has been presented in a specific order, one skilled in the art will understand, however, that the order of at least some of the steps could be altered, without deviating from the scope of the invention.

Claims

1 . A method of processing sensor data of an exercise activity, by a computing device ( 2) comprising a processor (21 ) and a display ( 22), the method comprising the following steps: generating, by the processor ( 21 ), instructions for an exercise activity, which exercise activity is based on a user profile (241 ) assigned to a user ( 1 ); generating, by the processor ( 21 ), a target activity score xO, based on the user profile (241 ); indicating, by the display ( 22), to the user ( 1 ), to begin performing the exercise activity, according to instructions for the exercise activity; and repeatedly executing the following sequence of steps: recording, by the processor (21 ), from a sensor module (31 ), exercise data of the exercise activity being performed by the user

( 1 ); generating, by the processor ( 21 ), an activity score x using the exercise data; calculating, by the processor (21 ), a normalized activity score y, using a function whose inputs are the activity score xand the target activity score xO, wherein the function has a maximum yOwhen the activity score is equal to the target activity score xO ; indicating, by the display (22), the normalized activity score y as the user ( 1 ) performs the exercise activity; and indicating, by the display (22), to the user ( 1 ), to stop performing the exercise activity, once the normalized activity score y has reached the maximum value yO.

2. The method of claim 1 , wherein recording, by the processor ( 21 ), from the sensor module (31 ), exercise data, comprises the sensor module (31 ) transmitting one or more of the following types of data of the exercise activity from one or more of the following types of hardware modules, respectively: time data, received from a timing module (31 1 ); distance data, received from a GPS module (31 2); step count data, received from a step count module (31 3); video data, received from a camera module (31 4); heart rate data, received from a heart rate module (31 5); movement data, received from a movement module (31 6); and power data, received from a power module (31 7).

3. The method of claim 2, wherein the hardware modules are integrated in the computing device (2) or integrated into a separate tracking device (3).

4. The method of claim 2 or 3, wherein the method further comprises: analyzing, by the processor (21 ), video data provided by the camera module; comparing, by the processor ( 22), the video data to a predetermined execution of the exercise; determining, by the processor, whether the user ( 1 ) is performing the exercise activity according to the predetermined execution of the exercise; and indicating, by the display (22), whether the user ( 1 ) is performing the exercise activity correctly.

5. The method of claims 1 - 4, wherein the user profile ( 241 ) comprises one or more of the following: user parameters, user preferences, user physiological parameters, and exercise data of completed exercise activities.

6. The method of claims 1 - 5, wherein the method further comprises the computing device (2) updating the user profile (241 ) using the exercise data and/or the normalized activity score.

7. The method of claims 1 - 6, wherein the exercise activity is one or more of the following types of exercise activity: walking, hiking, jogging, running, cycling, swimming, rowing, aerobics, calisthenics, yoga, gymnastics, and exercising with fitness machines/devices.

8. The method of claims 1 - 7, wherein the method further comprises the following steps: transmitting, by the processor ( 21 ), to a server device (4), using a communication module (23), one or more normalized activity scores of the user ( 1 ) from one or more exercise activities, generating, by the server device (4), a cumulative score using one or more normalized activity scores and/or a group score using a plurality of cumulative scores from a plurality of users ( 1 ); and receiving, by the processor ( 21 ), from the server device (4), using the communication module (23), the cumulative score and/or the group score.

9. A computing device ( 2) for processing sensor data of an exercise activity, the computing device (2) comprising a processor ( 21 ) and a display (22), the processor (21 ) being configured to: generate instructions for an exercise activity, which exercise activity is based on a user profile ( 241 ) assigned to a user ( 1 ); generate a target activity score xO, based on the user profile (241 ); indicate, via the display ( 21 ), to the user ( 1 ), to begin performing the exercise activity, according to instructions for the exercise activity; and repeatedly executing the following sequence of steps: record, from a sensor module (31 ), exercise data of the exercise activity being performed by the user ( 1 ); generate an activity score x using the exercise data; calculate a normalized activity score y, using a function f whose inputs are the activity score x and the target activity score xO, wherein the function has a maximum yO when the activity score x is equal to the target activity score xO ; indicate, via the display ( 21 ), the normalized activity score as the user performs the exercise activity; and indicate, via the display ( 21 ), to the user ( 1 ), to stop performing the exercise activity, once the normalized activity score y has reached the maximum value yO.

1 0. The computing device (2) of claim 9, wherein the processor ( 22) is further configured to record, from the sensor module, one or more of the following types of data of the exercise activity from one or more of the following types of hardware modules, respectively: time data, received from a timing module (31 1 ); distance data, received from a GPS module (31 2); step count data, received from a step count module (31 3); video data, received from a camera module (31 4); heart rate data, received from a heart rate module (31 5); movement data, received from a movement module (31 6); and

5 power data, received from a power module (31 7).

1 1 . The computing device (2) of claims 9 or 1 0, wherein the processor (21 ) is further configured to: analyze video data, provided by the camera module (31 4); compare the video data to a predetermined execution of the exercise; 0 determine whether the user ( 1 ) is performing the exercise activity according to the predetermined execution of the exercise; and indicate, via the display (22), whether the user is performing the exercise activity correctly.

1 2. The computing device ( 2) of claims 9 - 1 1 , wherein the hardware modules are5 integrated in the computing device (2) or integrated into a separate tracking device (3) .

1 3. The computing device (2) of claims 9 - 1 2, wherein the user profile (241 ) comprises one or more of the following: user parameters, user preferences, user physiological parameters, and exercise data of completed exercise activities.

1 4. The computing device (2) of claims 9 - 1 3, wherein the processor ( 21 ) is further configured to update the user profile ( 241 ) using the normalized activity score y-

1 5. The computing device (2) of claims 9 - 1 4, wherein the exercise activity is one or more of the following types of exercise activity: walking, hiking, jogging, running, cycling, swimming, rowing, aerobics, calisthenics, yoga, gymnastics, and exercising with fitness machines/devices.

1 6. A system comprising the computing device ( 2) of claims 9 - 1 5 and a server device (4), wherein the computing device (2) further comprises a communication module (23) and the processor ( 21 ) is further configured to transmit, to the server device (4), using the communication module ( 23), one or more normalized activity scores of the user ( 1 ) from one or more exercise activities, the server device (4) is configured to generate a cumulative score using the one or more normalized activity scores and/or a group score using a plurality of cumulative scores from a plurality of users; and the processor ( 21 ) is further configured to receive, from the server device (4), using the communication module ( 23), the cumulative score and/or the group score.