US20120071770A1

US20120071770A1 - Methods for promoting fitness in connection with electrophysiology data

Info

Publication number: US20120071770A1
Application number: US13/239,079
Authority: US
Inventors: Alexander B. Grey; Abhishek Belani; Edward Frank Hejtmanek
Original assignee: Somaxis Inc
Current assignee: Somaxis Inc
Priority date: 2010-09-21
Filing date: 2011-09-21
Publication date: 2012-03-22
Also published as: WO2012040388A2; US20150305672A1; WO2012040390A3; WO2012040390A2; WO2012040401A2; US20150313500A1; US20150374302A1; US9131888B2; US11445919B2; WO2012040388A3; US20160206225A1; US10058265B2; US10010260B2; US20120071732A1; WO2012040402A3; US9107627B2; US20150305665A1; WO2012040401A3; US9918654B2; US9295424B2

Abstract

A task assessment protocol configured to utilize modified operant conditioning to incentivize physical fitness through rewards associated with units of effort including the steps of selecting the task to be performed, breaking the task to be performed into smaller units, associating the data with a reward using a reward system, gathering subject data into a database for each unit performed, and providing awards to the subject for each unit completed wherein rewards are diversified through monetary based rewards and social capital based rewards. Sensors can be worn to monitor the progress of the subject participating in an activity, competition, or challenge, and the method can provide real time feedback of data gathered to the subject.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This patent application claims the benefit of U.S. Provisional Application Nos. 61/385,046, 61/385,038, 61/385,048, 61/385,049, 61/385,051, and 61/385,053 all of which were filed on Sep. 21, 2010. In addition, this patent application claims the benefit of U.S. Provisional Application No. 61/514,148, filed Aug. 2, 2011. All of the aforementioned provisional applications are incorporated herein by specific reference in their entirety.

BACKGROUND

Generally, there are various methods for monitoring and analyzing muscle condition and/or performance. Often, such muscle monitoring and analysis involves some form of myometry, which measures the strength of a muscle by measuring the force that the muscle can generate. For an example of myometry, a user squeezes a device which in turn measures and transmits force information back to a computer, and the computer computes a force/time curve. The measurement is usually via electronic components, and thereby can be referred to as electromyometry. These electronic devices are typically fully wired systems that require immediate proximity to a computer, and which are designed to be operated by physicians or clinicians in appropriate controlled settings.
Surface electromyometry (sEMG) is a type of myometry that uses surface sensors to obtain information about the functionality of one or more muscles during a muscular activity. The sEMG assessments can be sorted into three general groups of muscle activity: static muscle activity, dynamic muscle activity, or combination of static and dynamic muscle activities. The different muscle activity paradigms can be useful for different muscle assessments.
A static muscle activity may occur with no load (i.e. sitting) or with an isometric load (no movement of limb). Static muscle activity evaluation can include observation of the rectified amplitude of the sEMG data. The static muscle activity evaluation can be useful for a specific muscle or muscle group or as a comparison to other muscles or muscle groups. Absolute levels of the sEMG data can be monitored through root mean square of the sEMG amplitude (e.g., RMS sEMG amplitude), and abnormally large values of the RMS sEMG can be identified or determined. Rhythmic contraction patterns of the muscle or muscle groups can be identified or determined, and may also be based on rectified amplitude. During an isometric loading protocol, a user can exert an amount of force while keeping the limb fixed in a single position. Usually, the force exerted is measured as a fixed percentage of Maximum Voluntary Contraction (MVC). Then, the median frequency (MF) or mean power frequency (MPF) can be measured or determined by observing or analyzing the frequency spectrum of the sEMG. In this manner, the fatigue level of the muscles can be established, and the point at which fatigue begins to occur may be identified.
Dynamic muscle activity evaluations can ascertain relationships between sEMG amplitude and force, which have been shown to be “curvilinear”, or non-linear at the extremes of the force range (e.g., very little force, or a lot of force) and essentially linear for the majority of the force/amplitude relationship. Evaluating that relationship is useful for dynamic muscle activity sEMG evaluation. Methods for implementing dynamic muscle activity evaluations can include incrementally increasing the force exerted by the muscle by way of a machine that measures force, and measuring the sEMG amplitude of the muscle activity that is associated with various force levels. Dynamic muscle activity evaluations can be used in the evaluation of torque and paralysis. There are dynamic muscle activity evaluation methods for: muscle imbalance, trigger points, cocontractions, and fasciculations.
The current approach to promoting fitness revolves around providing the users with information to make rational and informed decisions. For the most part, the population at large is aware that diet and exercise are the foundation of a healthy lifestyle. The informational approach, while enjoying some success, has largely failed to take into account the primary roadblocks to maintaining a health regimen consisting of a dietary regimen, exercise regimen, or a combination of the two.
Operant conditioning is largely known in the art as a form of psychological learning where an individual modifies the occurrence and form of their own behavior due to the association of the behavior with a stimulus. Attempts have been made to apply this type of model to the field of rehabilitative medicine. U.S. Pat. No. 5,243,998 is one example of such a system which uses a device to track the posture of an individual with automatic feedback such as audible alarms. However, the operant conditioning model has not yet been successfully applied to the average consumer's physical fitness goals where the stimulus is any given reward. It is therefore the needed in the art, a method, a system, or a device that uses a modified operant conditioning model to incentivize fitness goals.

SUMMARY

In general, the present invention relates to a method and a device for task assessment. The method is related to the assessment of the fitness of a subject by taking measurements and associating the measurements with progress made toward a goal predetermined by the user. The method uses sensors and a processor for gathering biometric data of the subject during the completion of a task related to a larger goal. The data is uploaded to a computing system and is entered into a database which will associate the data with a reward system. As the goals are associated with a reward, the subject is further incentivized to continue progressing towards the predetermined goal. The task assessment system can be characterized as a modified operant conditioning system.
In an additional embodiment, the task assessment system can be used to create additional incentives by associating progress towards a goal with social capital through a social network. In another embodiment, the task assessment system can be used to create additional incentives to increase performance in furtherance of a predetermined goal by creating competitions between to subjects, or users, of the method. In a further embodiment, the method can be used to measure competitions between two individuals allowing real time data feedback to the subjects, or users.
The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and following information as well as other features of this disclosure will become more fully apparent from the following description and appended claims, taken in conjunction with the accompanying drawings. Understanding that these drawings depict only several embodiments in accordance with the disclosure and are, therefore, not to be considered limiting of its scope, the disclosure will be described with additional specificity and detail through use of the accompanying drawings, in which:

FIG. 1 is a depiction of the method of task assessment and encouragement method which associates the accomplishment of individual units with rewards, and uses the rewards to encourage and assess the accomplishment of the larger task;

FIG. 2 is a depiction of a computer connected to a network of other computers that allows the subject to provide the data gathered to a database and shared with others.

FIG. 3 is a depiction of how a larger task can be divided into smaller units of accomplishment and rewards can be associated with each unit;

FIG. 4 is a depiction of a graph that shows how an alert can be created when a subject's frequency in accomplishing smaller units drops below a target level;

FIG. 5 is a depiction of the competition that can be established by two or more subjects when connected to a network, providing real time updates to each subject relating to the progress of the subject and each other subject participating;

FIG. 6 includes a schematic representation of a computing system that can be used in the systems and methods of the present invention; and

FIG. 7 describes a method of reinforcing fitness patterns and progress by creating custom challenges based on electrophysiology data;

arranged in accordance with at least one of the embodiments described herein, and which arrangement may be modified in accordance with the disclosure provided herein by one of ordinary skill in the art.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

In the following detailed description, reference is made to the accompanying drawings, which form a part hereof. In the drawings, similar symbols typically identify similar components, unless context dictates otherwise. The illustrative embodiments described in the detailed description, drawings, and claims are not meant to be limiting. Other embodiments may be utilized, and other changes may be made, without departing from the spirit or scope of the subject matter presented herein. It will be readily understood that the aspects of the present disclosure, as generally described herein, and illustrated in the figures, can be arranged, substituted, combined, separated, and designed in a wide variety of different configurations, all of which are explicitly contemplated herein.
The present invention relates generally to sensors which provide biofeedback for task assessment and achievement. The biofeedback is configured to train individuals to accomplish a selected task using a modified operant conditioning system. The modified operant conditioning system divides a larger task into smaller units, and associates those units with quantifiable rewards. Typically, the tasks relate to muscle activities, such as exercise and athletics.
The present invention includes systems and methods for implementing task assessment protocols. The assessment protocols can be implemented in a manner such that a common person can use the system to assess the individual progress toward a goal, such as improved muscular activation and performance. The assessment protocols can be implemented by the user to associate progress toward a goal with rewards to encourage and incentivize the continuing progress.
As such, embodiments of the present invention can be implemented in order to improve a subject's ability to assess the progress toward accomplishing a task. Often, the task will be related to activities intended for improved muscle activation and/or performance. Additionally, another embodiment of the present invention provides incentives to encourage the subject to accomplish the task. According to one embodiment of the present invention, the subject selects a larger task to complete, such as to increase the amount of weight that can be lifted, running speed, or running longevity or endurance. Once a task selected, one embodiment of the invention will divide the task into units of effort or accomplishment for a muscle activity. According to another embodiment of the invention, as the subject completes the units of effort or accomplishment, in route to accomplishing the larger task, rewards will be associated with the units completed and given to the subject. According to a different embodiment of the invention, competitions may be established between two or more subjects. The competitions may be used to encourage performance and additional rewards may be given to the winner of any particular competition. In another embodiment, competitions may be established between two or more participating subjects that gathers and sends data in real time to each subject as the competition progresses. In this embodiment, the subjects can compare performance in real time and adjust their effort accordingly.
The present invention can include modified operant condition systems that can provide or improve motivation to perform exercise routines to promote fitness over just diet and exercise alone. The modified operant conditioning systems of the present invention establish a reward system that is associated with the accomplishment of a subject, or user's, established goal. A given reward could include, but is not limited to: social capital, redeemable points, discounts on retail goods, discounts on retail services, discounts on competition fees, discounts on association fees, or the like. Also, the reward can include points which contribute to a publicly viewable experience level, or points which contribute toward publicly viewable social status ranking, which can be applied as social capital. Although the methods and systems are described as being applied to physical fitness, the present invention can also be useful to any area where physical activity and performance is measured or any muscle activity.
In the current invention, a “subject” can be user of the invention described, and the terms “subject” and “user” are used interchangeably. Additionally, in the descriptions of the embodiments below, frequently the example of running is used. However, it should be understood that these systems and processes can be applied to continuous or noncontinuous muscle activities. Some examples of muscle activities can include one or more of walking, jogging, running, sprinting, hiking, cycling, rollerblading, roller skating, skiing, cross-country skiing, rowing, swimming, snowboarding, yoga, pilates, golf, football, weight lifting, or the like.
Method for Modifying Fitness Patterns Using an Adaptation of the Operant Conditioning Model with Incentives Based on Electrophysiology Data
It has been found that obtaining or improving muscle activation and performance or other aspects of a healthy lifestyle and the benefits associated can be an intimidating process. An effective fitness regimen requires continued and increasing effort throughout a long period of time for a distant reward. This period of time between the effort and the subsequent reward is a large disincentive to maintain a given regimen. It is further exacerbated when progress is very gradual, and thus more difficult to perceive. The availability of a short-term reward can incentivize the user in continuing progress. A short-term reward is especially important when considering a user faces a range of distractions vying for their attention and effort, many of which will provide more immediate satisfaction.
In one embodiment of the present invention, the short-term reward problem is addressed using a modified operant conditioning model 100. FIG. 1 depicts one embodiment of the method. First, a large task is chosen (block 102). The larger task can be long-term or short term with high performance expectations. The larger task is then broken down into a series of manageable discrete units of effort (block 104). The discrete units of effort mark the progress of the individual user towards the larger goal. The discrete units are then associated with a reward (block 106). The reward can be an amount of points associated with metrics including, but not limited to, progress being made, the amount of work done, the amount of calories burned, and the amount of improvement. Then the subject's data is recorded as the subject performs each unit (block 108). Once the rewards have been associated with each unit performed, the rewards are provided to the subject (block 110).
In one embodiment, each unit that is successfully completed results in an explicit reward of points, awards, or a monetary incentive such as: cash, or cash equivalents, goods, discounts on retail goods, services, discounts on retail services, discounts on competition fees, discounts on association fees, redeemable vouchers, coupons, or the like. It has been established that the operant conditioning model with reinforcement is an effective means of modifying behavioral patterns through associated research in physical therapy when applied to improving muscle activation or performance or overall fitness.
As shown in FIG. 2, to verify that the user has in fact completed the discrete task, such as a single bike ride, the electrophysiology data gathered by a processor or computing system coupled to the data gathering sensors measured during the completion of the task must be uploaded to a database. In FIG. 2, data is being gathered by sEMG sensors 205, and an ergometer 207. The data gathered by the sensors 205 and/or the ergometer 207 is then communicated to a network, such as the Internet 209, through a connected computer 201. The database and coupled computing system tracks the progress of the subject based on metrics of interest to the subject. In one embodiment, the gathered data will be automatically transmitted to a computing system 201. A processor would analyze the electrophysiology data and display the metrics of interest. Each metric can be associated alone, or together with a reward.
In one embodiment, the reward is composed of one or more parts. The primary component is based on the effort of the subject with each successive unit completed. Another reward component can be proportional to the performance of the subject in the activity performed. Another reward component can be based upon improvement in performance compared to previously completed performances. Another reward component can be associated with levels based on the user's total accumulated point value. As shown in FIG. 2 the associated internet computing system 201 and server 203 can be configured to compute the rewards, or associated points, to be given to the subject based on the electrophysiology data and return this total to the database tracking the individual's progress. The data in the database would be accessible by the subject in order to gauge progress, review points accumulated, trade points, redeem points, or wager points.
FIG. 3 shows for example, a subject may set a goal to burn 10,000 calories by running. The subject would then create a regimen by which she runs for 30 minutes 3 times a week. The computing system will associated the larger task with smaller units of effort, and associate each smaller unit with a reward. After each run the subject uploads the electrophysiology data for that run. The database will associate each unit completed with an award, in this example an amount of redeemable points. After one week of running, the subject will have data from 3 runs uploaded to the database. Therefore, each run the subject receives a nominal amount of points associated with the effort of completing each unit, for example 500 points. Also, the subject receives points based on the number of calories burned associating points with performance. Further, the subject receives points based on the improvement in performance compared to previous runs. The accumulated points can be associated with certain levels of accumulated points. For example, at the end of the one week period assume that the subject has accumulated 2,400 points. In one embodiment, the subject can be awarded an incremental level for each 2000 points accumulated, moving from a level 1 user to a level 2 user in a given scenario to be rewarded with an additional 500 points.
The above scenario is an example only, and not should be considered limiting. The present invention can be configured to work with any activity requiring muscle activity where a goal has been determined for a subject engaging in the activity. As the subject incrementally progresses toward any goal related to muscle activity, the system can provide incentives for continued progress. Some examples of other muscle activities can include one or more of walking, jogging, running, sprinting, hiking, cycling, rollerblading, roller skating, skiing, cross-country skiing, rowing, or others.
Method for Reinforcement of Incentives Based on Electrophysiology Data Using a Social Network
In the previous embodiment, rewards were associated with various monetary incentives. In addition, there exists an opportunity for non-monetary rewards and incentives as well in social capital. Social capital, optionally, can then be associated with monetary incentives. Creating social capital derived from the rewards based on electrophysiology data can increase the subject's motivation. Social capital is a concept which refers to the value associated with social relations. Here, social capital can be thought of including: the expectative benefits derived from sharing of individual goals and progress toward that goal with a group. In one embodiment, the reward the subject receives a number of points proportional to effort, performance, and/or total amount of points accumulated, and this point total is then displayed on the subject's profile page of an online social network.
In this embodiment, the points are given value by being displayed on the user's personal page on the social network. By sharing this information with peers, the subject is then further incentivized to increase this score, based on the knowledge that other people will be aware of the subject's progress. Additionally, feedback loop is then created by giving the subject additional points for sharing the data with a larger populations of users.
Continuing the example above, in one embodiment, the subject would publish the subject's goal of burning 10,000 calories. The subject would then choose to display the cumulative calories burned metric approximated from the electrophysiology data uploaded to the database of the social network. The subject's profile would then display the calories burned per run by the subject, the cumulative number of calories burned by the subject, and the cumulative number of points earned by the subject, as well as any awards or achievements such as increasing in rewards level or improvement in performance.
Additionally, if the subject shared this page with 10 other users the subject might receive 100 points for each user that views her progress for a total of 1000 points added to the subject's cumulative total. Once again the subject may redeem these points by the means, not limited to but including, mentioned previously such as: cash, or cash equivalents, discounts on retail goods, discounts on retail services, discounts on competition fees, discounts on association fees, or others.

Method for Modifying Fitness Patterns Using a Support System Based on Electrophysiology Data and Social Networks

As the subject builds relationships with other users of the social network, these relationships can help motivate the subject to sustain a fitness regimen. This can be reinforced by an alert that updates the other users whenever the subject's fitness activities, as measured by electrophysiology data uploads to the social network, begin to diminish in frequency. FIG. 4 depicts a graph of the subject's update frequency versus time. When the subject's frequency drops below a given threshold, an associated user will be notified. The user will then be given options to contact the subject. As a user becomes aware that the subject is making less progress the user will be prompted to contact the subject and offer encouragement and support.
Therefore, a reward system can be associated with the previously mentioned reward associations such as effort, performance, and improvement, but also with social networking effort. Thus, a user can be assigned rewards or points for the sharing a goal and associated progress based on the number of social networks and/or the number of social network members with whom the data is shared. Additional points can be associated with users that receive more feedback, encouragement, inquiries, and incentives from social capital.
Continuing the above example, if the subject entered the third week of her fitness regimen and missed the first 2 runs of week 3 an alert would be sent to the ten users that the subject had shared her progress with. A portion of these users might inquire with the subject as to why she had missed these runs and offer support and encouragement to continue with the fitness regimen. The subject would then respond to this encouragement by returning to the fitness regimen as measured by a return to uploading electrophysiology data after each run. In one embodiment, the user will receive more points for the amount of feedback they receive. In one embodiment, the user will receive more points for feedback occurs before a diminished update frequency.

Method for Reinforcing Fitness Patterns by Creating Custom Challenges Based on Electrophysiology Data

In another embodiment, the invention described can be used to establish challenges based on the subject's performance. In general, the challenge system described herein provides competitive reinforcement for a subject displaying positive progress. FIG. 7 depicts a method 700 of creating a challenge in which a user will compete for additional rewards, or points, with at least one other user.
First, as the subject exceeds a minimum competitive threshold for a given electrophysiology metric, or combination of metrics, the subject becomes eligible to compete around that given metric (block 701). A computing system will then search for other subjects that are also eligible to compete around the given metric or combination of metrics (block 703). The computing system will take into account the absolute performance of the user and the subject in the metric, or combination of metrics, based on past uploads of electrophysiology data. If the user and the subject have similar performances within a given range in that metric, or combination of metrics, the social network will recommend to the subject that she challenge the other user that has been suitably matched and selected by the computing system (block 705). The challenge is then issued to matched subjects (block 707), and each subject accept or reject the challenge (block 709), and a winner is determined based on the outcome of the challenge (block 711).
In embodiment of the present invention, assume that in the previous example the subject has entered week four of the fitness regimen and has burned a cumulative total of 4000 calories, averaging between 300-500 calories burned per run. If the subject is in turn related to a user that is also within the range of 300-500 calories burned per run, the system would identify the user to the subject and propose a challenge. In this case the challenge would focus on maximizing the calories burned in a 60 minutes run. The challengers may wager a portion of their accumulated points on the outcome of the run after the odds of either user or subject winning have been calculated by the algorithm. Alternatively, winning the challenge may be worth a specific number of points based on the implementation of the algorithm and the social network.

Live Non-Local Racing Using a Wireless Device Connected to a Social Network Based on Electrophysiology Data

In another embodiment the invention can be used in to assess achievement of a goal and encourage progress by enabling Live Non-Local Racing (LNLR). LNLR is a method of using performance metrics to allow non-local athletes to compete against each other in a meaningful way. FIG. 5 depicts one LNLR configuration contemplated by the current invention. Subject 1 can compete with at least one other subject, in FIG. 5, Subject 2. Both subjects wear sensors to gather data related to their respective performance. Both subjects' data is communicated to a computing device 501, 503 connected to the internet 505. Both Subject 1 and Subject 2 are able to receive real-time data relating to their own performance and the other subject's performance. Real-time data streaming allows a subject to adjust accordingly to improve performance. An increase in performance ultimately assists the subject in obtaining the larger goal. Additionally, the subject can be awarded points based on the results of the LNLR.
As an example, a subject in California and a subject in New York might decide to have a 1-mile race. They each have preferred sites with zero elevation for the one mile in question. The computing system coordinates the start times, and the runners begin to race. Both subjects are recording biometric data such as sEMG and/or ECG. Both subjects are competing not only to see who can finish first, but also who can perform better according to other metrics such as (MFOI), warm-up index (WUI), mean power frequency (MPF), sEMG amplitude, caloric expenditure, proximity to ideal heart rate, muscle work estimation index (MWEI), and work performed. All available metrics can be used to assess relative performance of the two runners, and these metrics can stream live between the two runners so they can try and out-perform the other runner based on secondary information of these metrics, not just speed and distance traveled by the runner. For example, even if Runner A is winning, if Runner B knows that A's fatigue burn rate is much faster than B's, they may choose not to worry as much about the absolute position of A, and instead focus on keeping their own pace, since A is likely to slow down due to fatigue. In one embodiment, the user will be enabled to read the real time competition data on a graphical user interface worn or carried by the user. Although not disclosed here, the present invention contemplates all different permutations of LNLR that can be directly useful as training tools to competitive athletes. The embodiment of LNLR of this invention precludes the necessity of geographic proximity of the subjects engaged in the competition.
In one embodiment, the invention described herein can be implemented with the sensors or systems described in U.S. Provisional Application Nos. 61/385,048 and 61/514,148 and U.S. patent application Ser. No. ______ (Attorney Docket Number S1061.10011US02, the serial number to be inserted here after the filing thereof). Additionally, the invention described herein can be implemented with metrics and algorithms described in U.S. Provisional Application No. 61/385,046 and U.S. patent application Ser. No. ______ (Attorney Docket Number S1061.10010US02, the serial number to be inserted here after the filing thereof). Also, the invention described herein can be implemented with methods of promoting fitness described in U.S. Provisional Application No. 61/385,038 and U.S. patent application Ser. No. ______ (Attorney Docket Number S1061.10009US02, the serial number to be inserted here after the filing thereof). Further, the invention described herein can be implemented with graphing methods described in U.S. Provisional Application No. 61/385,049. Also, the invention described herein can be implemented with the multi-functional carrying case and associated biometric sensors and transceivers described in U.S. Provisional Application No. 61/385,051. The invention described herein can be implemented with the systems and/or methods described in U.S. Pat. Nos. 7,593,769 and 7,809,435. The patents and patent applications recited herein are incorporated herein by specific reference in their entirety.
One skilled in the art will appreciate that, for this and other processes and methods disclosed herein, the functions performed in the processes and methods may be implemented in differing order. Furthermore, the outlined steps and operations are only provided as examples, and some of the steps and operations may be optional, combined into fewer steps and operations, or expanded into additional steps and operations without detracting from the essence of the disclosed embodiments.
The present disclosure is not to be limited in terms of the particular embodiments described in this application, which are intended as illustrations of various aspects. Many modifications and variations can be made without departing from its spirit and scope, as will be apparent to those skilled in the art. Functionally equivalent methods and apparatuses within the scope of the disclosure, in addition to those enumerated herein, will be apparent to those skilled in the art from the foregoing descriptions. Such modifications and variations are intended to fall within the scope of the appended claims. The present disclosure is to be limited only by the terms of the appended claims, along with the full scope of equivalents to which such claims are entitled. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.
In one embodiment, the present methods can include aspects performed on a computing system. As such, the computing system can include a memory device that has the computer-executable instructions for performing the method. The computer-executable instructions can be part of a computer program product that includes one or more algorithms for performing any of the methods of any of the claims. The computer readable medium can also be a part of a larger network such as the Internet.
In one embodiment, any of the operations, processes, methods, or steps described herein can be implemented as computer-readable instructions stored on a computer-readable medium. The computer-readable instructions can be executed by a processor of a wide range of computing systems from desktop computing systems, portable computing systems, tablet computing systems, hand-held computing systems as well as network elements, and/or any other computing device.
There is little distinction left between hardware and software implementations of aspects of systems; the use of hardware or software is generally (but not always, in that in certain contexts the choice between hardware and software can become significant) a design choice representing cost vs. efficiency tradeoffs. There are various vehicles by which processes and/or systems and/or other technologies described herein can be effected (e.g., hardware, software, and/or firmware), and that the preferred vehicle will vary with the context in which the processes and/or systems and/or other technologies are deployed. For example, if an implementer determines that speed and accuracy are paramount, the implementer may opt for a mainly hardware and/or firmware vehicle; if flexibility is paramount, the implementer may opt for a mainly software implementation; or, yet again alternatively, the implementer may opt for some combination of hardware, software, and/or firmware.
The foregoing detailed description has set forth various embodiments of the processes via the use of block diagrams, flowcharts, and/or examples. Insofar as such block diagrams, flowcharts, and/or examples contain one or more functions and/or operations, it will be understood by those within the art that each function and/or operation within such block diagrams, flowcharts, or examples can be implemented, individually and/or collectively, by a wide range of hardware, software, firmware, or virtually any combination thereof. In one embodiment, several portions of the subject matter described herein may be implemented via Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), digital signal processors (DSPs), or other integrated formats. However, those skilled in the art will recognize that some aspects of the embodiments disclosed herein, in whole or in part, can be equivalently implemented in integrated circuits, as one or more computer programs running on one or more computers (e.g., as one or more programs running on one or more computer systems), as one or more programs running on one or more processors (e.g., as one or more programs running on one or more microprocessors), as firmware, or as virtually any combination thereof, and that designing the circuitry and/or writing the code for the software and or firmware would be well within the skill of one of skill in the art in light of this disclosure. In addition, those skilled in the art will appreciate that the mechanisms of the subject matter described herein are capable of being distributed as a program product in a variety of forms, and that an illustrative embodiment of the subject matter described herein applies regardless of the particular type of signal bearing medium used to actually carry out the distribution. Examples of a signal bearing medium include, but are not limited to, the following: a recordable type medium such as a floppy disk, a hard disk drive, a CD, a DVD, a digital tape, a computer memory, etc.; and a transmission type medium such as a digital and/or an analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link, etc.).
Those skilled in the art will recognize that it is common within the art to describe devices and/or processes in the fashion set forth herein, and thereafter use engineering practices to integrate such described devices and/or processes into data processing systems. That is, at least a portion of the devices and/or processes described herein can be integrated into a data processing system via a reasonable amount of experimentation. Those having skill in the art will recognize that a typical data processing system generally includes one or more of a system unit housing, a video display device, a memory such as volatile and non-volatile memory, processors such as microprocessors and digital signal processors, computational entities such as operating systems, drivers, graphical user interfaces, and applications programs, one or more interaction devices, such as a touch pad or screen, and/or control systems including feedback loops and control motors (e.g., feedback for sensing position and/or velocity; control motors for moving and/or adjusting components and/or quantities). A typical data processing system may be implemented utilizing any suitable commercially available components, such as those generally found in data computing/communication and/or network computing/communication systems.
The herein described subject matter sometimes illustrates different components contained within, or connected with, different other components. It is to be understood that such depicted architectures are merely exemplary, and that in fact many other architectures can be implemented which achieve the same functionality. In a conceptual sense, any arrangement of components to achieve the same functionality is effectively “associated” such that the desired functionality is achieved. Hence, any two components herein combined to achieve a particular functionality can be seen as “associated with” each other such that the desired functionality is achieved, irrespective of architectures or intermedial components. Likewise, any two components so associated can also be viewed as being “operably connected”, or “operably coupled”, to each other to achieve the desired functionality, and any two components capable of being so associated can also be viewed as being “operably couplable”, to each other to achieve the desired functionality. Specific examples of operably couplable include but are not limited to physically mateable and/or physically interacting components and/or wirelessly interactable and/or wirelessly interacting components and/or logically interacting and/or logically interactable components.
FIG. 6 shows an example computing device 600 that is arranged to perform any of the computing methods described herein. In a very basic configuration 602, computing device 600 generally includes one or more processors 604 and a system memory 606. A memory bus 608 may be used for communicating between processor 604 and system memory 606.
Depending on the desired configuration, processor 604 may be of any type including but not limited to a microprocessor (μP), a microcontroller (μC), a digital signal processor (DSP), or any combination thereof. Processor 604 may include one more levels of caching, such as a level one cache 610 and a level two cache 612, a processor core 614, and registers 616. An example processor core 614 may include an arithmetic logic unit (ALU), a floating point unit (FPU), a digital signal processing core (DSP Core), or any combination thereof. An example memory controller 618 may also be used with processor 604, or in some implementations memory controller 618 may be an internal part of processor 604.
Depending on the desired configuration, system memory 606 may be of any type including but not limited to volatile memory (such as RAM), non-volatile memory (such as ROM, flash memory, etc.) or any combination thereof. System memory 606 may include an operating system 620, one or more applications 622, and program data 624. Application 622 may include a determination application 626 that is arranged to perform the functions as described herein including those described with respect to methods described herein. Program Data 624 may include determination information 628 that may be useful for analyzing the contamination characteristics provided by the sensor unit 240. In some embodiments, application 622 may be arranged to operate with program data 624 on operating system 620 such that the work performed by untrusted computing nodes can be verified as described herein. This described basic configuration 602 is illustrated in FIG. 6 by those components within the inner dashed line.
Computing device 600 may have additional features or functionality, and additional interfaces to facilitate communications between basic configuration 602 and any required devices and interfaces. For example, a bus/interface controller 630 may be used to facilitate communications between basic configuration 602 and one or more data storage devices 632 via a storage interface bus 634. Data storage devices 632 may be removable storage devices 636, non-removable storage devices 638, or a combination thereof. Examples of removable storage and non-removable storage devices include magnetic disk devices such as flexible disk drives and hard-disk drives (HDD), optical disk drives such as compact disk (CD) drives or digital versatile disk (DVD) drives, solid state drives (SSD), and tape drives to name a few. Example computer storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data.
System memory 606, removable storage devices 636 and non-removable storage devices 638 are examples of computer storage media. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which may be used to store the desired information and which may be accessed by computing device 600. Any such computer storage media may be part of computing device 600.
Computing device 600 may also include an interface bus 640 for facilitating communication from various interface devices (e.g., output devices 642, peripheral interfaces 644, and communication devices 646) to basic configuration 602 via bus/interface controller 630. Example output devices 642 include a graphics processing unit 648 and an audio processing unit 650, which may be configured to communicate to various external devices such as a display or speakers via one or more A/V ports 652. Example peripheral interfaces 644 include a serial interface controller 654 or a parallel interface controller 656, which may be configured to communicate with external devices such as input devices (e.g., keyboard, mouse, pen, voice input device, touch input device, etc.) or other peripheral devices (e.g., printer, scanner, etc.) via one or more I/O ports 658. An example communication device 646 includes a network controller 660, which may be arranged to facilitate communications with one or more other computing devices 662 over a network communication link via one or more communication ports 664.
The network communication link may be one example of a communication media. Communication media may generally be embodied by computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and may include any information delivery media. A “modulated data signal” may be a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media may include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), microwave, infrared (IR) and other wireless media. The term computer readable media as used herein may include both storage media and communication media.
Computing device 600 may be implemented as a portion of a small-form factor portable (or mobile) electronic device such as a cell phone, a personal data assistant (PDA), a personal media player device, a wireless web-watch device, a personal headset device, an application specific device, or a hybrid device that include any of the above functions. Computing device 600 may also be implemented as a personal computer including both laptop computer and non-laptop computer configurations. The computing device 600 can also be any type of network computing device. The computing device 600 can also be an automated system as described herein.
The embodiments described herein may include the use of a special purpose or general-purpose computer including various computer hardware or software modules.
Embodiments within the scope of the present invention also include computer-readable media for carrying or having computer-executable instructions or data structures stored thereon. Such computer-readable media can be any available media that can be accessed by a general purpose or special purpose computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a computer, the computer properly views the connection as a computer-readable medium. Thus, any such connection is properly termed a computer-readable medium. Combinations of the above should also be included within the scope of computer-readable media.
Computer-executable instructions comprise, for example, instructions and data which cause a general purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions. Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
As used herein, the term “module” or “component” can refer to software objects or routines that execute on the computing system. The different components, modules, engines, and services described herein may be implemented as objects or processes that execute on the computing system (e.g., as separate threads). While the system and methods described herein are preferably implemented in software, implementations in hardware or a combination of software and hardware are also possible and contemplated. In this description, a “computing entity” may be any computing system as previously defined herein, or any module or combination of modulates running on a computing system.
With respect to the use of substantially any plural and/or singular terms herein, those having skill in the art can translate from the plural to the singular and/or from the singular to the plural as is appropriate to the context and/or application. The various singular/plural permutations may be expressly set forth herein for sake of clarity.
It will be understood by those within the art that, in general, terms used herein, and especially in the appended claims (e.g., bodies of the appended claims) are generally intended as “open” terms (e.g., the term “including” should be interpreted as “including but not limited to,” the term “having” should be interpreted as “having at least,” the term “includes” should be interpreted as “includes but is not limited to,” etc.). It will be further understood by those within the art that if a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation no such intent is present. For example, as an aid to understanding, the following appended claims may contain usage of the introductory phrases “at least one” and “one or more” to introduce claim recitations. However, the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles “a” or “an” limits any particular claim containing such introduced claim recitation to embodiments containing only one such recitation, even when the same claim includes the introductory phrases “one or more” or “at least one” and indefinite articles such as “a” or “an” (e.g., “a” and/or “an” should be interpreted to mean “at least one” or “one or more”); the same holds true for the use of definite articles used to introduce claim recitations. In addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such recitation should be interpreted to mean at least the recited number (e.g., the bare recitation of “two recitations,” without other modifiers, means at least two recitations, or two or more recitations). Furthermore, in those instances where a convention analogous to “at least one of A, B, and C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., “a system having at least one of A, B, and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). In those instances where a convention analogous to “at least one of A, B, or C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., “a system having at least one of A, B, or C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). It will be further understood by those within the art that virtually any disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase “A or B” will be understood to include the possibilities of “A” or “B” or “A and B.”
In addition, where features or aspects of the disclosure are described in terms of Markush groups, those skilled in the art will recognize that the disclosure is also thereby described in terms of any individual member or subgroup of members of the Markush group.
As will be understood by one skilled in the art, for any and all purposes, such as in terms of providing a written description, all ranges disclosed herein also encompass any and all possible subranges and combinations of subranges thereof. Any listed range can be easily recognized as sufficiently describing and enabling the same range being broken down into at least equal halves, thirds, quarters, fifths, tenths, etc. As a non-limiting example, each range discussed herein can be readily broken down into a lower third, middle third and upper third, etc. As will also be understood by one skilled in the art all language such as “up to,” “at least,” and the like include the number recited and refer to ranges which can be subsequently broken down into subranges as discussed above. Finally, as will be understood by one skilled in the art, a range includes each individual member. Thus, for example, a group having 1-3 cells refers to groups having 1, 2, or 3 cells. Similarly, a group having 1-5 cells refers to groups having 1, 2, 3, 4, or 5 cells, and so forth.
From the foregoing, it will be appreciated that various embodiments of the present disclosure have been described herein for purposes of illustration, and that various modifications may be made without departing from the scope and spirit of the present disclosure. Accordingly, the various embodiments disclosed herein are not intended to be limiting, with the true scope and spirit being indicated by the following claims. All references recited herein are incorporated herein by specific reference in their entirety.

Claims

What is claimed is:

1. A method of implementing a task assessment protocol, the method comprising:

selecting an exercise task to be performed;

breaking the exercise task to be performed into smaller units;

associating data of the exercise task with a reward using a reward system;

gathering subject muscle data and/or heart data into a database for each unit performed; and

providing awards to the subject for each unit completed based on the muscle data of the subject.

2. The methods of claim 1, comprising deriving the rewards by:

a first component based on the effort of the subject; and

a second component based on the performance of the subject.

3. The method of claim 1, comprising creating access to the database for the subject by:

providing access to the database through an internet web page; and

providing access to the database through a graphical user interface of a computing device.

4. The method of claim 1, comprising associating the rewards with points that are useful for trading.

5. The method of claim 1, comprising associating the rewards with points for levels of accumulated rewards.

6. The method of claim 1, comprising associating the rewards with social capital through additional steps by:

sharing the subject's goal with a social network of members; and

sharing the subject's progress with a social network of members.

7. The method of claim 6, comprising generating additional social capital by increased feedback from a social network by:

associating additional points related to the number of social network members shared with; and

associating additional points to a subject who has shared with a social network and received feedback from the social network members.

8. The method of claim 6, comprising associating the social capital with points that are useful for trading.

9. The method of claim 6, comprising defining social capital by:

the expectative benefits derived from sharing of individual goals and/or progress toward that goal with a group.

10. The method of claim 6, creating additional social capital by:

alerting members of the social network when progress drops below a predetermined level; and

providing members of the social network with options for providing one or more of feedback, inquiries, and/or incentives.

11. The method of claim 1, comprising reinforcing fitness patterns through additional steps by:

comparing at least one subject's progress with the progress of at least one other subject; and

creating a competition between a plurality of subjects.

12. The steps of claim 11, wherein additional points are assigned to the subject who wins the challenge.

13. The steps of claim 11, wherein the subject wagers accumulated awards based on the outcome of the competition.

14. The task assessment protocol of claim 11, wherein the data is associated with established performance metrics.

15. A competition assessment protocol comprising:

establishing an exercise competition between a plurality of subjects;

gathering muscle data for each of the plurality of subjects;

comparing the data for each subject with at least one other subject; and

enabling at least one subject access to the data of two or more of the subjects as it is being compared.

16. The competition protocol of claim 15, described as Live Non-Local Racing (LNLR).

17. The competition assessment protocol of claim 15, wherein the data is compared on the basis of performance metrics comprising: heart rate, beats per minute, muscle fatigue onset index (MFOI), warm-up index (WUI), mean power frequency (MPF), sEMG amplitude, caloric expenditure, proximity to ideal heart rate, muscle work estimation index (MWEI), and work performed.

18. The competition assessment protocol of claim 15, wherein data can be observed by the subject during the competition through a graphical user interface worn or carried by the subject.

19. A method for providing incentives to a subject to encourage progress towards a muscle activity goal, comprising:

gathering data from a sensor worn by a subject during a muscular activity increment;

determining the performance exerted by the subject;

associating completion, performance, and improvement during the increment, of a subject with a reward system based on a subject's predetermined long-term goal; and

providing incentive to continue progress toward the predetermined long-term goal by assigning rewards to the subject.

20. A method of claim 19, providing incentives to subjects, comprising:

assigning rewards based on a level of a subject's accumulated rewards;

assigning rewards based on the extent which a subject shares their goal with the members of a social network;

assigning rewards based on the extent which a subject receives feedback and encouragement from the members of the social network; and

assigning rewards based on the extent which a subject outperforms other members in the social network.