US20130090213A1

US20130090213A1 - Exercise-Based Entertainment And Game Controller To Improve Health And Manage Obesity

Info

Publication number: US20130090213A1
Application number: US13/427,738
Authority: US
Inventors: Navid Amini; Majid Sarrafzadeh
Original assignee: University of California
Current assignee: University of California
Priority date: 2011-03-25
Filing date: 2012-03-22
Publication date: 2013-04-11

Abstract

Monitoring and rewarding of physical activity are carried out by: (1) receiving a measurement of a physical activity from a sensor; (2) processing the measurement of the physical activity to derive a valid extent of the physical activity; and (3) controlling an entertainment device based on the valid extent of the physical activity.

Description

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional Application Ser. No. 61/467,744 filed on Mar. 25, 2011, the disclosure of which is incorporated herein by reference in its entirety.

FIELD OF THE INVENTION

The invention generally relates to the monitoring of exercise or other forms of physical activity and, more particularly, to the monitoring and rewarding of physical activity.

BACKGROUND

The detrimental effects of childhood obesity on the health and lifespan of an individual coupled with its far reaching grip on today's youth have caused concern that approaches the level of a nationwide pandemic. A sedentary lifestyle can be a significant contributor to childhood obesity. On the other hand, exercise can help children control their weight, and can help to reduce the risk of illnesses such as high blood pressure, heart disease, and sleep problems. However, many children fail to exercise because they excessively spend time doing stationary activities such as playing video games or watching television.
It is against this background that a need arose to develop the apparatus, system, and method described herein.

SUMMARY

One aspect of the invention relates to a non-transitory computer-readable storage medium. In one embodiment, the storage medium includes executable instructions to: (1) receive a measurement of a physical activity from a sensor; (2) process the measurement of the physical activity to derive a valid extent of the physical activity; and (3) control an entertainment device based on the valid extent of the physical activity.
Another aspect of the invention relates to a system for monitoring and rewarding physical activity. In one embodiment, the system includes: (1) a processing unit; and (2) a memory connected to the processing unit and including executable instructions to: (a) receive an identification of valid instances of a physical activity by a user; and (b) control access of the user to an entertainment device based on the valid instances of the physical activity.
Other aspects and embodiments of the invention are also contemplated. The foregoing summary and the following detailed description are not meant to restrict the invention to any particular embodiment but are merely meant to describe some embodiments of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

For a better understanding of the nature and objects of some embodiments of the invention, reference should be made to the following detailed description taken in conjunction with the accompanying drawings.

FIG. 1: Block diagram of a system for monitoring and rewarding children's physical activity, in accordance with one embodiment of the invention.

FIG. 2: Block diagram of hardware and software components of a physical activity monitor, in accordance with one embodiment of the invention.

FIG. 3: Applying step-matching to an acceleration signal, according to an embodiment of the invention.

FIG. 4: Histogram similarity approach, according to an embodiment of the invention.

FIG. 5: A computer configured in accordance with one embodiment of the invention.

FIG. 6: A gait cycle divided into four time intervals, according to an embodiment of the invention.

DETAILED DESCRIPTION

1. General Description of System

FIG. 1 shows a block diagram of a system for monitoring and rewarding children's physical activity, in accordance with one embodiment of the invention. The system allows children to use a set of entertainment appliances 1 through N, such as a television set, a video game console, an audio equipment, or another electronic entertainment device, depending on the amount of exercise or other physical activity performed by the children. In one embodiment, the system operates in a substantially automatic manner. By providing positive reinforcement, the system can provide the children with a sense of achievement, while addressing concern by parents about the children's lack of physical activity.
As shown in FIG. 1, the system includes three main, interconnected components: (1) a physical activity monitor (or module) 1; (2) a main host 2 including a computer interface; and (3) a power controller (or controller module) 3. The power controller 3 is connected to power outlets 6, which supply power to the entertainment appliances 1 through N, and the power controller 3 can activate and deactivate the entertainment appliances 1 through N by adjusting the amount of power supplied by the power outlets 6. In some embodiments, and depending on the amount of physical activity performed by the children, the power controller 3 can selectively activate (or selectively deactivate) a subset of the entertainment appliances 1 through N, while a remaining subset of the entertainment appliances 1 through N is deactivated (or activated). As shown in FIG. 1, the system also includes a web server 4, which provides functionalities for kids, parents, and caregivers, such as sign-up, reporting, behavior monitoring, diagnostic, and other functionalities. In some embodiments, physical activity monitors 1 can be directly or indirectly connected to entertainment appliances such as televisions. In such embodiments, the power controller 3 and the main host 2 can be incorporated in an entertainment appliance. Moreover, data uploads and other communications with the web server 4 can be directly performed by the entertainment appliance itself.
FIG. 2 shows a block diagram of hardware (a) and software components (b) of the physical activity monitor 1, in accordance with one embodiment of the invention. The physical activity monitor 1 can measure and process data associated with a physical activity, such as acceleration data in one or more spatial dimensions as a function of time.
As shown in FIG. 2, the physical activity monitor 1 includes a processor 9 (e.g., a central processing unit (CPU)), which is connected to a storage medium 10 and a set of sensors 7. The set of sensors 7 can include a single sensor or a combination of sensors of the same type or different types, which measure a physical activity such as walking, running, load carrying, or jumping. The set of sensors 7 can be included in the physical activity monitor 1, or can be separate from and connected to the physical activity monitor 1. The physical activity monitor 1 can be physically attached to, or carried by, a child (or another performer of a physical activity), and can be connected to the main host 2 through a wireless or a wired connection of a communication unit 8. The physical activity monitor 1 can include a pedometer, for example. Alternatively or in addition, the physical activity monitor 1 can include other types of sensors, such as a heart-rate monitor or pressure sensors. The physical activity monitor 1 also can be in the form of a software application on a smart phone that includes an accelerometer. For example, the application can incorporate computer code to detect physical activity based on data measured by an accelerometer built in or connected to the smart phone. The application can be developed for a particular operating system of the smart phone, such as Android.
In one embodiment, the physical activity monitor 1 can identify or recognize the type of exercise being carried out by a child. For example, the physical activity monitor 1 can be configured to distinguish between different activities such as walking uphill or downhill, walking on a level surface, running, heavy load carrying, and so forth. The physical activity monitor 1 also can be configured to distinguish between different types of environments in which a physical activity is performed, such as the type surface including walking on grass, uneven ground, gravel, sand, carpet, and so forth. The recognition of the type of activity and the type of environment can be carried out in accordance with supervised techniques or unsupervised techniques. For example, certain aspects of an unsupervised technique for exercise recognition is set forth in U.S. Provisional Application Ser. No. 61/448,602 filed on Mar. 2, 2011, the disclosure of which is incorporated herein by reference in its entirety. Such function can be carried out by a module 13 stored or residing in the storage medium 10. Alternatively or in addition, either of, or both, the main host 2 and the web server 4 can perform such function by processing data measured by the physical activity monitor 1.
In one embodiment, the physical activity monitor 1 can calculate or derive parameters indicative of an extent of a physical activity, such as distance traveled, duration of exercise, intensity of exercise (e.g., pace of a walk or run), and calories or energy burned as a result of exercise. The calculation of such parameters can be based on the type of exercise that is performed, the type of environment in which the exercise is performed, or both. For example, the physical activity monitor 1 can use the notion of MET (Metabolic Equivalent of Task) to derive the number of calories burned by a child. The calculation of exercise parameters can be carried out by a module 14 stored or residing in the storage medium 10. Alternatively or in addition, either of, or both, the main host 2 and the web server 4 can perform such function by processing data measured by the physical activity monitor 1.
In one embodiment, the physical activity monitor 1 can perform processing of measurements of physical activity by the set of sensors 7 to reduce or minimize the vulnerability of the system to false positives and cheating. The processing of measurements to mitigate against false positives and cheating can be carried out by modules 11 and 12 stored or residing in the storage medium 10. Alternatively or in addition, either of, or both, the main host 2 and the web server 4 can perform such function by processing data measured and provided by the physical activity monitor 1.
In one embodiment, the physical activity monitor 1 can validate, or determine a valid extent of, measurements of a physical activity made by the set of sensors 7. A measurement of a physical activity can be invalid (or have a valid extent of zero). For example, if some form of cheating has occurred, such as when a first child attaches the physical activity monitor 1 to a second child who performs an exercise, a measurement of the exercise can be deemed invalid. In another example, a measurement of a physical activity, such as a step count, can be deemed invalid because other types of physical activities, such as shaking of a pedometer, can be mistakenly interpreted by the pedometer as steps. Also, a measurement of a physical activity can be substantially valid (or have a positive valid extent). For example, the physical activity monitor 1, through processing of pressure data or acceleration data, can validate or determine a valid (accurate) extent of a step count associated with the pressure data or acceleration data resulting from a walking or running activity.
Referring back to FIG. 1, the main host 2 can reside in, or correspond to, a parent's computer. When a child activates the physical activity monitor 1, a software component of the main host 2 can retrieve data from the physical activity monitor 1 and store that data in the parent's computer. The data from the physical activity monitor 1 can be transmitted to either of, or both, the main host 2 (through a home network via Wi-Fi or LAN, or using protocols such as Bluetooth, Zigbee, or other similar protocols) and the web server 4 through the Internet (such as via cellular communications). In this manner, a database of the main host 2 and a database of the web server 4 can be updated with the latest information regarding the child's daily activity. In one embodiment, these databases can be synchronized even if, for example, cellular coverage is not available or the child is not in the vicinity of the main host 2.
Based on a valid extent of a physical activity, the main host 2 can issue a command to the power controller 3, which activates (or deactivates) one or more of the entertainment appliances 1 through N in accordance with the command. In this manner, the main host 2, in combination with the power controller 3, can control operation of the entertainment appliances 1 through N as a reward for physical activity, while mitigating against false positives and cheating. In one embodiment, the power controller 3 can be integrated into a home automation system that controls the power outlets 6 in a wireless fashion or via underlying power lines. Based on a physical activity level of a child, the main host 2 can allot a time budget for one or more of the power outlets 6 corresponding to specific appliances. In this embodiment, the power controller 3 can deactivate a corresponding appliance when the time budget expires, so that the child is forced to leave the appliance. In this manner, the main host 2, in combination with the power controller 3, can control a child's access to the functionality of the corresponding appliance. To do so, the main host 2 can issue a command to the power controller 3, and the power controller can transmit a radiofrequency (RF) signal to activate (or deactivate) one or more of the power outlets 6.
Alternatively or in addition, a controller module can be included as a software application that interacts with entertainment applications residing in a child's computer 5, such as video games. If a physical activity by the child has a sufficient valid extent, the child can be rewarded with a stronger avatar for local or web-based games on the child's computer 5, or can be rewarded, based on the child's exercise records, with other types of visual feedback incentives through interaction with the child's computer 5. These additional types of incentives, in addition to control of access to the entertainment appliances 1 through N, can further persuade the child to engage in healthy physical activity.
In one embodiment, a mapping between a valid extent of a physical activity by a child and an allotted time budget (or amount of another type of incentive described above) can be adjusted or otherwise configured. For example, the time budget can linearly increase as a function of the valid extent of the physical activity by the child. Alternatively or in addition, the time budget can increase as a step function. For example, the child can receive no time budget until the valid extent of the physical activity by the child exceeds or reaches some minimum value. Allocation of the time budget can be up to a maximum value that a child can receive per period of time, such as per day. In one embodiment, the mapping between the valid extent of the physical activity by the child and the time budget (amount of another type of incentive described above) can vary across different types of appliances and across different applications, such as video games. In one embodiment, the main host 2 has a recommended mode that calculates a time budget based on characteristics such as age, sex, height, and weight. It is contemplated that adults also can benefit from the system in addition to children.

2. Determining Valid Extent of Physical Activity with a Second Type of Sensor

This section and the following sections describe the processing of measurements of a physical activity to mitigate against false positives and cheating. As previously described, in one embodiment, a measurement of a physical activity, such as a step count for walking or running, can be deemed invalid because other types of physical activities, such as shaking of a pedometer, can be mistakenly interpreted by the pedometer as steps.
In one embodiment, a first sensor can be a pedometer attached to a person's clothing, placed in the person's pocket, or embedded in the person's shoe. The first sensor can provide a first measurement of a physical activity such as walking or running. In some instances, a significant fraction of detected steps can be a result of false positives stemming from intentional or unintentional movements along a vertical axis. To combat this issue, a second sensor of a different type from the first sensor can provide a second measurement of the physical activity. The first sensor and the second sensor can be included in the physical activity monitor 1, or can be separate sensors that communicate with the physical activity monitor 1.
In one embodiment, the second sensor can include a first pressure sensor located in a first area of a shoe insole corresponding to a heel area of a foot, and a second pressure sensor located in a second area of the shoe insole corresponding to a ball area of the foot. As indicated by FIG. 6, in each gait cycle for walking, there is a time interval when a considerable amount of pressure is applied to the heel area, namely a heel strike. Also, there is a time interval when a considerable amount of pressure is applied to the ball of the foot, namely right before a toe off. Therefore, checking an output of the pressure sensors at the right time (or checking a pattern or time variation of the output versus an expected gait cycle) can be used to verify that a recent detected step is indeed an actual step, rather than some other type of physical activity. It is worth noting that similar strategies can be applied for running (with a potentially different pattern) to decrease the number of false positives.
Alternatively or in addition, the second sensor can include additional pressure sensors. For example, the second sensor can include three, four, or more pressure sensors located in the heel area, the ball area, and other areas of the foot.
For the example set forth in FIG. 6, a pressure threshold for the first pressure sensor located in the heel area of the shoe insole can be configured as a value T1=(weight of person (kg)·g (N/Kg))/(50 (cm²)) N/cm². If a pressure detected by the first pressure sensor exceeds or reaches T1, then a heel strike (corresponding to a “1” in the leftmost bit of the two-bit pairs shown in FIG. 6) is detected. Otherwise a “0” is detected by the first pressure sensor. Similarly, a pressure threshold for the second pressure sensor located in the ball area of the shoe insole can be configured as a value T2=(weight of person (kg)×g (N/Kg))/(50 (cm²)) N/cm². If the pressure detected by the second pressure sensor exceeds or reaches T2, then a ball strike (corresponding to a “1” in the rightmost bit of the two-bit pairs shown in FIG. 6) is detected. Otherwise a “0” is detected by the second pressure sensor. The value of 50 cm²for T1 and T2 represents a typical value of the heel area or the ball area, and can be adjusted or otherwise configured for a particular person.
The data measured by the pressure sensors in the shoe insole can be valuable when the physical activity monitor 1 uses a typical pedometer to measure a physical activity. In this case, to prevent false positives (e.g., as a result of the pedometer being intentionally or unintentionally shaken), recent pressure data is checked to see if a considerable amount of pressure has been applied to at least one of the heel area and the ball area. In one embodiment, the physical activity monitor 1 validates, or determines a valid extent of, data measured by the pedometer for a physical activity based on data measured by the pressure sensors for the same physical activity. Alternatively or in addition, either of, or both, the main host 2 and the web server 4 can perform such function by processing data measured by the physical activity monitor 1.
To determine a valid extent of a first measurement by the first sensor (such as a pedometer), data from the first pressure sensor and the second pressure sensor are checked for at least a subset of possible (or candidate) steps detected by the pedometer. For example, if output of the pedometer is active (e.g., a possible step is detected by the pedometer), then recent pressure data measured by the first pressure sensor (heel area) and the second pressure sensor (ball area) are checked for a “01” pattern, a “11” pattern, or a “10” pattern (as shown in FIG. 6). In one embodiment, the recent pressure data is pressure data measured in a time period of one second or less prior to the detection of the possible step by the pedometer. Note that a time interval between a heel strike and a ball strike is typically less than 0.5 seconds, even for a slow walk. The detection of one of these patterns (or a sequence of these patterns) validates the detected step by the pedometer, as the step detected by the pedometer correlates to a recent application of sufficient pressure to at least one of the pressure sensors. In one embodiment, the step detected by the pedometer can be deemed valid based on the detection of any of the “01”, “11”, or “10” patterns in the recent time period.
In one embodiment, each possible step detected by the first sensor (such as a pedometer) can be checked against data from the second sensor (such as first and second pressure sensors). Alternatively, a subset of possible steps detected by the first sensor can be checked against data from the second sensor. The number of detected steps can be corrected or otherwise adjusted based on a percentage of steps that were detected correctly by the first sensor. For example, if 90% of the detected steps by the first sensor are validated based on the second sensor, then a valid extent of the step data can be 90% of the step data measured by the first sensor. An entertainment appliance, such as an electronic entertainment device, can then be controlled based on this valid extent of the step data.

3. Determining Valid Extent of Physical Activity with a Physical Activity Template

As previously described, in one embodiment, processing by the physical activity monitor 1 can determine a valid (accurate) extent of a physical activity, such as walking or running. For example, the physical activity monitor 1 can determine a valid step count based on acceleration data. This processing can be facilitated by determining a physical activity template, and by applying the physical activity template to measured acceleration data to count a number of instances of the activity that have occurred, such as a number of steps for a walking or running activity.
In one embodiment, an accelerometer can be included in a sensor that measures a physical activity such as walking or running. The accelerometer can be included in the physical activity monitor 1. A template matching approach can reliably measure a number of steps taken by a person. The template matching approach is based on a template, which represents a typical step cycle. More generally, a template can identify or represent an aspect of a physical activity of a particular type, such as a walking step, a running step, and so forth.
In one embodiment, an acceleration data signal can be divided into multiple data blocks having a particular duration in time, such as data blocks of about 10 seconds. FIG. 3( a) depicts a 10-second data block measured from a left foot along the x-axis, containing six step cycles. A low-pass filter with a cutoff frequency of about 20 Hz is applied to the signal to facilitate further processing, as shown in FIG. 3( b).
The template matching approach can then examine whether any physical activity template already exists, such as residing in the storage medium 10. The physical activity template can be derived from measurements of the same type of physical activity during a training period, which can be a time duration of at least about 10 seconds, such as a time duration of about 1 minute. Alternatively or in addition, a first step cycle (e.g., a time duration at the beginning of the measured data signal, such as an initial 10 second period of the measured data signal) can be extracted as a temporary template. Another portion of the measured data signal also can be extracted as the temporary template. In one embodiment, the template can be derived by the physical activity monitor 1. Alternatively or in addition, the template can be derived by either of, or both, the main host 2 and the web server 4.
An instance of a physical activity (or another event) can be detected in a measured data signal when there is a sufficient degree of similarity between the measured data signal and the template. In one embodiment, the template is slid across the entire or a portion of the data signal, and a normalized cross-correlation is calculated between the template and the measured data signal (see FIG. 3( c)). The normalized cross-correlation indicates the similarity between the template and the measured data signal, as set forth in
$\begin{matrix} R_{N} [k] = \frac{〈 X, Y 〉}{\sqrt{ X  \cdot  Y }} = \frac{R_{XY} (k)}{\sqrt{R_{XX} (0) \cdot R_{YY} (0)}}, & (1) \end{matrix}$
In equation (1), X represents the template, Y represents the measured data signal, k is an index representing a time lag, <X, Y> is the inner product of X and Y, ∥X∥ is the norm of X, ∥Y∥ is the norm of Y, R_XY(k) is the cross-correlation of X and Y for arbitrary k, R_XX(0) is the auto-correlation of X at zero lag, and R_YY(0) is the auto-correlation of Y at zero lag. In one embodiment, the cross-correlation can be derived by the physical activity monitor 1. Alternatively or in addition, the cross-correlation can be derived by either of, or both, the main host 2 and the web server 4.
In one embodiment, a maximum value for the normalized cross-correlation is 1 for absolute identity, which allows a uniform threshold to be set for all data despite varying amplitudes. Peaks in the normalized cross-correlation in FIG. 3( c) can indicate significant similarity between the template and the data signal segment, and thus the occurrence of an event (e.g., a step). An interval during which the cross-correlation exceeds or reaches a threshold T (e.g., 0.4) can be defined as a peak searching interval. Such intervals are marked with a solid line in FIG. 3( c) and with dashed lines in FIG. 3( d). Local maxima falling within the peak searching intervals in the filtered signal are marked as fiducial points of steps, and denoted by asterisks in FIG. 3( d). Using the template matching approach, initial positive peaks of steps, which occur when feet lift off the ground, are detected, and the number of steps is correspondingly counted.
In one embodiment, a physical activity template can be derived based on an average of multiple step cycles, which can be a more representative template than a temporary template. For example, in FIG. 3, six step cycles can be detected based on locating the peaks in the data block. These six step cycles can be aligned based on the location of their peaks and averaged together to derive a new template, which can be applied for further processing of subsequent data blocks. Alternatively or in addition, multiple step cycles in a longer time duration, such as about 1 minute, can be detected based on locating peaks in an initial data block of a shorter time duration. These multiple step cycles can be aligned based on the location of their peaks and averaged together to derive a new template, which can be applied for further processing.
Step cycles can be detected based on various techniques, such as (a) finding zeros of a signal; (b) computing the signal's energy; or (c) using the concept of salience used in speech processing. In one embodiment, given that a signal from a sensor, such as an accelerometer, is mixed with noise, the third technique can yield a higher accuracy. The salience of a given data sample can be defined as the length of the longest interval over which the sample is a maximum. The term salience vector denotes a signal containing the salience of each sample in an original, input signal. As a result of feet striking the ground while walking, a start of each walking cycle typically has a large salience. Therefore, cycles can be detected by locating such distinct points.
In one embodiment, the number of steps in a data block, such as a block of acceleration data for walking, can be derived as follows. First, a salience of each sample of the accelerometer data in an input signal r can be found, and a corresponding salience vector, s, can be created. Then, the vector u=(r·s)/max(s) is computed, where “·” represents an element-wise multiplication. This transformation makes the peaks of r more pronounced and attenuates other elements of r. Then, elements in u beyond or reaching a certain threshold are extracted as potential cycle indices. Then, a difference d between these results is computed. Any results differing by a single sample can be discarded. Based on an original signal assumption, an average (or mean) of the difference d can correspond to be an average (or mean) of a cycle length. Then, the difference d is normalized around its mean, and the indices which fall within the threshold are extracted. These are the cycle starting and ending points. The number of steps in the data block is then derived as: (number of extracted indices −1).
If a template is already present, peaks can be detected using the techniques stated above. Before a next data block is processed using the same template, a determination can be made as to whether the template will be updated. A step signal may change dynamically with time; accordingly, the template may not accurately represent a current step signal. In one embodiment, if major peaks in a normalized cross-correlation are lower than 0.55 (or another threshold), a new template can be derived using step cycles in a current data block. Otherwise, peak detection is carried out in the current data block using the existing template.

4. Determining Valid Extent of Physical Activity Through User Authentication

As previously described, in one embodiment, a measurement of a physical activity by a first sensor, such as a step count for walking or running, can be deemed invalid because a detected identity of a performer of the physical activity (as measured by the first sensor) does not correspond to an identity associated with, or assigned to, the first sensor. In one embodiment, an unique identifier can be assigned to a given physical activity monitor 1 (which can include the first sensor) to associate the physical activity monitor 1 with a given person. If exercise performed by a different person is measured by the physical activity monitor 1, then the system can detect the exercise as cheating.
To detect this type of cheating, the system can determine whether the physical activity monitor 1 is being carried by the person to whom the physical activity monitor 1 is assigned, or by a different person. In one embodiment, such determination is carried out through a histogram comparison to derive a similarity score.
A first histogram, namely a template histogram, can be derived that identifies or represents characteristics of a first instance of a physical activity of a particular type, such as walking or running, where it is known that the first instance of the physical activity is performed by the person to whom the physical activity monitor 1 is assigned. The template histogram can be derived during a training period. In one embodiment, the template histogram can be derived by the physical activity monitor 1. Alternatively or in addition, the template histogram can be determined by either of, or both, the main host 2 and the web server 4.
A second histogram, namely a measured histogram to be validated, can be derived that identifies or represents characteristics of a second instance of the same type of physical activity, where it is desired to determine whether the second instance of the physical activity is performed by the person to whom the physical activity monitor 1 is assigned, or by a different person. In one embodiment, the measured histogram can be derived by the physical activity monitor 1. Alternatively or in addition, the measured histogram can be determined by either of, or both, the main host 2 and the web server 4.
Based on a comparison of the template histogram to the measured histogram, a valid extent of measurements of the second instance of the physical activity can be derived. In particular, the system can determine whether the second instance of the physical activity is performed by the person to whom the physical activity monitor 1 is assigned (if the template histogram is sufficiently similar to the measured histogram), or by a different person. The comparison of the template histogram to the measured histogram can occur during a verification period separate from the training period.
Certain factors can affect the accuracy of a histogram similarity determination for user authentication. First, each histogram can include a number of bins (or resolution) that can correspond to the number of different recognizable outputs that a sensor (such as an accelerometer) can provide. Second, each histogram can include a number of observations (data points) that can correspond to a sampling rate of the sensor times a duration of the physical activity, such as each step.
In one embodiment, the template histogram is derived by measuring a first instance of a physical activity of a known type (such as walking or running) and performed by a known person to whom the physical activity monitor 1 is assigned. A duration of the first instance of the physical activity can be long enough to include at least several cycles of the physical activity, such as multiple steps or strides. For example, the duration of the first instance of the physical activity can be at least about ten seconds, and can be about one minute or more, such as up to about five minutes, about ten minutes, or more.
In one embodiment, the measured histogram is determined by measuring a second instance of the same type of physical activity. A duration of the second instance of the physical activity can be long enough to include at least several cycles of the physical activity, such as multiple steps or strides. For example, the duration of the second instance of the physical activity can be at least about ten seconds, and can be about one minute or more, such as up to about five minutes, about ten minutes, or more. The duration of the second instance of the physical activity can be the same as, or different from, the duration of the first instance of the physical activity.
In one embodiment, an output range of a sensor, such as an accelerometer, is divided into n intervals (typically 100 bins for sampling rates no more than about 100 Hz). Each interval can correspond to a bin of at least one of the template histogram and the measured histogram. With regard to the template histogram, each data point from the first instance of the physical activity can be included in the template histogram. For a sampling rate of about 100 Hz, all data points can be taken into consideration, namely the number of observations is equal to the number of data points.
Various metrics can be used to determine a similarity between the template histogram and the measured histogram. In one embodiment, an absolute distance metric can be used to derive a similarity score between these histograms. The template histogram and the measured histogram can be normalized prior to their comparison, and an absolute distance can be derived as set forth in equation (2):
$\begin{matrix} dist (x, y) = \sum_{i = 1}^{n} \langle x_{i} - y_{i} \rangle & (2) \end{matrix}$
Here, x_iis the probability of a data point residing in bin i of the normalized template histogram, and y_iis the probability of a data point residing in bin i of the normalized measured histogram. In one embodiment, this distance value represents a similarity score between two acceleration signals. This metric is both computationally streamlined and effective at measuring similarity between histograms for authenticating the identity of a person performing various types of physical activities.
If a physical activity is performed by the same person to whom the physical activity monitor 1 is assigned, the distance value is typically smaller than a resulting distance value when the physical activity is performed by an impostor. A combined acceleration signal, namely an acceleration signal that combines accelerations along multiple axes (e.g., all three axes), can yield further improvements in authenticating the identity of a performer of the physical activity. In one embodiment, operations involved in comparing two gait samples using the histogram similarity approach are visualized in FIG. 4.
FIG. 5 illustrates a computer 800 configured in accordance with one embodiment of the invention. The computer 800 includes a CPU 802 connected to a bus 806. Input/output (I/O) devices 804 are also connected to the bus 806, and can include a keyboard, mouse, display, and the like. A computer program for determining a valid extent of measurements as described above is stored in a memory 808, which is also connected to the bus 806. Computer programs providing functionality corresponding to at least one of the physical activity controller 1, the main host 2, the power controller 3, and the web server 4 can also be stored in the memory 808.
An embodiment of the invention relates to a non-transitory computer-readable storage medium having computer code thereon for performing various computer-implemented operations. The term “computer-readable storage medium” is used herein to include any medium that is capable of storing or encoding a sequence of instructions or computer codes for performing the operations described herein. The media and computer code may be those specially designed and constructed for the purposes of the invention, or they may be of the kind well known and available to those having skill in the computer software arts. Examples of computer-readable storage media include, but are not limited to: magnetic media such as hard disks, floppy disks, and magnetic tape; optical media such as CD-ROMs and holographic devices; magneto-optical media such as floptical disks; and hardware devices that are specially configured to store and execute program code, such as application-specific integrated circuits (“ASICs”), programmable logic devices (“PLDs”), and ROM and RAM devices. Examples of computer code include machine code, such as produced by a compiler, and files containing higher-level code that are executed by a computer using an interpreter or a compiler. For example, an embodiment of the invention may be implemented using Java, C++, or other object-oriented programming language and development tools. Additional examples of computer code include encrypted code and compressed code. Moreover, an embodiment of the invention may be downloaded as a computer program product, which may be transferred from a remote computer (e.g., a server computer) to a requesting computer (e.g., a client computer or a different server computer) via a transmission channel. Another embodiment of the invention may be implemented in hardwired circuitry in place of, or in combination with, machine-executable software instructions.
While the invention has been described with reference to the specific embodiments thereof, it should be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the true spirit and scope of the invention as defined by the appended claims. In addition, many modifications may be made to adapt a particular situation, material, composition of matter, method, operation or operations, to the objective, spirit and scope of the invention. All such modifications are intended to be within the scope of the claims appended hereto. In particular, while certain methods may have been described with reference to particular operations performed in a particular order, it will be understood that these operations may be combined, sub-divided, or re-ordered to form an equivalent method without departing from the teachings of the invention. Accordingly, unless specifically indicated herein, the order and grouping of the operations is not a limitation of the invention.

Claims

What is claimed is:

1. A non-transitory computer-readable storage medium, comprising executable instructions to:

receive a first measurement of a physical activity from a first sensor;

process the first measurement of the physical activity to derive a valid extent of the physical activity; and

control an entertainment device based on the valid extent of the physical activity.

2. The non-transitory computer-readable storage medium of claim 1, further comprising executable instructions to receive a second measurement of the physical activity from a second sensor that is different from the first sensor, and wherein the executable instructions to process the first measurement of the physical activity include executable instructions to derive the valid extent of the physical activity based on the second measurement of the physical activity.

3. The non-transitory computer-readable storage medium of claim 2, wherein the first measurement is a measurement of acceleration, and the second measurement is a measurement of pressure.

4. The non-transitory computer-readable storage medium of claim 3, wherein the executable instructions to derive the valid extent of the physical activity include executable instructions to correlate the measurement of acceleration with sufficient pressure applied to at least one area of a foot relative to a threshold pressure value.

5. The non-transitory computer-readable storage medium of claim 1, wherein the executable instructions to process the first measurement of the physical activity include executable instructions to:

derive a physical activity template; and

apply the physical activity template to the first measurement to derive the valid extent of the physical activity.

6. The non-transitory computer-readable storage medium of claim 5, wherein the executable instructions to apply the physical activity template include executable instructions to:

derive a cross-correlation between the physical activity template and the first measurement; and

detect a number of peaks in the cross-correlation.

7. The non-transitory computer-readable storage medium of claim 1, further comprising executable instructions to receive a second measurement of the physical activity from the first sensor, and wherein the executable instructions to process the first measurement of the physical activity include executable instructions to authenticate an identity of a performer of the physical activity based on the second measurement of the physical activity.

8. The non-transitory computer-readable storage medium of claim 7, wherein the first measurement and the second measurement are measurements of acceleration.

9. The non-transitory computer-readable storage medium of claim 7, wherein the executable instructions to authenticate the identity of the performer of the physical activity include executable instructions to:

derive a measured histogram and a template histogram corresponding to the first measurement and the second measurement, respectively; and

derive a similarity score between the measured histogram and the template histogram.

10. The non-transitory computer-readable storage medium of claim 1, wherein the executable instructions to control the entertainment device include executable instructions to activate the entertainment device based on the valid extent of the physical activity.

11. The non-transitory computer-readable storage medium of claim 1, wherein the executable instructions to control the entertainment device include executable instructions to allot a time budget for the entertainment device based on the valid extent of the physical activity.

12. A system for monitoring and rewarding physical activity, comprising:

a processing unit; and

a memory connected to the processing unit and including executable instructions to:

receive an identification of valid instances of a physical activity by a user; and

control access of the user to an entertainment device based on the valid instances of the physical activity.

13. The system of claim 12, wherein the memory further includes executable instructions to:

receive a measurement from a sensor that is applied to the user; and

process the measurement to identify the valid instances of the physical activity.

14. The system of claim 13, wherein the measurement is indicative of multiple, candidate instances of the physical activity, and the executable instructions to process the measurement include executable instructions to identify a subset of the candidate instances as the valid instances of the physical activity.

15. The system of claim 14, wherein the executable instructions to process the measurement include executable instructions to compare the measurement with a physical activity template to identify the valid instances of the physical activity.

16. The system of claim 14, wherein the measurement is a first measurement, the sensor is a first sensor, the memory further includes executable instructions to receive a second measurement from a second sensor that is applied to the user, and the executable instructions to process the first measurement include executable instructions to identify the subset of the candidate instances as correlated with the second measurement.

17. The system of claim 13, wherein the executable instructions to process the measurement include executable instructions to authenticate an identity of the user to whom the sensor is assigned.

18. The system of claim 17, wherein the executable instructions to authenticate the identity of the user include executable instructions to:

derive a measured histogram corresponding to the measurement; and

derive a similarity score between the measured histogram and a template histogram assigned to the user.

19. The system of claim 12, wherein the executable instructions to control access to the entertainment device include executable instructions to activate the entertainment device based on the valid instances of the physical activity.

20. The system of claim 12, wherein the executable instructions to control access to the entertainment device include executable instructions to allot a time budget for the entertainment device based on the valid instances of the physical activity.