Unitless activity assessment and associated methods

Information

  • Patent Grant
  • 10645991
  • Patent Number
    10,645,991
  • Date Filed
    Tuesday, July 30, 2019
    5 years ago
  • Date Issued
    Tuesday, May 12, 2020
    4 years ago
Abstract
A system assesses activity and displays a unitless activity value. A detector senses activity of a user. A processor reads sensed activity data from the detector. A display displays the unitless activity value. An enclosure houses the detector and the processor. The processor periodically reads the sensed activity data from the detector and processes the data to generate an activity number, the number being used to generate the unitless activity value based upon a maximum number and a display range.
Description
BACKGROUND

Shoes (including sneakers or boots, for example) provide comfort and protection for feet. More importantly, shoes provide physical support for feet to reduce risk of foot injuries. A shoe is often necessary to provide support during intense physical activity, such as running, soccer and American football. As a shoe wears, physical support provided by the shoe decreases, thereby reducing associated protection from injury. When a critical wear level is reached, even if the shoe looks like it is not particularly worn, the shoe may not provide adequate support and may, in fact, cause damage to feet.


SUMMARY

In one embodiment, a shoe wear out sensor includes at least one detector for sensing a physical metric that changes as a shoe wears out, a processor configured to process the physical metric, over time, to determine if the shoe is worn out, and an alarm for informing a user of the shoe when the sole is worn out.


In another embodiment, a system determines the end of a shoe's life. Use of the shoe is sensed by at least one detector. A processor is configured to measure the use of the shoe and to determine if the shoe is worn out. An alarm informs a user of the shoe when the shoe is worn out.


In another embodiment, a body bar sensing system includes a housing with at least one detector for sensing a physical metric that indicates repeated movement of the housing when attached to the body bar, a processor configured to process the physical metric, over time, to determine repetitions thereof, and a display for informing a user of the repetitions.


In another embodiment, a system assesses activity and displaying a unitless activity value and includes a detector for sensing activity of a user of the system, a processor for processing sensed activity data from the detector, a display for displaying the unitless activity value, and an enclosure for housing the detector and the processor. The processor periodically reads the sensed activity data from the detector and processes the data to generate an activity number, the number being used to generate the unitless activity value based upon a maximum number and a display range.


In another embodiment, a method determines a unitless activity value for a desired period of activity. A period accumulator is cleared prior to the start of the activity period. A detector is periodically sampled to obtain data that is processed to determine a number representative of the sampling period. The number is added to the period accumulator. The unitless activity value is then determined based upon the period accumulator, a maximum activity number and a display range. The unitless activity value is then displayed. The sampling, processing and adding are repeated until data is sampled for the desired period of activity.


In another embodiment, a method assesses activity unitlessly by detecting motion of a user, processing the detected motion, over time, to determine an activity value, ratioing the activity value to a maximum activity value, and reporting a scaled unitless activity value to the user based upon the ratio and a scale.


A software product has instructions, stored on computer-readable media, that, when executed by a computer, perform steps for determining a unitless activity value for a desired period of activity, including instructions for: detecting motion of a user, processing detected motion, over time, to determine an activity value, ratioing the activity value to a maximum activity value, and reporting a scaled unitless activity value to the user based upon the ratio and a scale.





BRIEF DESCRIPTION OF THE FIGURES


FIG. 1 shows one exemplary embodiment of a shoe wear-out sensor.



FIG. 2 shows one exemplary embodiment of a shoe with a shoe wear out sensor.



FIG. 3 shows another exemplary embodiment of a shoe with a shoe wear out sensor.



FIG. 4A shows one exemplary process for determining shoe wear out.



FIG. 4B shown one exemplary process for determining shoe wear out.



FIG. 4C shows one exemplary process for determining shoe wear out.



FIG. 4D shown one exemplary process for determining shoe wear out.



FIG. 5 shows one body bar sensing system embodiment.



FIG. 6 shows one part of an exemplary body bar with a body bar sensing system embodiment attached.



FIG. 7 shows one part of a body bar in an embodiment showing a weight and a body bar sensing system that secures the weight onto the body bar.



FIG. 8 shows one exemplary process for reporting body bar usage.



FIG. 9 shows an embodiment of a sensor that unitlessly assesses activity.



FIG. 10 shows a process for unitlessly determining activity.





DETAILED DESCRIPTION OF THE FIGURES


FIG. 1 shows one shoe-wear out sensor 100. Sensor 100 includes a processor 102, a detector 104 and an alarm 106. A battery 108 may be used to power processor 102, detector 104 and alarm 106; alternatively, a magnetic coil generator (not shown) or other mechanical motion-to-electricity conversion device may be employed with sensor 100 to power these elements. Detector 104 is for example an accelerometer and/or a force sensing resistor (FSR). Alarm 106 is for example a light emitting diode (LED) and/or a small speaker and/or a small sound actuator (e.g., a buzzer, piezoelectric beeper etc).



FIG. 2 shows a shoe 200 with a shoe-wear out sensor 210. Shoe 200 is for example a running or sport shoe, boot (e.g., a snowboard or hiking boot), slipper, dress shoe or flip-flop; shoe 200 may alternatively be an orthopedic shoe for providing special foot support. Sensor 210 may represent sensor 100, FIG. 1. In the illustrated embodiment, shoe 200 has a sole 202 and an upper part 204. Sole 202 has an outsole 206 and a heel 208. Sensor 210 is shown contained within heel 208; however sensor 210 may be placed elsewhere within or on the shoe to function similarly.



FIG. 3 shows one exemplary embodiment of a shoe with a shoe-wear out sensor 310. Sensor 310 may again represent sensor 100, FIG. 1. Shoe 300 is shown with a sole 302 and an upper part 304. Sole 302 has an outsole 306 and a heel 308. Shoe 300 may again represent, for example, a running shoe, sports shoe or orthopedic shoe (or other type of shoe or boot). Electronics 310a of sensor 310 are shown contained within heel 308; but detector 312 is shown located within outer sole 306, illustrating that the elements of sensor 100 (FIG. 1) may be dispersed to various locations of the shoe while providing similar functionality. Detector 312 is for example detector 104, FIG. 1; it may thereby be a force sensing resistor and/or a piezoelectric foil that is electrically connected, via connection 314, to electronics 310a of sensor 310. If detector 312 is a piezoelectric foil (or other piezoelectric device), use of shoe 300 results in flexing of detector 312 which may generate sufficient electricity to power electronics 310a of sensor 310, avoiding the need for battery 108.



FIGS. 1, 2 and 3 are best viewed together with the following description. Sensor 100 may be embedded in a shoe (e.g., sensors 210, 310 within shoes 200, 300) and configured to determine when that shoe has “worn out”. It then informs the user, via alarm 106, that it is time to buy a new shoe (usually a new pair of shoes). In an embodiment, alarm 106 is an LED 217 that is positioned at the outside of the shoe such that it may be seen, when activated, by the user of the shoe, as illustratively shown in FIG. 2.


Processor 102 may operate under control of algorithmic software 103 (which is illustratively shown within processor 102, though it may reside elsewhere within sensor 100, for example as stand alone memory of sensor 100). Algorithmic software 103 for example includes algorithms for processing data from detector 104 to determine when a shoe is worn out.



FIG. 4A for example illustrates one process 400 performed by processor 102 of FIG. 1. In step 402, processor 102 samples detector 104 to determine a physical metric associated with the shoe. In an example of step 402, detector 104 is an accelerometer and thereby provides acceleration data resulting from movement of the shoe upon a surface as the physical metric. For example, as the shoe strikes the ground when in use, processor 102 takes a plurality of samples using detector 104 to form an impact profile. In step 404, processor 102 processes the physical metric and compares it against a predetermined threshold, response curve or other data reference. In an example of step 404, processor 102 compares the impact profile determined from the accelerometer against an impact profile of a “new” shoe. In another example of steps 402, 404, the physical metric is power spectral density corresponding to certain frequencies of interest; and the power spectral density is compared, during use of the shoe, to a data reference containing power spectral density of a new or acceptably performing shoe. If the current data (i.e., physical metric) is too large or exceeds the data reference, for example, then processor 102 sets off alarm 106 (e.g., lights LED 217) in step 406. In one embodiment, upon first use of the shoe, processor 102 determines an impact profile of the new shoe that is then used (e.g., as the threshold or data reference) in comparison against subsequently determined impact profiles. Or, upon first use of the shoe, for example, processor 102 may store the appropriate data reference (e.g., power spectral density or threshold) for comparison against data captured in latter uses of the shoe. In this way, therefore, process 400 may be efficiently used to inform a user of shoe wear out.


As noted, data from detector 104 may be processed in the frequency domain (e.g., using Fourier transforms of data from detector 104) so as to evaluate, for example, power spectral density of the physical metric (e.g., acceleration or force), in step 404. In this manner, therefore, a range of frequencies may be evaluated (e.g., an area under the curve for certain frequencies may be integrated) from detector 104 and then compared to similar data (as the threshold) of a new shoe. As a shoe wears, the elasticity of the material from which it is made changes; thus the ability of the material to absorb the shock of the shoe contacting the ground deteriorates, resulting in more shock force being transferred to the foot within the shoe. By determining the increase of the shock force above the threshold, in this embodiment, the wear on the shoe may be determined.


We now specifically incorporate by reference the teachings and disclosure of: U.S. Pat. Nos. 6,539,336; 6,266,623; 6,885,971; 6,856,934; 6,8963,818; 6,499,000; and 8,280,682. These patents provide useful background, power sensing and weight/movement monitoring techniques suitable for use with the teachings of this present application.


In an embodiment, similar to the embodiment of FIG. 3, processor 102 determines wear of shoe 300 based upon weight of the user of shoe 300. By using signals from detector 312 to determine an approximate weight of the user of shoe 300 (for example by using a pressure sensor and fluid-filled cavity as detector 104), processor 102 may determine a life expectancy of shoe 300. Since the wear on the shoe is roughly proportional to the weight applied by the wearer, during activity, by determining the weight of the wearer and the amount the shoe is used (e.g., how often and how long the shoe is used), processor 102 may thus determine shoe wear with increased accuracy. That is, a shoe used by someone who spends most of their time sitting at a desk receives less wear that a shoe used by someone who spends most of the day standing on their feet.


In another embodiment, by sensing when the shoe is used—or for how long—the teachings herein may instead be applied so as to set off the alarm after a term or time of use has expired. For example, if a shoe is specified for use to at least 100 hours or 500 miles (or other similar metric specified by the shoe manufacturer), then by sensing weight or acceleration (or other physical metric, via detector 104) that use may be determined; processor 102 then activates alarm 106 when the use is exceeded. For example, using one or more accelerometers as detector 104, speed of the shoe may be determined through operation of processor 102 using an appropriate algorithm within software 103; this processor 102 then uses the speed information to determine distance traveled and sets off alarm 106 when, for example, the manufacturer's specified distance use is met. Illustratively, in another example, if the manufacturer specifies that the shoe may be used under normal conditions for 500 hours (or some other time), then detector 104 in the form of an accelerometer may determine when the shoe is in use; processor 102 then determines the period of use, over time (e.g., weeks and months) and sets off alarm 106 when the accumulated use exceeds the specified limit.



FIG. 4B for example illustrates one process 450 performed by processor 102 of FIG. 1 for determining shoe wear out. In step 452, processor 102 samples detector 104 to determine one or more physical metrics associated with the shoe. In an example of step 402, detector 104 includes a fluid filled cavity and a pressure sensor and thereby provides a signal representative of force upon the shoe (e.g., a value representative of the weight of the user of the shoe). For example, as the shoe is used, processor 102 takes a plurality of pressure reading from detector 104. In step 454, processor 102 determines an approximate weight upon the shoe based upon samples of step 452. In one example of step 454, processor 102 utilizes algorithms of software 103 to determine an approximate weight of the user of the shoe based upon pressure values sensed by detector 104. In step 456, processor 102 determines the duration of the shoe's use. In one example of step 456, processor 102 utilizes algorithms of software 103 to measure the duration that the shoe is used based upon readings from detector 104 and an internal timer of processor 102. In step 458, processor 102 determines the shoe use for the sample period of step 452. In one example of step 458, processor utilizes algorithms of software 103 to determine a use factor based upon the determined weight of step 454 and the duration of use of step 458. In step 460, processor 102 determines remaining life of the shoe based upon the determined shoe use of step 458. In one example of step 460, processor 102 maintains a cumulative value of usage determined in step 458 for comparison against a manufacturer's expected usage of the shoe. In step 462, processor 102 enables alarm 106 if the shoe's life is exceeded. Steps 452 through 462 repeat periodically throughout the life of the shoe to monitor shoe usage based upon wear determined from the weight of the user and the duration of use.


In the above description of process 450, it is not necessary that weight be determined. Rather, in an embodiment, it may instead be determined that the shoe is in “use” based on an algorithm using the pressure or force based detector 104; and then this use is accumulated time-wise to determine when the shoe's life expectancy is exceeded. For example, once a user puts weight onto this detector (in this embodiment), then processor 102 detects (through use of an algorithm as software 103) that the shoe is in use due to the presence of weight onto detector 104.



FIG. 4C for example illustrates one process 470 performed by processor 102 of FIG. 1 for determining shoe wear out. In step 471, processor 102 samples detector 104 periodically over a defined period. In one example of step 471, detector 104 is an accelerometer that is sampled periodically by processor 102 over a period often seconds. In step 472, processor 102 determines if the shoe is in use. In one example of step 472, processor 102 utilizes algorithms of software 103 to process the samples of step 471 to determine if the shoe is in use. Step 473 is a decision. If, in step 473, processor 102 determines that the shoe is in use, process 470 continues with step 474; otherwise process 470 continues with step 475. In step 474, processor 102 adds a value representative of the defined period of step 471 to an accumulator. In one example of step 474, a non-volatile accumulator is incremented by one, where the one represents a period often seconds. Step 475 is a decision. If, in step 475, processor 102 determines that the shoe is worn out, process 470 continues with step 476; otherwise process 470 continues with step 471. In one example of the decision of step 475, processor 102 compares the use accumulator of step 474 against a value representative of the expected life of the shoe. Steps 471 through 475 repeat throughout the lifetime of the shoe. As appreciated, power saving measures may be used within sensor 100 when it is determined that the shoe in which sensor 100 is installed is not in use. In step 476, processor 102 enables alarm 106. In one example of step 476, processor 102 may periodically activate LED 217, FIG. 2, until battery 108 is exhausted.


Process 470 thus determines the wear on a shoe by measuring the amount of use and comparing it against the expected use defined by a manufacturer, for example. In an embodiment, the use accumulator of step 474 is a timer within processor 102. This timer is started when step 473 determines that the shoe is in use and is stopped when step 473 determines that the shoe is not in use. This timer thus accumulates, in real time, the use of the shoe for comparison against a manufacturer's expected use. In another embodiment, step 472 may determine the number of steps a shoe has taken such that the use accumulator of step 474 accumulates the total number of steps taken by the shoe. This total number of steps is then compared to the manufacturer's recommended number of steps expected in the shoes life time.



FIG. 4D illustrates one process 480 performed by processor 102 of FIG. 1 for determining shoe wear out. In step 481, processor 102 samples detector 104 periodically over a defined period. In one example of step 481, detector 104 is an accelerometer and processor 102 samples acceleration values over a period of 1 second. In step 482, processor 102 determines if the shoe is in use. In one example of step 482, processor 102 utilizes algorithms of software 103 to determine if characteristics of samples values of step 481 indicate that the shoe is in use. Step 483 is a decision. If, in step 483, processor 102 determines that the shoe is in use, process 480 continues with step 484; otherwise process 480 continues with step 486. In step 484, processor 102 determines a distance traveled over the defined period of step 481. In one example of step 484, processor 102 utilizes algorithms of software 103 to first determine speed of the shoe, and then determines distance covered in one second. In step 485, processor 102 accumulates the distance traveled. In one example of step 485, processor 102 adds the distance determined in step 484 to a total distance traveled accumulator. In one example, this accumulator is stored in non-volatile memory. Step 486 is a decision. If, in step 486, processor 102 determines that the shoe is worn out, process 480 continues with step 487; otherwise process 480 continues with step 481. In one example of step 486, processor 102 compares the total accumulated distance of step 485 against the manufacturer's recommended maximum distance for the shoe. Steps 481 through 486 repeat throughout the lifetime of the shoe. As appreciated, power saving measures may be used within sensor 100 when it is determined that the shoe is not in use. In step 487, processor 102 enables alarm 106. In one example of step 487, processor 102 may periodically activate LED 217, FIG. 2, until battery 108 is exhausted. Process 480 thus determines shoe wear by measuring the distance traveled by the shoe, using one or more accelerometers, and compares that distance to a manufacturer's recommended maximum distance for the shoe.



FIG. 5 shows a body bar sensing system 500. System 500 includes a housing 502, a processor 504, a detector 506 and either an internal display 508 or an external display 512. A battery 510 may be used to power processor 504, detector 506 and display 508/512. Detector 506 is for example an accelerometer or a Hall Effect sensor. Display 508/512 is for example a liquid crystal display and/or a small speaker (e.g., that emits voice annunciations or other sounds generated by processor 504).



FIG. 6 shows one part of an exemplary body bar 602 with body bar sensing system 500 attached; a weight 604 and a retaining clip 606 are also shown to secure weight 604 onto body bar 602 (note, some body bars use no weights but weight is shown in FIG. 6 for illustrative purposes). Body bar 602 may represent a work out bar used by people in the gym, or a barbell, or other similar apparatus that requires a number of repetitions in exercise. FIG. 7 shows body bar 602 in an embodiment with another body bar sensing system 500 that secures weight 604 onto body bar 602. That is, sensing system 500 in addition operates as retaining clip 606, FIG. 6.



FIGS. 5, 6 and 7 are best viewed together with the following description. Housing 502 attaches to body bar 602 as shown in FIG. 6 or as shown in FIG. 7. Processor 504 utilizes detector 506 to determine when system 500 (as attached to body bar 602) has performed one repetition; it then informs the user, via display 508/512 for example, of a number of repetitions (or whether the user has performed the right number or any other number of planned repetitions as programmed into processor 504).


Where display 512 is used (i.e., remote from housing 502), a wireless transmitter (not shown) may be included within housing 502 to remotely provide data from processor 504 to remote display 512 (as shown in dotted outline). Where display 508 is integral with housing 502, then display 508 provides a visual display for a user when housing 502 attaches to the body bar. In one embodiment, display 512 (shown in dotted outline) is part of a watch (or a MP3 player or a cell phone) that may be seen when worn or used by the user when performing exercises; and measurements determined by processor 504 are transmitted to the watch (or to the MP3 player or cell phone) for display upon display 512.


Processor 504 may operate under control of algorithmic software 505 (which is illustratively shown within processor 504 although it may reside elsewhere within housing 502, such as stand alone memory within housing 502). Algorithmic software 505 for example includes algorithms for processing data from detector 506 to determine the repetitions performed by a user of body bar 602.



FIG. 8 shows one exemplary process 800 performed by processor 504. In step 802, detector 506 samples a physical metric associated with body bar 602. In an example of step 802, detector 506 is an accelerometer and thereby provides acceleration as the physical metric. In another example of step 802, detector 506 is a Hall effect sensor which detects inversion (and thus repetition) of bar 602. In step 804, processor 504 processes the physical metric to assess whether the metric indicates a repetition of body bar 602. In an example of step 804, processor 504 evaluates the acceleration to determine if body bar 602 has been raised or lowered within a certain time interval. In step 806, repetition information is displayed to the user. In an example of step 806, the number of repetitions is relayed remotely (wirelessly) to a watch that includes display 512. That watch may also include a processor to store data and inform the user of repetitions for workouts, over time.



FIG. 9 shows one exemplary system 900 for unitlessly assessing activity of a user. System 900 has a processor 904, a detector 906 and a battery 908 within an enclosure 902 (e.g., a plastic housing). System 900 may include a display 910 for displaying unitless units to the user. Alternatively (or in addition), a remote display 912 is used to display the unitless units; in this case, enclosure 902 includes a wireless transmitter 913 in communication with, and controlled by, processor 904, so that transmitted unitless assessment numbers are sent to remote display 912.


In an embodiment, detector 906 is an accelerometer and processor 904 determines a value representing an activity level of the user of system 900 for display on display 910 or display 912. The accelerometer is for example positioned within housing 902 so that, when housing 902 is attached to a user, accelerometer 906 senses motion perpendicular to a surface (e.g., ground or a road or a floor) upon which the user moves (e.g., runs, dances, bounces). Data from the accelerometer is for example processed in the frequency domain as power spectral density (e.g., by frequency binning of the data). Multiple accelerometers (e.g., a triaxial accelerometer) may also be used as detector 906—for example to sense motion in other axes in addition to one perpendicular to the surface—and then processed together (e.g., in power spectral density domain) to arrive at a unitless value (as described below).


Processor 904 may utilize one or more algorithms, shown as software 905 within processor 904, for processing information obtained from detector 906 to assess the activity of the user. For example, processor 904 may periodically sample detector 906 to measure acceleration forces experienced by the user (when enclosure 902 is attached to the user, e.g., at the user's belt or shoe). Processor 904 may then process these forces to assess the activity level of the user. This activity level may represent effort exerted by the user when skiing.


The following represents a typical use of system 900, in an embodiment. In this example, detector 906 is one or more accelerometers. First, processor 904 determines when system 900 is in use, for example by sensing movement of housing 902 that corresponds to known activity (e.g., skiing or running). Alternatively, system 900 includes a button 915 that starts processing (in which case, separate determination of a known activity is not necessary). In an embodiment, button 915 is located proximate to display 912, and communicated wirelessly with processor 904. In this case, wireless transmitter 913 is a transceiver and button 915 includes a transmitter or a transceiver.


Once processor 904 knows (by sensing motion) or is notified (by button 915) that system 900 is operating in the desired activity, then it collects data over a period of that activity—for example over 1 hour (a typical aerobic hour), 4 hours (a typical long run), 8 hours (a typical “ski” day) or over one full day, each of these being typical sport activity periods; however any time may be used and/or programmed in system 900. In an example, processor 904 integrates power spectral density of acceleration over this period of time to generate a number. This number in fact is a function of g's, frequency units and time, which does not make intuitive sense to the user. For example, consider a professional athlete who snowboards down difficult, double diamond terrain for eight hours. When system 900 measures his activity over this period, his number will be high (e.g., 500 “units” of power spectral density) because of his extreme physical capabilities. Then, when a less capable user uses system 900, a number of, e.g., 250 units may be generated because the user is not as capable (physically and skilled) as the professional. Therefore, in this example, an expected maximum number, shown as MAX 914 within processor 904, may be set at 500. A display range, shown as RNG 916 within processor 904, may also be defined such that system 900 may display a unitless value that is relative to the maximum number. Continuing with the above example, if RNG 916 is set to 100, system 900 displays a unitless value of 100 for the professional athlete and a unitless value of 50 for the less capable user (i.e., the less capable user has a 50% value of the professional athlete). By setting RNG 916 to other values, the displayed output range of system 900 may be modified.


In one example of use, system 900 is formed as a wrist watch to facilitate attachment to a child's wrist. System 900, when worn by the child, may then determine the child's activity level for the day. In another example of use, system 900 may be attached to a person's limb that is recuperating from injury (e.g., sporting injury, accident and/or operation etc.) such that system 900 may determine if the limb is receiving the right amount of activity to expedite recovery.


In another example of use, two skiers each use a system 900 when skiing for a day. The first skier, who is experienced and athletic, skis difficult ski runs (e.g., black double diamonds) all day, whereas the second skier is less experienced and skis easy runs (e.g., green runs) all day. At the end of the day, the first skier has a unitless activity value of 87 and the second skier has a unitless activity value of 12. Thus, these unitless activity values indicate the relative activity levels of each skier.



FIG. 10 shows a flowchart illustrating one process 1000 for determining and displaying a unitless value representative of a user's activity. Process 1000 may represent algorithms within software 905 of FIG. 9, for example, to be executed by processor 904. In step 1002, process 1000 clears a period accumulator. In one example of step 1002, processor 904, under control of software 905, clears period accumulator 918. In step 1004, process 1000 samples the detector to obtain data. In one example of step 1004, processor 904 periodically samples detector 906 over a sample period to determine data representative of the user's activity for that period. In step 1006, process 1000 processes the data of step 1004 to determine a number. In one example of step 1006, processor 904 integrates power spectral density of acceleration sampled in step 1004 over the sample period of step 1004 to generate a number. In step 1008, the number determined in step 1006 is added to the period accumulator. In one example of step 1008, processor 904 adds the number determined in step 1006 to period accumulator 918. In step 1010, process 1000 determines a unitless activity value from the accumulator. In one example of step 1010, processor 904 converts the accumulated value to a display value based upon MAX 914 and RNG 916. In step 1012, process 1000 displays the determined unitless activity value. In one example of step 1012, processor 904 sends the determined unitless activity value to display 912 via wireless transmitter 913. Step 1014 is a decision. If, in step 1014, the activity period for display has ended, process 1000 terminates; otherwise process 1000 continues with step 1004. Steps 1004 through 1014 thus repeat until the desired activity period is over.


Changes may be made to this application without departing from the scope hereof. It should thus be noted that the matter contained in the above description or shown in the accompanying drawings should be interpreted as illustrative and not in a limiting sense. The following claims are intended to cover all generic and specific features described herein, as well as all statements of the scope of the present method and system, which, as a matter of language, might be said to fall there between.

Claims
  • 1. A method of assessing usage by a user of an electronic system comprising a detector and a processor, the method comprising: detecting, with the detector, use data indicative of use of the electronic system by the user during a use period;processing, with the processor, the detected use data to determine a number representative of the detected use data during the use period; andgenerating, with the processor, a value based on a comparison of the determined number and an expected maximum number for the use period.
  • 2. The method of claim 1, further comprising: prior to the generating, identifying a type of activity of the user performed during the use period; andprior to the generating, identifying the expected maximum number for the use period based on the identified type of activity.
  • 3. The method of claim 2, wherein the identifying the type of activity comprises detecting at least one press of a button.
  • 4. The method of claim 2, wherein the identifying the type of activity comprises processing at least a portion of the detected use data.
  • 5. The method of claim 1, further comprising presenting the generated value to the user.
  • 6. The method of claim 5, further comprising repeating the detecting, the processing, the generating, and the presenting for a plurality of consecutive use periods.
  • 7. The method of claim 1, further comprising repeating the detecting, the processing, and the generating for a plurality of consecutive activity periods.
  • 8. The method of claim 1, wherein the processing the detected use data to determine the number comprises integrating power spectral density of acceleration data of the detected use data over the period of time of the use period.
  • 9. The method of claim 1, wherein the use period is at least eight hours.
  • 10. The method of claim 1, wherein the detected use data is indicative of a number of physical repetitions.
  • 11. The method of claim 1, wherein the value is based on an intensity of the use of the user during the use period.
  • 12. The method of claim 1, wherein the value is based on a length of the use period.
  • 13. The method of claim 1, wherein the detected use data is indicative of at least two different activities.
  • 14. The method of claim 1, wherein the generating the value comprises: determining a ratio based on the comparison of the determined number and the expected maximum number for the use period; andmultiplying the determined ratio by a range number.
  • 15. A system comprising: a detector configured to detect movement data indicative of movement over a movement duration of time; anda processor configured to: determine a number representative of the detected movement data over the movement duration of time; andgenerate a value based on the determined number and a maximum number for the movement duration of time.
  • 16. The system of claim 15, further comprising an enclosure that at least partially houses each one of the detector and the processor.
  • 17. The system of claim 16, wherein the enclosure is configured to be worn on a wrist of a user during the movement duration of time.
  • 18. A method of assessing data, comprising: detecting data;sampling the detected data during a time period;processing the sampled data to determine a number representative of the sampled data for the time period;adding the number to an accumulator number to provide an updated accumulator number; anddetermining a value based upon the updated accumulator number and an expected maximum number, wherein the determining the value comprises: determining a ratio based on a comparison of the updated accumulator number and the expected maximum number; andmultiplying the determined ratio by a range number.
  • 19. The method of claim 18, further comprising presenting the determined value to a user.
  • 20. The method of claim 18, wherein the detected data is indicative of a number of physical repetitions.
RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 15/972,959 filed May 7, 2018 (now U.S. Pat. No. 10,376,015), which is a continuation of U.S. patent application Ser. No. 15/443,392 filed Feb. 27, 2017 (now U.S. Pat. No. 9,968,158), which is a continuation of U.S. patent application Ser. No. 14/298,454 filed Jun. 6, 2014 (now U.S. Pat. No. 9,578,927), which is a continuation of U.S. patent application Ser. No. 13/544,733 filed Jul. 9, 2012 (now U.S. Pat. No. 8,749,380), which is a continuation of U.S. patent application Ser. No. 13/034,311 filed Feb. 24, 2011 (now U.S. Pat. No. 8,217,788), which is a continuation of U.S. patent application Ser. No. 12/083,726 filed Apr. 16, 2008 (now U.S. Pat. No. 7,911,339), which is a 35 U.S.C. 371 National Phase entry of International Patent Application No. PCT/US2006/040970 filed Oct. 18, 2006, which claims priority to US Provisional Patent Application No. 60/728,031 filed Oct. 18, 2005. All of these earlier applications are incorporated herein by reference.

US Referenced Citations (312)
Number Name Date Kind
3612265 Dickerson Oct 1971 A
3769723 Masterson Nov 1973 A
3807388 Orr et al. Apr 1974 A
3918058 Noyori et al. Nov 1975 A
3958459 Shimomura May 1976 A
3978725 Hadtke Sep 1976 A
4089057 Eriksson May 1978 A
4101873 Anderson et al. Jul 1978 A
4114450 Shulman et al. Sep 1978 A
4125801 Leenhouts Nov 1978 A
4195642 Price et al. Apr 1980 A
4210024 Ishiwatari et al. Jul 1980 A
4223211 Allsen et al. Sep 1980 A
4248244 Charnitski et al. Feb 1981 A
4317126 Gragg Feb 1982 A
4371188 Hull Feb 1983 A
4371945 Karr et al. Feb 1983 A
4375674 Thornton Mar 1983 A
4423630 Morrison Jan 1984 A
4434801 Jiminez et al. Mar 1984 A
4516110 Overmyer May 1985 A
4516865 Hideo May 1985 A
4566461 Lubell et al. Jan 1986 A
4578769 Frederick Mar 1986 A
4603698 Cherniak Aug 1986 A
4625733 Saynajakangas Dec 1986 A
4649552 Yukawa Mar 1987 A
4694694 Vlakancic et al. Sep 1987 A
4699379 Chateau et al. Oct 1987 A
4703445 Dassler Oct 1987 A
4720093 Del Mar Jan 1988 A
4722222 Purdy et al. Feb 1988 A
4736312 Dassler et al. Apr 1988 A
4757453 Nasiff Jul 1988 A
4757714 Purdy et al. Jul 1988 A
4759219 Cobb et al. Jul 1988 A
4763275 Carlin Aug 1988 A
4763284 Carlin Aug 1988 A
4763287 Gerhaeuser et al. Aug 1988 A
4771394 Cavanagh Sep 1988 A
4774679 Carlin Sep 1988 A
4775948 Dial et al. Oct 1988 A
4780837 Namekawa Oct 1988 A
4821218 Potsch Apr 1989 A
4822042 Landsman Apr 1989 A
4824107 French Apr 1989 A
4829812 Parks et al. May 1989 A
4830021 Thornton May 1989 A
4862394 Thompson et al. Aug 1989 A
4862395 Fey et al. Aug 1989 A
4873867 McPherson et al. Oct 1989 A
4876500 Wu Oct 1989 A
4883271 French Nov 1989 A
4903212 Yokouchi et al. Feb 1990 A
4935887 Abdalah et al. Jun 1990 A
4955980 Masuo Sep 1990 A
5033013 Kato et al. Jul 1991 A
5036467 Blackburn et al. Jul 1991 A
5056783 Matcovich et al. Oct 1991 A
5067081 Person Nov 1991 A
5088836 Yamada et al. Feb 1992 A
5144226 Rapp Sep 1992 A
5148002 Kuo et al. Sep 1992 A
5150310 Greenspun et al. Sep 1992 A
5162828 Furness et al. Nov 1992 A
5181181 Glynn Jan 1993 A
5200827 Hanson et al. Apr 1993 A
5243993 Alexander et al. Sep 1993 A
5258927 Havriluk et al. Nov 1993 A
5295085 Hoffacker Mar 1994 A
5316249 Anderson May 1994 A
5324038 Sasser Jun 1994 A
5335664 Nagashima Aug 1994 A
5339699 Carignan Aug 1994 A
5343445 Cherdak Aug 1994 A
5348519 Prince et al. Sep 1994 A
5382972 Kannes Jan 1995 A
5396429 Hanchett Mar 1995 A
5420828 Geiger May 1995 A
5426595 Picard Jun 1995 A
5436838 Miyamori Jul 1995 A
5446775 Wright et al. Aug 1995 A
5450329 Tanner Sep 1995 A
5452269 Cherdak Sep 1995 A
5471405 Marsh Nov 1995 A
5475725 Nakamura Dec 1995 A
5485402 Smith et al. Jan 1996 A
5486815 Wagner Jan 1996 A
5509082 Toyama et al. Apr 1996 A
5513854 Daver May 1996 A
5524637 Erickson Jun 1996 A
5526326 Fekete et al. Jun 1996 A
5528228 Wilk Jun 1996 A
5539336 Nguyen et al. Jul 1996 A
5541604 Meier Jul 1996 A
5546307 Mazur et al. Aug 1996 A
5546974 Bireley Aug 1996 A
5564698 Honey et al. Oct 1996 A
5574669 Marshall Nov 1996 A
5583776 Levi et al. Dec 1996 A
5590908 Carr Jan 1997 A
5592401 Kramer Jan 1997 A
5605336 Gaoiran et al. Feb 1997 A
5615132 Horton et al. Mar 1997 A
5617084 Sears Apr 1997 A
5618995 Otto et al. Apr 1997 A
5627548 Woo et al. May 1997 A
5629131 Keyzer et al. May 1997 A
5633070 Murayama et al. May 1997 A
5636146 Flentov et al. Jun 1997 A
5646857 McBurney et al. Jul 1997 A
5671010 Shimbo et al. Sep 1997 A
5671162 Werbin Sep 1997 A
5673691 Abrams et al. Oct 1997 A
5688183 Sabatino et al. Nov 1997 A
5690119 Rytky et al. Nov 1997 A
5690591 Kenmochi et al. Nov 1997 A
5690773 Fidalgo et al. Nov 1997 A
5694340 Kim Dec 1997 A
5701257 Miura et al. Dec 1997 A
5720200 Anderson et al. Feb 1998 A
5721539 Goetzl Feb 1998 A
5723786 Klapman Mar 1998 A
5724265 Hutchings Mar 1998 A
5734337 Kupersmit Mar 1998 A
5738104 Lo et al. Apr 1998 A
5743269 Okigami et al. Apr 1998 A
5745037 Guthrie et al. Apr 1998 A
5749615 Itson May 1998 A
5761096 Zakutin Jun 1998 A
5771485 Echigo Jun 1998 A
5779576 Smith, III et al. Jul 1998 A
5781155 Woo et al. Jul 1998 A
5790477 Hauke Aug 1998 A
5796338 Mardirossian Aug 1998 A
5807284 Foxlin Sep 1998 A
5812056 Law Sep 1998 A
5862803 Besson et al. Jan 1999 A
5886739 Winningstad Mar 1999 A
5891042 Sham et al. Apr 1999 A
5897457 Mackovjak Apr 1999 A
5899963 Hutchings May 1999 A
5901303 Chew May 1999 A
5905460 Odagiri et al. May 1999 A
5914659 Herman et al. Jun 1999 A
5918281 Nabulsi Jun 1999 A
5918502 Bishop Jul 1999 A
5925001 Hoyt et al. Jul 1999 A
5929335 Carter Jul 1999 A
5930741 Kramer Jul 1999 A
5936523 West Aug 1999 A
5946643 Zakutin Aug 1999 A
5947917 Carte et al. Sep 1999 A
5955667 Fyfe Sep 1999 A
5959568 Woolley Sep 1999 A
5960380 Flentov et al. Sep 1999 A
5963523 Kayama et al. Oct 1999 A
5963891 Walker et al. Oct 1999 A
5976083 Richardson et al. Nov 1999 A
5977877 McCulloch et al. Nov 1999 A
5978972 Stewart et al. Nov 1999 A
5984842 Chu Nov 1999 A
6002982 Fry Dec 1999 A
6009629 Gnepf et al. Jan 2000 A
6011491 Goetzl Jan 2000 A
6013007 Root et al. Jan 2000 A
6018677 Vidrine et al. Jan 2000 A
6018705 Gaudet et al. Jan 2000 A
6020851 Busack Feb 2000 A
6028617 Sawano et al. Feb 2000 A
6028625 Cannon Feb 2000 A
6032084 Anderson et al. Feb 2000 A
6032108 Seiple et al. Feb 2000 A
6032530 Hock Mar 2000 A
6043747 Altenhofen Mar 2000 A
6045364 Dugan et al. Apr 2000 A
6052654 Gaudet et al. Apr 2000 A
6057756 Engellenner May 2000 A
6059576 Brann May 2000 A
6073086 Marinelli Jun 2000 A
6074271 Derrah Jun 2000 A
6075443 Schepps et al. Jun 2000 A
4745564 Tennes et al. Jul 2000 B2
6091342 Janesch et al. Jul 2000 A
6111541 Karmel Aug 2000 A
6111571 Summers Aug 2000 A
6122340 Darley et al. Sep 2000 A
6122959 Hoshal et al. Sep 2000 A
6122960 Hutchings et al. Sep 2000 A
6125686 Haan et al. Oct 2000 A
6127931 Mohr Oct 2000 A
6135951 Richardson et al. Oct 2000 A
6148271 Marinelli Nov 2000 A
6151647 Sarat Nov 2000 A
6157898 Marinelli Dec 2000 A
6160254 Zimmerman et al. Dec 2000 A
6163021 Mickelson Dec 2000 A
6167356 Squadron et al. Dec 2000 A
6183425 Whalen et al. Feb 2001 B1
6195921 Truong Mar 2001 B1
6196932 Marsh et al. Mar 2001 B1
6204813 Wadell et al. Mar 2001 B1
6212427 Hoover Apr 2001 B1
6226622 Dabbiere May 2001 B1
6238338 DeLuca et al. May 2001 B1
6245002 Beliakov Jun 2001 B1
6249487 Yano et al. Jun 2001 B1
6254513 Takenaka et al. Jul 2001 B1
6263279 Bianco et al. Jul 2001 B1
6266623 Vock et al. Jul 2001 B1
6305221 Hutchings Oct 2001 B1
6356856 Damen et al. Mar 2002 B1
6357147 Darley et al. Mar 2002 B1
6360597 Hubbard, Jr. Mar 2002 B1
6385473 Haines et al. May 2002 B1
6436052 Nikolic et al. Aug 2002 B1
6441747 Khair et al. Aug 2002 B1
6456261 Zhang Sep 2002 B1
6459881 Hoder et al. Oct 2002 B1
6463385 Fry Oct 2002 B1
6493652 Ohlenbusch et al. Dec 2002 B1
6498994 Vock et al. Dec 2002 B2
6499000 Flentov et al. Dec 2002 B2
6501393 Richards et al. Dec 2002 B1
6504483 Richards et al. Jan 2003 B1
6516284 Flentov et al. Feb 2003 B2
6527711 Stivoric et al. Mar 2003 B1
6529131 Wentworth Mar 2003 B2
6531982 White et al. Mar 2003 B1
6539336 Vock et al. Mar 2003 B1
6560903 Darley May 2003 B1
6563417 Shaw May 2003 B1
6570526 Noller et al. May 2003 B1
6571193 Unuma et al. May 2003 B1
6582342 Kaufman Jun 2003 B2
6595929 Stivoric et al. Jul 2003 B2
6600418 Francis et al. Jul 2003 B2
6605038 Teller et al. Aug 2003 B1
6606556 Curatolo et al. Aug 2003 B2
6611782 Wooster et al. Aug 2003 B1
6611789 Darley Aug 2003 B1
6614349 Proctor et al. Sep 2003 B1
6617962 Horwitz et al. Sep 2003 B1
6619835 Kita Sep 2003 B2
6633743 Berlinsky Oct 2003 B1
6643608 Hershey et al. Nov 2003 B1
6714121 Moore Mar 2004 B1
6716139 Hosseinzadeh-Dolkhani et al. Apr 2004 B1
6735630 Gelvin et al. May 2004 B1
6748902 Boesch et al. Jun 2004 B1
6790178 Mault et al. Sep 2004 B1
6793607 Neil Sep 2004 B2
6813586 Vock et al. Nov 2004 B1
6825777 Vock et al. Nov 2004 B2
6856934 Vock et al. Feb 2005 B2
6883694 Abelow Apr 2005 B2
6885971 Vock et al. Apr 2005 B2
6898550 Blackadar et al. May 2005 B1
6900732 Richards May 2005 B2
6959259 Vock et al. Oct 2005 B2
6963818 Flentov et al. Nov 2005 B2
6968179 De Vries Nov 2005 B1
7009517 Wood Mar 2006 B2
7016687 Holland Mar 2006 B1
7020508 Stivoric et al. Mar 2006 B2
7030735 Chen Apr 2006 B2
7042360 Light et al. May 2006 B2
7054784 Flentov et al. May 2006 B2
7062225 White Jun 2006 B2
7064669 Light et al. Jun 2006 B2
7072789 Vock et al. Jul 2006 B2
7092846 Vock et al. Aug 2006 B2
7171331 Vock et al. Jan 2007 B2
7174277 Vock et al. Feb 2007 B2
7200517 Darley et al. Apr 2007 B2
7219067 McMullen et al. May 2007 B1
7251454 White Jul 2007 B2
7278966 Hjelt et al. Oct 2007 B2
7285090 Stivoric et al. Oct 2007 B2
7292867 Werner et al. Nov 2007 B2
7299195 Tawakol et al. Nov 2007 B1
7454002 Gardner et al. Nov 2008 B1
7455621 Anthony Nov 2008 B1
7519327 White Apr 2009 B2
7618345 Corbalis et al. Nov 2009 B2
7670263 Ellis et al. Mar 2010 B2
7911339 Vock Mar 2011 B2
8217788 Vock Jul 2012 B2
8749380 Vock Jun 2014 B2
9578927 Vock Feb 2017 B2
9968158 Vock et al. May 2018 B2
10376015 Vock Aug 2019 B2
20010049890 Hirsch et al. Dec 2001 A1
20020070862 Francis et al. Jun 2002 A1
20020077784 Vock et al. Jun 2002 A1
20020107033 Kim Aug 2002 A1
20020121975 Struble et al. Sep 2002 A1
20030014210 Vock et al. Jan 2003 A1
20030050211 Hage et al. Mar 2003 A1
20030065805 Barnes Apr 2003 A1
20030093248 Vock et al. May 2003 A1
20030097878 Farringdon et al. May 2003 A1
20030163287 Vock et al. Aug 2003 A1
20040104845 McCarthy Jun 2004 A1
20040177531 DiBenedetto Sep 2004 A1
20040253642 Zimmermann et al. Dec 2004 A1
20050113650 Pacione et al. May 2005 A1
20050172311 Hjelt et al. Aug 2005 A1
20050177929 Greenwald et al. Aug 2005 A1
20060030335 Zellner et al. Feb 2006 A1
20060152377 Beebe Jul 2006 A1
20070011919 Case, Jr. Jan 2007 A1
Foreign Referenced Citations (17)
Number Date Country
10325805 Jan 2005 DE
0336782 Oct 1989 EP
0917893 May 1999 EP
1292217 Nov 2005 EP
1292218 Apr 2006 EP
1567238 May 1980 GB
2137363 Oct 1984 GB
03-152469 Jun 1991 JP
2000-122044 Apr 2000 JP
2001-321202 Nov 2001 JP
2002-101908 Apr 2002 JP
9806466 Feb 1998 WO
9854581 Dec 1998 WO
0051259 Aug 2000 WO
0078170 Dec 2000 WO
0101706 Jan 2001 WO
02093272 Nov 2002 WO
Non-Patent Literature Citations (150)
Entry
U.S. Appl. No. 09/992,966, Notice of Allowance dated Sep. 3, 2004.
U.S. Appl. No. 09/992,966, Office Action dated Jan. 6, 2004.
U.S. Appl. No. 09/992,966, Office Action dated Jul. 18, 2003.
U.S. Appl. No. 09/992,966, Office Action dated Mar. 28, 2002.
U.S. Appl. No. 09/992,966, Response to Office Action dated Feb. 3, 2003.
U.S. Appl. No. 09/992,966, Response to Office Action dated Jan. 6, 2004.
U.S. Appl. No. 09/992,966, Response to Office Action dated Jul. 18, 2003.
U.S. Appl. No. 09/992,966, Response to Office Action dated Mar. 28, 2002.
U.S. Appl. No. 09/992,966, Office Action dated Feb. 3, 2003.
U.S. Appl. No. 10/234,660, Dec. 23, 2003 Response to Office Action dated Oct. 31, 2003.
U.S. Appl. No. 10/234,660, Final Office Action dated Oct. 31, 2003.
U.S. Appl. No. 10/234,660, Response to Office Action dated Mar. 31, 2003.
U.S. Appl. No. 10/234,660; Advisory Action dated Jan. 27, 2004.
U.S. Appl. No. 10/234,660; Amendment filed Jul. 20, 2004.
U.S. Appl. No. 10/234,660; Appeal Brief filed Jun. 14, 2004.
U.S. Appl. No. 10/234,660; Marked up Claims by USPTO dated Jul. 28, 2004.
U.S. Appl. No. 10/234,660; Notice of Allowance; dated Aug. 2, 2004. U.S. Appl. No. 10/297,270 Office Action dated Jul. 29, 2004.
U.S. Appl. No. 10/234,660, Office Action dated Mar. 31, 2003.
U.S. Appl. No. 10/297,270 Office Action dated Dec. 13, 2004.
U.S. Appl. No. 10/297,270 Office Action dated Feb. 9, 2006.
U.S. Appl. No. 10/297,270 Office Action dated Jan. 11, 2007.
U.S. Appl. No. 10/297,270 Office Action dated Jul. 13, 2005.
U.S. Appl. No. 10/297,270 Office Action dated Jul. 26, 2007.
U.S. Appl. No. 10/297,270 Request Deletion of Named Inventors Pursuant to 37 CFR .sctn. 1.63 (d)(2) received by thePatent Office on Oct. 4, 2002.
U.S. Appl. No. 10/297,270 Response to Office Action dated Feb. 9, 2006.
U.S. Appl. No. 10/297,270 Response to Office Action dated Jan. 11, 2007.
U.S. Appl. No. 10/297,270 Response to Office Action dated Jul. 13, 2005.
U.S. Appl. No. 10/297,270 Response to Office Action dated Jul. 26, 2007.
U.S. Appl. No. 10/297,270 Response to Office Action dated Jul. 29, 2004.
U.S. Appl. No. 10/297,270 Response to Office Action dated Sep. 25, 2006.
U.S. Appl. No. 10/297,270 Office Action dated Sep. 25, 2006.
U.S. Appl. No. 10/297,270 Response to Office Action dated Dec. 13, 2004.
U.S. Appl. No. 10/601,208 Notice of Allowance dated Dec. 8, 2006.
U.S. Appl. No. 10/601,208 Office Action dated Aug. 26, 2004.
U.S. Appl. No. 10/601,208 Office Action dated Feb. 15, 2006.
U.S. Appl. No. 10/601,208 Office Action dated Jun. 15, 2004.
U.S. Appl. No. 10/601,208 Office Action dated May 11, 2005.
U.S. Appl. No. 10/601,208 Office Action dated Sep. 26, 2006.
U.S. Appl. No. 10/601,208 Preliminary Amendment, dated Jun. 20, 2003.
U.S. Appl. No. 10/601,208 Response to Office Action dated Aug. 26, 2004.
U.S. Appl. No. 10/601,208 Response to Office Action dated Feb. 15, 2006.
U.S. Appl. No. 10/601,208 Response to Office Action dated Jun. 15, 2004.
U.S. Appl. No. 10/601,208 Response to Office Action dated May 11, 2005.
U.S. Appl. No. 10/601,208 Response to Office Action dated Sep. 26, 2006.
U.S. Appl. No. 10/601,208 Second Response to Office Action dated Aug. 26, 2004.
U.S. Appl. No. 10/842,947, Notice of Allowance dated Feb. 9, 2006.
U.S. Appl. No. 10/842,947, Office Action dated Nov. 30, 2004.
U.S. Appl. No. 10/842,947, Preliminary Amendment dated May 11, 2004.
U.S. Appl. No. 10/842,947, Response to Office Action dated Jun. 30, 2005.
U.S. Appl. No. 10/842,947, Response to Office Action dated Nov. 30, 2004.
Cole, George, “The Little Label with an Explosion of Applications”, Financial Times, Ltd., 2002, pp. 1-3.
Deem, “Fast Forward Go for a Ride on the World's Fastest Sailboat”, Popular Mechanics, www.popularmechanics.com, Feb. 2001, pp. 1-2.
Desmarais et al., “How to select and use the right temperature,” www.sensorsmag.com, Jan. 2001, pp. 30-36.
Desmarais, “Solutions in Hand”, BEI Technologies, Inc., www.sensormag.com, Jan. 2001, pp. 1-2.
Gerhauser et al, “The Electronic Shoe⋅ for Jogging, Sports and Reconvalescence”, 3 pages, 1989 IEEE.
GPS Locator for Children, Klass Kids Foundation Jul. 15, 2004.
Henkel, Research & Developments, Sensors, Nov. 2000. p. 18.
Janssens et al., “Columbus: A Novel Sensor System for Domestic Washing Machines”, Sensors Magazine Online, Jun. 2002, pp. 1-9.
Licking, Special Report: E-Health, “This is the Future of Medicine”, Business Week E. Biz, Dec. 11, 2000, pp. 77 and 78, US.
Li-Ron, Tomorrow's Cures, Health & Fitness Special Section Online, Newsweek, Dec. 10, 2001, pp. 3-10.
Mark of Fitness Flyer, “High Quality, Self-Taking Blood Pressure Monitors”, four pages, Shrewsbury, NJ, US, dated prior to Feb. 24, 2011.
Martella, Product News, “Temperature Monitoring System”, Nov. 2000, p. 77.
No author listed, “Ever Forget to Bring Your Cell Phone or Keys?”, Catalog Page, PI Manufacturing Corp, 20732Currier Rd., Walnut, CA 91789, Home Office Accessory, Catalog Nos. TA-100N; TA-100M; TA-100F, US.
No author listed, The GPS Connection, Popular Mechanics, Feb. 2001, p. 65.
No author listed, WarmMark Time Temperature Indicators, www.coldice.com/warmmark.sub.-temperature.sub.-indicators.html, Cold Ice., Inc., 3 pages, Nov. 20, 2000.
No author listed, Wireless Temperature Monitor, www.echo-on.nel/mob/, 1 page, Nov. 20, 2000.
No author listed. “Your Next . . . ” Newsweek, Jun. 25, 2001, p. 52 US.
Nobbe. “Olympic Athletes Get a Boost from Technology”, Machine Design, vol. 60, No. 19, Aug. 25, 1988.
Office Action dated Mar. 26, 2009, issued in U.S. Appl. No. 11/746,863, filed May 10, 2007.
Paradiso et al., Design and Implementation of Expressive Footwear, May 12, 2000, IBM Systems Journal, val. 39, Nos. 3 & 4, pp. 511-529.
Paradiso, et al. “Instrumented Footwear for Interactive Dance” Version 1.1, Presented at the XII Colloquium on Musical Informatics, Gorizia, Italy, Sep. 24-26, 1998, pp. 1-4.
Sellers. Gear to Go, Mitch Mandel Photography, Mar. 2001, pp. 61-62.
Shannon P. Jackson and Harold Kirkham, “Weighing Scales Based on Low-Power Strain-Gauge Circuits”, NASA Tech Briefs, Jun. 2001, p. 49 US.
Sharp, A Sense of the Real World, www.idsystems.com/reader/2000.sub.--09/sens0900.htm, Sep. 2000,4 pages.
Skaloud et al., DGPS—Calibrated Accelerometric System for Dynamic Sports Events, Sep. 19-22, 2000, ION GPS2000.
Smith et al., “Flexible and Survivable Non-Volatile Memory Data Recorder”, AFRL Technology Horizons, Dec. 2000, p. 26.
U.S. Appl. No. 09/089,232, Appeal Brief mailed Jul. 26, 2002.
U.S. Appl. No. 09/089,232, Comments on Allowance dated Oct. 16, 2002.
U.S. Appl. No. 09/089,232, Notice of Allowance dated Oct. 2, 2002.
U.S. Appl. No. 09/089,232, Office Action dated Apr. 26, 2002.
U.S. Appl. No. 09/089,232, Office Action dated Jan. 27, 2003.
U.S. Appl. No. 09/089,232, Appeal Brief mailed Jan. 2, 2002.
U.S. Appl. No. 09/698,659, Notice of Allowance dated Apr. 9, 2003.
U.S. Appl. No. 09/698,659, Office Action dated Mar. 19, 2002.
U.S. Appl. No. 09/698,659, Office Action dated Nov. 21, 2002.
U.S. Appl. No. 09/698,659, Response to Office Action dated Mar. 19, 2002.
U.S. Appl. No. 09/698,659, Response to Office Action dated Nov. 21, 2002.
U.S. Appl. No. 09/848,445, Office Action dated Dec. 5, 2003.
U.S. Appl. No. 09/848,445, Office Action dated May 6, 2004.
U.S. Appl. No. 09/848,445, Response to Office Action (Rule 116) dated May 6, 2004.
U.S. Appl. No. 09/848,445, Response to Office Action dated Dec. 5, 2003.
U.S. Appl. No. 09/848,445, Preliminary Amendment dated Dec. 5, 2001.
U.S. Appl. No. 09/886,578, Notice of Allowance dated Sep. 9, 2002.
U.S. Appl. No. 09/886,578, Office Action dated Jun. 5, 2002.
U.S. Appl. No. 09/886,578, Office Action dated Nov. 8, 2001.
U.S. Appl. No. 09/886,578, Preliminary Amendment dated Jun. 21, 2001.
U.S. Appl. No. 09/886,578, Response to Office Action dated Jun. 5, 2002.
U.S. Appl. No. 09/886,578, Response to Office Action dated Nov. 8, 2001.
U.S. Appl. No. 09/992,966, Examiner Summary dated Oct. 27, 2003.
U.S. Appl. No. 09/992,966, Notice of Allowance dated Apr. 15, 2004.
U.S. Appl. No. 10/842,947, Office Action dated Jun. 30, 2005.
U.S. Appl. No. 10/921,743; Advisory dated Nov. 25, 2005.
U.S. Appl. No. 10/921,743; Notice of Allowance; dated Feb. 16, 2006.
U.S. Appl. No. 10/921,743; Office Action dated Mar. 4, 2005.
U.S. Appl. No. 10/921,743; Office Action dated May 26, 2005.
U.S. Appl. No. 10/921,743; Office Action dated Sep. 13, 2005.
U.S. Appl. No. 10/921,743; Response to Office Action dated Mar. 4, 2005.
U.S. Appl. No. 10/921,743; Response to Office Action dated May 26, 2005.
U.S. Appl. No. 10/921,743; Response to Office Action dated Sep. 13, 2005 and Advisory dated Nov. 25, 2005.
U.S. Appl. No. 10/950,897, Amendment to Notice of Allowance dated Dec. 13, 2005.
U.S. Appl. No. 10/950,897, Office Action dated Jun. 23, 2005.
U.S. Appl. No. 10/950,897, Office Action dated Mar. 7, 2005.
U.S. Appl. No. 10/950,897, Office Action dated Nov. 25, 2005.
U.S. Appl. No. 10/950,897, Office Action dated Sep. 9, 2005.
U.S. Appl. No. 10/950,897, Response to Office Action dated Jun. 23, 2005.
U.S. Appl. No. 10/950,897, Response to Office Action dated Mar. 7, 2005.
U.S. Appl. No. 10/950,897, Response to Office Action dated Nov. 25, 2005.
U.S. Appl. No. 10/950,897, Response to Office Action dated Sep. 9, 2005.
U.S. Appl. No. 10/950.897, Notice of Allowance dated Feb. 13, 2005.
U.S. Appl. No. 11/434,588: Office Action dated Jan. 31, 2007.
U.S. Appl. No. 11/434,588; Notice of Allowance; dated Jul. 11, 2007.
U.S. Appl. No. 11/434,588; Response to Office Action dated Jan. 31, 2007.
U.S. Appl. No. 11/221,029; Preliminary Amendment dated Aug. 22, 2006.
U.S. Appl. No. 11/221,029; Notice of Allowance; dated Oct. 3, 2006.
U.S. Appl. No. 11/221,029; Office Action dated Sep. 8, 2006.
U.S. Appl. No. 11/221,029; Response to Office Action dated Sep. 8, 2006.
U.S. Appl. No. 11/252,576; Notice of Allowance; dated Dec. 11, 2007.
U.S. Appl. No. 11/358,508, Notice of Allowability & Interview Summary dated Oct. 18, 2006.
U.S. Appl. No. 11/358,508, Preliminary Amendment dated Jul. 26, 2006.
U.S. Appl. No. 11/358,508, Preliminary Amendment dated Mar. 30, 2006.
U.S. Appl. No. 11/358,508, Response to Notice dated Sep. 12, 2006.
U.S. Appl. No. 11/358,508, Response to Office Action dated Aug. 14, 2006.
U.S. Appl. No. 11/358,508, Rule 312 Amendment dated Oct. 24, 2006.
U.S. Appl. No. 11/358,508. Notice of Non Compliance Amendment dated Sep. 12, 2006.
U.S. Appl. No. 11/358,508, Office Action dated Aug. 14, 2006.
U.S. Appl. No. 11/434,588; Notice of Allowance; dated Nov. 6, 2007.
U.S. Appl. No. 11/484,199 Preliminary Amendment; dated Sep. 7, 2006.
U.S. Appl. No. 11/484,199 Notice of Allowance and Examiner Interview Summary; dated Oct. 6, 2006.
U.S. Appl. No. 11/598,410 Response to Office Action dated Jun. 13, 2007.
U.S. Appl. No. 11/598,410, Notice of Allowability dated Sep. 26, 2007.
U.S. Appl. No. 11/598,410, Office Action dated Jun. 13, 2007.
U.S. Appl. No. 11/646,768, Office Action dated May 7, 2007.
U.S. Appl. No. 11/646,768, Office Action dated Oct. 29, 2007.
U.S. Appl. No. 11/646,768, Response to Office Action dated May 7, 2007.
U.S. Appl. No. 11/646,768, Response to Office Action dated Oct. 29, 2007.
U.S. Appl. No. 11/646,768; Notice of Allowance; dated Jan. 18, 2008.
U.S. Appl. No. 11/747,081; Office Action dated Jan. 24, 2008.
Unattributed, 3M MonitorMark Indicator Data Sheet [online), [retrieved on Aug. 9, 2004], retrieved from the Internet: URL: http://www.3m.com/us/healthcare/medicalspecialties/monitor/products.html; 4 pages.
Webster's II New Riverside University Dictionary, 1988, The Riverside Publishing Company, p. 1138.
Wysocki, Jr., Staff Reporter, “Do Devices Measuring Body Signs Appeal to the Sick or Healthy”, Pittsburgh, US, 2 pages, dated prior to Feb. 24, 2011.
Related Publications (1)
Number Date Country
20190350306 A1 Nov 2019 US
Provisional Applications (1)
Number Date Country
60728031 Oct 2005 US
Continuations (6)
Number Date Country
Parent 15972959 May 2018 US
Child 16525875 US
Parent 15443392 Feb 2017 US
Child 15972959 US
Parent 14298454 Jun 2014 US
Child 15443392 US
Parent 13544733 Jul 2012 US
Child 14298454 US
Parent 13034311 Feb 2011 US
Child 13544733 US
Parent 12083726 US
Child 13034311 US