Analyzing physiological state for fitness exercise

US10507358B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-10507358-B2
Application numberUS-201113177610-A
CountryUS
Kind codeB2
Filing dateJul 7, 2011
Priority dateJul 12, 2010
Publication dateDec 17, 2019
Grant dateDec 17, 2019

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Abstract

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A method, apparatus, and a computer program for monitoring a fitness exercise are described. A plurality of heart-rate variability values and a plurality of exertion parameter values are measured during an exercise measured. The heart rate variability values correlate with the exertion parameter values through a human physiological mechanism, and the exertion parameter values characterize the physical exertion of the exercise. A mathematical correspondence is then constructed from the plurality of measured heart rate variability values and associated exertion parameter values. The mathematical correspondence describes correlation between the heart rate variability values and the exertion parameter values and the user's physiological state during the exercise. Then, the physical exertion of the exercise is monitored by applying the mathematical correspondence.

First claim

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What is claimed is: 1. An apparatus that processes exercise-related measurement data, the apparatus comprising: exercise-related parameter measurement circuitry; at least one biometric sensor comprising at least one heart activity sensor; and a processor configured to cause the apparatus to perform operations comprising: acquiring a plurality of heart rate variability values and a plurality of exertion parameter values measured by the at least one heart activity sensor during an exercise using the exercise-related parameter measurement circuitry, wherein the heart rate variability values represent a measure of variation in heart beat intervals and correlate with the exertion parameter values through a human physiological mechanism, and wherein the exertion parameter values characterize physical exertion of the exercise; constructing a mathematical correspondence from the plurality of measured heart rate variability values and associated exertion parameter values, the mathematical correspondence describing correlation between the heart rate variability values and the exertion parameter values and describing the user's physiological state during the exercise; determining an overall training effect of the exercise by computing, for each of a plurality of exertion level zones, from the mathematical correspondence, a factor characterizing a training effect at that exertion level zone in the user's physiological state during the exercise and determining the overall training effect of the exercise by using the factors, said computing the factor for each of the plurality of exertion level zones comprising: a) assigning, when the mathematical correspondence indicates that the user is tired or exhausted, a higher weight to lower exertion level zones than to higher exertion level zones to provide a better training effect on the lower exertion level zones than on the higher exertion level zones; and b) assigning, when the mathematical correspondence indicates that the user is well rested, an equal weighting to all exertion level zones; and outputting the overall training effect of the exercise to the user. 2. The apparatus of claim 1 , wherein the operations further comprise monitoring the physical exertion of the exercise by adapting ranges of the plurality of exertion level zones of the exercise to the mathematical correspondence, wherein the ranges of the exertion level zones are defined as exertion parameter values. 3. The apparatus of claim 2 , wherein the operations further comprise initializing an exercise profile comprising a plurality of said exertion level zones with different ranges defined as initial values of the exertion parameter values; and changing a range of at least one exertion level zone by changing at least one initial value of the exertion parameter value of said at least one exertion level zone on the basis of the constructed mathematical correspondence. 4. The apparatus of claim 2 , wherein the apparatus further comprises a user interface comprising a display unit, and wherein the operations further comprise causing the apparatus to display at least one range of the plurality of exertion level zones to the user. 5. The apparatus of claim 2 , wherein the operations further comprise adapting the range of the at least one exertion level zone by acquiring, using the mathematical correspondence, an adapted exertion parameter value associated with a predetermined different heart rate variability value, which has not been measured from the user, and using the adapted exertion parameter value to define the range, and by setting the exertion parameter value as an upper limit or a lower limit of the at least one exertion level zone. 6. The apparatus of claim 1 , wherein said exertion parameter level includes a level of at least one of the following exertion parameters: heart rate, speed of motion, pedaling power, and motion intensity. 7. The apparatus of claim 1 , wherein the operations further comprise causing the apparatus to construct the mathematical correspondence by providing a plurality of different candidate mathematical correspondence models, by determining correlation between the acquired heart-rate variability values and said plurality of different candidate mathematical correspondence models, and by selecting a mathematical correspondence model having the highest correlation with the acquired heart-rate variability values. 8. The apparatus of claim 1 , wherein the apparatus further comprises a user interface comprising a display unit, and wherein the operations further comprise causing the apparatus to input an exertion parameter value, and to display the exertion parameter value to the user along with a reference exertion parameter value obtained from the mathematical correspondence. 9. The apparatus of claim 1 , wherein the operations further comprise causing the apparatus to monitor the physical exertion of the exercise by determining a target heart rate variability value or a target heart rate variability range for the exercise, by obtaining, from the mathematical correspondence, a target exertion parameter level or range corresponding to the target heart rate variability value or range, and by instructing the user to achieve the target exertion parameter level or range. 10. The apparatus of claim 1 , wherein the apparatus further comprises: a memory module configured to store the overall training effect; and processing circuitry configured to adapt at least one of the plurality of exertion level zones based on the stored overall training effect, and to generate an output indicating adaptation of the at least one of the plurality of exertion level zones based on the stored overall training effect. 11. A computer program product embodied on a non-transitory distribution medium comprising a set of computer program instructions that, when executed by a processor, cause the processor to perform operations comprising: acquiring a plurality of heart rate variability values and a plurality of exertion parameter values measured by at least one heart activity sensor during an exercise using exercise-related parameter measurement circuitry, wherein the heart rate variability values represent a measure of variation in heart beat intervals and correlate with the exertion parameter values through a human physiological mechanism, and wherein the exertion parameter values characterize physical exertion of the exercise; constructing a mathematical correspondence from the plurality of measured heart rate variability values and associated exertion parameter values, the mathematical correspondence describing correlation between the heart rate variability values and the exertion parameter values and describing the user's physiological state during the exercise; determining an overall training effect of the exercise by computing, for each of a plurality of exertion level zones, from the mathematical correspondence, a factor characterizing a training effect at that exertion level zone in the user's physiological state during exercise and determining the overall training effect of the exercise by using the factors, said computing the factor for each of the plurality of exertion level zones comprising: a) assigning, when the mathematical correspondence indicates that the user is tired or exhausted, a higher weight to lower exertion level zones than to higher exertion level zones; and b) assigning, when the mathematical correspondence indicates that the user is well rested, an equal weighting to all exertion level zones; and outputting the overall training effect of the exercise to the user. 12. A method of processing exercise-related measurement data in an apparatus, the met

Assignees

Inventors

Classifications

  • relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising · CPC title

  • heartbeat characteristics, e.g. ECG, blood pressure modulations · CPC title

  • Comparison to target or threshold, previous performance or not real time comparison to other individuals · CPC title

  • combined with detection or measurement of physiological parameters, e.g. heart rate · CPC title

  • Absolute positions, e.g. by using GPS · CPC title

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What does patent US10507358B2 cover?
A method, apparatus, and a computer program for monitoring a fitness exercise are described. A plurality of heart-rate variability values and a plurality of exertion parameter values are measured during an exercise measured. The heart rate variability values correlate with the exertion parameter values through a human physiological mechanism, and the exertion parameter values characterize the p…
Who is the assignee on this patent?
Kinnunen Hannu, Haataja Jarkko, Posio Tero, and 1 more
What technology area does this patent fall under?
Primary CPC classification A63B24/0062. Mapped technology areas include Human Necessities.
When was this patent published?
Publication date Tue Dec 17 2019 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).