Surgery – Diagnostic testing – Cardiovascular
Reexamination Certificate
1998-11-20
2001-08-21
Evanisko, George R. (Department: 3762)
Surgery
Diagnostic testing
Cardiovascular
C600S484000, C128S925000
Reexamination Certificate
active
06277080
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The invention relates to a method for measuring exercise condition, especially to a method for providing an exertion endurance indicator representing an exercise condition of a subject to be measured, such as maximal oxygen uptake or any such exertion endurance indicator representing an exercise condition.
The invention further relates to an apparatus for measuring exercise condition, especially to an apparatus for measuring an exertion endurance indicator representing an exercise condition of a subject to be measured, such as maximal oxygen uptake or any such exertion endurance indicator representing physical fitness.
2. Description of the Prior Art
Condition classification representing exercise exertion based on measuring maximal oxygen uptake is used as an indicator of physical exercise condition that is, exertion endurance, for example to measure human physical performance, such as exertion endurance.
Prior art solutions for determining and measuring an exercise condition are either direct exertion measurement or indirect measurement. In direct exertion measurement, the maximal oxygen uptake ability is measured directly from respiratory gases under maximum exertion by means of a running mat or a bicycle ergometer, for example. In indirect measurement, the work performed is measured within a specific period of time, such as in so-called Cooper test where a distance run during 12 minutes is measured. In both known methods the measurement of exercise condition takes place by measuring an active performance, wherefore these methods are laborious, difficult and expensive to arrange in order to determine condition. Average resting heartbeat is considered to be one indicator of condition, but it does not give reliable results as the correlation of resting heartbeat to maximal oxygen uptake ability is only at the rate of 0.4 to 0.45. Other heartbeat parameters also do not attain better correlations to maximal oxygen uptake ability.
OBJECTS AND SUMMARY OF THE INVENTION
An object of the present invention is to provide a new method that will avoid the problems associated with prior art methods.
This object is attained in accordance with a method of the invention in which a calculation formula obtained by means of a neural network is used for measuring an exertion endurance indicator representing an exercise condition, to which formula input parameters representing the subject to be measured are supplied. Such input parameters comprise at least one or more of the following physiological parameters: sex, age, height, weight. One or more output parameters representing the exertion endurance indicator representing the fitness of the subject to be measured are obtained from the calculation formula. The neural network construction used for formulating the calculation formula is trained with a sufficiently large number of real measuring results comprising similar input parameters and one or more similar output parameters. In addition to the physiological parameters, one or more resting heartbeat parameters measured specifically from resting heartbeat are used as the input parameters of the calculation formula. Similar resting heartbeat parameters are used in the training of the neural network used in formulating the calculation formula of the exertion endurance indicator representing an exercise condition.
This object is attained in a second embodiment of the present invention using the method of the invention. In accordance with the method, physiological input parameters representing the subject to be measured are supplied to a predetermined calculation formula, the input parameters comprising at least one or more of the following physiological parameters, such as sex, age, height, weight. From the calculation formula, one or more output parameters representing the exertion endurance indicator, such as maximal oxygen uptake ability or any other such exertion endurance indicator representing the exercise condition of the subject to be measured, are obtained. In addition to the physiological parameters, one or more resting heartbeat parameters measured from resting heartbeat are used as input parameters of the calculation formula
An apparatus according to the invention comprises means for detecting resting heartbeat and sending resting heartbeat data to a calculation unit. Means are provided for supplying physiological parameters representing the subject to the calculation unit. The calculation unit generates an exertion endurance signal representing an exercise condition, such as maximal oxygen uptake ability, condition classification or any such physical condition indicator based on the physiological parameters and resting heartbeat data supplied to it. A display and/or a memory are provided for indicating and/or storing the physical condition data.
The method and apparatus of the invention are based on the idea that resting heartbeat parameters are used as input data of exercise exertion endurance, and a calculation formula predetermined preferably by means of a neural network is used. Resting heartbeat parameters and human physical parameters are supplied to the formula as input data and maximal oxygen uptake (for example) is calculated as output data representing human physical condition, that is, exertion endurance. In formulating the calculation formula, the neural network, if used, would be trained by corresponding data by using an extensive real measurement material. Different parameters of a person's heartbeat and heartbeat variation measured during a few minutes are needed as measurement data and, in addition to the parameters obtained from their heartbeat, human physical measurement parameters, such as weight, height, age and sex, are utilized. The data measured from resting heartbeat and personal pre-data are provided to the calculation formula as supply data. When determining the calculation formula by a neural network, different rules have been made by means of fuzzy logic, that is, the effect of different variables or variable combinations on the end result is made fuzzy. The calculation formula determined by means of the neural network calculates by weightings obtained on the basis of training material the maximal uptake ability of a person from the new supply data and determines a corresponding condition class.
Neural networks are known per se, and they have been used previously for measuring a patient's condition of health, the seriousness of a person's infarct, the risk of death for elderly persons or a person's blood pressure. These solutions have been disclosed for example in EP-555591.
DE-4307545 further discloses an apparatus that determines the location and the extent of a person's infarct. This apparatus employs multi-channel EKG measurement, and infarct determination is based on the trained use and classification of neural network construction in the apparatus.
EP-650742 discloses an apparatus which controls a pacemaker, i.e. a defibrillator by means of a neural network. This apparatus measures the EKG curve, compares it to the data bank and decides if a pacemaker pulse is needed.
WO-92/03094 discloses an apparatus in which a patient's heart is diagnosed by means of heart sounds by using a neural network construction.
U.S. Pat. No. 5,251,626 discloses an apparatus for detecting and classifying arrhythmias which is similar to that in EP 650742 cited above.
U.S. Pat. No. 5,280,792 discloses an apparatus for detecting and classifying arrhythmias that is similar to what is disclosed in EP 650742 and U.S. Pat. No. 5,251,626 cited above.
DE-4338958 discloses an apparatus and a method for determining a person's optimal exercise heartbeat. In this solution an optimal exercise heartbeat is determined by using an iterative method where first an initial heartbeat level/load is determined by using known formulae and then heartbeat level under load is measured. The difference between assumed and measured heartbeat level is used to optimize the correct heartbeat level/load level. The result
Nissila Seppo
Röning Juha
Ruha Antti
Väinämö Kauko
Evanisko George R.
Hoffman & Baron LLP
Polar Electro OY
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