Abstract
The aim of the present study is to obtain models
for estimating energy expenditure based
on the heart rates of people with spinal cord
injury without requiring individual calibration.
A cohort of 20 persons with spinal cord injury
performed a routine of 10 activities while their
breath-by-breath oxygen consumption and heart
rates were monitored. The minute-by-minute
oxygen consumption collected from minute 4 to
minute 7 was used as the dependent variable. A
total of 7 features extracted from the heart rate
signals were used as independent variables. 2
mathematical models were used to estimate the
oxygen consumption using the heart rate: a multiple linear model and an artificial neural network. We determined that the neural network provided a better estimation than the multiple linear
model. The goodness of fit was similar to previous reported linear
models involving individual calibration. In conclusion,
we have validated the use of the heart
rate to estimate oxygen consumption in paraplegic
persons without individual calibration and,
under this constraint, we have shown that the artificial neural network is the mathematical tool
that provides the better estimation.
