Abstract:
|
The study aims to assess the changes in Heart Rate
Variability (HRV) indexes in healthy subjects whi
le
driving in a real environment in order to detect
drowsiness. The ECG of ten professional drivers was
acquired while driving on routes familiar to the subjects.
RR time series were quantified using a sliding window of
300 beats. Mean (mRR), standard devi
ation (SDNN),
standard deviation of the differentiated time series
(rmsDD), power of the low (PLF) and high (PHF)
frequency bands as well as the ratio LF/HF were
computed. In addition, the median frequency of the power
spectrum (MEDF), the bandwidth that c
ontains the 50%
of the power (BW50) and a measure of the asymmetry of
the spectrum (AFS) were obtained. Moreover, the Hurst
exponent estimated by fractional differintegration (HFDI)
and the short scaling exponent obtained by detrended
fluctuation analysis
(α
1
) were computed. Two observers
classified the state of the drivers minute by minute by
inspection of video recordings as alert or drowsy driver.
Five subjects were alert for the whole recording while the
others presented one or more periods of drowsines
s in
seven recordings between resting stops. There are not
significant differences between groups for all indexes but
BW50 (p<0.05). Nevertheless paired tests comparing
drowsy and alert periods show significant differences
(p<0.05) for SDNN, HFDI, mRR, BW
50
, AFS, α
1
,
LF/HF and MEDF. |