njit-etd2003-081 - New Jersey Institute of Technology

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5.6 Principal Component Analysis
As mentioned in section 3.14, the principal components were arranged in order of
decreasing variance with the most informative principal component listed first, and the
least informative listed last. The dimensionality of the problem was reduced, i.e.,
reduces the number of variables without losing much of the information. Thus instead of
analyzing a large number of the original variables with complex interrelationships, the
data could be analyzed by a small number of uncorrelated principal components.
Figure 5.60 presented a principal component plot of the data set containing 48
COPD and 8 normal subjects at rest. The data set gave the following principal
components (PC):
1 st PC: LF_coh_HR_rsp — Coherence of HR and respiration signals in the LF
range (0.04 - 0.15 Hz).
2nd PC: HF _ coh _ BP _rsp — Coherence of BP and respiration signals in the HF
range (0.15 - 0.4 Hz).
3 rd PC: rsp — The respiration rate.
This indicated that the largest variance between COPD and normal subjects was
the interrelationships between heart rate and respiration. The second largest variance was
the interrelationships between blood pressure and respiration. The third largest variance
was the respiration rate itself.