Takayasu’s arteritis (TA) is a rarely studied primary systemic vasculitis involving the aorta and other major arteries of the body. This work proposes a novel noninvasive assessment method, combining both time domain and frequency domain analysis of peripheral signals such as photo plethysmography (PPG) in normal and TA patients providing information about the severity of the TA disease. The novelty of the proposed method is twofold: one, a novel signal processing technique Auto-correlated Spectrum for analyzing PPG signals, and two, use of noninvasive techniques from multiple-site PPG for quantifying the severity. PPG from twenty TA patients and twenty normal subjects have been acquired from five different peripheral sites in the body and compared. The Auto-correlated Spectrums of multiple-site PPG signals are calculated. A novel parameter called P-measure is derived using the relation between the number of peaks and the average distance of the peaks from origin of the spectrum. P-measure is used for classifying normal and diseased using a binary classification method, when greater than or equal to 0.32 the subject is considered as normal and otherwise diseased. The sensitivity and specificity values of this classification method are 96 and 83% respectively. This method is also compared with other frequency domain analysis and this technique can be a simple cost-effective assessment tool to reduce cardiovascular morbidity and mortality in the rarely studied TA, and perhaps other arterial diseases. The small group of TA population due to the rarity of TA disease is a major problem in acquiring data. © 2018, Springer International Publishing AG.