The manner in which characteristics of time series in the frequency domain can enhance discrimination between physiologic and parkinsonian tremor when tremor amplitude is low was examined. Rest tremor and postural tremor with and without visual feedback were recorded twice in the two hands of a group of patients with Parkinson's disease (PD) (n = 21) and a group of healthy control subjects (n = 30) using displacement laser systems. Recordings were analyzed quantitatively using amplitude and seven frequency domain characteristics. Postural tremor with no visual feedback allowed the most efficient discrimination between the two groups of subjects especially in velocity and acceleration (derived from displacement) and allowed identification of more patients with PD as separate from the range observed in the control group. Moreover, the frequency domain characteristics that were investigated identified the majority of the patients even when amplitude did not. After eliminating redundant (correlated) characteristics, it was found that the frequency composition of tremor in PD can be described adequately with four characteristics, which are the most reliable, independent, and discriminative elements for detecting early or subtle modifications in tremor. Also, a series of finger flexions was found to enhance physiologic tremor but not tremor in PD. Discrimination of low-amplitude tremor in PD from normal physiologic tremor is enhanced by examining the median frequency of oscillations, the concentration of power in the power spectrum, and the distribution of power in particular ranges. Tremor measurement should not be limited to acceleration data as some information is more visible in velocity time series.