A new method is presented for identifying waveforms of fluctuations in turbulent plasmas. The method is based on heartbeat analysis in which the convolution of a waveform is obtained by employing the phase tracking method. Phase tracking is performed by correlating raw time-series data with a template waveform; the template is evaluated through iteration procedure. The method is applied to fluctuations in a PANTA plasma, and the nonlinear waveform and its distribution of periods are obtained. The identification of nonlinear waveforms is an essential task in the study of turbulent plasmas. The waveform, which includes information on higher harmonics (i.e., amplitude as well as phase), is the fundamental information that reflects nonlinearity in plasmas. A standard experimental approach is the convolution (i.e., conditional averaging) of time-series data. This approach has been applied to turbulent plasmas in the LMD-U device, and this has led to identification of large-amplitude solitary wave structures [1]. However, simple convolution within a prescribed period is not always sufficient because the period of oscillations can change over time. Intermittent variations in fluctuation periods, which often occur in turbulent plasmas, require a new method for identifying nonlinear waveforms.In this article, a new method is presented for identifying the waveforms of perturbations in turbulent plasmas. Convolution of a waveform is performed by employing the phase tracking method, which is based on heartbeat analysis [2]. The method is applied to fluctuations in PANTA plasmas [3], and the nonlinear waveform and its distribution of periods are obtained.At this point, we explain the new method. Figure 1 (a) illustrates a time series of observed fluctuations for a floating potential, which was observed in PANTA plasmas [1]. In this case, the perturbation is quasi-periodic, as can be