BACKGROUND Periodic leg movements (PLM) during sleep consist of involuntary periodic movements of the lower extremities. The debated functional relevance of PLM during sleep is based on correlation of clinical parameters with the PLM index (PLMI). However, periodicity in movements may not be reflected best by the PLMI. Here, an approach novel to the field of sleep research is used to reveal intrinsic periodicity in inter movement intervals (IMI) in patients with PLM. METHODS Three patient groups of 10 patients showing PLM with OSA (group 1), PLM without OSA or RLS (group 2) and PLM with RLS (group 3) are considered. Applying the "unfolding" procedure, a method developed in statistical physics, enhances or even reveals intrinsic periodicity of PLM. The degree of periodicity of PLM is assessed by fitting one-parameter distributions to the unfolded IMI distributions. Finally, it is investigated whether the shape of the IMI distributions allows to separate patients into different groups. RESULTS Despite applying the unfolding procedure, periodicity is neither homogeneous within nor considerably different between the three clinically defined groups. Data-driven clustering reveals more homogeneous and better separated clusters. However, they consist of patients with heterogeneous demographic data and comorbidities, including RLS and OSA. CONCLUSIONS The unfolding procedure may be necessary to enhance or reveal periodicity. Thus this method is proposed as a pre-processing step before analyzing PLM statistically. Data-driven clustering yields much more reasonable results when applied to the unfolded IMI distributions than to the original data. Despite this effort no correlation between the degree of periodicity and demographic data or comorbidities is found. However, there are indications that the nature of the periodicity might be determined by long-range interactions between LM of patients with PLM and OSA.