Frontiers in Neuroscience (Sep 2010)
Assessing periodicity of periodic leg movements during sleep
Abstract
Background: Periodic leg movements during sleep (PLMS) consist of involuntary periodic movements of the lower extremities. The debated functional relevance of PLMS is based on correlation of clinical parameters with the PLMS 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 PLMS. Methods: Three patient groups of 10 patients showing PLMS with OSA (group 1), PLMS without OSA or RLS (group 2) and PLMS with RLS (group 3) were considered. Applying the ``unfolding'' procedure, a method developed in statistical physics, enhanced or even revealed intrinsic periodicity of PLMS. The degree of periodicity of PLMS was assessed by fitting one-parameter distributions to the unfolded IMI distributions. Finally, it was investigated whether the shape of the IMI distributions allows to separate patients into different groups. Results: Despite applying the unfolding procedure, periodicity was neither homogeneous within nor considerably different between the three clinically defined groups. Data-driven clustering revealed more homogeneous and better separated clusters. However, they consisted of patients with heterogeneous demographic data and comorbidities, including RLS {em 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 PLMS 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 {em degree} of periodicity and demographic data or comorbidities was found. However, there were indications that the {em nature} of the periodicity might be determined by long-range interactions between LM of patients with PLMS and OSA.
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