This study delves into an examination of heart rhythm patterns among patients afflicted with disorders of consciousness. The research primarily focuses on the analysis of polysomnographic recordings in the time domain while also exploring methodologies for evaluating peripheral signals. An algorithm aimed at detecting heart rhythm was introduced and applied. Utilizing preprocessed signals, various indices, predominantly utilized for assessing other peripheral signals such as STD RRr, RMSSD, IBI, HURST, ApEn, NN300, HRT, and pNN300, were computed across 69 patient measurements sourced from the "Kliniki Budzik". These indices' values were compared among three diagnostic groups representing disorders of consciousness: Unresponsive Wakefulness Syndrome (UWS), Minimally Conscious State (MCS), and Emergence from the Minimally Conscious State (eMCS). Statistical analyses, conducted at a significance level of 5%, were employed to discern any notable differences among these groups. The assessment of heart signals serves as an integral component within polysomnographic recordings. Furthermore, the comprehensive analysis of heart rhythm, coupled with the examination of other physiological signals, not only contributes to a better understanding of circadian rhythms but also facilitates the assessment of consciousness levels in patients with disorders of consciousness.