Polysomnography (PSG) is the gold standard to assess sleep disorders, involving overnight recordings of several bio-signals. The PSG setting is uncomfortable and impractical to use at home. Hence, less invasive, cheaper, and more portable solutions are being proposed. In this thesis, the aim is to understand the limitations and potentials of the in-ear electroencephalography (in-ear-EEG). In particular, the assessment focuses on determining which of the standard PSG derivations is more similar to the in-ear-EEG signal. A per-class feature-based analysis is performed on ten healthy participants (18-60 years). Features in both time and frequency domains are extracted from the standard twenty-one PSG derivations and the in-ear-EEG signal.