Improvement of Performance in Freezing of Gait detection in Parkinsons Disease using Transformer networks and a single waist worn triaxial accelerometer

FOG affects between 50% and 80% of people with PD (Weiss et al., 2015), and its presence is associated with an increased risk of falls, affecting the quality of life (Moore et al., 2007). When a FOG episode appears, PD patients can present variability in the gait pattern, with a reduction in step length, shuffling steps, trembling of the legs, and total akinesia with a loss of movement of the limbs or trunk (Okuma, 2014). FOG episodes can have a duration of a few seconds (1 second or less for very short episodes and more than 5 seconds for long episodes) and appear more frequently during typical daily-life conditions than during straight walking assessments in clinical and laboratory settings (Okuma, 2014; Nonnekes et al., 2015). FOG assessment involves the identification of the presence (or absence) of FOG episodes and also aims to identify their severity (Mancini et al., 2019). Assessing FOG in the clinical practice is difficult because of the lack of an optimal freezing score, and difficulties related to the clinical assessment often performed on conditions that hinder the appearance of FOG events during evaluation; for example, the assessment is usually made in the ON state, while FOG occurs more often in OFF state (Schaafsma et al., 2003; Mancini et al., 2021). Although the clinical assessment provides relevant indicators for the characterization of FOG, the conditions whereby these are performed do not accurately represent the severity of FOG in daily life (Rahman et al., 2008; Snijders et al., 2008), such as the patients' homes, where FOG events tend to occur more frequently (Nieuwboer et al., 1998).