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Session: Poster session I
Session starts: Thursday 24 January, 15:00

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Rowena Emaus ()

Abstract:
Parkinson’s Disease patients sometimes experience a symptom called freezing of gait (FOG). During a FOG episode, patients are temporarily unable to produce effective leg movements. Appearance of FOG might either be triggered or prevented by perceptual input from a person’s environment. Whereas assistive perceptual cues during walking might alleviate cognitive load and decrease FOG prevalence, distractive non-relevant surroundings might increase cognitive load and therefore increase FOG. Differences in cognitive load may thus be a distinctive factor for triggering or preventing FOG. A well-examined correlate for cognitive load is the frequency of eye blinks (Bacher & Smotherman, 2004). Eye blink frequency is known to go up with an increase in cognitive load and potentially blinks could function as a measure of this load. In turn, cognitive load might be a predictive factor for prevalence of FOG This research is aimed at uncovering the relationship between eye blinks and occurrence of FOG. Specifically, the goal is to investigate deviating patterns preceding FOG, which might help in detecting or predicting a FOG episode before its onset. Parkinson patients (n=15) experiencing FOG were measured during different motor tasks; normal turning, rapid turning and stepping in place. During these tasks an electro-oculogram (EOG) was recorded. The measurements were split into three types of fragments: moments preceding a FOG episode, the FOG episode itself and fragments without FOG. For each fragment, several features of eye movements are extracted such as blinks per minute. These features are compared over conditions to investigate differences in eye blinks related to FOG. Results of this research have high clinical relevance. If any predictive value is present preceding FOG, this could be one step forward in recognizing FOG before it sets in. Moreover, eye blinks yield relatively robust signals in an EOG measurement and can also be easily measured with camera-based systems. Together, predictive values in robust signals might eventually contribute to developing a wearable device that announces FOG and assists patients in daily life.