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Session: Poster session II
Session starts: Thursday 24 January, 16:00

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Octavio Martinez Manzanera (University Medical Center Groningen)
Marit Sanders (University of Twente)
Jan Willem Elting (University Medical Center Groningen)
Natasha Maurits (University Medical Center Groningen)

Abstract:
Tremor is an ubiquitous, often disabling neurological disorder with varying etiologies. Some tremors, such as enhanced physiological tremor, essential tremor and psychogenic tremor, can be difficult to distinguish and therefore hard to diagnose. Moreover tremors might only occur during specific postures, movements or periods during the day, hampering tremor diagnosis by a physician on the basis of clinical symptoms alone. Long-term tremor recordings during daily life can help detecting more tremor occurrences and facilitating more extensive analyses. Here a method is presented to automatically detect tremor in long-term accelerometer recordings based on auto-regressive (AR) modeling [1], with the specific aim to distinguish psychogenic tremor from other tremors.