Towards a quantitative assessment of early-stage Parkinson’s disease using BioVRSea paradigm

Neurodegenerative diseases (NDDs) are considered one of the twenty-first century most pressing public health issues. One consistent risk factor for developing NDD is increasing age and the increased longevity of the world population results in the rise of NDDs. Parkinson's disease (PD) is the second most common NDD in the world today. Impaired motor functions characterize PD, and deficits in postural control are commonly seen. Currently, there is no cure for PD, and treatment options mainly focus on managing patients symptoms. The disease progresses over time, and the severity of symptoms increases, causing increasing disability and severe complications. The disease progression is repeatedly assessed subjectively with the support of standardized rating scales. Over the years, quantitative assessments of PD progression have gained interest among researchers to improve patient interaction, therapeutic decisions, and patient quality of life. BioVRSea is a novel multi-metric measurement setup used to quantify physiology and postural control responses to a moving platform and virtual reality (VR) with biomedical sensors, such as electroencephalography (EEG), electromyography (EMG), heart rate (HR), and center of pressure (COP). This study aimed to quantitatively evaluate the postural control responses of early-stage PD subjects using the BioVRSea paradigm and compare their responses to an age-match healthy group. Measurements were performed on 9 PD and 37 age-match healthy subjects. Additionally, within the PD group, five subjects were clinically assessed with postural instability (PI), and their postural control responses were compared with the PD subjects without PI. The responses were evaluated by analyzing BioVRSea signal parameters, and the results showed quantitative postural control response differences between the groups. This work is a step towards quantitatively assessing PD and understanding quantitative physiology associated with pathological conditions such as PD using the BioVRSea paradigm.

Author dc:creator

• Sigrún Anna Auðardóttir 1993-

Contributors dc:contributor

• Háskólinn í Reykjavík

• Heilbrigðisverkfræði
• Biomedical engineering
• Meistaraprófsritgerðir
• Parkinsonsveiki
• Stöðuskyn
• Heilarit
• Posture
• Sýndarveruleiki
• Parkinson's disease
• Electroencephalography
• Virtual reality

Language dc:language.iso

en

Handle dc:identifier.uri

http://hdl.handle.net/1946/43319

OAI identifier oai:identifier

oai:skemman.is:1946/43319