4.5 Article

A new postural stability-indicator to predict the level of fear of falling in Parkinson's disease patients

Journal

BIOMEDICAL ENGINEERING ONLINE
Volume 19, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12938-020-00808-w

Keywords

Fear of falling; Parkinson's disease; Postural control; Force platform; Diagnosis

Funding

  1. Iran University of Medical Sciences (IUMS) [95-02-87-28529]

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Background Fear of falling (FoF) is defined as a lasting concern about falling that causes a person to limit or even stop the daily activities that he/she is capable of. Seventy percent of Parkinson's disease (PD) patients report activity limitations due to FoF. Timely identification of FoF is critical to prevent its additional adverse effects on the quality of life. Self-report questionnaires are commonly used to evaluate the FoF, which may be prone to human error. Objectives In this study, we attempted to identify a new postural stability-indicator to objectively predict the intensity of FoF and its related behavior(s) in PD patients. Methods Thirty-eight PD patients participated in the study (mean age, 61.2 years), among whom 10 (26.32%) were identified with low FoF and the rest (73.68%) with high FoF, based on Falls Efficacy Scale-International (FES-I). We used a limit of stability task calibrated to each individual and investigated the postural strategies to predict the intensity of FoF. New parameters (FTR(i)s; functional time ratio) were extracted based on the center of pressure presence pattern in different rectangular areas (i = 1, 2, and 3). The task was performed on two heights to investigate FoF-related behavior(s). Results FTR1/2(the ratio between FTR1 and FTR2) was strongly correlated with the FES-I (r = - 0.63, p < 0.001), Pull test (r = - 0.65, p < 0.001), Timed Up and Go test (r = - 0.57,p < 0.001), and Berg Balance Scale (r = 0.62, p < 0.001). The model ofFTR(1/2)was identified as a best-fitting model to predicting the intensity of FoF in PD participants (sensitivity = 96.43%, specificity = 80%), using a threshold level of <= 2.83. Conclusions Using the proposed assessment technique, we can accurately predict the intensity of FoF in PD patients. Also, theFTR(1/2)index can be potentially considered as a mechanical biomarker to sense the FoF-related postural instability in PD patients.

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