Ecological Fall Prediction Sensitivity, Specificity, and Accuracy in Patients with Mild Cognitive Impairment at a High Risk of Falls

Author:

Kim Chaesu12,Park Haeun12,You Joshua (Sung)12

Affiliation:

1. Sports Movement Artificial-Intelligence Robotics Technology (SMART) Institute, Department of Physical Therapy, Yonsei University, Wonju 26493, Republic of Korea

2. Department of Physical Therapy, Yonsei University, Wonju 26943, Republic of Korea

Abstract

While falls among patients with mild cognitive impairment (MCI) have been closely associated with an increased postural sway during ecological activities of daily living, there is a dearth of postural sway detection (PSD) research in ecological environments. The present study aimed to investigate the fall sensitivity, specificity, and accuracy of our PSD system. Forty healthy young and older adults with MCI at a high risk of falls underwent the sensitivity, specificity, and accuracy tests for PSD by simultaneously recording the Berg Balance Scale and Timed Up and Go in ecological environments, and the data were analyzed using the receiver operating characteristic curve and area under the curve. The fall prediction sensitivity ranged from 0.82 to 0.99, specificity ranged from 0.69 to 0.90, and accuracy ranged from 0.53 to 0.81. The PSD system’s fall prediction sensitivity, specificity, and accuracy data suggest a reasonable discriminative capacity for distinguishing between fallers and non-fallers as well as predicting falls in older adults with MCI in ecological testing environments.

Funder

National Research Foundation of Korea

Korea Institute for Robot Industry Advancement

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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