The aging process may lead to the degradation of lower extremity function in the elderly population, which can restrict their daily quality of life and gradually increase the fall risk. We aimed to determine whether objective measures of physical function could predict subsequent falls. Ground reaction force (GRF) data, which was quantified by sample entropy, was collected by foot force sensors. Thirty eight subjects (23 fallers and 15 non-fallers) participated in functional movement tests, including walking and sit-to-stand (STS). A feature selection algorithm was used to select relevant features to classify the elderly into two groups: at risk and not at risk of falling down, for three KNN-based classifiers: local mean-based k-nearest neighbor (LMKNN), pseudo nearest neighbor (PNN), local mean pseudo nearest neighbor (LMPNN) classification. We compared classification performances, and achieved the best results with LMPNN, with sensitivity, specificity and accuracy all 100%. Moreover, a subset of GRFs was significantly different between the two groups via Wilcoxon rank sum test, which is compatible with the classification results. This method could potentially be used by non-experts to monitor balance and the risk of falling down in the elderly population.

// <![CDATA[ $('.header-date').hide();$('#titleAuthors').hide();$('#abstractHeader').hide(); // ]]> Dan Wang1, *, Shengyun Liang2, *, Zhao Zhang3, *, Guoru Zhao2, Yuan Hu4, Shengran Liang5, Xipeng Zhang3, Santasree Banerjee6, * 1Department of Pathology, Tianjin Medical University General Hospital, Tianjin 300052, China 2Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China 3Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin 300121, China 4Department of Hematology, Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510006, China 5School of Life Science and Biopharmaceuticals, Guangdong Pharmaceutical University, Guangzhou 510006, China 6Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Hangzhou 310000, China *These authors contributed equally to this work Correspondence to: Santasree Banerjee, email: santasree.banerjee@yahoo.com Xipeng Zhang, email: zxp2266@163.com Keywords: familial adenomatous polyposis, APC gene, splice acceptor site mutation, targeted next-generation sequencing, colorectal cancer Received: September 06, 2016 Accepted: January 27, 2017 Published: February 20, 2017