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Feature Selection and Predictors of Falls with Foot Force Sensors Using KNN-Based Algorithms., , , , , , и . Sensors, 15 (11): 29393-29407 (2015)A wearable action recognition system based on acceleration and attitude angles using real-time detection algorithm., , , , , , , , и . EMBC, стр. 2385-2389. IEEE, (2017)Relationship between dynamical characteristics of sit-to-walk motion and physical functions of elderly humans., , , , , , и . EMBC, стр. 871-875. IEEE, (2016)A MAC protocol with high scalability for motion capture based on frequency division multiple and time division multiple access., , , , , , , , , и . EMBC, стр. 697-701. IEEE, (2017)Real-time Action Recognition and Fall Detection Based on Smartphone., , , , , и . EMBC, стр. 4418-4422. IEEE, (2018)Fall risk factors analysis based on sample entropy of plantar kinematic signal during stance phase., , , , , , , и . EMBC, стр. 4832-4836. IEEE, (2016)Elderly Fall Risk Prediction with Plantar Center of Force Using ConvLSTM Algorithm., , , и . CBS, стр. 36-41. IEEE, (2019)Accurate Fall Detection Algorithm Based on SBPSO-SVM Classifier., , , , , , и . ICBBT, стр. 83-86. ACM, (2018)Pre-impact Alarm System for Fall Detection Using MEMS Sensors and HMM-based SVM Classifier., , , , , и . EMBC, стр. 4401-4405. IEEE, (2018)