Review of fall detection techniques: A data availability perspective. (January 2017)

• Record Type: Journal Article
• Authors: Khan, Shehroz S.; Hoey, Jesse
• Is Part Of: Medical engineering & physics. Volume 39(2017)
• Page Start: 12
• Page End: 22
• Publication Date: 2017-01
• Subjects: Fall detection -- One-class classification -- Outlier detection -- Anomaly detection -- Cost-sensitive learning; 00-01 -- 99-00; Biomedical engineering -- Periodicals; Biomedical Engineering -- Periodicals; Physics -- Periodicals; Génie biomédical -- Périodiques; Biomedical engineering; Electronic journals; Periodicals; 610.28
• DOI: 10.1016/j.medengphy.2016.10.014
• Languages: English
• ISSNs: 1350-4533

Abstract

Highlights: Review of fall detection techniques from the perspective of availability of fall data. Proposed a taxonomy to study fall detection that is independent of the type of sensors used and specific feature extraction/selection methods. Identified the approach of treating a fall as an abnormal activity as a plausible research direction. Abstract: A fall is an abnormal activity that occurs rarely; however, missing to identify falls can have serious health and safety implications on an individual. Due to the rarity of occurrence of falls, there may be insufficient or no training data available for them. Therefore, standard supervised machine learning methods may not be directly applied to handle this problem. In this paper, we present a taxonomy for the study of fall detection from the perspective of availability of fall data. The proposed taxonomy is independent of the type of sensors used and specific feature extraction/selection methods. The taxonomy identifies different categories of classification methods for the study of fall detection based on the availability of their data during training the classifiers. Then, we present a comprehensive literature review within those categories and identify the approach of treating a fall as an abnormal activity to be a plausible research direction. We conclude our paper by discussing several open research problems in the field and pointers for future research.