Unified framework for triaxial accelerometer-based fall event detection and classification using cumulants and hierarchical decision tree classifier.
In this Letter, the authors present a unified framework for fall event detection and classification using the cumulants extracted from the acceleration (ACC) signals acquired using a single waist-mounted triaxial accelerometer. The main objective of this Letter is to find suitable representative cumulants and classifiers in effectively detecting and classifying different types of fall and non-fall events. It was discovered that the first level of the proposed hierarchical decision tree algorithm implements fall detection using fifth-order cumulants and support vector machine (SVM) classifier. In the second level, the fall event classification algorithm uses the fifth-order cumulants and SVM. Finally, human activity classification is performed using the second-order cumulants and SVM. The detection and classification results are compared with those of the decision tree, naive Bayes, multilayer perceptron and SVM classifiers with different types of time-domain features including the second-, third-, fourth- and fifth-order cumulants and the signal magnitude vector and signal magnitude area. The experimental results demonstrate that the second- and fifth-order cumulant features and SVM classifier can achieve optimal detection and classification rates of above 95%, as well as the lowest false alarm rate of 1.03%.
['Kambhampati|Satya Samyukta|SS|', 'Singh|Vishal|V|', 'Manikandan|M Sabarimalai|MS|', 'Ramkumar|Barathram|B|']
triaxial accelerometer-based fall event detection hierarchical decision tree classifier decision trees cumulant extraction single waist-mounted triaxial accelerometer accelerometers fifth-order cumulants support vector machines support vector machines fall event classification algorithm human activity classification second-order cumulants naive Bayes multilayer perceptron SVM classifiers time-domain features optimal detection lowest false alarm rate ACC signals acceleration measurement acceleration signals biomedical measurement body sensor networks feature extraction fourth-order cumulants medical signal processing signal classification supports vector machine third-order cumulants