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This paper presents a fall detection system for elder people using wearable single inertial sensor. In contrast with multiple wearable sensors, we deploy only one 3-axis accelerator on human body for continuously monitoring fall incident. Support Vector Machine is exploited to be the classifier for predicting the behavior. The dedicated features including intensity of acceleration, ascending coefficient and descending coefficient are selected for training model. The experimental results have shown that the positive detection rate can reach 92.5% after optimizing SVM parameters.

Fall Detection for Elder People Using Single Inertial Sensor