Mitigating false alarms using accumulator rule and dynamic sliding window in wireless body area
Tóm tắt
Faulty measurements of sensors in critical applications like remote patient monitoring systems may sometimes lead to misdiagnose or unnecessary interventions from healthcare professionals. The main motivation of this paper is to mitigate false alarms thereby improving the accuracy of the system. In this paper, we propose an approach for detecting anomalous sensor measurements. This paper utilizes dynamic sliding window, Weighted Moving Average for prediction purposes and accumulator rule for improving the accuracy in identifying true medical conditions. Finally we validate the performance of the proposed approach using a publicly available dataset and has been compared with existing approaches using statistical metrics. We achieved 37.40% reduction in False Positive Rate when compared with existing approaches.
Tài liệu tham khảo
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