4.7 Article

An optimal sensor placement algorithm (O-SPA) for improving tracking precision of human activity in real-world healthcare systems

Journal

COMPUTER COMMUNICATIONS
Volume 148, Issue -, Pages 9-16

Publisher

ELSEVIER
DOI: 10.1016/j.comcom.2019.09.001

Keywords

Feature extraction; Information sensing; Naive Bayes classifier; Sensor positioning; Wearable sensor; Placement algorithm

Funding

  1. Deanship of Scientific Research at King Saud University, Saudi Arabia [RG-1439-053]

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In this article, an Optimal Sensor Placement Algorithm (O-SPA) is designed for improving the precision of human activity. This placement algorithm is designed based on the fact of improving the Rate of Observation (RO) and sensing in the day-to-day activities of human. SPA for RO and sensing improves the analysis precision by accumulating and classifying useful sensor information. Useful sensor information is achieved by approximating the sensor data mitigating positioning errors. The analysis process differentiates useful and less preference information from the placed sensors to reduce complications in classification. This device positioning algorithm is more specific for the precision of data accumulation and manipulation by reducing sensing errors to improve the efficiency of healthcare systems The efficiency of healthcare systems with optimal sensor deployment is measured in terms of accuracy (98.9%), classification time (0.079s), replications (4.12), recall (96.29%), and error factor (0.000021). The efficiency results are the best compared to Hybrid sensing aided human activity recognition (HHAR), Multi-sensor fusion with ensemble pruning system (MSF-EP) and Activities of daily living Compressive sensing (ADL).

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