Hua Wang1, Yingyou Wen1,2, Dazhe Zhao1,3. 1. School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China. 2. State Key Laboratory of Software Architecture, Neusoft Corporation, Shenyang, Liaoning, China. 3. Key Laboratory of Medical Image Computing, Ministry of Education, Northeastern University, Shenyang, Liaoning, China.
Abstract
BACKGROUND: Medical applications have begun to benefit from Internet of Things (IoT) technology through the introduction of wearable devices. Several medical applications require accurate patient location as various changes affect pressure parameters inside the body. OBJECTIVE: This study aims to develop a system to measure indoor altitude for IoT medical applications. METHODS: We propose a differential barometric-based positioning system to estimate the altitude between a reference sensor and a localizing sensor connected to the human body. The differential barometric altimetry model is introduced to estimate indoor elevations and eliminate environmental artifacts. In addition, a Gaussian filter processing is adopted to remove noise from the elevation measurements. The proposed system is then investigated through extensive experiments, using various evaluation criteria. RESULTS: The results indicate that the proposed system yielded good accuracy with reduced implementation complexity and fewer costs. CONCLUSIONS: The proposed system is resilient compared to other indoor localization approaches, even when numerous environmental artifacts in indoor environments are present.
BACKGROUND: Medical applications have begun to benefit from Internet of Things (IoT) technology through the introduction of wearable devices. Several medical applications require accurate patient location as various changes affect pressure parameters inside the body. OBJECTIVE: This study aims to develop a system to measure indoor altitude for IoT medical applications. METHODS: We propose a differential barometric-based positioning system to estimate the altitude between a reference sensor and a localizing sensor connected to the human body. The differential barometric altimetry model is introduced to estimate indoor elevations and eliminate environmental artifacts. In addition, a Gaussian filter processing is adopted to remove noise from the elevation measurements. The proposed system is then investigated through extensive experiments, using various evaluation criteria. RESULTS: The results indicate that the proposed system yielded good accuracy with reduced implementation complexity and fewer costs. CONCLUSIONS: The proposed system is resilient compared to other indoor localization approaches, even when numerous environmental artifacts in indoor environments are present.
Entities:
Keywords:
Internet of Things; barometric altimetry; health monitoring system; medical monitoring; wearable wireless sensors