Danger-Pose Detection System Using Commodity Wi-Fi for Bathroom Monitoring

Author:

Zhang Zizheng,Ishida ShigemiORCID,Tagashira Shigeaki,Fukuda Akira

Abstract

A bathroom has higher probability of accidents than other rooms due to a slippery floor and temperature change. Because of high privacy and humidity, we face difficulties in monitoring inside a bathroom using traditional healthcare methods based on cameras and wearable sensors. In this paper, we present a danger-pose detection system using commodity Wi-Fi devices, which can be applied to bathroom monitoring, preserving privacy. A machine learning-based detection method usually requires data collected in target situations, which is difficult in detection-of-danger situations. We therefore employ a machine learning-based anomaly-detection method that requires a small amount of data in anomaly conditions, minimizing the required training data collected in dangerous conditions. We first derive the amplitude and phase shift from Wi-Fi channel state information (CSI) to extract low-frequency components that are related to human activities. We then separately extract static and dynamic features from the CSI changes in time. Finally, the static and dynamic features are fed into a one-class support vector machine (SVM), which is used as an anomaly-detection method, to classify whether a user is not in bathtub, bathing safely, or in dangerous conditions. We conducted experimental evaluations and demonstrated that our danger-pose detection system achieved a high detection performance in a non-line-of-sight (NLOS) scenario.

Funder

Japan Science and Technology Agency

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference28 articles.

Cited by 21 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Novelty detection algorithms to help identify abnormal activities in the daily lives of elderly people;IEEE Latin America Transactions;2024-03

2. A review on fall detection systems in bathrooms: challenges and opportunities;Multimedia Tools and Applications;2024-01-12

3. Wi-Gitation: Replica Wi-Fi CSI Dataset for Physical Agitation Activity Recognition;Data;2023-12-30

4. Investigation on Deployment Pattern of Wi-Fi Transceivers for CSI-Based Indoor Localization and Activity Recognition;2023 Fourteenth International Conference on Mobile Computing and Ubiquitous Network (ICMU);2023-11-29

5. Human Pose Estimation Using Commodity WiFi and Deep Learning Approach;2023 5th International Conference on Frontiers Technology of Information and Computer (ICFTIC);2023-11-17

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