Human gesture sensor using ambient wireless signals based on passive radar technology

Tang, Mu-Cyun; Wang, Fu-Kang; Horng, Tzyy‐Sheng

doi:10.1109/mwsym.2015.7167080

Cited by 10 publications

(3 citation statements)

References 7 publications

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“…Furthermore, the utilization of radio frequencies in wireless communications, such as Wi-Fi signals, has been examined in the development of systems for detecting human motions. Mu-Cyun et al [7] proposed exploiting ambient wireless signals to identify gestures using a passive Doppler radar. For demonstration reasons, a prototype radar was created, and field-tested in a typical indoor Wi-Fi scenario.…”

Section: Wifi Signals Applicationmentioning

confidence: 99%

“…The proposed radar can employ wireless signals of any form or combination. It is straightforward to implement as part of the RF (Radio Frequency) circuitry in a mobile device without consuming too much power [7]. Furthermore, Chokemongkol Nadee and Kosin Chamnongthai presented an ultrasonic array sensor for monitoring human fall detection by classifying fall gestures and positions in their research.…”

Section: Wifi Signals Applicationmentioning

confidence: 99%

“…The framework trials yield encouraging results, with accuracy improving with increasing crowd size. Additionally, Tang et al [7] introduce a distinctive passive Doppler radar system that detects and recognizes human gestures at a short distance using ambient wireless signals. This radar requires no correlated source and is not affected by radio interference.…”

Section: Wifi Signals Applicationmentioning

confidence: 99%

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A Contactless Smart WiFi-Based Application Presence or Fall Detection System: Analyzing Channel State Information (CSI) Signals

Al-Rajab,

Al Zraiqat,

John

et al. 2023

IJEMD-CSAI

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Falls are considered to be the most common accident among people of determination and the elderly. Recently, many solutions have been proposed, whether wearable or noncontact, for people presence or falling detection (FD). These solutions can use wearable sensors to effectively monitor the health condition of elderly people at home and ensure their performance. However, all of these solutions require users to always wear specialized devices and sensors in their bodies, which limits the deployment of large-scale systems. Additionally, camera-based systems can raise privacy concerns. Recently, the non-contact Wi-Fi approach is becoming more and more popular because of its ubiquitous and non-invasiveness. In this paper, we propose a smart contactless system that uses Artificial Intelligence (AI) to analyze the Channel State Information (CSI) signals extracted from Wi-Fi signals. Our proposed application can help the people of determination and senior citizens (e.g., remote monitoring of the elderly) to be engaged all the time through closed monitoring based on ability to analyse the CSI signals extracted from Wi-Fi signals. This system can detect the presence, and falls of users without requiring them to wear any specialized devices or sensors. We believe that this application can help elderly and disabled people to remain engaged and monitored at all times, providing their communities with the means to better care for and serve them.

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Section: Wifi Signals Applicationmentioning

confidence: 99%

Section: Wifi Signals Applicationmentioning

confidence: 99%

Section: Wifi Signals Applicationmentioning

confidence: 99%

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