Vehicle In-Cabin Contactless WiFi Human Sensing

Ibrahim, Mona E.; Brown, Kenneth N.

doi:10.1109/secon52354.2021.9491580

Cited by 3 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Parkinson detection [56], 2D pose estimation [48], gesture recognition [89], [90], pedestrian flow estimation [91] respiration [63], sleep vitals monitoring [64] 2020 pose estimation [50], driver activity & falling [92], 3D pose estimation [49], gesture [93], [94], daily activity [42] respiration [65], [66], respiration and heart rate [50], [67] [67] DWT, hampel filter FFT N/A vitals from entirely different mechanisms. In a WiFi system, outliers can be caused by hardware or software errors.…”

Section: Main Components Of Contactless Wifi Sensingmentioning

confidence: 99%

Contactless WiFi Sensing and Monitoring for Future Healthcare - Emerging Trends, Challenges, and Opportunities

Taha

Shah

et al. 2023

IEEE Rev. Biomed. Eng.

View full text Add to dashboard Cite

WiFi sensing has received recent and significant interest from academia, industry, healthcare professionals, and other caregivers (including family members) as a potential mechanism to monitor our aging population at a distance without deploying devices on users' bodies. In particular, these methods have the potential to detect critical events such as falls, sleep disturbances, wandering behavior, respiratory disorders, and abnormal cardiac activity experienced by vulnerable people. The interest in such WiFi-based sensing systems arises from practical advantages including its ease of operation indoors as well as ready compliance from monitored individuals. Unlike other sensing methods, such as wearables, camera-based imaging, and acoustic-based solutions, WiFi technology is easy to implement and unobtrusive. This paper reviews the current state-of-the-art research on collecting and analyzing channel state information extracted using ubiquitous WiFi signals, describing a range of healthcare applications and identifying a series of open research challenges, including untapped areas of research and related trends. This work aims to provide an overarching view in understanding the technology and discusses its use-cases from a perspective that considers hardware, advanced signal processing, and data acquisition.

show abstract

Section: Main Components Of Contactless Wifi Sensingmentioning

confidence: 99%

Contactless WiFi Sensing and Monitoring for Future Healthcare - Emerging Trends, Challenges, and Opportunities

Taha

Shah

et al. 2023

IEEE Rev. Biomed. Eng.

View full text Add to dashboard Cite

show abstract

“…However, the approach relies on a high level of accuracy of the CSI information, which cannot always be guaranteed for general WiFi devices. Mohammed Ibrahim implemented WiFi-based sensing within a vehicle to monitor the respiration rate of passengers in real-time [23]. The CSI data for a subcarrier is randomly selected and smoothed using a Savitzky-Golay filter.…”

Section: Introductionmentioning

confidence: 99%

High-Resolution Indoor Sensing Using Channel State Information of WiFi Networks

Zhou,

Zhang,

Temiz

2023

Electronics

View full text Add to dashboard Cite

Indoor sensing is becoming increasingly important over time as it can be effectively utilized in many applications from digital health care systems to indoor safety and security systems. In particular, implementing sensing operations using existing infrastructures improves our experience and well-being, and exhibits unique advantages. The physical layer channel state information for wireless fidelity (WiFi) communications carries rich information about scatters in the propagation environment; hence, we exploited this information to enable detailed recognition of human behaviours in this study. Comprehensive calibration and filtering techniques were developed to alleviate the redundant responses embedded in the channel state information (CSI) data due to static objects and accidental events. Accurate information on breathing rate, heartbeat and angle of arrival of the incoming signal at the receiver side was inferred from the available CSI data. The method and procedure developed can be extended for sensing or imaging the environment utilizing wireless communication networks.

show abstract