Wi-Fi Signal Analysis for Heartbeat and Metal Detection: A Comparative Study of Reliable Contactless Systems

Khan, Faiza; Bhuiyan, Zakirul Alam; Islam, Monirul; Zaman, Aliuz; Tao, Hai

doi:10.1109/dsa.2019.00018

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…Numerous systems and algorithms have been designed and implemented in the last several years. These include Wisee, Witalk, Wi‐hear, Wi‐Hear, gateID, FreeSense, Wi‐key, and so forth 11‐18 . Nonetheless, these Wi‐Fi‐based advances are still immature.…”

Section: Introductionmentioning

confidence: 99%

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Unauthorized and privacy‐intrusive human activity watching through Wi‐Fi signals: An emerging cybersecurity threat

Zhao

Bhuiyan

et al. 2022

Concurrency and Computation

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Summary Nowadays, wireless radio signals are ubiquitous and are around us; some signals pass through us, and some reflect off us. Substantial advancements in recent years demonstrate that such signals are utilized for diverse emerging applications, including people activity, motion watches, healthcare, and so forth. A few questions would be that may raise severe concerns in future cybersecurity and private domains. For example, what if Wi‐Fi signals are utilized to watch a person doings and actions, which are mostly without the person's authorization and authentication. How far such signal utilization can attack privacy intrusively, silently, more particularly, what/where we do, say, command, see, write, draw, go, perform, everything can be known. In this article, we investigate watching human activities by leveraging Wi‐Fi signals and discuss a few application prototypes. We attempt to learn whether or not attackers have the ability to passively watch our Internet activity as well as physical activities and motions through Wi‐Fi. With all‐new advances, one must be aware that cyberattackers may apply unauthorized use of these advances to their benefit. We discuss some of the countermeasures and approaches to mitigate these risks with Wi‐Fi signal leveraging.

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Section: Introductionmentioning

confidence: 99%

“…Witalk, Wi-hear, Wi-Hear, gateID, FreeSense, Wi-key, and so forth. [11][12][13][14][15][16][17][18] Nonetheless, these Wi-Fi-based advances are still immature. A plenty of research and development still needs to be done in the future to make it successful and usable regarding the security, privacy, and comfort in human life.…”

mentioning

confidence: 99%

Unauthorized and privacy‐intrusive human activity watching through Wi‐Fi signals: An emerging cybersecurity threat

Zhao

Bhuiyan

et al. 2022

Concurrency and Computation

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A WiVi Based IoT Framework for Detection of Human Trafficking Victims Kept in Hideouts

Samanta

Singhar

Gandomi

et al. 2020

Lecture Notes in Computer Science

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ECG-grained Cardiac Monitoring Using UWB Signals

Wang

Jin

et al. 2022

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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With the development of wireless sensing, researchers have proposed many contactless vital sign monitoring systems, which can be used to monitor respiration rates, heart rates, cardiac cycles and etc. However, these vital signs are ones of coarse granularity, so they are less helpful in the diagnosis of cardiovascular diseases (CVDs). Considering that electrocardiogram (ECG) is an important evidence base for the diagnoses of CVDs, we propose to generate ECGs from ultra-wideband (UWB) signals in a contactless manner as a fine-grained cardiac monitoring solution. Specifically, we analyze the properties of UWB signals containing heartbeats and respiration, and design two complementary heartbeat signal restoration methods to perfectly recover heartbeat signal variation. To establish the mapping between the mechanical activity of the heart sensed by UWB devices and the electrical activity of the heart recorded in ECGs, we construct a conditional generative adversarial network to encode the mapping between mechanical activity and electrical activity and propose a contrastive learning strategy to reduce the interference from noise in UWB signals. We build the corresponding cardiac monitoring system named RF-ECG and conduct extensive experiments using about 120,000 heartbeats from more than 40 participants. The experimental results show that the ECGs generated by RF-ECG have good performance in both ECG intervals and morphology compared with the ground truth. Moreover, diseases such as tachycardia/bradycardia, sinus arrhythmia, and premature contractions can be diagnosed from the ECGs generated by our RF-ECG.

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Wi-Fi Signal Analysis for Heartbeat and Metal Detection: A Comparative Study of Reliable Contactless Systems

Cited by 3 publications

References 25 publications

Unauthorized and privacy‐intrusive human activity watching through Wi‐Fi signals: An emerging cybersecurity threat

Unauthorized and privacy‐intrusive human activity watching through Wi‐Fi signals: An emerging cybersecurity threat

A WiVi Based IoT Framework for Detection of Human Trafficking Victims Kept in Hideouts

ECG-grained Cardiac Monitoring Using UWB Signals

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