Feng-Yu Wang

Prof. Dr. Feng-Yu Wang

1. Center for Applied Mathematics, Tianjin University, Tianjin 300072, China
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Research Focus & Metrics

Academic Career Length

38Years (1989-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2018 in Stochastic Processes and their Applications
Verified
Journal Article
Closed access
Feng-Yu WangFeng-Yu Wang
Feng-Yu Wang

1 November 1997 in Probability Theory and Related Fields
Verified
Journal Article
Closed access
PDF file
Feng-Yu WangFeng-Yu Wang
Feng-Yu Wang

1 October 2001 in Journal of Functional Analysis
Verified
Journal Article
Closed access
MRMichael Röckner
Michael Röckner
Feng-Yu WangFeng-Yu Wang
Feng-Yu Wang

1 July 2007 in Journal of Differential Equations
Verified
Journal Article
Closed access
JRJiagang Ren
Jiagang Ren
MRMichael Röckner
Michael Röckner
Feng-Yu WangFeng-Yu Wang
Feng-Yu Wang

23 April 2021 in IEEE Internet of Things Journal
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Journal Article
Closed access
Feng-Yu WangFeng-Yu Wang
Feng-Yu Wang
XZXiaolu Zeng
Xiaolu Zeng
CWChenshu Wu
Chenshu Wu
BWBeibei Wang
Beibei Wang
KLK. J. Ray Liu
K. J. Ray Liu
Heart rate variability (HRV), which measures the fluctuation of heartbeat intervals, has been considered as an important indicator for general health evaluation. To alleviate the user burden and explore the usability for long-term health monitoring, noncontact methods for HRV monitoring have drawn tremendous attention. In this article, we present mmHRV, the first contact-free multiuser HRV monitoring system using commercial millimeter-wave (mmWave) radio. The design of mmHRV consists of two key components. First, we develop a calibration-free target detector to identify each user’s location. Second, a heartbeat signal extractor is devised, which can optimize the decomposition of the phase of the channel information modulated by the chest movement and, thus, estimate the heartbeat signal. The exact time of heartbeats is estimated by finding the peak location of the heartbeat signal while the interbeat intervals (IBIs) can be further derived for evaluating the HRV metrics of each target. We evaluate the system performance and the impact of different settings, including the distance between human and the device, user orientation, incidental angle, and blockage. Experimental results show that mmHRV can measure the HRV accurately with a median IBI estimation error of 28 ms (with respect to 96.16% accuracy). In addition, the root-mean-square error (RMSE) measured in the nonline-of-sight (NLOS) scenarios is 31.71 ms based on the experiments with 11 participants. The performance of the multiuser scenario is slightly degraded compared with the single-user case; however, the median error of the 3-user case is within 52 ms for all three tested locations.

1 January 2000 in Journal of Functional Analysis
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Journal Article
Closed access
Feng-Yu WangFeng-Yu Wang
Feng-Yu Wang