Signal Processing For Sensing
Signal Processing for Sensing is a computational methodology that transforms raw sensor data into meaningful information by filtering, analyzing, and interpreting signals specifically for the purpose of extracting context-aware, environment-related, or human-centric insights in mobile sensing applications.
59
Publications
3.4K
Citations
220
Authors
102
Institutions
Publications per year
2017–2026
25
Parents
59
More Is Less: Signal Processing and the Data Deluge
Richard G. Baraniuk · Science · 2011 · 243 citations
Monitoring vital signs using millimeter wave
Zhicheng Yang, Parth H. Pathak, Yunze Zeng et al. · 2016 · 178 citations
Engineering, Biomedical Engineering, Electrical Engineering +17
Jian Wang, Neeraj Varshney, Camillo Gentile et al. · IEEE Internet of Things Journal · 2022 · 170 citations · Full text
Engineering, Electrical Engineering, Systems Engineering +17
1–5 of 59
220
6
h-index
4
h-index
2
h-index
2
h-index
2
h-index
1–5 of 220
102

University of Massachusetts Amherst
Amherst Center, United States
5 h-index
9 publications
422 citations

Peking University
Beijing, China
4 h-index
13 publications
813 citations
Institut Polytechnique de Paris
Palaiseau, France
3 h-index
4 publications
193 citations
Massachusetts Institute of Technology
Cambridge, United States
2 h-index
11 publications
260 citations

Imperial College London
London, United Kingdom
2 h-index
2 publications
94 citations
University of California, Davis
Davis, United States
2 h-index
6 publications
948 citations
University of Alabama
Tuscaloosa, United States
2 h-index
6 publications
189 citations
University of Technology Sydney
Sydney, Australia
2 h-index
6 publications
1.1K citations
1–8 of 102
4 publications · 393 citations
4
h-index
3 publications · 60 citations
3
h-index
2 publications · 60 citations
2
h-index
Conference · 2 publications · 95 citations
2
h-index
IMWUT · 2 publications · 112 citations
2
h-index
1–5