Philip Schmidt

47 papers receiving 1.8k citations

Philip Schmidt's Hit Papers

Deep PPG: Large-Scale Heart Rate Estimation with Convolutional Neural Networks 2019 · 240 citations
2400+2+5Years since publication250500750

Peers

Philip Schmidt
Comparison fields: 5 of 133
  • Experimental and Cognitive Psychology 580
  • Architecture 43
  • Cardiology and Cardiovascular Medicine 520
  • Cognitive Neuroscience 358
  • Applied Psychology 78
Replace Martin Gjoreski with:
Martin Gjoreski Slovenia
Yekta Said Can Türkiye
Alexandros Pantelopoulos United States
Juha Pärkkä Finland
Bahareh Nakisa Australia
Regina Stoll Germany
Muhammad Majid Pakistan
Hugo Gambôa Portugal
Hristijan Gjoreski North Macedonia
Ane Alberdi Spain
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Citations per year

Countries citing papers authored by Philip Schmidt

Since Specialization
Citations

This map shows the geographic impact of Philip Schmidt's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Philip Schmidt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philip Schmidt more than expected).

Fields of papers citing papers by Philip Schmidt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Philip Schmidt. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Philip Schmidt. The network helps show where Philip Schmidt may publish in the future.

Co-authors

The 25 scholars most cited alongside Philip Schmidt, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Philip Schmidt Line = papers co-authored together Philip Schmidt links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Introducing WESAD, a Multimodal Dataset for Wearable Stress and Affect Detection
Hit paper breakdown →
2018768
2
Deep PPG: Large-Scale Heart Rate Estimation with Convolutional Neural Networks
Hit paper breakdown →
2019240
3 2017192
4 2019162
5 200063
6
The environmental behaviour of radium: revised edition
201454
7 201945
8 201631
9 199826
10 199026
11 199723
12 201820
13 201818
14
Industrial Energy Management And Utilization
198718
15 201817
16 199415
17 199415
18 199614
19 199812
20 198710

About Philip Schmidt

Philip Schmidt is a scholar working on Mechanical Engineering, Media Technology, Architecture, Biomedical Engineering and Cardiology and Cardiovascular Medicine, having authored 51 papers that have together received 1.9k indexed citations. Recurring topics across this work include Engineering Education and Pedagogy (6 papers), Experimental Learning in Engineering (6 papers), Industrial Gas Emission Control (5 papers), Emotion and Mood Recognition (5 papers), Engineering Education and Curriculum Development (4 papers), Mental Health Research Topics (4 papers), Heart Rate Variability and Autonomic Control (4 papers) and Non-Invasive Vital Sign Monitoring (3 papers). The work is most often cited by research in Experimental and Cognitive Psychology (580 citations), Architecture (43 citations), Cardiology and Cardiovascular Medicine (520 citations), Cognitive Neuroscience (358 citations) and Applied Psychology (78 citations). Philip Schmidt has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Attila Reiss, Kristof Van Laerhoven, Claus Marberger, Robert Dürichen, Rainer Stiefelhagen, Michael Hanselmann, David W. Price, C.H. Twu, Ronald E. Barr and Thomas Plötz. Their work appears in journals such as Energy, Journal of Heat Transfer, Journal of Microwave Power and Electromagnetic Energy, Sensors and Journal of the Air & Waste Management Association.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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