Shing-Hong Liu

1.9k total citations
98 papers, 1.4k citations indexed

About

Shing-Hong Liu is a scholar working on Biomedical Engineering, Cardiology and Cardiovascular Medicine and Surgery. According to data from OpenAlex, Shing-Hong Liu has authored 98 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Biomedical Engineering, 57 papers in Cardiology and Cardiovascular Medicine and 24 papers in Surgery. Recurrent topics in Shing-Hong Liu's work include Non-Invasive Vital Sign Monitoring (51 papers), Cardiovascular Health and Disease Prevention (25 papers) and Heart Rate Variability and Autonomic Control (22 papers). Shing-Hong Liu is often cited by papers focused on Non-Invasive Vital Sign Monitoring (51 papers), Cardiovascular Health and Disease Prevention (25 papers) and Heart Rate Variability and Autonomic Control (22 papers). Shing-Hong Liu collaborates with scholars based in Taiwan, Japan and United Arab Emirates. Shing-Hong Liu's co-authors include Kang-Ming Chang, Tan-Hsu Tan, Jia-Jung Wang, Munkhjargal Gochoo, Da‐Chuan Cheng, Wenxi Chen, Chun-Hung Su, Shih-Chia Huang, Wen-Chang Cheng and Chin‐Teng Lin and has published in prestigious journals such as PLoS ONE, Scientific Reports and IEEE Access.

In The Last Decade

Shing-Hong Liu

90 papers receiving 1.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Shing-Hong Liu Taiwan 21 769 615 379 232 157 98 1.4k
Ali Al‐Naji Australia 21 767 1.0× 314 0.5× 375 1.0× 263 1.1× 104 0.7× 83 1.6k
Myoungho Lee South Korea 18 945 1.2× 995 1.6× 185 0.5× 260 1.1× 322 2.1× 99 1.7k
Dwaipayan Biswas Belgium 20 1.2k 1.5× 758 1.2× 237 0.6× 294 1.3× 307 2.0× 75 1.8k
Sarah Ostadabbas United States 21 561 0.7× 196 0.3× 389 1.0× 145 0.6× 191 1.2× 106 1.5k
Yannick Benezeth France 17 785 1.0× 492 0.8× 618 1.6× 235 1.0× 131 0.8× 58 1.7k
Martin Gjoreski Slovenia 18 426 0.6× 435 0.7× 277 0.7× 81 0.3× 289 1.8× 69 1.4k
Se Dong Min South Korea 16 528 0.7× 259 0.4× 85 0.2× 112 0.5× 182 1.2× 56 997
Hsiao‐Lung Chan Taiwan 21 552 0.7× 730 1.2× 148 0.4× 79 0.3× 469 3.0× 82 1.4k
Vaidotas Marozas Lithuania 20 622 0.8× 813 1.3× 68 0.2× 201 0.9× 355 2.3× 110 1.5k
Ren-Guey Lee Taiwan 19 405 0.5× 256 0.4× 311 0.8× 62 0.3× 207 1.3× 71 1.4k

Countries citing papers authored by Shing-Hong Liu

Since Specialization
Citations

This map shows the geographic impact of Shing-Hong Liu'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 Shing-Hong Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shing-Hong Liu more than expected).

Fields of papers citing papers by Shing-Hong Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shing-Hong Liu. 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 Shing-Hong Liu. The network helps show where Shing-Hong Liu may publish in the future.

Co-authorship network of co-authors of Shing-Hong Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Shing-Hong Liu. A scholar is included among the top collaborators of Shing-Hong Liu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shing-Hong Liu. Shing-Hong Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Liu, Shing-Hong, et al.. (2025). Estimating gait parameters from sEMG signals using machine learning techniques under different power capacity of muscle. Scientific Reports. 15(1). 12575–12575. 2 indexed citations
2.
Liu, Shing-Hong, et al.. (2025). Using machine learning models for cuffless blood pressure estimation with ballistocardiogram and impedance plethysmogram. Frontiers in Digital Health. 7. 1511667–1511667. 1 indexed citations
3.
Wang, Jia-Jung, et al.. (2025). Recognition of Knee Osteoarthritis by 1D and 2D Convolutional Neural Networks Using Vibroarthrographic Signals. IEEE Access. 13. 102771–102783. 1 indexed citations
4.
Wang, Jia-Jung, et al.. (2024). Prediction of Vascular Access Stenosis by Lightweight Convolutional Neural Network Using Blood Flow Sound Signals. Sensors. 24(18). 5922–5922. 2 indexed citations
5.
Tan, Tan-Hsu, et al.. (2024). Human Activity Recognition Based on Deep Learning and Micro-Doppler Radar Data. Sensors. 24(8). 2530–2530. 4 indexed citations
6.
Liu, Shing-Hong, et al.. (2024). Estimation of Gait Parameters for Adults with Surface Electromyogram Based on Machine Learning Models. Sensors. 24(3). 734–734. 3 indexed citations
7.
Chin, Chiun-Li, Chia-Chun Lin, Jingwen Wang, et al.. (2023). A Wearable Assistant Device for the Hearing Impaired to Recognize Emergency Vehicle Sirens with Edge Computing. Sensors. 23(17). 7454–7454. 5 indexed citations
8.
9.
Wang, Jia-Jung, et al.. (2023). Signal Quality Analysis of Single-Arm Electrocardiography. Sensors. 23(13). 5818–5818. 4 indexed citations
10.
Liu, Shing-Hong, et al.. (2017). Using impedance-plethysmography technique for cuffless blood pressure measurement. 395–399. 2 indexed citations
11.
Wang, Jia-Jung, et al.. (2016). A vibration-based approach to quantifying the dynamic elastance of the superficial arterial wall. BioMedical Engineering OnLine. 15(1). 40–40. 3 indexed citations
12.
Liu, Shing-Hong, et al.. (2016). Assessment of the endothelial function with changed volume of brachial artery by menstrual cycle. BioMedical Engineering OnLine. 15(1). 106–106. 5 indexed citations
13.
Cheng, Da‐Chuan, et al.. (2016). Accurate Measurement of Cross-Sectional Area of Femoral Artery on MRI Sequences of Transcontinental Ultramarathon Runners Using Optimal Parameters Selection. Journal of Medical Systems. 40(12). 260–260. 3 indexed citations
14.
Cheng, Da‐Chuan & Shing-Hong Liu. (2014). Automated Vessel Boundary Detection Using 3D Expansion of Dynamic Programming.. 197–202. 1 indexed citations
15.
Liu, Shing-Hong. (2011). Motion Artifact Reduction in Electrocardiogram Using Adaptive Filter. Journal of Medical and Biological Engineering. 31(1). 67–72. 27 indexed citations
16.
Liu, Shing-Hong, Jia-Jung Wang, & Da‐Chuan Cheng. (2009). Non-invasive determination of instantaneous brachial blood flow using the oscillometric method. Biomedizinische Technik/Biomedical Engineering. 54(4). 171–177. 3 indexed citations
17.
Liu, Shing-Hong, et al.. (2008). Heart Rate Extraction from Photoplethysmogram Waveform Using Wavelet Multi-resolution Analysis. Journal of Medical and Biological Engineering. 28(4). 229–232. 36 indexed citations
18.
Liu, Shing-Hong, Jia-Jung Wang, & Zu‐Chi Wen. (2007). Extraction of an Arterial Stiffness Index from Oscillometry. Journal of Medical and Biological Engineering. 27(3). 116–123. 5 indexed citations
19.
Wang, Jia-Jung, Chin‐Teng Lin, Shing-Hong Liu, & Zu‐Chi Wen. (2002). Model-based synthetic fuzzy logic controller for indirect blood pressure measurement. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 32(3). 306–315. 22 indexed citations
20.
Liu, Shing-Hong & Chin‐Teng Lin. (2001). A model-based fuzzy logic controller with Kalman filtering for tracking mean arterial pressure. IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans. 31(6). 676–686. 12 indexed citations

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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