People

Dr Xin Li

Lecturer in Biomedical Engineering

School/Department: Engineering, School of

Telephone: +44 (0)116 229 7380

Email: xin.li@leicester.ac.uk

Address: E1001, Engineering Building

Web:

Research gate

Group webpage

Profile

I am a Lecturer in Biomedical Engineering jointly appointed at the School of Engineering and Department of Cardiovascular Sciences.

I obtained BEng in Electrical Information Engineering from the University of Science and Technology Beijing 2011 and MSc in Electrical Electronic Engineering from the University of Leeds in 2012. I completed my PhD in Biomedical Engineering from the University of Leicester in 2016. I worked as Research Associate from 2016 and Lecturer from October 2019. 

 

 

Research

Research Interests

My research interest focuses on digital signal processing and intelligent algorithms of biological and biomedical signals:

Improving target identification for catheter ablation using advanced signal processing techniques and intelligent algorithms for human persistent atrial fibrillation

Algorithms development for novel ECG risk makers for sudden cardiac death

Machine learning Classification and Regression

Recurrent Quantification Analysis

Mapping and Cardiac Arrythmias

Body surface potential mapping

Electrocardiogram (ECG) analysis

Publications

(0)

Chu, G. S*., X. Li*, P. J. Stafford, F. J. Vanheusden, J. L. Salinet, T. P. Almeida, N. Dastagir, A. J. Sandilands, P. Kirchhof, F. S. Schlindwein and G. A. Ng.Simultaneous Whole-Chamber Non-contact Mapping of Highest Dominant Frequency Sites During Persistent Atrial Fibrillation: A Prospective Ablation Study. Front. Physiol, 2022, Vol 13. doi:10.3389/fphys.2022.826449

Pooranachandran V, Nicolson W, Vali Z, Li X, Ng G. Non-invasive markers for sudden cardiac death risk stratification in dilated cardiomyopathy. Heart,  20 October 2021. doi: 10.1136/heartjnl-2021-319971

Z. Jiang, F. Zhou, A. Zhao, X. Li, L. Li, D. Tao, X. Li, H. Zhou, "Muti-view Mouse Social Behaviour Recognition with Deep Graphic Model," in IEEE Transactions on Image Processing, 2021, doi: 10.1109/TIP.2021.3083079.

Li, X., Chu, G.S, Almeida, T.P., Vanheusden F.J., Salinet, J., Dastagir, N., Mistry, A. R., Vali, Z, Sidhu B, Starfford, P. J., Schlindwein, F.S., Ng, G.A., 2021. Automatic Extraction of Recurrent Patterns of High Dominant Frequency Mapping during Human Persistent Atrial Fibrillation. Front. Physiol, 2021 Vol. 12 Issue 286, DOI: 10.3389/fphys.2021.649486

Almeida, T.; Soriano, D.; Mase, M.; Ravelli, F.; Bezerra, A.; Li, X.; Chu, G.; Salinet, J.; Stafford, P.; Andre Ng, G.; Schlindwein, F.; Yoneyama, T. Unsupervised Classification of Atrial Electrograms for Electroanatomic Mapping of Human Persistent Atrial Fibrillation. IEEE Transactions on Biomedical Engineering 2020, 1-1. https://doi.org/10.1109/TBME.2020.3021480.

Li, X., Almeida, T.P., Dastagir, N., Guillem, M.S., Salinet, J., Chu, G.S., Stafford, P.J., Schlindwein, F.S., Ng, G.A., 2020. Standardizing Single-Frame Phase Singularity Identification Algorithms and Parameters in Phase Mapping During Human Atrial Fibrillation. Front. Physiol. 11, 869. doi: doi.org/10.3389/fphys.2020.00869

Almeida, T.P., Li, X., Soriano, D.C., Schlindwein, F.S. and Ng, G.A. (2020), Pitfalls in the definition of complex fractionated atrial electrograms for atrial fibrillation studies. J Cardiovasc Electrophysiol, 31: 373-374. doi:10.1111/jce.14302

O’Shea, Holmes, Yu, Winter, Wells, Correia, Boukens, Chu, Li, Ng, Kirchhof, Fabritz, Rajpoot, Pavlovic, ElectroMap: High-throughput open-source software for analysis and mapping of cardiac electrophysiology, Scientific Reports - Nature 2019;9:1389.

Vanheusden FJ, Chu GS, Li X, Salinet J, Almeida TP, Dastagir N, et al. Systematic differences of non-invasive dominant frequency estimation compared to invasive dominant frequency estimation in atrial fibrillation. Comput Biol Med. 2019;104:299-309.

Ng GA, Mistry A, Li X, Schlindwein FS, Nicolson WB. LifeMap: towards the development of a new technology in sudden cardiac death risk stratification for clinical use. Europace. 2018;20(FI2):f162-f70.

Almeida TP, Schlindwein FS, Salinet J, Li X, Chu GS, Tuan JH, et al. Characterization of human persistent atrial fibrillation electrograms using recurrence quantification analysis. Chaos. 2018;28(8).

Salinet JL, Schindwein FS, Stafford PJ,Almeida TP, Li X, Vanheusden FJ, et al. Propagation of Meandering Rotors Surrounded by High Dominant Frequency Areas in Persistent Atrial Fibrillation. Heart Rhythm. 2017

Li X, Salinet JL, Almeida TP, Vanheusden FJ, Chu GS, Ng GA, et al. An interactive platform to guide catheter ablation in human persistent atrial fibrillation using dominant frequency, organization and phase mapping. Computer Methods and Programs in Biomedicine. 2017;141:83-92.

 
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Supervision

I am looking for talented self-motivated PhD students and researchers to work in the field of intelligent biomedical signal processing in complex cardiac arrhythmias. If you're interested feel free to contact me.

Supervision

PhDs:

Mohamed Rumi Ismail (PT) - started 2021

Noor N Qaqos - started 2022

PDRAs:

Long Chen - started 2021

MSCs (Engineering):

Xuanlin Chen - 2020 - Distinction & best student award

Snehal Sanjay Shevate - 2020

BSCs (Medical): LUMRS Link projects

Jason R Armstrong - started 2021

Marcus O Panchal - started 2021

Ibrahim A Nasser - started 2021

Jakevir S Shoker - started 2021

Visiting students:

Jack Hall - started 2021

Teaching

EG2004 - Engineering Experimentation and Analysis - Academic Lead

EG1006 - Engineering Design and Experimentation - Academic Lead

EG7020 - MSc Individual Project BS3X00 - 3rd year projects (School of Biological Sciences)

Press and media

Call for Papers

Submissions are welcome to our research topic in Frontiers in Physiology on Computational Methods in Cardiac rhythm disturbances.

Link: https://www.frontiersin.org/research-topics/18724/exploring-mechanisms-of-cardiac-rhythm-disturbances-using-novel-computational-methods-prediction-cla

Deadline: 30 Sept 2021

Awards

Young Investigator Competition Finalist at Heart Rhythm Congress 2017

MRC Proximity to Discovery (P2D): Adhoc Industry Engagement Activities 2016/17. £3k (PI)

MRC Confidence in Concept funds 2017 (LD3): 2017/18. £42k (NC)

Journal Paper selected as Editor's Choice - Computer Methods and Programs in Biomedicine - April 2017

MRC Confidence in Concept funds 2019 (LD3): Deep learning for refining LifeMap 2019/20. £43k (CI)

British Heart Foundation Project Grant (PG/18/33/33780). 2018/20. £93k (NC)

Biomedical Catalyst DPFS Developmental Pathway Funding (MR/S00582X/1). 2019/22. £1m (NC)

IAX Events and Meetings Funding. 2019. £1k (PI) ECR and research staff funding - Doctoral College - Short-term visiting grants 2019. £4k (PI)

The van Geest Heart and Cardiovascular Diseases Research Fund. ""Deep learning methods for early detection of myocardial ischemia using digital and paper ECGs"" 2020/21 £11.8k (PI)

MRC Confidence in Concept funds 2020 (LD3): Optimising deep neural networks for fully automating a novel technology for risk stratification of sudden cardiac death. 2020/21. £43k (CI)

Knowledge Exchange Impact and Proof of Concept fund: Towards utilising a novel non-invasive test for risk stratification for sudden cardiac death. 2022. £5.5k (CI).

*(PI: principle investigator; CI: co-investigator; NC: named candidate)

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