Current Professional Societies

Member of Education and Training Branch of China Medical Equipment Association

Research Areas

1. Research and Development of Medical Electronic and Information Processing Technology and Intelligent Medical Equipment;

2. Noninvasive Detection of Pulse Wave Hemodynamics and Its Clinical Application;

3. Research on the Detection of Exercise Cardiovascular Function and the Monitoring and Evaluation of Exercise Load.

Honors

1. Third prize of Beijing Science and Technology Award, 2011;

2. Third prize of Chinese Medical Science and Technology Award, 2012;

Publications

1. Y. Meng, L. Yang, S. Zhang, G. H. Wu, X. H. Liu, D. M. Hao, Y. M. Yang and X. W. Li. Changes in Gaussian Modelling Parameters of PPG Pulse During Healthy Pregnancy. Journal of Medical Imaging and Health Informatics. 2021, 11: 1-4.

2. G. Sun, L. Yang, W. W. Wang, S. Zhang, Z. C. Luo, G. H. Wu, X. H. Liu, D. M. Hao, Y. M. Yang and X. W. Li. An Algorithm for the Noninvasive and Personalized Measurement of Microvascular Blood Viscosity Using Physiological Parameters. Biomed Res Int. 2020: 7013212.

3. L. Yang, G. Sun, A. R. Wang, H. Q. Jiang, S. Zhang, Y. M. Yang, X. W. Li, D. M. Hao, M. Z. Xu and J. Shao. Predictive Models of Hypertensive Disorders in Pregnancy Based On Support Vector Machine Algorithm. Technol Health Care. 2020, 28(S1): 181-186.

4. L. Yang, J. Z. Yang, S. Zhang, et al. Studies on Pulse Wave Model Based On Multiple Gaussian Decomposition. Journal of Medical Imaging and Health Informatics. 2020, 10(3): 641-645.

5. L. Yang, Q. Luo, Y. Lu, et al. Individualized Sports Management Scheme for Pregnant Women in China. Journal of Mechanics in Medicine and Biology. 2019, 19(8): 1940055.

6. K. Y. Li, S. Zhang, L. Yang, et al. Changes of Arterial Pulse Waveform Characteristics with Gestational Age during Normal Pregnancy. Scientific Reports. 2018, 8(15571).

7. K. Y. Li, S. Zhang, L. Yang, et al. Gaussian Modelling Characteristics of Peripheral Arterial Pulse: Difference between Measurements from the Three Trimesters of Healthy Pregnancy. Journal of Healthcare Engineering. 2018, (1308419).

8. Q. Luo, L. Yang, S. Zhang, et al. Monitoring and Evaluation of Sports Load for Primary and Middle School Students. Journal of Mechanics in Medicine and Biology. 2018.

9. A. R. Wang, L. Yang, W. M. Wen, et al. Gaussian Modelling Characteristics Changes Derived from Finger Photoplethysmographic Pulses during Exercise and Recovery. Microvasc Res. 2018, 116: 20-25.

10. A. R. Wang, L. Yang, W. M. Wen, et al. Quantification of Radial Arterial Pulse Characteristics Change during Exercise and Recovery. J Physiol Sci. 2018, 68(2): 113-120.

11. G. F. Li, S. Zhang, L. Yang, et al. Influence of Gestational Age and Time of Day in Baseline and Heart Rate Variation of Fetuses. Technology and Health Care. 2016, 242: S471-S476.

12. G. F. Li, S. Zhang, L. Yang, et al. Computerized Analysis of Acceleration Parameter for the Non-Stress Test Normal and Potentially Abnormal Fetuses. Computer Assisted Surgery. 2016, 211(1): 1-5.

13. W. J. Wu, L. Yang, S. Zhang, et al. Development of a New Characteristic Parameter - Waveform Index of Finger Blood Volume Pulse. Computer Assisted Surgery. 2016, 211: 6-10.

14. A. R. Wang, L. Yang, C. Y. Liu, et al. Athletic Differences in the Characteristics of the Photoplethysmographic Pulse Shape: Effect of Maximal Oxygen Uptake and Maximal Muscular Voluntary Contraction. Biomed Res Int. 2015: 752570.

15. T. T. Yan, L. Yang, S. Zhang, et al. Detecting Differences in Volume Pulse Wave Parameters among Fingers and Toes in Four Different Postures. Bio-Medical Materials and Engineering. 2015, 261(s1): S389-S394.

16. L. Yang, W. Y. Zhang, L. Zhang, et al. Gestational Hypertension Risk Evaluation Based on Epidemiological, Biochemical, and Hemodynamic Factors. Clin Exp Obstet Gynecol. 2013, 40(1): 61-65.

Personal statement

Yang Lin has been engaged in Biomedical Engineering Research for more than 10 years. He always takes "the combination of production, learning and research" as the development route, and pays attention to the combination of academic theoretical research and practical application. His research mainly includes non-invasive detection of pulse wave hemodynamics, detection of cardiovascular function of athletes, monitoring and evaluation of youth's exercise load, monitoring of gestational hypertension, prediction of premature delivery by uterine myoelectricity, research and development of intelligent fetal monitoring system, etc.

Yang Lin has presided over and participated in more than 20 research projects. In addition to more than 100 published papers and 20 patents as the lead author and corresponding author, he translated the book TheUse and Safety of Medical Device, which fills the gap of lack of professional medical device safety guidebooks in China.

Yang Lin has undertaken the project of "Monitoring and Evaluation of Sports Load in Primary and Secondary School Students", developed a wristband heart rate monitor during doing sports, established a physiological evaluation and monitoring system, and provided the foundation for physical exercise process monitoring and evaluation. It has been successfully applied in many primary schools in Beijing and is up to the local standards in Beijing. This study is of great significance to promote the development of physical education, improve the physical quality of primary and secondary school students, and promote the healthy growth of young people.

Yang Lin's research group used pulse wave hemodynamics to predict gestational hypertension and developed MP gestational hypertension monitoring system. On this basis, Yang Lin, together with researchers in many hospitals and Beijing YES Medical Equipment Co., Ltd., further carried out the research on the risk monitoring method and device of gestational hypertension based on physical and chemical and hemodynamic information, which was successfully used in many hospitals. This study can be wildly used to study the factors of gestational hypertension, predict and monitor gestational hypertension, guide the scientific and reasonable clinical intervention, and reduce the rate of maternal and infant diseases.

As a major participant, Yang Lin participated in the research on the prediction of premature birth by EMG, which was supported by the Bill and Melinda Gates Foundation's Science and Technology Innovation Challenge Project and the fund for key research and development project by the Ministry of Science and Technology of China. At present, he is researching the recognition and classification of the EMR data based on deep learning and the classification model of the fetal state. The research results are applied to obstetric clinical and family monitoring, providing technical support for ensuring the safety of mother and fetus and improving the quality of childbirth.