Hao Dongmei

Personal profile

Name: Hao Dongmei

Gender: Female

Degrees: Ph.D.

Title: Professor

E-mail: haodongmei@bjut.edu.cn

Current Professional Societies

1. Member of Chinese Society of Biomedical Engineering;

2. Member of China Instrument and Control Society;

3. Member of China Association of Medical Equipment.

Research Areas

1.Intelligent Physiological Measurement and Clinical Transformation;

2. Medical Instrument Development;

3. Medical Pattern Recognition.


1.‘Chinese Medical Science and Technology Award’ for an outstanding clinical study of preeclampsia with hemodynamics;

2. The students I have supervised received 60+ Awards including the Science and Technology Innovation, Excellent Graduation Thesis, National Scholarship for Graduates, Beijing Outstanding Graduates, Academic Excellence, Merit Student and Excellent Student Cadre.


[1]Xiaoxiao Song, Xiangyun Qiao, Dongmei Hao* et al. Automatic Recognition of Uterine Contractions with Electrohysterogram Signals Based on the Zero-Crossing Rate.Sci Rep,2021, 11:1956

[2]Jin Peng, Dongmei Hao*, Lin Yang et al. Evaluation of electrohysterogram measured from different gestational weeks for recognizing preterm delivery: a preliminary study using random Forest.Biocybern Biomed Eng, 2020,40:1–11

[3]Dongmei Hao, Xiaoxiao Song, Qian Qiu et al. Effect of electrode configuration on recognizing uterine contraction with electrohysterogram: Analysis using a convolutional neural network.Int J Imag Syst Tech,2020, 10: 1-9

[4]Dongmei Hao*, Jin Peng, Ying Wang et al. Evaluation of convolutional neural network for recognizing uterine contractions with electrohysterogram.Comput Biol Med2019; 113: 103394

[5]Dongmei Hao*, Jin Peng, Haipeng Liu et al. Preliminary study on the efficient electrohysterogram segments for recognizing uterine contractions with convolutional neural work.BioMed Res Int.2019; https://doi.org/10.1155/2019/3168541

[6]Dongmei Hao*, Qiang Qiu, Xiya Zhou et al. Application of decision tree in determining the importance of surface electrohysterography signal characteristics for recognizing uterine contractions.Biocybern Biomed Eng, 2019; 39: 806– 813

Personal Statement

Hao Dongmei, the professorand doctoral supervisor, is the dean of Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation. She has been leading projects funded by the Bill & Melinda Gates Foundation, the National Key R&D Program of China, the National Natural Science Foundation of China, and the Beijing Natural Science Foundation. She published 70+ scientific papers on peer-reviewed prestigious journals and obtained 10+ patents in the field of biomedical engineering. She has close connections with the leading hospitals and high-tech companies in China and has successfully commercialized the Monitoring System for Hypertensive Disorders of Pregnancy.