郝冬梅 ，博士生/硕士生导师
E-mail：haodongmei@bjut.edu.cn
通讯地址：
北京市朝阳区平乐园100号，
威尼斯wns.8885556威尼斯wns.8885556，北京100124
教育背景
先后获得天津大学、中国协和医科大学生物医学工程专业工学学士、理学硕士，威尼斯wns.8885556模式识别与智能系统工学博士。
工作经历
先后在首都医科大学生物医学工程系、威尼斯wns.8885556生命科学与生物工程学院、威尼斯wns.8885556威尼斯wns.8885556工作。
研究方向
智能化生理测量，医学模式识别
课程教学
电路分析基础，医学仪器综合设计，医学模式识别与人工智能。
奖项荣誉
威尼斯wns.8885556优秀硕士论文指导奖7项、本科特优毕业设计 1 项 ；威尼斯wns.8885556优秀教育教学成果奖一等奖和二等奖；北京市科技进步奖三等奖等。
主要科研项目
[1] 基于子宫肌电的早产预测研究，比尔&梅琳达盖茨基金
[2] 腹电式动态胎儿监护仪，国家重点研发计划
[3] 手抓握时大脑皮层与上肢肌肉间信息传输的研究，国家自然科学基金
[4] 皮下脂肪厚度检测仪的研制，北京市教委项目
主要论文论著
[1] Xiaoxiao Song, Xiangyun Qiao, Dongmei Hao* et al. Automatic Recognition of Uterine Contractions with Electrohysterogram Signals Based on the Zero-Crossing Rate. Scientific Reports. 2021
[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. biocybernetics and biomedical engineering, 2020, 40:1–11
[3] Dongmei Hao*, Qian Qiu, Xiya Zhou et al. Application of decision tree in determining the importance of surface electrohysterography signal characteristics for recognizing uterine contractions. Biocybernetics and biomedical engineering, 2019, 39: 806– 813
[4] Dongmei Hao*, Jin Peng, Ying Wang et al. Evaluation of convolutional neural network for recognizing uterine contractions with electrohysterogram. Computers in Biology and Medicine. 2019, 113: 103394
[5] Dongmei Hao*, Yang An, Xiangyun Qiao et al. Development of Electrohysterogram Recording System for Monitoring Uterine Contraction. Journal of Healthcare Engineering, 2019, 4230157
[6] Jin Peng, Dongmei Hao*, Haipeng Liu et al. Preliminary study on the efficient electrohysterogram segments for recognizing uterine contractions with convolutional neural work. BioMed Research International. 2019, 3168541
