勇于冒险 甘于艰苦 乐于和谐

一、活动介绍

为锻炼生物医学工程系学生的科研展示能力，促进学术交流与合作，由生物医学工程系主办，生物医学工程系第二党支部承办的BME研究生学术沙龙火热拉开帷幕。该活动计划每月举行一次，每次由我系两个课题组的研究生或博士后进行学术分享。

三、活动流程

17:00-17:40  Normal talk

17:40-17:50  Short talk

18:00-18:30  活动闭幕及交流讨论

三、本期活动预告

【Normal talk】

肖靖雨（2019级博士生，郭琼玉课题组）

题目：体外再细胞肝脏模型在肝癌栓塞治疗，光热疗法以及免疫治疗中的应用 

报告摘要：

体外再细胞肝脏模型是在脱细胞大鼠肝脏的基础上围绕门静脉三联组回输大小和位置均可控的HepG2细胞集群获得的。这种模型保留了肝脏血管系统和细胞外基质的复杂结构，并同时通过肝静脉血管维持营养和氧气供应的动态生理环境，与肝癌独特的肿瘤微环境非常相似。当细胞回输完成后可以通过门静脉血管栓塞，光热及免疫杀伤进行治疗，有望对肝癌治疗策略进行有效模拟和评估。

报告时间：8月25日，17:00-17:20

杨膺琨（2018级博士生，陈放怡课题组）

报告题目：PDT精准损伤前庭器官治疗顽固性眩晕的方法研究

报告摘要：

顽固性前庭眩晕主要是前庭系统过度敏感或病变造成的。现有的临床治疗手段包括外科手术和局部注射耳毒性药物庆大霉素，通过损伤部分前庭感受器（毛细胞），来降低其敏感度从而减轻和控制眩晕症状。然而，外科手术的损伤较大，耳毒性药物则会在损伤前庭器官的同时也损伤邻近的听觉器官耳蜗而造成听力下降。由于光动力疗法有良好的时间和空间精确性，本课题将其应用于前庭器官的精确损伤。通过本课题组研发的小鼠前庭功能量化设备，我们显示了PDT可以实现定量地损伤小鼠不同部位的前庭器官，并且避免损伤听力。本研究提出了一种新型精准治疗顽固性眩晕的思路，并提供了临床前实验基础。

报告时间：9月28日，17:20-17:40

【Short talk】

报告题目：

Surveillance Camera-based Cardio-respiratory Monitoring for Critical Patients in ICU

报告摘要：

Camera-based vital signs monitoring has been extensively researched in non-medical fields in recent years. Intensive Care Unit (ICU) typically requires continuous monitoring of patients' physiology for alarming the emergency such as patient deterioration or delirium. In this paper, we propose to use the surveillance closed-circuit television (CCTV) cameras installed in ICU for cardio-respiratory monitoring of critically-ill patients, thus created a first clinical video dataset (including 10 deteriorated patients) in ICU using CCTV cameras. Along with the dataset, a video processing framework with the latest core algorithms designed for pulse and respiratory signal extraction has been demonstrated. A joint Region-of-Interest optimization approach using pulsatile living-skin maps and respiratory maps was proposed to improve the vital signs monitoring for ICU patients. A motion intensity based quality metric was designed to reject measurement outliers induced by patient motion or nurse operation. Based on the valid measurements selected by the metric, the overall Mean Absolute Error for heart rate is 1.7 bpm, and for breathing rate is 1.6 bpm. Preliminary clinical validations show that robust cardio-respiratory monitoring is indeed feasible for CCTV cameras in ICU, and such a warding solution can be quickly integrated into current hospital information systems for large-scale deployment, by leveraging the existing hardware and infrastructures of the Internet of Medical Things.

报告时间：9月28日，17:40-17:45

报告题目：

A Multi-modal Clinical Dataset for Critically-ill and Premature Infant Monitoring: EEG and Video

报告摘要：

The comprehensive monitoring of cardio-respiratory and neurological events of premature infants is desired for the Neonatal Intensive Care Unit (NICU). Video-based infant monitoring is an emerging tool for NICU as it eliminates skin irritations and enables new measurements like pain assessment. A multi-modal clinical dataset across the measurement of EEG and videos will be helpful in developing novel monitoring solutions for infant care. In this paper, we created such a dataset by simultaneously collecting the EEG signals and videos data from critically ill and preterm infants in NICU. Along with the recordings, we used the video-based cardio-respiratory measurements (heart rate and respiratory rate) to examine the validity of video recordings. We employed a classical video-based physiological measurement framework called Spatial Redundancy in combination with living-skin detection to measure the vital signs of recorded infants. The pilot measurements show the feasibility as well as the challenges that need to be addressed in algorithmic design in the next step. The dataset will be made publicly available to facilitate the research in this area. It will be useful for studying the video-based infant monitoring and its fusion with EEG, which may lead to new measurements such as a neonatal PSG for infant sleep staging and disease analysis (e.g. neonatal encephalopathy, neonatal respiratory distress syndrome).

报告时间：9月28日，17:45-17:50

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