- Date: November 3, 2020
- Venue: Shenzhen World Exhibition & Convention Center
- Organizer: Messe Muenchen Shanghai Co., Ltd.
- Scale: 200
- Status and trend of medical electronics
Wearable device and IOT for healthcare
AI in medicine and 5G communication
Siemens ⦁ Mindray Medical ⦁ Medtronic ⦁ CONTEC ⦁ ANKE ⦁ Besta Medical ⦁
Icar Medical ⦁ BNC Technologies ⦁ Noble Medical ⦁ SinoScape ⦁ Unitech ⦁
wootop medical ⦁ Smith Medical ⦁ Huawei ⦁ Schneider Electric
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Secretary General | China Association for Medical Devices Industry
Director of 5G Innovation Center Smart Medical Industry | China unicom
Shanghai Institute for Advanced Communication and Data Science, SICS | Dean
Professor | Shanghai University
CEO of UIH America, Inc | United IUnUnited Imaging Healthcareited Imaging HeUnited Imaging Healthcarealthcaremaging Healthcare
Dr. Hongdi Li is the CEO of United Imaging Healthcare America, Inc. located in Texas, and Senior VP of Shanghai United Imaging Healthcare Co. Ltd. Before he joined United Imaging in 2013, Dr. Li was a professor in Diagnostic Imaging division at the University of Texas, M.D. Anderson Cancer Center, where he spent 17 years in the development of ultra-high resolution and high sensitivity advanced molecular imaging instrumentation imaging.
Dr. Li has over 130 publications and about 20 patents, his research interests are the advanced technologies and clinical applications of ultra-high resolution and high sensitivity PET/CT and PET/MRI. It is the project leader of the world's first total-body dynamic PET/CT (uEXPLORER Explorer).
Advancing Molecular Imaging Through Innovation
The presentation introduces the world's most advanced molecular imaging technology and some prospective clinical research explorations in translational medicine.
Professor | Huazhong University of Science and Technology
Chief Scientist | Hubei Raysolution Digital Medical Imaging Technology Co. Ltd.
Qingguo Xie received his B. Sc. in Industrial Automation from Huazhong University of Science and Technology (HUST) in 1994, M. Sc. in Industrial Automation from Dalian University of Technology in 1997, and Ph. D. in Electrical Engineering from the HUST in 2001.
Dr. Xie is currently a distinguished professor in Department of Biomedical Engineering at the HUST, Wuhan National Lab for Optoelectronics (WNLO), and Mediterranean Neurological Institute (NEUROMED).
"Positron emission tomography (PET) is a functional imaging modality with enormous applications in both clinical diagnosis and biomedical research. In a traditional PET system, scintillation pulses are too fast to be accurately digitized using normal analog-to-digital converter (ADC) techniques. Thus, the data acquisition (DAQ) system resorts to mixed-signal front-end electronics to shape and process signals, which both deteriorate the data quality and complicate the system structure. System designs are hindered by the lack of flexibility, scalability and upgradability. PET’s application potentials are hardly fulfilled.
To address this problem, we have proposed the multi-threshold voltage (MVT) method which can recover accurate digital signal from samples of a scintillation pulse at several pre-defined points. Using MVT as the cornerstone, the all-digital PET is proposed as a new generation of nuclear imaging techniques. All-digital and modularized basic detector modules (BDMs) were developed. A BDM is a self-sufficient system, capturing a gamma photon and transferring the MVT samples to the server. The whole data-processing procedure, from pulse recovering and event coincidence to data correction and image-reconstruction, are all performed by software on the server, or even the cloud. The PET’s hardware is greatly simplified: it is no more than a group of BDMs put together per a desired geometry. On the other hand, the PET’s capability is much enhanced: its functions are defined by algorithm modules, which can be easily expanded and upgraded. PET system design has never been so simple and flexible.
Thanks to MVT digitizer, the all-digital PET provides scientists and engineers their “LEGO bricks” to build any system they like. A totally new landscape of PET applications is around the corner."
Principal Engineer | GE Healthcare China
WangXueli PH.D. Principal Engineer at GE Healthcare. Professor of Engineering. More than 18 years, focus on CT system & imaging chain R&D, from 1 to 256 row. Hold over 50 global patent filings in CT field. GEHC China Patent Maverick, Most innovative Award, Top Inventor Award etc. Good at innovation R&D/driving/training/IP protection.
Special experience: six-sigma. hold TRIZ training workshop over 13 years. Gradulated from ShanDong University, ZheJiang University and Xi'an JiaoTong university. Major in Mechanical Engineering, Signal Processing, and Image Procesing.
Principles and Applications of CT Spectral Imaging
CT Gemstone Spectral Imaging: Principle and Applications, 1.Traditional CT Imaging. 2.GSI Principle. 3. GSI Advanced Applications in clinic.
CEO | Shanghai Zhishu Enterprise Development Co., Ltd
The Bachelor of power system and automation of Shanghai Jiaotong University , with 15 years of GE Medical experience, covering the whole process of sales, market, service and R&D, has experienced two core projects of operation and business leadership training, Six Sigma Black Belt master, senior expert in the medical industry, product and service with sales management over $700 million, senior image center operation expert, the founder of huayicom company.
Internet of Things cloud platform of Medical equipments
Medical equipment has high technical content, high compliance requirements, complex types, diverse uses, scattered applicable standards and regulations, scattered locations, and large product life cycle span, which cause great challenges in the life cycle management, circulation, use, traceability, service and supervision of medical equipment products.
The industrial Internet application service platform for medical equipment management (hereinafter referred to as ZhiShu cloud) is oriented by the requirements of medical equipment life cycle management, and uses the cutting-edge technologies such as Internet of things, cloud computing, big data analysis, etc. Through the connection of SaaS application platform in the industrial Internet industry, it realizes scene online and data-based, and completely solves the industry difficulties that cannot be solved by traditional management methods To ensure the use safety of medical equipment, improve the rationality of resource allocation and efficiency of resource utilization, and build the industry data intelligent supervision application.
To carry out the innovation practice in the field of standardization of equipment account data of medical institutions, fill in the industry gap, and lay the foundation for the intelligent operation and management of master data in the secondary node industry of industrial Internet standard analysis of medical devices industry; realize the efficiency of the construction of equipment archives in stock more than 10 times higher than the traditional way; reduce the ineffective communication time of maintenance process by 90%; and solve the efficiency intelligent management The comprehensive efficiency of the active equipment can be improved by at least 10%, which can create an average value of more than 5 million per year for a tertiary hospital.
Professor | Fudan University
Jiawei Xu received the M.Sc. and the Ph.D. degrees both in electrical engineering from the Delft University of Technology, The Netherlands, in 2006 and 2016, respectively.
From 2006 to 2018, he was a senior researcher and project manager at imec/Holst Centre, Eindhoven, The Netherlands, where he led the IC design activities for noninvasive brain monitoring. From November, 2018, he joined the State Key Lab of ASIC & System at Fudan University, Shanghai, China, as a Professor.
He has published over 30 papers in journals and conferences, his research interests include low power biomedical ASIC for wearable devices, high precision amplifier, sensor interfaces. He was a recipient of the IEEE Solid-State Circuits Society (SSCS) Predoctoral Achievement Award in 2014 and the imec Scientific Excellence Award in 2014.
Low Power Biomedical ICs for Wearable Healthcare
The expectations towards better care, cure and prevention of chronic diseases has accelerated the rapid development of microelectronics technologies. Wearable medical devices have entered our daily life routine. As the heart of biomedical devices, low power analog front-end integrated circuits are responsible for measuring a variety of physiological vital signs (e.g. EEG, ECG, bio-impedance and PPG) and often determine the overall performance of the system. On the other hand, the analog front-end IC is in contact with the human body through the sensor, which is subjected to various interferences from the environment. The biggest challenge of biomedical IC design is to achieve medical-grade signal acquisition while consuming the lowest power. This talk will discuss the principles and key techniques to measure multimodal physiological signals from the electrical engineering point of view with some design examples.