Changqing Jiang
Tsinghua University
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Publication
Featured researches published by Changqing Jiang.
IEEE Transactions on Neural Systems and Rehabilitation Engineering | 2011
Changqing Jiang; Luming Li; Hongwei Hao
A new form of deep brain stimulation (DBS) electrode was proposed that was made of carbon nanotube yarns (CNTYs). Electrode interface properties were examined using cyclic voltammetry (CV) and electrochemical impedance spectrum (EIS). The CNTY electrode interface exhibited large charge storage capacity (CSC) of 12.3 mC/cm2 which increased to 98.6 mC/cm2 after acid treatment, compared with 5.0 mC/cm2 of Pt-Ir. Impedance spectrum of both untreated and treated CNTY electrodes showed that finite diffusion process occurred at the interface due to their porous structure and charge was delivered through capacitive mechanism. To evaluate stability electrical stimulus was exerted for up to 72 h and CV and EIS results of CNTY electrodes revealed little alteration. Therefore CNTY could make a good electrode material for DBS.
Journal of Neural Engineering | 2013
Changqing Jiang; Hongwei Hao; Luming Li
OBJECTIVE Deep brain stimulating (DBS) is a rapidly developing therapy that can treat many refractory neurological diseases. However, the traditional DBS electrodes which are made of Pt-Ir alloy may induce severe field distortions in magnetic resonance imaging (MRI) which leads to artifacts that will lower the local image quality and cause inconvenience or interference. A novel DBS electrode made from carbon nanotube yarns (CNTYs) is brought up to reduce the artifacts. This study is therefore to evaluate the artifact properties of the novel electrode. APPROACH We compared its MR artifact characteristics with the Pt-Ir electrode in water phantom, including its artifact behaviors at different orientations as well as at various off-center positions, using both spin echo (SE) and gradient echo (GE) sequences, and confirmed its performance in vivo. MAIN RESULTS The results in phantom showed that the CNTY electrode artifacts reduced as much as 62% and 74% on GE and SE images, respectively, compared to the Pt-Ir one. And consistent behaviors were confirmed in vivo. The susceptibility difference was identified as the dominant cause in producing artifacts. SIGNIFICANCE Employing the CNTY electrode may generate much less field distortion in the vicinity, improve local MR image quality and possibly be beneficial in various aspects.
Neuromodulation | 2016
Bo Li; Changqing Jiang; Luming Li; Jian-guo Zhang; Da-Wei Meng
In the treatment of Parkinsons disease for deep brain stimulation (DBS), the subthalamic nucleus (STN) is the most important target on a specific brain nucleus. Although procedural details are well established, targeting STN remains problematic because of its variable location and relatively small size.
Neuromodulation | 2015
Changqing Jiang; Xiaolong Mo; Yantao Dong; Fan-Gang Meng; Hongwei Hao; Jian-guo Zhang; Xiqiao Feng; Luming Li
Lead fracture is a common and troublesome hardware‐related complication in deep brain stimulation therapy. Frequent cervical movements are suspected as the main cause, but the underlying mechanisms are still unclear. We propose the integrity of the helical structure of the lead wires is important and conduct systematic experiments to demonstrate this. We aim to provide a new view on how lead fracture takes place.
international conference on reliability maintainability and safety | 2011
Changqing Jiang; Xiongwei Wen; Hongwei Hao; Luming Li
Reliability of a deep brain stimulator is very important. In this paper, the reliability performance of the extension and lead of a deep brain stimulator was evaluated based on an accelerated flexing test, and through a weakness detection, segment level improvement and assembly level improvement procedure, failure frequency was reduced and bending count till failure values got significant increased for the weak points of the extension and lead. The deep brain stimulator is now under clinical trial, and the results showed that the method and improvement strategy is helpful to reliability design and process improvement.
Biomedical Engineering Online | 2015
Yi Guo; Wanru Duan; Chao Ma; Changqing Jiang; Yikuan Xie; Hongwei Hao; Renzhi Wang; Luming Li
Electronics Letters | 2014
Changqing Jiang; Xiaolong Mo; Jianqi Ding; Yantao Dong; Feng Zhang; Hongwei Hao; Luming Li
Archive | 2013
Luming Li; Changqing Jiang; Hongwei Hao
Chinese Science Bulletin | 2014
Fu Xu; Xiaolong Mo; Sen Wan; Changqing Jiang; Hongwei Hao; Luming Li
Archive | 2013
Luming Li; Changqing Jiang; Hongwei Hao