IEEE Transactions on
Biomedical Engineering

IEEE Transactions on Biomedical Engineering contains basic and applied papers dealing with biomedical engineering. Papers range from engineering development in methods and techniques with biomedical applications to experimental and clinical investigations with engineering contributions.
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Xiaochuan Pan
Editor-in-chief
Editor-in-chief

"Xiaochuan Pan is currently Professor of Radiology, Radiation & Cellular Oncology, Committee in Medical Physics, the College, and the University of Chicago Medicine Comprehensive Cancer Center at The University of Chicago. He received the BS (1982) and MS (1985) degrees in physics from Beijing University and the Institute of Physics, Science Academy of China and the MS (1988) and PhD (1991) degrees in physics from The University of Chicago. Following post-doc training in medical imaging from 1992-1994 in the Department of Radiology at The University of Chicago, he was appointed as an Assistant Professor of Radiology before being promoted to Associate Professor and Professor of Radiology in 2001 and 2006.

Professor Pan’s research centers on physics, algorithms, and engineering underpinning tomographic imaging and its biomedical and clinical applications. He and his laboratory have conducted research on advanced theory and algorithms for... Read more

"Xiaochuan Pan is currently Professor of Radiology, Radiation & Cellular Oncology, Committee in Medical Physics, the College, and the University of Chicago Medicine Comprehensive Cancer Center at The University of Chicago. He received the BS (1982) and MS (1985) degrees in physics from Beijing University and the Institute of Physics, Science Academy of China and the MS (1988) and PhD (1991) degrees in physics from The University of Chicago. Following post-doc training in medical imaging from 1992-1994 in the Department of Radiology at The University of Chicago, he was appointed as an Assistant Professor of Radiology before being promoted to Associate Professor and Professor of Radiology in 2001 and 2006.

Professor Pan’s research centers on physics, algorithms, and engineering underpinning tomographic imaging and its biomedical and clinical applications. He and his laboratory have conducted research on advanced theory and algorithms for conventional and spectral computed tomography (CT), positron emission tomography (PET), single-photo-emission computed tomography (SPECT), and tomosynthesis especially digital breast tomosynthesis (DBT) and digital lung tomosynthesis (DLT). In collaborating with leading researchers in the field, he and his team have worked on magnetic resonance imaging (MRI) and have also investigated emerging imaging techniques, including electron-paramagnetic resonance imaging (EPRI), phase-contrast CT, and photo-acoustic tomography (PAT), among others. In recent years, he and his team have developed vigorous interest/effort in translating theoretical concepts and methods to biomedical application work that includes developing innovative hardware systems and workflows, enabled by advanced algorithms, with a strong emphasis on the relevance and impact of imaging technological solutions tailored to specific applications of biomedical and/or clinical significance, and have established continuous, close clinical and industrial collaboration and developed robust translational projects to facilitate this effort. Dr. Pan is a Fellow of AAPM, AIMBE, IAMBE, IEEE, OSA, and SPIE."

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Featured Articles

TBME, Volume 69, Issue 5, May 2022
IEEE Transactions on

Biomedical Engineering

MAY 2022
VOLUME 69
NUMBER 5
IEBEAX
69
Impedance Properties of Multi-Optrode Biopotential Sensing Arrays
This work demonstrates the advantage of using an optically inspired, liquid-crystal based biopotential recording technology over a conventional electrode and amplifier system. This optical electrode (optrode) system is favorable for its ability to adjust the input impedance levels in dense-array configurations. We conducted a benchtop experiment and circuit simulations to investigate the relationship between liquid-crystal transducer and interface impedances and the recording-site size in order to better understand the impedance properties of optrodes. This work is the starting point to optimize the layout and configuration of multi-optrode arrays to target various biomedical applications... Read more
Muscle-Specific High-Density Electromyography Arrays for Hand Gesture Classification
Muscle-specific, high-density, flexible electromyography (HD-EMG) electrode arrays were designed and applied to capture the myoelectric activity of key intrinsic hand muscles to classify motions and to allow individual analysis of each muscle. Myoelectric activity was displayed as spatio-temporal maps to visualize muscle activation. Time-domain and temporal-spatial HD-EMG features were extracted to train machine machine-learning classifiers to predict user motion, using data collected from intrinsic hand muscles. The muscle-specific electrode arrays can be combined with EMG decomposition techniques to assess motor unit activity and in applications involving the analysis of dexterous hand motions... Read more
Sleep Monitoring Using Ear-Centered Setups: Investigating the Influence From Electrode Configurations
We combine ear-EEG sleep recordings with a state-of-the-art sleep scoring model, ‘seqsleepnet’, to investigate the upper limits of mobile sleep scoring. We manage to further improve on the state of the art in this field, and perform a detailed analysis of the influence of electrode positioning. From this, we find a general rule of thumb that as long a data set contain EOG information and electrode distance on the order of the width of the head, then good automatic sleep scoring is possible. We also find indications that the obtained automatic scoring may be more reliable than the manual scoring... Read more
Design a Novel BCI for Neurorehabilitation Using Concurrent LFP and EEG Features: A Case Study
This work introduced for the first time a novel BCI that incorporate both intracortical LFP and scalp EEG (named, LFP-EEG-BCI) for motor intention decoding during neurorehabilitation. Concurrent intracortical and scalp signals were collected from a paraplegic patient undergoing motor imagery (MI) neurorehabilitation training. A common spatial filter approach was adopted for feature extraction and a decision fusion strategy was further introduced to obtain the decoding results. Transfer learning approach was also utilized to reduce the calibration. The proposed novel LFP-EEG-BCI may lead to new directions for developing practical neurorehabilitation systems in clinical applications... Read more
Acoustic beam mapping for guiding HIFU therapy in vivo using sub-therapeutic sound pulse and passive beamforming
This work aims at deriving the therapeutic energy distribution within the tissue at the pre-treatment stage to guide the HIFU procedure. A beamforming-based energy mapping technique was established to estimate in-situ beam path of the therapeutic energy in a non-invasive way, which is extremely useful in visualizing the sound beam, especially its focal region, for the HIFU surgery. Effectiveness of this technique has been validated with simulations, in-vitro experiments, ex-vivo experiments and in-vivo tests on a rabbit. The technique is safe, easy to be applied in clinical practices, and can potentially be adapted to other ultrasound-related beam manipulating applications... Read more