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IEEE Transactions on Biomedical Engineering, July 2016

Caitlin N.‎ Teague, Sinan Hersek, Hakan Töreyin, Mindy L.‎ Millard-Stafford, Michael L.‎ Jones, Geza F.‎ Kogler, Michael N.‎ Sawka, and Omer T.‎ InanGeorgia Institute of Technology, USA
The research reported in this paper was highlighted in several major news pieces including Scientific American and BBC Radio.
We present the framework for wearable joint rehabilitation assessment following acute knee injury based on the measurement of acoustical emissions from the knee with miniature microphones.‎ The knee is one of the most frequently injured parts of the body.‎ Additionally, knee injuries are among the most severe in terms of time of restricted and ‎/ or total loss of participation among athletes, military personnel, and other populations engaged in high performance activities.‎ This work can enable, for the first time, wearable sensing of knee joint acoustical emissions for longitudinal monitoring of in-depth knee joint health parameters for patients rehabilitating an acute knee injury.‎ Read More
 
 
Methods for ۲D and 3D Endobronchial Ultrasound Image Segmentation

Xiaonan Zang, Rebecca Bascom, Christopher Gilbert, Jennifer Toth, and William E.‎ Higgins, The Pennsylvania State University, USA,  Volume: 63, Issue:7, Pages: 1426-1493
Endobronchial ultrasound (EBUS) is now commonly used for cancer-staging bronchoscopy.  Unfortunately, EBUS is challenging to use, and interpreting EBUS video sequences is difficult.‎ To assist with these issues, we propose computer-based methods for segmenting ۲D EBUS frames and 3D EBUS sequences.‎  Both the ۲D and 3D segmtentation methods compare very favorably to ground-truth results for a human lung-cancer patient EBUS database.‎   We also demonstrate the potential of the methods for EBUS localization in a multimodal image-guided bronchoscopy system. Read More
 

 

QRS Detection Algorithm for Telehealth Electrocardiogram Recordings
Heba Khamis,Robert Weiss, Yang Xie, Chan-Wei Chang, Nigel H.‎ Lovell, and Stephen J.‎ Redmond, 

 UNSW Australia, Volume 63, Issue 7, Pages:1377-1388

QRS detection algorithms are needed to analyze electrocardiogram (ECG) recordings.‎ We describe a QRS detection algorithm that is suitable for clean clinical ECGs as well as poorer quality telehealth ECG. We evaluate the performance of the algorithm on both clinical and telehealth ECGs. The results demonstrate that the proposed algorithm is superior to published algorithms which have inadequate performance on poorer quality telehealth ECGs. The proposed algorithm could be used to manage increasing telehealth ECG analysis workloads.‎ A data repository of annotated telehealth ECGs has been made available on-line for future algorithmic development and testing.‎  Read More

 

Towards a Portable Cancer Diagnostic Tool Using a  Disposable MEMS-based Biochip

 

Hardik J.‎ Pandya, Kihan Park, Wenjin Chen, Lauri A.‎ Goodell, David J.‎ Foran, and Jaydev P.‎ Desai, Brigham and Women's Hospital - Harvard Medical School, University of Maryland, Rutgers Cancer Institute of New Jersey, Rutgers Robert Wood Johnson Medical School, Rutgers USA.‎ 
 
A portable cancer diagnostic tool integrated with a disposable MEMS-based biochip is developed for measuring electro-thermo-mechanical (ETM) properties of the breast tissue.‎ The ETM properties of the normal and cancerous breast tissues are measured by indenting the tissue placed on the biochip integrated inside the 3D printed tool.‎ To overcome the challenges posed by soldering or wire bonding in the microscale devices, we use press-fit contacts for taking out electrical contacts from the biochip, establishing a novel way of connecting biochip to the electronic module.‎ Our preliminary study shows that the cancer diagnostic tool can successfully delineate normal and cancerous tissues based on the ETM properties.‎  Read More