A Meta-Transfer Learning Approach to ECG Arrhythmia Detection.

Automatic classification of cardiac abnormalities is becoming increasingly popular with the prevalence of ECG recordings. Many signal processing and machine learning algorithms have shown the potential to identify cardiac ab-normalities accurately. However, most of these methods heavily rely on a large amount of relatively homogeneous datasets.

Design and implementation of an ultra-low energy FFT ASIC for processing ECG in Cardiac Pacemakers.

In embedded biomedical applications, spectrum analysis algorithms such as Fast Fourier Transform (FFT) are crucial for pattern detection and has been the focus of continued research. In deeply embedded systems such as cardiac pacemakers, FFT based signal processing is typically computed by Application Specific Integrated Circuits (ASIC) to achieve low power operation. This research proposes a data driven design approach for an FFT ASIC solution which exploits the limited range of data encountered by these embedded systems.

Resource Shared Galois Field Computation for Energy Efficient AES/CRC in IoT Applications.

End-to-end encryption and reliability of the transmitted data are essential requirements in the present era of internet enabled smart devices. Adhering to current industry standards, the Advanced Encryption Standard (AES) and Cyclic Redundancy Check (CRC) are the two most utilized methods for ensuring security and reliability. To integrate AES and CRC functionality in ultralow-power embedded System on Chips (SoCs), dedicated computation engines/co-processors are often used, consuming valuable silicon area and additional battery power.

An Ultra-Low Power Charge Redistribution Successive Approximation Register A/D Converter for Biomedical Applications.

Power consumption is one of the key design constraints in biomedical devices such as pacemakers that are powered by small non rechargeable batteries over their entire life time. In these systems, Analog to Digital Convertors (ADCs) are used as interface between analog world and digital domain and play a key role. In this paper we present the design of an 8-bit Charge Redistribution Successive Approximation Register (CR-SAR) analog to digital converter in standard TSMC 0.

Reducing Power and Cycle Requirement for FFT of ECG Signals through Low Level Arithmetic Optimizations for Cardiac Implantable Devices.

The Fast Fourier Transform or FFT remains to be the de facto standard in almost all disciplines for computing discrete Fourier transform. In embedded biomedical applications, efficient signal processing algorithms such as FFT for spectrum analysis are indispensable. The FFT is an O(NlogN) algorithm which requires complex multiplication and addition using floating point numbers.

Analysing the performance of personal computers based on Intel microprocessors for sequence aligning bioinformatics applications.

Aligning specific sequences against a very large number of other sequences is a central aspect of bioinformatics. With the widespread availability of personal computers in biology laboratories, sequence alignment is now often performed locally. This makes it necessary to analyse the performance of personal computers for sequence aligning bioinformatics benchmarks.

Endovascular exclusion of leaking thoracic aortic aneurysms.

Purpose: To describe the endovascular exclusion of leaking thoracic aortic aneurysms (TAA).

Case Report: Two elderly patients with leaking TAAs who were at high risk for surgical intervention were transferred to our institution for possible endovascular treatment. Both patients underwent successful endovascular exclusion of the leaking TAAs using multiple stacked AneuRx thoracic endoprostheses.