Publications by Ahmed Yasir Dogan

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According to the World Health Organization, lifestyle-related diseases, e.g., cardiovascular diseases are the major cause of mortality worldwide. An accurate and continuous medical supervision is highly required for diagnosis and treatment of such diseases ...

In this study, the authors explore sequential and parallel processing architectures, utilising a custom ultra-low-power (ULP) processing core, to extend the lifetime of health monitoring systems, where slow biosignal events and highly parallel computations ...

A multi-core architecture with ultra-low power consumption is needed for a wide variety of applications, especially in the bio-medical domain. In this patent, an ultra-low power multi-core architecture is presented: it is composed of one or more cores, sev ...

Personal health monitoring systems can offer a cost-effective solution for human healthcare. To extend the lifetime of health monitoring systems, we propose a near-threshold ultra-low- power multi-core architecture featuring low-power cores, yet capable of ...

This study presents a single-core and a multi-core processor architecture for health monitoring systems where slow biosignal events and highly parallel computations exist. The single-core architecture is composed of a processing core (PC), an instruction m ...

Embedded biosignal analysis involves a considerable amount of parallel computations, which can be exploited by employing low-voltage and ultra-low-power (ULP) parallel computing architectures. By allowing data and instruction broadcasting, single instructi ...

Compressed sensing (CS) is a universal technique for the compression of sparse signals. CS has been widely used in sensing platforms where portable, autonomous devices have to operate for long periods of time with limited energy resources. Therefore, an ul ...

Ahmed Yasir Dogan

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Energy-Aware Processing Platform Exploration for Embedded Biosignal Analysis

Low-power processor architecture exploration for online biomedical signal analysis

Ultra-Low Power Multicore Architecture For Parallel Biomedical Signal Processing

Multi-Core Architecture Design for Ultra-Low-Power Wearable Health Monitoring Systems

Power/Performance Exploration of Single-core and Multi-core Processor Approaches for Biomedical Signal Processing

Synchronizing Code Execution on Ultra-Low-Power Embedded Multi-Channel Signal Analysis Platforms

TamaRISC-CS: An Ultra-Low-Power Application-Specific Processor for Compressed Sensing