Refet Firat Yazicioglu

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This paper gives an overview of results of the Human++ research program [1]. This research aims to achieve highly miniaturized and nearly autonomous sensor systems that assist our health and comfort. It combines expertise in wireless ultra-low power communications, packaging and 3D integration technologies, MEMS energy scavenging techniques and low-power(More)
This paper presents an active electrode system for gel-free biopotential EEG signal acquisition. The system consists of front-end chopper amplifiers and a back-end common-mode feedback (CMFB) circuit. The front-end AC-coupled chopper amplifier employs input impedance boosting and digitally-assisted offset trimming. The former increases the input impedance(More)
An ECG signal processor (ESP) is proposed for ambulatory arrhythmia monitoring systems. The ESP consists of three heterogeneous processors and performs filtering, data compression, ECG classification, and encryption. A data reduction scheme, consisting of skeleton and Huffman coding, are employed to reduce the on-chip memory capacity and memory access(More)
This paper proposes a 3-channel biopotential monitoring ASIC with simultaneous electrode-tissue impedance measurements which allows real-time estimation of motion artifacts on each channel using an an external μC. The ASIC features a high performance instrumentation amplifier with fully integrated sub-Hz HPF rejecting rail-to-rail electrode-offset voltages.(More)
This paper presents the development of an ECG patch aiming at long term patient monitoring. The use of the recently standardized Bluetooth Low Energy (BLE) technology, together with a customized ultra-low-power ECG System on Chip (ECG SoC). including Digital Signal Processing (DSP) capabilities, enables the design of ultra low power systems able to(More)
Micro- and nano-technology has enabled development of smaller and smarter wearable devices for medical and lifestyle related applications. In particular, recent advances in EEG monitoring technologies pave the way for wearable, wireless EEG monitoring devices. Here, a low-power wireless EEG sensor platform that measures 8-channels of EEG, is described. The(More)