Design an open DSP-based system to acquire and process the bioelectric signal in realtime

Toan, Nguyen Vu Huy; Duc, Trinh Quang

doi:10.1109/bme-hust.2016.7782108

Cited by 4 publications

(1 citation statement)

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“…A 2016 work shows a FM modulation–demodulation approach used to acquire and transfer an ECG signal in real-time that could be easily connected and decoded using an audio PC card [ 11 ]. This work [ 11 ] uses relatively low frequencies (20 Hz to 20 kHz) and transfers/decodes a single signal.…”

Section: Introductionmentioning

confidence: 99%

A Frequency Modulation-Based Taxel Array: A Bio-Inspired Architecture for Large-Scale Artificial Skin

Assaf

2021

Sensors

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This work introduces an array prototype based on a Frequency Modulation (FM) encoding architecture to transfer multiple sensor signals on a single wire. The use case presented adopts Hall-effect sensors as an example to represent a much larger range of sensor types (e.g., proximity and temperature). This work aims to contribute to large area artificial skin systems which are a key element to enhance robotic platforms. Artificial skin will allow robotic platforms to have spatial awareness which will make interaction with objects and users safe. The FM-based architecture has been developed to address limitations in large-scale artificial skin scalability. Scalability issues include power requirements; number of wires needed; as well as frequency, density, and sensitivity bottlenecks. In this work, eight sensor signals are simultaneously acquired, transferred on a single wire and decoded in real-time. The overall taxel array current consumption is 36 mA. The work experimentally validates and demonstrates that different input signals can be effectively transferred using this approach minimizing wiring and power consumption of the taxel array. Four different tests using single as well as multiple stimuli are presented. Observations on performances, noise, and taxel array behaviour are reported. The results show that the taxel array is reliable and effective in detecting the applied stimuli.

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Section: Introductionmentioning

confidence: 99%