scholarly journals Open-Source Low-Cost Cardiac Optical Mapping System

2021 ◽  
Author(s):  
Dmitry Rybashlykov ◽  
Jaclyn Brennan ◽  
Zexu Lin ◽  
Igor R. Efimov ◽  
Roman Syunyaev

Fluorescent imaging with voltage- or calcium-sensitive dyes, i.e. optical mapping, is one of the indispensable modern techniques to study cardiac electrophysiology, unsurpassed by temporal and spatial resolution. High-speed CMOS cameras capable of optical registration of action potential propagation are in general very costly. We present a complete solution priced below US$1,000 (including camera and lens) at the moment of publication with an open-source image acquisition and processing software. We demonstrate that the iDS UI-3130CP rev.2 camera we used in this study is capable of 200x200 977 frames per second (FPS) action potential recordings from rodent hearts. The signal-to-noise-ratio of a conditioned signal was 16 ± 10 for rodent hearts. A comparison with a specialized MiCAM Ultimate-L camera has shown that signal-to-noise ratio (SNR) is sufficient for accurate measurements of AP waveform, conduction velocity (± 0.04 m/s) and action potential duration (± 7ms) in mouse and rat hearts. We measured the action potential prolongation during 4-aminopyridine administration in mouse heart, showing that proposed system signal quality is adequate for drug studies.

2016 ◽  
Vol 140 (4) ◽  
pp. 3212-3212
Author(s):  
Nobuaki Kosuge ◽  
Tsuneyosi Sugimoto ◽  
Kazuko Sugimoto ◽  
Chitose Kuroda ◽  
Noriyuki Utagawa

1995 ◽  
Vol 235 (5-6) ◽  
pp. 508-510
Author(s):  
Geng-Ying Li ◽  
Xue-Cheng Xu ◽  
Yi Liu ◽  
Xue-Wen Wu

2012 ◽  
Vol 83 (8) ◽  
pp. 083710 ◽  
Author(s):  
O. D. Payton ◽  
L. Picco ◽  
M. J. Miles ◽  
M. E. Homer ◽  
A. R. Champneys

2006 ◽  
Vol 14 (3) ◽  
pp. 243-250 ◽  
Author(s):  
Nicolò Cavina ◽  
Giovanni Cipolla ◽  
Francesco Marcigliano ◽  
Davide Moro ◽  
Luca Poggio

Author(s):  
S. J. Steinberg ◽  
R. King ◽  
C. Tiedemann ◽  
D. Peitsch

Active flow control is a powerful option to ensure secure operation and enhancement of the performance of axial compressors. To achieve these goals for aerodynamically highly loaded compressor blade profiles even under disturbed conditions, the magnitude of the actuation needs to be adjusted by a closed-loop controller. To this end, sensors must be placed at some meaningful positions at the surface of the blades giving information about the flow situation inside the passages. The sensor information can then lead to surrogate control variables to close the loop. Often, good sensor positions are unknown initially and therefore chosen naively or experience-driven. To obtain more informative surrogate control variables, a different approach is chosen here. Starting with a highly instrumented blade inside a linear stator cascade, featuring 16 pressure gauges in an area which is suspected to lead to high information content with respect to detrimental flow separations at the sidewalls, a Principal Component Analysis is done. The principal components provide valuable information about where and how intensively the flow is influenced by the actuation. This is validated by comparison with the results of oil flow visualizations and wake measurements. The goal is to find a linear combination of as few sensors as possible to provide a meaningful input for the closed-loop controller. As experiments are conducted up to Ma = 0.8, the signal-to-noise ratio becomes a critical issue. For this reason, specifically weighted data are introduced here. A linear combination of sensor data is obtained, describing the main effects of the actuation with an almost linear mapping. For the given set of sensors, that linear combination achieves a maximum signal-to-noise ratio, which makes it well suited as a control variable. The practical usefulness of the control variable within a robust ℋ∞-flow controller is verified in experiments in a high speed stator cascade.


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