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便携式树派平台用于自动解释侧向流量带测试

Natalia Nakou¹, Panagiotis K Tsikas¹, Despina P Kalogianni¹

¹Department of Chemistry, University of Patras, GR26504 Patras, Greece.

Sensors (Basel, Switzerland)

|January 28, 2026

概括

本研究介绍了一种使用Raspberry Pi驱动的系统,用于准确,自动量化核酸侧流检测 (NALFA). 这种低成本的方法提高了检测像SARS-CoV-2这样的病毒的诊断准确性.

科学领域:

生物医学工程生物医学工程
临床诊断临床诊断临床诊断临床诊断
生物传感器技术技术

背景情况:

基于纸质的快速测试对于临床诊断来说是简单而经济的,但缺乏定量准确性.
核酸侧流检测 (NALFA) 的现有方法通常依赖于主观的视觉解释,限制了它们的精度.

研究的目的:

开发一个使用Raspberry Pi平台对NALFA进行自动化,定量检测系统.
通过用客观图像分析取代主观解释,提高基于NALFA的诊断的准确性,特别是用于SARS-CoV-2检测.

主要方法:

将NALFA与使用Raspberry Pi和自定义Python软件 (3.12版本) 的自动图像采集系统集成.
使用蓝色聚乙烯微球作为报告器和负控制带用于信号量化,纠正照明和背景变化.
用不同DNA度的样本开发算法训练和验证的校准曲线.

主要成果:

自动化系统实现了SARS-CoV-2的定量检测,超过了视觉解释的准确性.
在分析具有不同DNA度的样本时,获得了84%至108%的恢复率.
展示了第一个以树派驱动的图像处理方法,用于准确的NALFA量化.

结论:

拟议的系统通过将简单的生物传感器与可访问的计算平台集成,为定量NALFA分析提供全自动化,低成本的解决方案.
这项工作为未来开发各种生物标志物的便携式,具有成本效益的诊断系统奠定了基础.

关键词:

它们是DNA DNA DNA DNA.打开CVV 打开CVV 在这里,Python是Python.这就是SARS-CoV-2病毒.珠子珠子珠子图像分析图像分析图像处理是图像处理的过程.侧向流量检测试验聚烯微粒的聚烯微粒.带条带条带条带条

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