Accurate Extraction of the Self-Rotational Speed for Cells in an Electrokinetics Force Field by an Image Matching Algorithm

Abstract

We present an image-matching-based automated algorithm capable of accurately determining the self-rotational speed of cancer cells in an optically-induced electrokinetics-based microfluidic chip. To automatically track a specific cell in a video featuring more than one cell, a background subtraction technique was used. To determine the rotational speeds of cells, a reference frame was automatically selected and curve fitting was performed to improve the stability and accuracy. Results show that the algorithm was able to accurately calculate the self-rotational speeds of cells up to ~150 rpm. In addition, the algorithm could be used to determine the motion trajectories of the cells. Potential applications for the developed algorithm include the differentiation of cell morphology and characterization of cell electrical properties.

A Hybrid Background Subtraction and Artificial Neural Networks for Movement Recognition in Memorizing Quran

“…In other words, the percentage of accuracy system in detecting the Quantum Maki Quran memorization movement is 91.67%. The accuracy percentage is calculated by using the equation in (7) The equation is generally used by other existing works. Hence, it is not required to replicate and compare the experiment from other existing works.…”

“…There are some important obstacles to consider for detecting objects on a video, such as the appearance of a background or another object that is similar to the focus of objects [1], the shadows on top of the focus of the object, and noise caused by several highlights [2]. Despite these obstacles, the object recognition technique on a video has been widely used in several fields, such as supervision [3], robotics [4], [5], agriculture [6], health [7], sports [8], education [9], and traffic [10]. This research is proposed to contribute in the field of education.…”

“…In total, we found that there are at least 30 references; one of them is [11] that uses a method with an optimal result of object detection. There are other methods that we found in the literature such as Feature Extraction [7], [12], Histogram of Oriented Gradients [13], [14], Neural Networks [15], [16], Face Detection Module [17], Fuzzy Inference System [18], Naïve method [9], Probabilistic method [19], Directed Acyclic Graph [20] with various results of object detection.…”

A Review on Optoelectrokinetics-Based Manipulation and Fabrication of Micro/Nanomaterials

“…This is how optical-electrokinetics-microfluidics integration works. Featuring the use of optically-projected images as virtual electrodes to directly manipulate micro/nanoparticles and without referring to metal-based electrodes, OEK has been widely used in the manipulation, separation, assembly, and fabrication of micro/nano-entities as well as extraction of their intrinsic properties [33][34][35][36][37][38], which has shown a highly promising new strategy in the development of micro/nanomanipulation and fabrication communities. More recently, Berkeley Lights Inc., the inventor of OEK, has commercialized this technology in bio-related fields, offering a unique approach to take the development of biomedical and bioengineering sciences to a new level.…”

Rapid Assembly of Carbon Nanoparticles Into Electrical Elements by Optically-Induced Electroosmotic Flow

“…In the past, our group assembled microparticles for various applications [26], [27]. Recently, our group also fabricated micro/nano-scaled structures and nanodevices using different types of nanoparticles [28]- [31] and developed new algorithms to identify and characterize micro/nano-scaled particles, including single biological cells [29], [32].…”