microfluidics

Electro-optical classification of pollen grains via microfluidics and machine learning

Author(s): Michele D’Orazio, Riccardo Reale, Adele De Ninno, Maria A. Brighetti, Arianna Mencattini, Luca Businaro, Eugenio Martinelli, Paolo Bisegna, Alessandro Travaglini, Federica Caselli
Electro-optical classification of pollen grains via microfluidics and machine learning 340 354 IEEE Transactions on Biomedical Engineering (TBME)
This interdisciplinary work involves sensor science, microfluidics, machine learning, and palynology. Palynology – i.e., the study of pollen and fungal spores – finds applications in high-impact fields like air quality control, allergology, and agriculture. Traditionally, the study of pollen takes place through microscopic analysis performed by specialized operators, after staining of the sample. The procedure requires long times and is prone to human errors. Therefore, there is an unmet need for accurate, label-free, and automated systems for the analysis of pollen, ideally within a field-portable and cost-effective platform. In this framework, we propose an original multimodal approach. read more

On-Chip Impedance Quantification of Parasitic Voltages During AC Electrokinetic Trapping

Author(s): Vahid Farmehini, Walter Varhue, Armita Salahi, Alexandra R. Hyler, Jaka Čemažar, Rafael Davalos, Nathan S. Swami
On-Chip Impedance Quantification of Parasitic Voltages During AC Electrokinetic Trapping 170 177 IEEE Transactions on Biomedical Engineering (TBME)
Monitoring the effectiveness and location of cell or particle trapping under microfluidic force fields is currently achieved by cumbersome imaging methods that require extensive microscopy to be conducted by a trained operator, with limited ability to rapidly trigger downstream decisions. We present an embedded circuit for an impedance sensor that directly interfaces to a microfluidic chip for the monitoring of cell or particle trapping based on the level and frequency response of parasitic voltage drops measured during AC electrokinetic manipulation, to enable assessment of trapping efficacy of the device geometry and to rapidly inform downstream cell separation decisions. read more
Epilepsy-on-a-chip System for Antiepileptic Drug Discovery

Epilepsy-on-a-chip System for Antiepileptic Drug Discovery

Author(s): Jing Liu, Anna R. Sternberg, Shabnam Ghiasvand, Yevgeny Berdichevsky
Epilepsy-on-a-chip System for Antiepileptic Drug Discovery 170 177 IEEE Transactions on Biomedical Engineering (TBME)

    Development of antiepileptic drugs is currently complicated by the long time course of epileptogenesis. This process occurs on a time scale of weeks to months in animal models, and…

read more

Nonlinear Dynamic Modelling of Platelet Aggregation via Microfluidic Devices

Author(s): Miguel E. Combariza, Xinghuo Yu, Warwick Nesbitt, Arnan Mitchell, Francisco J. Tovar-Lopez
Nonlinear Dynamic Modelling of Platelet Aggregation via Microfluidic Devices 216 284 IEEE Transactions on Biomedical Engineering (TBME)

Miguel E. Combariza, Xinghuo Yu, Warwick S. Nesbitt, Arnan Mitchell, and Francisco J. Tovar-Lopez, RMIT University, Australia, Volume 62, Issue 7, Page: 1718-1727 The development of blood clots at sites of atherosclerotic…

read more

Toward Integrated Molecular Diagnostic System (iMDx): Principles and Applications

Toward Integrated Molecular Diagnostic System (iMDx): Principles and Applications 556 235 IEEE Transactions on Biomedical Engineering (TBME)

Seung-min Park, Andrew Sabour, Jun Ho Son, Sang Hun Lee, Luke Lee Stanford University & University of California, Berkeley, Volume 61, Issue 5, Page: 1506-1521 A new golden age in medicine will…

read more