Continuous Mechanical Indexing of Single-Cell Spheroids Using a Robot-Integrated Microfluidic Chip

Shinya Sakuma, Ko Nakahara, Fumihito Arai

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


In single-cell/spheroid analyses, flow cytometry plays a key role in high-throughput measurements. Among the considerable numbers of indexes available for a target evaluation, mechanical characteristics such as a Young's modulus have been focused upon as new indexes related to physiological condition. However, a continuous mechanical indexing system has yet to be achieved due to the difficulty in flow control, which brings about a fluctuation of the force sensor probe. In this letter, we propose an automated mechanical indexing system of spheroids. By utilizing a combination of two syringe pumps, we succeeded in positioning the target spheroids without an undesirable pinching. We conducted experiments on the continuous mechanical indexing of single-cell spheroids using 26 mesenchymal stem cell spheroids. The evaluation results of positioning showed that the error in the position control was 14.1 mum with a standard deviation of 87.7 mum, which corresponded to a measurement error of the Young's modulus of under 2%. In addition, we succeeded in achieving a measurement throughput of 3.14 spheroids per minute, which is approximately 2 times faster than a manual operation. Finally, we demonstrated the on-chip sorting of single spheroids based on the mechanical index to show the adaptability of the proposed method toward the flow cytometry.

Original languageEnglish
Article number8740974
Pages (from-to)2973-2980
Number of pages8
JournalIEEE Robotics and Automation Letters
Issue number3
Publication statusPublished - Jul 2019
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence


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