Overview of the automation of embryo biopsy for pre-implantation genetic diagnosis

Issam M. Bahadur*, James K. Mills

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Embryonic biopsy routinely involves the removal of one or two blastomeres in the pre-implantation genetic diagnosis (PGD) procedure to determine the presence of a specific disease. The rapid development of the PGD technique and stem cell research has led to great demand for highly automated high precision equipment for cellular component micro-extraction. We first present a review of the existing and possible techniques for embryo biopsy. Additionally, this paper overviews the development of the overall automation of embryonic biopsy including the discussion of: automation steps and strategy embryo holding devices design and control of a piezoelectric-based cutter vision-based control. The present work proposes a new approach to transfer and immobilise biological cells. The unique configuration of fluidic channels is designed to increase cell mobility to overcome adhesion force at a low suction flow rate. Furthermore, a new simple model is proposed to describe the rate-dependent hysteresis for real-time compensation of non-linearities of piezoelectric cutter over wide range of frequency operation. The performance of the proposed visual-based controller is evaluated numerically. Finally, the preliminary numerical and experimental results demonstrate the effectiveness of the automated embryonic biopsy system.

Original languageEnglish
Pages (from-to)201-212
Number of pages12
JournalInternational Journal of Mechatronics and Automation
Volume1
Issue number3-4
DOIs
Publication statusPublished - 2011

Keywords

  • embryo biopsy
  • hysteresis, holding device
  • PGD
  • piezoelectric
  • pre-implantation genetic diagnosis
  • visual control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Mechanics
  • Industrial and Manufacturing Engineering
  • Computational Mathematics
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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