Sperm Manipulation and Selection Platform Using Optoelectronic Tweezers*
A sperm manipulation and selection platform using optoelectronic tweezers is proposed in this paper, fully leveraging the high throughput, damage-free, and contactless advantages of optoelectronic tweezers, combined with advanced computer vision techniques, to achieve precise manipulation and selection of sperm. Initially, through simulation, the force conditions of sperm under the optoelectronic tweezers are studied, followed by the development of a sperm detection algorithm based on YOLOv8, ByteTrack, and average speed strategies. This leads to the successful construction of a sperm manipulation and selection system encompassing detection, tracking, speed measurement, and manipulation. Experimental results demonstrate that the system can achieve high-precision manipulation of individual sperm, rapidly and orderly ar-range multiple sperms, and effectively select sperm based on morphology, speed, and vitality. Additionally, the system can significantly increase sperm concentration in a short period and effectively transport groups of sperm. With the increasing problem of infertility, particularly the decline in male sperm quality, this research provides an effective technical means for the development of efficient sperm manipulation and selection technology.
Authors
- Zijin Zeng
- Shunxiao Huang (ORCID: https://orcid.org/0009-0001-9230-4110)
- Chunyuan Gan (ORCID: https://orcid.org/0000-0002-6451-5818)
- Hongyi Xiong (ORCID: https://orcid.org/0009-0008-7051-6631)
- Wenxin Niu (ORCID: https://orcid.org/0000-0003-1349-4524)
- Lin Feng (ORCID: https://orcid.org/0000-0002-3924-9466)
- Bo Chen (ORCID: https://orcid.org/0000-0001-6743-9251)
- Chan Li (ORCID: https://orcid.org/0000-0002-7922-8053)
- Ao Wang (ORCID: https://orcid.org/0000-0002-8913-0885)
- Hongyan Sun (ORCID: https://orcid.org/0000-0003-0486-3797)
- Jingwen Ye
- Jiawei Zhac
Institutions
- Beijing Advanced Sciences and Innovation Center (CN)
- Beihang University (CN)
Publication Details
- Published
- 2024-12-10
- DOI
- https://doi.org/10.1109/robio64047.2024.10907732
- Citations
- 1
- Primary Topic
- Advanced Malware Detection Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.35