# Robotic Manipulation of Cumulus-Oocyte Complexes for Cumulus Cell Removal
## 5 Discussion  
Our results show that the AUC of the EPSANet50 network is more than 0.05 higher than that of other state-of-the-art methods, demonstrating outstanding performance across all the classification thresholds (i.e., from 0 to 1). Compared with the ResNet50 network, the EPSANet50 network can extract multi-scale COC features using the PSA module. Although the DenseNet50 and the SENet50 networks improve the feature extraction by introducing the PSA module and SEWeight module, respectively, they failed to combine these modules effectively. In contrast, the EPSANet50 network integrated the SEWeight module into the PSA module, enriching the extracted COC's features and paying more attention to key features such as COC's polar body. Due to the occlusion of the polar body by surrounding cumulus cells, embryologists remove cumulus cells without assessment of oocyte's maturity, which affects the maturation process and eventually leads to maturation failure. Therefore, it is important that the EPSANet50 network was developed to accurately assess the maturity of oocytes based on the features of the polar body. Our results suggest that the proposed adaptive controller outperformed LQR and PD controllers in terms of positioning accuracy, overshoot, and settling time. During aspiration, for the PD controller, the \(k_{p}\) and \(k_{d}\) (\(k_{p}\) = 100, \(k_{d}\) = 2600) were obtained by empirical tuning, which did not take the varying mass of the COC into account and thus caused a larger overshoot. Although the LQR controller calculated the \(k_{p}\) and \(k_{d}\) based on the mass of the COC before each aspiration, it ignored the varying mass of the COC during the whole aspiration. In contrast, the proposed adaptive controller updated the mass of the COC in real time during aspiration and calculated \(k_{p}\) and \(k_{d}\) according to Equation (10), compensating for the positioning errors caused by the varying COC mass. Since the mass of the COC varies as the cumulus cell are removed during aspiration, the acceleration of the COC will change if a fixed external force is applied to it, leading to the large positioning errors and the loss of the COC inside the micropipette. Therefore, it is essential that the adaptive controller was designed to compensate for the positioning errors and accurately position the COC at the target position inside the micropipette. Our results demonstrate that the improved Yolov5s network achieved the best performance of cumulus cell detection. The Res2 Net-COT and BiFPN modules contributed to the increase in the mAP and recall, since the Res2 Net-COT module acquired the effective semantic information and extracted the fine cumulus cell features, while the BiFPN module was able to address insufficient feature fusion and incomplete feature transmission. The inception module contributed to the increase in the FPS, since its parallel transmission structure effectively improved the inference speed and real-time performance. As the cumulus cells are small, blurry, and varied in size, embryologists cannot accurately calculate the number of the remaining cumulus cells, leading to incomplete cumulus cell removal. Therefore, it is vital that the improved Yolov5s was proposed to quantify both the number and size of cumulus cells, ensuring accurate assessment of the completeness of cumulus cell removal. We found that the robotic group had higher success and lower discard rates. Compared with the manual group, the accurate assessment of cumulus cell removal was enhanced by the improved Yolov5s in the robotic group. Additionally, the accurate positioning of COCs achieved by the designed adaptive controller increased the success rate of the robotic group, reducing COC loss caused by the large overshoot. The lower discard rate of the robotic group was attributed to the accurate assessment of oocyte's maturity by the proposed EPSANet50 network before removing cumulus cells from the COCs. Existing methods, such as microfluidic and vortexing devices [13; 14], have also been developed for cumulus cell removal.