# Shoulder-Elbow Joint Angle Prediction Using COANN with Multi-Source Information Integration
## 2 COANN Network Optimization Algorithm Architecture
### COANN Network Optimization Algorithm
Experiments show that the COANN achieves high-precision prediction of shoulder and elbow joint angles (RMSE < 0.01\({}^{\circ}\), R\({}^{2}\) > 0.99) through multi-information fusion and global optimization of the COA, which provides a reliable basis for the problem of upper-limb movement disorders brought about by upper-limb hemiplegia, frozen shoulder, and other diseases. ## 7 Future Work

While the present findings demonstrate significant advances, this study contains inherent limitations requiring methodological refinement:

(1) Subject Pool Limitations: The experimental cohort, comprising only five healthy participants (aged 23-26 years), provides representative data for specific demographics but lacks inclusion of geriatric or clinical populations, potentially constraining the model's generalizability to pathological conditions. (2) Task Specificity Constraint: Validation procedures were exclusively validated on periodic extension movements, without targeted evaluation of complex aperiodic motionsin individual muscle groups (e.g., brachioradialis activation patterns), necessitating multi-task dataset construction for comprehensive robustness assessment. Future research will focus on extending the COANN framework to encompass complex aperiodic rehabilitation exercises targeting multi-muscle coordination (e.g., bi-ceps/triceps brachii synergies), while implementing cross-domain adaptation for activities of daily living (ADLs) and functional lower-limb movements. Through collaborative efforts with medical institutions, we will expand sample diversity (targeting \"n\" \(\geq\) 50 with pathological case integration) and conduct multi-center validation to test model adaptability using clinical neuromotor data, thereby rigorously validating the COANN's robustness in complex neuromotor dysfunction scenarios. Conceptualization, S.Z. and Z.J. ; methodology, W.L. and S.Z. ; software, Z.J. ; validation, W.L., Z.Y. and D.S. ; formal analysis, W.L., Z.Y. and D.S. ; investigation, Z.J. ; resources, W.L., Z.Y. and D.S. ; writing--original draft preparation, S.Z. ; writing--review and editing, S.Z. ; visualization, W.L. and D.S. ; supervision, W.L. and D.S. ; project administration, W.L. and Z.Y. All authors have read and agreed to the published version of the manuscript. This research was funded by Jilin Province Development and Reform Commission 2024 Budgeted Capital Funding, grant number 2024C009-6. The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Changchun University scientific and technological ethical committee. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. All data used in this experiment were collected and recorded by high-precision equipment. We would like to express our gratitude to Shandong Jite Industrial Technology Co., Ltd., Rizhao. They not only provided the high-performance PC equipment for this experiment but also actively carried out the manufacturing of the prototype for the subsequent experiments. Shandong Jite Industrial Technology Co., Ltd., Rizhao. showed high professionalism and strong technical capability throughout the project, ensuring smooth experiments and high-quality results. In addition, their team demonstrated an extremely high sense of responsibility and dedication in working with us, providing all-round support and assistance for the experiment. This close cooperation not only accelerated the experimental process but also laid a solid foundation for the smooth development of the subsequent projects. We would like to thank Shandong Jite Industrial Technology Co., Ltd., Rizhao. for their generous funding and technical support for this experiment and look forward to continued cooperation in the future to promote scientific research and technological innovation. Author [PERSON] is affiliated with the company Shandong Jite Industrial Technology Co., Ltd.