# Shoulder-Elbow Joint Angle Prediction Using COANN with Multi-Source Information Integration
## 2 COANN Network Optimization Algorithm Architecture
### COANN Network Optimization Algorithm
All volunteers were in good physical condition, had not suffered any injuries, did not suffer from any muscle-related diseases or disorders, and had not engaged in strenuous exercise during the week before the start of the experiment to ensure that the experimental data could be controlled at the level of individual differences to the greatest extent possible. Before the start of the experiment, each volunteer signed an informed consent form and understood the whole experimental procedure in detail. It should be emphasized that this experiment was designed with safety in mind and would not cause any adverse effects on the volunteers, who also knew the purpose of the experiment and all the contents clearly. The experiment was carried out in a shielded laboratory (area 49 m\({}^{2}\), temperature \(23\pm 1\)\({}^{\circ}\)C, humidity \(50\pm 5\%\)), which was tested for electromagnetic compatibility (based on the GB/T 17626.3-2016 standard [15]) with an ambient noise intensity of \(\leq\)40 dB and an IF interference of \(\leq\)0.1 mV, in order to ensure that the sEMG signal acquisition was free from external interference. ### Data Acquisition

The laboratory conducted extensive market research and comparative analysis on the selection of surface EMG signal acquisition equipment. Finally, the EMG_06 six-channel sEMG acquisition system (Wuxi Porunin Technology Co., Ltd., Wuxi, China) was selected \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Experiment No.** & **Gender** & **Height** & **Weight** & **Age** & **BMI** \\ \hline A1 & female & 164.3 & 57.8 & 26 & 21.4 \\ \hline A2 & female & 168.4 & 62.7 & 25 & 22.1 \\ \hline A3 & male & 178.7 & 68.2 & 25 & 21.4 \\ \hline A4 & male & 175.2 & 73.1 & 25 & 23.8 \\ \hline A5 & male & 183.8 & 76.7 & 26 & 22.7 \\ \hline \hline \end{tabular} Note: BMI classification is based on the Chinese health industry standard WS/T 428-2013: thin (BMI: \(\leq\)18.4); normal (BMI: 18.5-23.9); heavy (BMI: 24.0-27.9); obese (BMI: \(\geq\)28.0).

\end{table} 
Table 1: Volunteer basic information sheet (_n = 5_). Figure 1: Experimental program flow design. with the following technical parameters: input impedance >100 M\(\Omega\), common mode rejection ratio \(\geq\)110 dB, built-in high-pass filter (cutoff frequency 20 Hz) and 50 Hz trap, and signal quantization accuracy of 16 bit--which meets the experimental requirements. This system is equipped with a six-lead EMG module and is combined with the STM32 development kit as shown in the figure below. Each wire of the device is equipped with three key acquisition points distinguished by color: red is the reference electrode to stabilize the potential reference; green is the ground electrode to construct the ground loop; and yellow is the working electrode to pick up the core signal. In this study, the 12-axis inertial measurement unit (IMU) model WT9011 DCL-BT50 of Shenzhen Witte Intelligent Technology Co., Ltd., Shenzhen, China. is used as the joint angle acquisition device. This device was selected through comprehensive screening and market comparison to ensure a sampling frequency of 200 Hz and support for Bluetooth 5.0 wireless transmission protocols. The WT9011 DCL-BT50 acquisition system demonstrates exceptional cost-effectiveness compared with high-end devices such as Xsens, MTw, and Awinda, with a purchase price equivalent to 16% and a physical footprint reduced to 60% of premium alternatives. Notably, it exhibits superior technical performance and enhanced development compatibility, fulfilling the operational requirements of this study. This system has been successfully implemented in multiple biomechanical investigations [16; 17], validating its reliability in dynamic motion capture through rigorous experimental verification protocols. During data acquisition, subjects were placed in an upright position (body perpendicular to the ground \(\pm 5^{\circ}\)) with arms naturally hanging down and forearms fixed on a stand Figure 2) to minimize the effects of motion artifacts and positional changes on the sEMG signal.