## 2 Materials and Methods  
### Experimental Process  
The experiment lasted for four days, from 2 January 2024 to 5 January 2024. During this period, relevant data were collected for research purposes. The author had access to the participants' identifiable information both during and after the data collection phase. A total of 12 volunteers participated in this study. All the subjects were school students, aged between 24 and 30 years old. The height was between 174.3 and 185.6 cm, weight was between 75.6 and 92.8 KG, and body mass index was between 21.3 and 25.9. Before the experiment began, all participants were fully informed about the research objectives, procedures, and potential risks. Written informed consent was obtained from each participant prior to the implementation of the experimental protocol. Figure 1 is the flowchart of the experiment and research. In this study, participants were required to perform three specific upper limb movements at a constant speed: arm forward raise, bicep curl, and arm lateral raise. To ensure consistency in movement execution, participants were instructed to maintain a steady and controllable rhythm throughout the exercise. During the exercise, small contact microphones were attached to the skin over the anterior deltoid, medial deltoid, posterior deltoid, and the biceps brachii to record the MMG signals. To enhance the amplitude and quality of the MMG signals, participants were required to hold a dumbbell during the exercise. This additional load was chosen to increase muscle activation within a safe and manageable range for all participants. The weight of the dumbbells was 0.5 KG and 1 KG, and finally the prescribed movements are completed without dumbbells. Three load conditions were compared to determine whether changes in muscle activation due to varying loads could improve the accuracy of the model in predicting joint angles. Heavier dumbbells were not used, as greater weights might cause muscles to fatigue too quickly, leading to significant changes in the characteristics of the MMG signals and a substantial reduction in the accuracy of the model's joint angle predictions. This is not the main focus of the current study. A metronome was used to guide participants to maintain a constant speed, set at 30 beats per minute, to ensure consistency across all trials and participants. For each subject, a total of 60 min of data were collected for each exercise, among them, 20 min of data are without load, 20 min of data are with load of 0.5 KG, and 20 min of data are with load of 1 KG. During the subject's exercise, the subject rested for one minute after every one minute of exercise, and no data were collected during the rest period. This research aims to focus on joint angle prediction using MMG signals in non-fatigued states, as fatigue causes significant alterations in MMG signal characteristics, which would substantially reduce the model's generalization performance and significantly increase training costs. According to previous studies [28], one minute of low-intensity exercise will not cause muscle fatigue, and the characteristics of muscle sound signals will not change significantly. The fatigue status of the subjects was recorded throughout the collection process. During the experiment, no subject felt obvious fatigue. Figure 2 is a schematic diagram of data collection during the experiment. The MMG signal is continuously recorded by a data acquisition system with a sampling rate of 400 Hz. Joint angles are measured by multiple inertial measurement units (IMUs) with a sampling rate of 200 Hz. The MMG signal is a signal generated by muscle contraction and precedes joint movement, so it can be used for joint angle prediction [29; 30]. However, the IMU data are synchronous with joint movement, compared with IMU data, MMG signals are more suitable for joint angle prediction. Figure 1: Flowchart of the experiment and research.