## 2 Methodology
### Methods for Collection and Processing of Respiration Signals
#### 2.1.3 Respiration Data Acquisition Based on Millimeter-Wave Radar  
We designed the entire experimental system according to a closed-cabin environment, and placed the millimeter-wave radar inside the backrest of a chair. According to the pre-test, this method can collect the signal according to the demand and at the same time avoid the interference of the previous radar, which needs to be placed in front of the experiment. Because the relative distance between the participant and sensor changes very little, it is important that the deployment method allows the signal processing method to disregard the distance as much as possible. Since the radar sensor can detect only one person at a time, only one subject was allowed to remain in the experimental area once the experiment began, to ensure accurate data collection.  
The participants were screened according to the requirements of the diving mission by consulting with experts related to manned deep diving missions, and the experiment was conducted on 20 male participants, aged 21-40 years, at intervals of at least two days. All subjects had no history of cardiovascular or psychiatric disorders or other medical contraindications. Additionally, none had consumed alcohol within the previous three days, and all reported adequate sleep. This sample selection was balanced using a convenience sampling method, which allowed us to easily recruit participants from an existing pool [31]. Convenience sampling was deemed appropriate for this preliminary study to gather initial data quickly and evaluate the feasibility of the proposed emotion recognition method. During the experiment, the RSP signals of each participant were measured while watching different video clips that elicited different emotions, as shown in Figure 4.  
Figure 3: Valence–arousal (VA) two-dimensional model of emotion.  
The experimental setup is illustrated in Figure 5. To test whether the methodology of this study could be applied to a closed-cabin environment, this experiment was conducted in the closed-cabin laboratory at the Department of Industrial Design, College of Electrical and Mechanical Engineering, Northwestern Polytechnical University. The laboratory is an electrically shielded and soundproof room with manually controlled light and temperature. The room temperature is set at 25 \({}^{\circ}\)C, and the lighting conditions are configured to 6500 K \(\times\) 600 k, which, according to a previous study [20], can help create a relaxed atmosphere. The experimental steps and details were explained to all participants prior to the experiment, and written informed consent was obtained from all participants, who were assured that the data obtained from this experiment would not be used for other purposes. The experiment was approved by Northwestern Polytechnical University (No. 202202053) and complied with the Declaration of Helsinki.  
A total of 1200 sets of 1 min RSP signal sequences were collected from each of the 20 participants, including 300 sets for each emotion. The data were randomly selected for training (80%) and testing (20%).  
To achieve rapid onsite emotion recognition, we evaluated different lengths of RSP signal segments, ranging from 5 to 60 s. After considering both effectiveness and efficiency, we decided to use 20 s segments. Given that our sampling rate was set at 32 Hz, we segmented the signal data into 20 s segments, starting from the beginning of each record, with the segmentation window moving every second. This means that in two adjacent segments, the latter segment starts from 2-s of the former segment, resulting in a 19 s  
Figure 4: Flowchart of respiration data acquisition experiment.  
Figure 5: Experiment Scenario.  
overlap between adjacent segments. Thus, for a 60 s trial video, we obtained 41 segments. Each participant performed 60 trials, and each trial produced 41 segments, resulting in a total of 49,200 data samples.