# Multi-Session Electrocardiogram-Electromyogram Database for User Recognition
## 3 Measured Method of Multi-Session Biosignal Benchmarking DBs
### Multi-Biosignal Measurement Method  
In the case of CSU_MBDB1, signals were recorded during the performance of six hand gestures (Table 4) by each participant. These gestures include the following: (1) clenching the fist, (2) pressing the index finger with the thumb while clenching the fist, (3) simultaneously flexing the index, middle, and ring fingers, (4) flexing the wrist, (5) extending the wrist outward, and (6) rotating the wrist 90 degrees to the left. The construction of CSU_MBDB1 involved the active participation of 60 subjects. Each hand gesture followed a rest period-gesture period-rest period sequence, repeated 10 times within a single session. The gesturing method for each gesture was specifically standardized in certain steps to ensure consistency across all subjects. Figure 2 shows an example of the rest period-gesture period-rest period situation during a single execution of the gesture. The ECG and EMG were measured across two sessions, with the DB's construction including a minimum one-week interval between the sessions to facilitate the analysis of biosignal variability. We used the Biopac MP160 as the biosignal construction equipment, measuring ECG with one channel and EMG with two channels. When ECG and EMG were acquired simultaneously, interference occurred between the ECG sensor and the EMG sensor. Therefore, we \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Category** & **DB Name** & **Biosignal Types** & **Session** & **No. of** \\  & & & **Type** & **Subjects** \\ \hline
1 & MeganePro MDS1 [25] & EMG, video, gaze & Single & 45 \\
2 & DEAP dataset [26] & EEG, EOG, EMG, etc. & Single & 32 \\
3 & DREAMER dataset [27] & EEG, ECG & Single & 25 \\
4 & Stress Recognition in & ECG, EMG, EDA, etc. & Multi & 9 \\  & Automobile Drivers [28] & ECG, EEG, gaze & Single & 30 \\
5 & MAHNOD-implicit-tagging [29] & tracking, etc. & Single & 30 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Benchmarking multi-biosignal DB description. Figure 2: Examples of DB recording method (an example of the biosignal recording procedure for the fist-clenching gesture). attached the EMG sensor to the position where the muscles are activated while performing hand gestures, changed the ECG sensor location, as shown in Figure 3, and checked for interference between sensors. The location where the final ECG and EMG sensors were attached was where interference between the sensors was minimized. ECG sensors were positioned under the left and right biceps brachii, with the GND attached above the left biceps brachii. For EMG, Ch1 was attached to the flexor carpi radialis, Ch2 to the extensor indicis proprius, and GND to the outside of the upper arm. Figure 4 shows the ECG and EMG sensor positions. The signal bandwidth was set to 0.5-35 Hz, the sampling rate to 2000 Hz, and the ADC resolution to 16 bits. For CSU_MBDB2, signals were recorded as each subject performed six hand gestures, outlined in Table 5: (1) clenching the fist, (2) flexing the wrist, (3) extending the wrist upward, (4) rotating the wrist 90 degrees to the left, (5) rotating the wrist 90 degrees to the right, and (6) raising the cell phone 90 degrees. The DB was designed for expansion since CSU_MBDB2 has the same three hand gestures as CSU_MBDB1 (CSU_MBDB1: gesture no. 1 and CSU_MBDB2: gesture no. 1; CSU_MBDB1: gesture no. 4 and CSU_MBDB2: gesture no. 2; CSU_MBDB1: gesture no. 6 and CSU_MBDB2: gesture no. 4). Each hand gesture was repeated 10 times in one session, following the same rest period-gesture period-rest period procedure as in CSU_MBDB1. Signals were recorded across two sessions with an interval of at least one week. A hundred subjects participated in the construction of CSU_MBDB2.