Signal Processing Methods for Sensors
A signal processing, sensor technology
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Embodiment 1
[0029] Such as Figures 1 to 15 , respectively collect 2 left arm signals, 2 right arm signals, and 2 left leg signals through 6 viscous electrode sensors, which can be recorded as LA2, LA3, RA2, RA3, LL2, and LL3 respectively. Afterwards, 15 different sets of ECG data were acquired, including RA2-LA2, RA2-LA3, LA2-RA3, LL2-RA3, RA3-LA3, RA2-LL2, RA2-LL3, LA2-LA3, LL2-LA3, RA3- LL3, RA2-RA3, LA2-LL2, LA2-LL3, LL2-LL3, LA3-LL3. The ECG data difference of each group is separately stored as a group of ECG data. After that, the spectral density coefficient (coefficient) is obtained through calculation. From Figure 11 It can be known that its spectral density coefficient is 0.9994, which is the highest value, and can be determined as the best ECG signal.
Embodiment 2
[0031] Collect 3 left arm signals, 3 right arm signals, and 3 left leg signals through 9 fiber sensors to obtain several sets of different ECG data. Afterwards, the ECG data difference values of each group are separately stored as a group of ECG data. Due to the large number of fiber sensors, more raw ECG data can be obtained, and more optimal results can be obtained. In this way, the spectral density coefficient is obtained through the final calculation, and the one with the highest value can be selected.
[0032] It can be seen from the above text description in conjunction with the accompanying drawings that after adopting the present invention, it has the following advantages:
[0033] 1. It can be combined according to the obtained left arm signal, right arm signal and left leg signal to obtain more comparable ECG data.
[0034] 2. The spectral density coefficient is introduced as a reference to obtain better ECG signals.
[0035] 3. The implementation is simple and ...
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