Figure 1:
System model depiction of real-time HRV measurement using PPG.
Figure 2:
Block diagram for real-time HRV measurement using PPG.
Figure 3.
Steps involved in an android application design.
Figure 4:
Single frame of YUV 420.
Figure 5:
Value of RGB and Hue for diverse smart phone devices.
Table 2:
Video specification
| Video specification | Formulae | Sample |
|---|---|---|
| Video data | V (m, n, c, t) | 320 × 240 |
| Resolution | m x n | |
| m = 0 …M - 1 | ||
| n = 0 …N - 1 | ||
| t = 0 …T - 1 | ||
| Channel | C = 1, 2, 3 | RGB |
| Number of frames | T | |
| Frame rate | F | 30 fps |
Figure 6:
Extraction of RGB.
| Examine the input signal of FFT M(T) |
| Assess the signal with n filter, as N(T) |
| Perform Dot product among the signal |
| Evaluate the low band Wavelet coefficient |
| Evaluate the High Band Wavelet coefficient |
| Based on these approximate coefficient decimation results are obtained |
Table 3:
Implementation details
| Implementation details | |
|---|---|
| RAM | 16 GB |
| Configuration | Windows 11 |
| Version | 2024b |
| Software | Python |
| ROM | More than 100 GB |
| Clock speed | 3 GHz |
Figure 7:
Experimental outcome of developed model. HF, high frequency; LF, low frequency; PPG, photoplethysmography; PSD, power spectral density; RGB, red, green, and blue; VLF, very low frequency.
Table 4:
Mean and SD estimation
| Parameters | Mean | SD |
|---|---|---|
| Age (years) | 22.1 | 4 |
| LF% | 32.3 | 10.9 |
| HF% | 67.7 | 10.9 |
| LF/HF | 0.49 | 0.59 |
| RMSSD in ms | 152.97 | 34.44 |
| HR (Smart phone) | 93.19 | 18.36 |
| HR (Oximeter) | 93.67 | 15.42 |
| % Error | 5.97 | 2.93 |
Figure 8:
Achieved results of android application. HF, high frequency; HRV, heart rate variability; LF, low frequency; VLF, very low frequency.