# The Impact of Contact Force on Signal Quality Indices in Photoplethysmography Measurements
## 5 Discussion  
This study evaluates the influence of CF on the SQI of PPG signals for the first time and addresses the cross-comparison limitations due to individual variability. The normalization of the CF proposed in this work enables a better comparison between different data records. The signals analyzed in this study have undergone minimal processing, sufficient only to separate the AC and DC components and filter out high-frequency noise. Efforts have been made to preserve the morphological characteristics of the original signal, enabling a comprehensive examination of all the features present in a physiologically representative PPG signal. The statistical analysis was performed on the normalized wavelengths, with a specific focus on the 940 nm wavelength. This wavelength was used as a reference because it not only penetrates deeper into the tissue but also contains optical information representative of other wavelengths with lower tissue penetration (470, 525, 590, and 631 nm). The analysis results validate this choice, showing consistent optimal ranges across all the wavelengths evaluated. This suggests that the 940 nm wavelength effectively represents global behavior concerning the SQIs analyzed. Using the 940 nm wavelength as a reference simplifies the presentation while ensuring that the findings apply to a broader range of conditions and wavelengths. The statistical analysis of \(S_{SQI}\) and \(K_{SQI}\) reveals that the quality of the PPG AC signal is highly dependent on the CF between the sensor and the skin. The intermediate ranges of CF (0.2-0.4 and 0.4-0.6) provide the most stable and consistent signal, showing moderate positive skewness and kurtosis close to zero. The range of 0.4 to 0.6 is the most optimal for these SQIs. On the other hand, both the low range (0-0.2) and the high ranges (0.6-0.8 and 0.8-1.0) show high variability and distortion in the signal, indicating problems in terms of insufficient or excessive contact. Furthermore, the \(Z_{SQI}\) analysis reveals that the frequency of zero crossings is quite consistent across the different CF ranges, with a slight decrease at the highest CF values. This suggests that, in terms of signal stability, the CF does not significantly impact the frequency of sign changes, except in the highest range, where there may be spikes in variability due to excessive pressure. The statistical analysis of \(E_{SQI}\) shows that the complexity of the PPG AC signal is the greatest in the range of CF 0.4-0.6, where the signal captures the greatest amount of physiological detail. The lower and higher CF ranges present less complexity and greater variability. The signal quality in \(R_{SQI}\) is also the best in the CF 0.4-0.6 range, where the signal shows the highest proportion of useful signal to noise. The lower (0-0.2) and higher (0.8-1.0) ranges show greater variability and extreme values, indicating inconsistencies in signal quality. On the other hand, the \(P_{SQI}\) suggests that the optimal CF range for extracting information about perfusion and blood flow is 0.2 to 0.4. The differences between the optimal ranges suggested by the \(P_{SQI}\) and the rest of the SQIs can be explained by the contrasts in the metrics evaluated and the impact of the CF. The PI measures the relationship between the pulsatile and non-pulsatile components of the signal, focusing on the peripheral perfusion and signal quality in terms of the blood flow. The other metrics evaluated measure different aspects of signal quality, such as complexity,stability, and the ratio of useful signal to noise. The results suggest that the CF range of 0.2-0.4 provides sufficient pressure for good perfusion, resulting in a high \(P_{SQI}\). However, this pressure may not be ideal for capturing all the complex details of the signal, which is reflected in the lower \(E_{SQI}\) values. On the other hand, the CF range 0.4-0.6 provides a balance where the pressure is adequate to capture a complex and detailed signal (high entropy) and maintain a good, useful signal-to-noise ratio ( \(R_{SQI}\)).