# Camera-Based Vital Sign Estimation Techniques and Mobile App Development
## 4 Discussion
### Future Work  
On the algorithmic side, we plan to address the automation of color difference signal amplification scaling and improve the accuracy of the SpO2 estimation equation. We will also identify reliable frequency bands for HR and RR detection. To validate the general applicability of the proposed method, a comprehensive database will be constructed, encompassing various lighting conditions and diverse ethnic groups. In addition, to enhance the usability and accuracy of the currently developed mobile application, improvements will be made to both the app's user interface design and the measurement result analysis algorithms. Specifically, the convenience of reviewing bio-signal measurement history will be improved, and a food recommendation algorithm based on the user's current health status will be added. And, regarding the image sequence quality problem, we will focus on enhancing the removal of motion artifacts under diverse conditions by incorporating advanced deep learning architectures. In particular, the integration of deformable kernels, transformers, and diffusion-based models will be explored to improve robustness against complex motion and lighting variations [23]. Additionally, lightweight designs and training strategies across varied datasets will be considered to enable real-time performance and improved generalizability. Future studies should focus on reducing the measurement bias in rPPG that arises from variations in skin tone across different ethnic groups. Darker skin tones, characterized by higher melanin concentrations, exhibit lower reflectance in the visible spectrum, which consequently degrades the reliability of physiological signal estimation. To overcome this limitation, future work will aim to incorporate large-scale training datasets that sufficiently represent a wide range of skin tones, employ color space transformation techniques for channel normalization, and implement skin-tone-aware deep learning compensation networks. In addition, multi-modal approaches using auxiliary channels such as IR, themal, or multispectral imaging will be investigated to structurally mitigate the optical bias introduced by skin pigmentation. For the proposed method to be used in practical medical applications, it must demonstrate minimal differences compared to actual vital sign measurement devices. Additionally, to enhance user convenience, the method should be developed into applications compatible with smartphones, tablets, and small PCs. Furthermore, to accommodate elderly users, the applications will incorporate simplified interfaces and voice recognition technology. The following supporting information can be downloaded at [[https://www.mdpi.com/article/10.3390/app15158509/sl](https://www.mdpi.com/article/10.3390/app15158509/sl)]([https://www.mdpi.com/article/10.3390/app15158509/sl](https://www.mdpi.com/article/10.3390/app15158509/sl)): Figure S1: Reflection model of rPPG signal; Figure S2: Mobile device camera-based HR measurement system; Figure S3: Hamming windows in (a) time and (b) frequency domains; Figure S4: HR detected by time interval; Figure S5: Relative PPG amplitude according to wavelength; Figure S6: Time moving average processing procedure for noise removal; Figure S7: Time divisions used to obtain periodogram. Conceptualization, T.W.B. and Y.C.K. ; methodology, K.K.K. and T.W.B. ; software, Y.C.K. and T.W.B. ; validation, Y.C.K. and K.K.K. ; formal analysis, Y.C.K. and T.W.B. ; investigation, I.H.S. ; resources, Y.C.K. and T.W.B. ; data curation, I.H.S. ; writing--original draft preparation, T.W.B. ; writing--review and editing, T.W.B. and Y.C.K. ; visualization, Y.C.K. and T.W.B. ; supervision, K.K.K. ; project administration, K.K.K. ; funding acquisition, K.K.K. All authors have read and agreed to the published version of the manuscript. This work was supported by an Electronics and Telecommunications Research Institute (ETRI) grant funded by the Korean government and the Gimhae Biomedical Industry promotion Agency.