Quantitative Analysis of PPG Signals

Samenvatting

Nowadays, the field of computer science is deeply involved with medical applications in different perspectives like imaging, physiological measurements, monitoring, etc. Photoplethysmography (PPG) is a non-invasive optical technique for measuring physiological parameters like heart rate and blood oxygen saturation or detecting physiological problems. Numerous studies for analyzing the signal, filtering, reconstructing, removing motion artifacts, etc., contribute to this technology’s evolution. These techniques involve time domain and frequency domain analysis of different features and using them for other methods for optimizing the PPG signal. It is unique because it is usually obtained through a light-emitting diode (LED) in the red, infra-red,
or yellow optical spectrum and a photo-detective diode that measures the light absorbed and transforms it into the current. These properties enable the possibility of scaling down PPG sensors and obtaining recordings from tiny devices. Additionally, it was quickly adopted in the mobile industry, making it state-of-art for wearable devices, smartphones, and biomedical applications. Nevertheless, what makes PPG a unique signal? What are the challenges of this technology? As always, efficient and cheap technologies come with different challenging problems. In this paper, a study of all the different studies, techniques, and methodologies is done, going through different publications on Google Scholar. It also includes different approaches to data
analysis for different signals to investigate different Signal Quality Indices (SQIs) behavior. As a study result, a quantitative comparison of the data will be made in order to compare different SQIs behavior on the signals.

Datum prijs	28 okt. 2021
Originele taal	English
Begeleider	Bruno Tiago da Silva Gomes (Promotor), Johan Stiens (Co-promotor) & Joan Lambert Cause (Advisor)