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|Title:||Photoplethysmography analysis tool with heart rate variability through poincare and sequence bandwidth assessment||Authors:||Lim, Si Zhou||Keywords:||Engineering::Mechanical engineering||Issue Date:||2022||Publisher:||Nanyang Technological University||Source:||Lim, S. Z. (2022). Photoplethysmography analysis tool with heart rate variability through poincare and sequence bandwidth assessment. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158479||Project:||A146||Abstract:||As the number of people affected by cardiovascular diseases (CVD) increases each year with hypertension, maintaining of blood pressure levels becomes crucial. Traditionally, it was done using sphygmomanometer which is the clinical standard for measurement. However, the method has proven to be impractical due to the lack of constant monitoring and convenience. Many researchers have thus investigated Photoplethysmography (PPG) wearable technologies in search for a better alternative. The wearables that are currently available such as smartwatches have demonstrated to be relatively inaccurate with motion and noise artifacts and they are not suitable for the adoption in healthcare applications with the lack of clinical information. Hence, there is significant need to develop a technique for obtaining accurate and useful clinical information from PPG. This study presents the development of a PPG analysis tool with the assessment of Heart Rate Variability (HRV). With a prototype that was initially developed prior the start of this project, data collection of ECG and PPG signals alongside heart rates and blood pressures using a blood pressure monitor was carried out. Subsequently, a simple yet accurate original window extraction algorithm was developed to carefully select and extract proper PPG waveforms to be used for analysis. The process included signal pre-processing, filtering, feature detection, window extraction and signal reconstruction. Following that, various measures of HRV such as time domain, frequency domain, non-linear (Poincaré) and its bandwidth were extracted to better analyse the PPG signals. The main focus of the study was to evaluate and analyse PPG through Poincaré and HRV sequence bandwidth. These 2 measures were used for analysis due to their potential significance in providing clinical usefulness and possibility of a new breakthrough. Lastly, a Graphical User Interface (GUI) application was designed to provide easy viewing of a summary of the HRV analysis.||URI:||https://hdl.handle.net/10356/158479||Schools:||School of Mechanical and Aerospace Engineering||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||MAE Student Reports (FYP/IA/PA/PI)|
Updated on Sep 23, 2023
Updated on Sep 23, 2023
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