Development of Predictive Remote Photoplethysmography Algorithm for Blood Pressure Assessment and Monitoring
试验速览
- 阶段
- 不适用
- 入组人数
- 300
- 试验地点
- 1
- 主要终点
- To validate this predictive model by comparing blood pressure readings obtained using rPPG with standard procedures such as contact sensors and automated oscillometry.
研究概览
简要总结
Significant advancements in the field of medical technologies have resulted in the rise of contact-free methods of haemodynamic monitoring. Remote photoplethysmography (rPPG) is a videobased, contactless form of monitoring that operates through a camera-enabled device. This innovation interprets minute variations in skin colour due to blood flow which, when analysed with complex signal processing algorithms, generates vital sign readings. Currently, Nervotec's rPPG technology allows for the collection of rPPG waveforms, which enables the measurement of heart rate, heart rate variability, respiration rate and blood oxygen saturation (SpO2) level through signal processing techniques. The plethysmography signals can be used to estimate blood pressure through the creation and training of a predictive model. By examining and extracting key features of a continuous PPG waveform by training an artificial neural network, correlations between these features and BP can be studied.
详细描述
This is a prospective, feasibility study.Background literature has shown that plethysmography (PPG) signals can be used to estimate blood pressure through the creation and training of a predictive model. By examining and extracting key features of a continuous PPG waveform by training an artificial neural network, correlations between these features and blood pressure can be studied.
Nervotec, a digital health and AI company , has successfully used rPPG technology to allow for collection of rPPG waveforms, which enables the measurement of heart rate (HR), heart rate variability (HRV), respiration rate (RR) and blood oxygen saturation (SpO2) level through signal processing techniques. They have incorporated rPPG technology into a mobile application using smartphone cameras for scanning an individual's face. However, this is yet to be established for blood pressure. We aim to perform a prospective study to evaluate the feasibility and accuracy of obtaining blood pressure measurements through rPPG.
Hypothesis
Remote photoplethysmography can be used to determine blood pressure and this algorithm can develop into a customised smartphone based application.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Health Services Research
- 盲法
- None
入排标准
- 年龄范围
- 21 Years 至 100 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Age ≥ 21 years old
- •Ability to provide informed consent
- •Any surgery except head and neck surgeries
排除标准
- •Age ≤ 21 years old
- •Inability to provide informed consent
- •Patients going for head and neck surgery
结局指标
主要结局
To validate this predictive model by comparing blood pressure readings obtained using rPPG with standard procedures such as contact sensors and automated oscillometry.
时间窗: 1 year
To determine the correlation between remote photoplethysmography (rPPG) and blood pressure variations.
时间窗: 1 year
To develop a predictive model in using rPPG for determination of blood pressure.
时间窗: 1 year
次要结局
未报告次要终点