Wearable Pulse Oximeter for Swimming Pool Safety.
Elżbieta KałamajskaJacek MisiurewiczJerzy WeremczukPublished in: Sensors (Basel, Switzerland) (2022)
The purpose of this research was to develop an algorithm for a wearable device that would prevent people from drowning in swimming pools. The device should detect pre-drowning symptoms and alert the rescue staff. The proposed detection method is based on analyzing real-time data collected from a set of sensors, including a pulse oximeter. The pulse oximetry technique is used for measuring the heart rate and oxygen saturation in the subject's blood. It is an optical method; subsequently, the measurements obtained this way are highly sensitive to interference from the subject's motion. To eliminate noise caused by the subject's movement, accelerometer data were used in the system. If the acceleration sensor does not detect movement, a biosensor is activated, and an analysis of selected physiological parameters is performed. Such a setup of the algorithm allows the device to distinguish situations in which the person rests and does not move from situations in which the examined person has lost consciousness and has begun to drown.
Keyphrases
- heart rate
- blood pressure
- heart rate variability
- machine learning
- electronic health record
- label free
- deep learning
- big data
- finite element
- high speed
- high resolution
- gold nanoparticles
- air pollution
- quantum dots
- sensitive detection
- neural network
- loop mediated isothermal amplification
- molecularly imprinted
- mass spectrometry
- low cost