Reflective oxygen saturation monitoring at hypothenar and its validation by human hypoxia experiment

Abstract

BackgroundPulse oxygen saturation (SpO2) is an important parameter for healthcare, and wearable sensors and systems for SpO2 monitoring have become increasingly popular. The aim of this paper is to develop a novel SpO2 monitoring system, which detects photoplethysmographic (PPG) signals at hypothenar with a reflection-mode sensor embedded into a glove.MethodsA special photo-detector section was designed with two photodiodes arranged symmetrically to the red and infrared light-emitting diodes (LED) to enhance the signal quality. The reflective sensor was placed in a soft silicon substrate sewn in a glove to fit the surface of the hypothenar. To lower the power consumption, the LED driving current was reduced and energy-efficient electronic components were applied. The performance for PPG signal detection and SpO2 monitoring was evaluated by human hypoxia experiments. Accelerometer-based adaptive noise cancellation (ANC) methods applying the least mean squares (LMS) and recursive least squares (RLS) algorithms were studied to suppress motion artifact.ResultsA total of 20 subjects participated in the hypoxia experiment. The degree of comfort for wearing this system was accepted by them. The PPG signals were detected effectively at SpO2 levels from about 100–70%. The experiment validated the accuracy of the system was 2.34%, compared to the invasive measurements. Both the LMS and RLS algorithms improved the performance during motion. The total current consumed by the system was only 8 mA.ConclusionsIt is feasible to detect PPG signal and monitor SpO2 at the location of hypothenar. This novel system can achieve reliable SpO2 measurements at different SpO2 levels and on different individuals. The system is light-weighted, easy to wear and power-saving. It has the potential to be a solution for wearable monitoring, although more work should be conducted to improve the motion-resistant performance significantly.

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Study on design of a human vital signs simulator

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Happy Hypoxia Early Detection Tool in IoT Based for COVID-19 Patients Using SpO2 Sensor, Body Temperature and Electrocardiogram (ECG)

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