JOURNAL ARTICLE

Wearable Multimodal Vital Sign Monitoring Sensor With Fully Integrated Analog Front End

Yishan WangFen MiaoQi AnZeng-Ding LiuCong ChenYe Li

Year: 2022 Journal:   IEEE Sensors Journal Vol: 22 (13)Pages: 13462-13471   Publisher: IEEE Sensors Council

Abstract

Cardiovascular disease (CVD) is a widespread disease and the leading cause of death worldwide. Home care is essential for patients with CVD, and it involves the daily monitoring of important CVD-related vital signs using methods including electrocardiography (ECG), heart rate monitoring, pulse oximetry (SpO2), and continuous blood pressure measurement. However, a wearable device that can monitor these parameters simultaneously remains unavailable; herein, we propose a lightweight, highly integrated sensor that can do so. In this sensor, an analog front end (AFE) integrated chip (IC) is implemented in the sensor to detect one-lead ECG and two-wavelength photoplethysmography (PPG) signals. The highly integrated IC minimizes both the size and power requirement of the sensor. Moreover, its comprehensive functions include adjustable gain, current compensation, lead off, and fast recovery—all of which are crucial for wearable applications in large populations. Accordingly, the sensor can apply the adaptive adjust method to automatically adjust the IC parameters to suit a range of applications and users. In addition, the heart rate is calculated from the R-R interval from the ECG signals, whereas the SpO2 is calibrated with a univariate quadratic equation with less than 1% mean error. Our sensor can also calculate the systolic blood pressure (SBP) and diastolic blood pressure (DBP) by using a support vector machine based calibration-less model with the features of infrared PPG and ECG signals. The model is trained on our pre-collected wearable dataset and has a mean error ± standard deviation of −2.10 ± 7.07 mmHg for SBP and 0.04 ± 7.34 mmHg for DBP in 16 volunteers. In conclusion, this paper reports on a multimodal, vital sign monitoring sensor—with small size, low power, and dynamic compatibility—suitable for patients with CVD under home care.

Keywords:
Remote patient monitoring Wearable computer Photoplethysmogram Computer science Pressure sensor Vital signs Analog front-end Front and back ends Electrocardiography Blood pressure Real-time computing Artificial intelligence Electronic engineering Computer vision Embedded system Engineering Medicine Cardiology

Metrics

29
Cited By
3.22
FWCI (Field Weighted Citation Impact)
29
Refs
0.88
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Non-Invasive Vital Sign Monitoring
Physical Sciences →  Engineering →  Biomedical Engineering
ECG Monitoring and Analysis
Health Sciences →  Medicine →  Cardiology and Cardiovascular Medicine
Heart Rate Variability and Autonomic Control
Health Sciences →  Medicine →  Cardiology and Cardiovascular Medicine
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