Ambient Light-Driven Wireless Wearable Finger Patch for Monitoring Vital Signs From PPG Signal

• Published in: IEEE sensors journal Vol. 24; no. 1; pp. 931 - 942
• Main Authors: Sadaghiani, Shahab Mahmoudi, Ardakani, Amir, Bhadra, Sharmistha
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Ambient light; Analog circuits; analog front end (AFE); Batteries; Biomedical monitoring; Blood pressure; blood pressure (BP); Charging; finger patch; Fingers; Heart rate; heart rate (HR); Light emitting diodes; Lithium ions; no-light-emitting diode (LED) mode photoplethysmogram (PPG) signal; Photodiodes; Power consumption; Power management; PPG; Rechargeable batteries; Sensors; Signal quality; Substrates; Telemedicine; Vital signs; Wearable computers; Wearable technology; Wireless communication; Wireless sensor networks; wireless wearable
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2023.3335309

In recent years, wearable health monitoring using photoplethysmogram (PPG) has become a popular trend. However, one of the main challenges of PPG sensing is the power usage of the light-emitting diode (LED) in the technique. In this work, we designed a wireless wearable finger patch that can record PPG signals solely using ambient light, entirely eliminating the requirement for LED power consumption. The finger patch is implemented on a two-layer flexible polyimide substrate and is based on a high sensitivity silicon photodiode (PD) and a high dynamic range analog front end (AFE). The entire circuit is powered by a rechargeable Li-ion coin battery. It also uses a Bluetooth module to send the PPG data wirelessly. The system is validated with 12 healthy subjects for the collection of PPG signals under three ambient light conditions. Assessment of the PPG signals quality demonstrates that the PPG signals acquired under the ambient light conditions can be placed in the reliable or acceptable category. Finally, two vital signs: heart rate (HR) and blood pressure (BP) are extracted from the no-LED mode PPG signals obtained from 12 subjects using the finger patch. The calculated maximum mean absolute error (MAE) for HR in comparison to the reference measurement is small (3.4 BPM). For BP prediction AlexNet network with training of all layers with finger patch PPG data shows better performance and produces BP with an average MAE of 8.1 mmHg and 6.05 mmHg for systolic BP (SBP) and diastolic BP (DBP), respectively. Without any need to turn on any LED, the finger patch can save power and will have the potential for long-term health monitoring without frequently charging batteries.