A Reflectance-based multimodal wearable photoplethysmography (PPG) sensor.

Area of Science:

• Biomedical Engineering
• Wearable Technology
• Physiological Monitoring

Background:

• Conventional photoplethysmography (PPG) sensors struggle with accuracy in diverse skin tones due to melanin interference.
• Optical attenuation in darker skin can lead to significant measurement errors in vital signs.
• Existing wearable sensors often lack robust performance across the full spectrum of human skin pigmentation.

Purpose of the Study:

• To introduce ChromaSense, a novel reflectance-based wearable PPG sensor.
• To demonstrate ChromaSense's capability for accurate vital sign monitoring (SpO2, pulse, respiration) across diverse skin tones.
• To address and mitigate skin-tone-dependent variability in PPG measurements.

Main Methods:

• ChromaSense integrates spectral colorimetric sensing with PPG.
• It adaptively adjusts LED drive current based on estimated skin reflectance.
• The system was validated on 50 participants representing the Fitzpatrick skin tone scale.

Main Results:

• ChromaSense achieved SpO2 accuracy (1.36% RMS error) meeting ISO standards (≤3.5%), outperforming previous technologies.
• Pulse rate estimation accuracy was within ±10% for 84% of measurements.
• Respiration rate estimation accuracy was within ±5 breaths per minute for 90% of measurements.
• No statistically significant SpO2 measurement error differences were found across Fitzpatrick skin types (p = 0.518).

Conclusions:

• The multimodal sensing strategy in ChromaSense effectively mitigates skin-tone-dependent variability.
• ChromaSense enables consistent and accurate physiological measurement performance across diverse users.
• This technology advances equitable and reliable wearable health monitoring solutions.