Optical blood volume sensors found in fitness trackers rely on light emission and reflection to track blood oxygen saturation. These sensors direct optical pulses toward dermal tissue and analyze photonic return signals to track pulsatile arterial flow. However, skin pigmentation levels significantly alters how light penetrates and scatters. People with deeper skin pigmentation contain greater quantities of melanin, which reduces light penetration depth. This leads to diminished optical responsiveness, making it harder to reliably calculate SpO₂ or pulse rate.

Several independent research papers have demonstrated that many commercial fitness trackers display significantly higher error rates among users with higher Fitzpatrick skin types compared to those with lighter skin tones. This performance gap is not a result of manufacturing errors but stems from algorithmic bias rooted in homogeneous data. Consequently, the signal processing algorithms often misinterpret physiological artifacts in darker skin types.

Leading wearable brands are beginning to expand their training datasets and enhancing sensor hardware by adding infrared and green LED combinations. Yet, progress remains inconsistent across product lines. People of color may experience inconsistent or erratic readings, leading to reduced confidence in data.

Health-conscious users should understand the accuracy disparities when choosing a fitness tracker. Depending solely on PPG readings may be unreliable if performance varies by skin tone. Healthcare providers must factor in demographic variability when interpreting patient metrics. Solving this challenge demands ongoing collaboration among data scientists, medical experts, and underrepresented populations to ensure that health monitoring technology deliver consistent performance for every demographic group.