Indeed, there are studies and discussions showing that wearable devices may have racial bias in health monitoring, and the main reasons for this include the following aspects: 1. Insufficient data collection and algorithm training: The data sets of many health monitoring devices may mainly come from a specific population (such as white or Asian), and lack sufficient representation of other races. When the trained algorithms are applied to other skin colors or races, errors or deviations may occur, resulting in inaccurate monitoring results. 2. Sensor design and calibration issues: Take optical sensors as an example, such as photoplethysmography (PPG) technology, which is often used for heart rate and blood oxygen monitoring. Different skin colors have different absorption and reflection characteristics for light, especially dark skin may absorb more light, resulting in reduced signal quality. If these differences are not fully considered during the device design and calibration process, it may have an adverse effect on people of certain skin colors in actual use. 3. Insufficient consideration of physiological and anatomical variations: In addition to skin color, different races may have differences in skin thickness, hair growth, and local blood flow, which may also affect the accuracy of sensor reading and monitoring. 4. Insufficient clinical validation and supervision: Some devices may not be adequately clinically validated for different races before they are put on the market, exposing limitations in applicability and accuracy in actual use. Overall, although wearable health monitoring devices have brought convenience to people and greatly promoted the real-time acquisition of health data, it is key to ensure diversified data collection, adequate validation testing, and calibration for different populations during research and development and clinical application. With the increasing demand for health equity, more and more manufacturers and research teams are paying attention to this issue and working hard to improve device design and algorithms to reduce racial bias and protect the health rights and interests of all people.