Is Skin Color a Factor in the Measurement of Heart Rate Monitoring?

Health trackers and watches can precisely measure variation in heart rate across a range of skin tones.  Variations between units begin to occur significantly throughout a variety of day by day activities.

The current study emphasizes a need for a more in-depth understanding of the reliability of these devices and how the variation in their results may have a direct effect on research findings and further device development.

Due to a lack of published information from the manufacturers on device performance across the spectrum of skin colors, the study sets out to collect these metrics along with conditions where the measurements may have significant variations. 

Fifty-three subjects with a diverse spectrum of skin tones participated in a study of the performance of six different measurement devices. 

The technology used in these biometric measurement devices is photoplethysmography, commonly known as PPG. This process shines a certain wavelength of green light, on the area contacted by the sensor, most frequently the wrist. A pulse oximeter then takes measurements of variations in the tissues that absorb the light. This data is then converted into a digital heart rate.

An additional point of interest of the study was to establish performance ratings of the trackers during varying daily activities.

A variety of medical-grade and commonly available devices were measured across varying skin tones, activity types, and levels to compare measurement accuracy and performance.

Activities creating significant wrist movements such as typing were shown to provide less accurate results, regardless of skin tone than in other activities with more generalized movement.

 

rare-disease3 KEY POINTS

  1. No significant statistical changes in the results of device measurement were found between skin tones in this study.
  2. The study concludes that there is a higher degree in the variability of readings for those wearers that engage in significantly more wrist motion than in those of more stable wrist mobility.
  3. The findings from this study open a pathway for improvements in measurement devices for their use in clinical research applications.

 

“We want to use these devices to measure digital biomarkers and predict disease outcomes, so if there are disparities in how these devices work, we need to identify them.” says Jessilyn Dunn, assistant professor of biomedical engineering at Duke.

 

#DigitalHealth,  #DeviceStudy, #ElectronicDataCapture

Article Source: http://bit.ly/2vKhOZz

 

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