Apple Watch’s secret and changeable data algorithms are an issue for researchers due to inconsistent data.
A Harvard biostatistician is rethinking plans to use Apple Watches as part of a research study after finding inconsistencies in the heart rate variability data collected by the devices. Because Apple tweaks the watch’s algorithms as needed, the data from the same time period can change without warning.
“These algorithms are what we would call black boxes — they’re not transparent. So it’s impossible to know what’s in them,” JP Onnela, associate professor of biostatistics at the Harvard T.H. Chan School of Public Health and developer of the open-source data platform Beiwe, told The Verge.
For the most part, his teams use research-grade devices that are designed to collect data for scientific studies. As part of a collaboration with the department of neurosurgery at Brigham and Women’s Hospital, though, he was interested in the commercially available products… So, they checked in on heart rate data his collaborator Hassan Dawood, a research fellow at Brigham and Women’s Hospital, exported from his Apple Watch…
Because the two exported datasets included data from the same time period, the data from both sets should theoretically be identical. Onnela says he was expecting some differences. The “black box” of wearable algorithms is a consistent challenge for researchers. Rather than showing the raw data collected by a device, the products usually only let researchers export information after it has been analyzed and filtered through an algorithm of some kind.
MacDailyNews Take: If Apple wants to keep the Apple Watch algorithms secret for competitive reasons, the company should provide a way for researchers to access the devices’ raw data. Problem solved.