Part 6/12:
One common critique of current wearables is their tendency to generate vast amounts of health data with limited guidance on actionable insights. For instance, a journalist’s two-year-old smartwatch accumulated half a million health metrics, yet awareness of how to leverage that information remains vague.
To address this, data is being analyzed by specialized algorithms developed by medical researchers. For example, a team from Lee Kong Chien School of Medicine is creating patterns from passive health data to identify hidden health risks, like depression, with notable accuracy. They emphasize that such analysis does not replace doctors but acts as an aid—spotting subtle patterns humans might miss.