Using Longitudinal Sleep Data as a Vital Sign to Predict Disease Risk with Colin Lawlor Sleep ai

Colin Lawlor, CEO of Sleep ai, is focused on exploring sleep intelligence and sleep as a vital sign of health. The Sleep ai platform measures sleep longitudinally using data from consumer wearables and smartphones, with an emphasis on night-to-night variability, which is not captured in a single-night sleep lab. Poor sleep and variation in sleep patterns have been identified as highly predictive indicators of over 130 chronic diseases and have an impact on mental well-being and the effectiveness of medical treatments. Colin explains, "What we're doing is we're measuring sleep longitudinally, over the long term, and we're measuring it from whatever device the consumer has. For some consumers or patients, it may be wearable, and there are many, many different wearables, or for others, it's simply from their phone. We have the ability to collect high-quality sleep data from everyone every day. And that's really important because when we get into this, we'll talk about why longitudinal measurement is really helpful in dealing with sleep challenges themselves, but also in seeing sleep as a window into literally everything to do with our health."   "There are several factors going on here. The first one is that globally, four billion people wake up tired almost every day. We do not have, and we will never have, a sufficient number of sleep labs to send all of them for a one-night study. And if we collect data for only one night, we're only getting one picture of how that person is sleeping. But as we all know, life gets in the way. We may have had a stressful day, or we may have had an argument with our significant other. We may be suffering from a cold."   "Whatever it is, all of these multiple factors influence sleep. So if we over-rely on one data point to understand what's going on, it's just not sufficient. So what we are finding is that, actually, the variance night to night is probably the most useful and insightful thing we can see. Because when we look at the variance across many nights, we have a much more accurate picture of what's happening with the person's sleep, and that's highly predictive of many, many other conditions, issues, and challenges."  #SleepAI #DigitalHealth #SleepAsAVitalSign #ChronicDisease #PopulationHealth #AIinHealthcare #Wearables #LongitudinalData #SleepHealth, #SleepScience  sleep.ai Download the transcript here