Dig Deeper, or It Is About Time We Standardlize our Tools – Noam Hadas

I have been active in sleep for the past 15 years, and I am excited to see the explosive growth in activity and the recognition that sleep medicine has achieved over this period. Indeed, there are very few examples in medicine that showed such a move from a curiosity item hailed by some researchers, into a well-accepted and active medical specialty. Still, in at least one aspect, I believe sleep medicine is still in its infancy stage.

Some years ago I invented the SleepStrip – the disposable sleep apnea screening device. It is a very simple device, nothing more than three thermistors and a miniature processor that analyzes breathing in real time, counts apnea and hypopnea events and reports the estimated AHI in the morning. During R&D, and after the device was launched, we were testing and validating the device’s accuracy by comparing its readings to AHI derived from full-scale, in-lab, same-night recordings, and this is when we began to see awkward things.

The same device, tested in different labs across the globe, received highly variable reviews. In some labs correlation with the sleep lab results was excellent, and in others – poor. Sensitivity, specificity and total accuracy were similarly inconsistent. As more and more studies were completed and published, the picture and the question that it presented became very clear: How can the same device, when tested against the gold standard, show such wildly different results? I have been thinking about this for several years now, and cannot escape the unavoidable conclusion: Not all sleep labs are created equal.

I am an engineer for the sleep sensor manufacturer SleepSense. I design sleep sensors for a living, performing activities such as calculating airflow patterns over a sensor and simulating the dynamics of chest movements when a person breathes. As part of the design process I consider many highly technical parameters that impact the signal the sensor will eventually produce in different circumstances. Knowing what I know about sensors and signal processing, it is easy to put a finger to at least a few of the variables people usually neglect when selecting sensors and sleep testing systems, or when scoring a study.

Ask yourself: What is the time constant of your pulse oximeter? Are you aware of the fact that different processing algorithms and time behaviors of the oximeter can greatly affect your study results? As an engineer, I think it is about time the experts took more interest in the tools they use and formulate standards for sensors and signal processing parameters that will, hopefully, make the sleep labs a little more “golden”. Not all wiggly lines are the same, and if sleep medicine is to mature into a science, it is time that we take a hard, long look at the tools of the trade and set standards.

Noam Hadas,
President and CEO,
SLP Inc, St Charles, IL

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