I agree with Curtis’ premise. What I don’t see is how this will be achieved. Several current digital health technologies are profiled, especially in the illustrations. These include an iPhone glucose meter add-on (GlucoDock) and an implanted glucose sensor and monitor (Dexcom SEVEN PLUS), a mobile ultrasound device (MobiUS SP1), and a smart pill box (Vitality GlowCap). Mention is also made of activity and diet monitoring – topics I have also covered.
To realize the vision of a phone being able to identify sickness, a vastly larger number of health parameters would seem to be necessary. However, sensors for these will appear long before we expect them since massively parallel development is underway worldwide. This is being actively encouraged; take for example the X PRIZE for the development of a health TRICORDER (fans of Star Trek will understand the term).
But focus for a moment on the specific issue – knowing that I am sick. That might actually be relatively easy to achieve. There are some obvious markers such as body temperature. If you have an infectious disease your temperature rises as your body mounts a response (i.e. fever). However, body temperature fluctuates normally over a 24 hour period ranging from 36.4 to 37.5 °C. So to be sure of a positive diagnosis, we currently we look for a marked increase in temperature to a level not normally found at any time. But if a device was constantly monitoring core temperature, the typical daily temperature levels for a given individual would be known, so deviations could be spotted earlier. Sensitivity could also be improved by accounting for local environmental temperature, seasonal variations and personal activity levels, etc.
As a side benefit, such a device could also ‘watch’ for the beginning of hyperthermia or hypothermia, which would be useful for people, especially the elderly, in extreme environments.
Behavioural monitoring through activity sensors might well give indications before we are consciously aware of them.
These are simple metrics. But what makes them so useful is when they are combined with other current technologies:
- Constant monitoring by mobile devices
- Long-term data-logging and analysis, likely through connected cloud services, and
- Automated interpretation based on aggregated population data (i.e. big data)