Are Activity Trackers ready for Deep Learning?

At the “REWORK Deep Learning in Healthcare Summit” 2017 Johanna Ernst from Oxford University presented her research on Activity Trackers to collect patient’s vitals as a basis for Deep Learning Monitoring Apps. The Patient’s vital data correlated with his heart frequency, giving information on the success of a surgery.

She sees the main challenges in the application of trackers by different brands in:

• Patent Expiration
• R&D Cost
• Creation of a One Size fits all Model

Further Challenges are finding a marker / a parameter (as the basis for the development of a Deep Learning Algorithm) and actually getting the raw data from the provider of the activity tracker. Also markers are not always accurate enough.

Although an activity tracker is very useful for creating monitoring Apps with Deep Learning in creating patient compliance, it has a negative psychological effect on the patient: Patients tend to reward themselves, after looking at their successes tracked by their device.

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