Providing insights in patients vitality data for homecare organisations requires to aggregate sensitive personal health data produced by personal vitality sensors and activity trackers. This data ranges from ambient sensors in the home, e.g. location, movement, light and temperature sensors, or the use of certain devices, to data from sensors on the monitored patients themselves, e.g. wearables or sensors on a smartphone. From these sensor measurements, various activities can be extracted. The DAHCC dataset will be used for purpose.
As pod contain sensitive data, special measures need to be taken even when providing aggregations on top of this sensitive data. Both multi-patient aggregations ,e.g. how many patients are sleeping, and aggregation for a single patient, e.g. how many social interactions did this patient have this week.
Desired solution
An Aggregator that can handle both data streams and sensitive personal data.
This requires:
the aggregator to be notified or actively monitors the pods for new events in the data streams
the aggregation to be efficiently updated when new data arrives on each pod
no personal data can be extracted from the aggregation
Acceptance criteria
A demo that show cases an solution would need to be able to:
show a monitoring dashboard regarding a large number of personal health data pods
show that the aggregations/metrics/graphs/tables/... shown in the dashboard are updated when new data is produced
both multi-patient as single patient aggregations are shown
show that no sensitive data can be extracted -> TBD how to best handle this
Pitch
Providing insights in patients vitality data for homecare organisations requires to aggregate sensitive personal health data produced by personal vitality sensors and activity trackers. This data ranges from ambient sensors in the home, e.g. location, movement, light and temperature sensors, or the use of certain devices, to data from sensors on the monitored patients themselves, e.g. wearables or sensors on a smartphone. From these sensor measurements, various activities can be extracted. The DAHCC dataset will be used for purpose. As pod contain sensitive data, special measures need to be taken even when providing aggregations on top of this sensitive data. Both multi-patient aggregations ,e.g. how many patients are sleeping, and aggregation for a single patient, e.g. how many social interactions did this patient have this week.
Desired solution
An Aggregator that can handle both data streams and sensitive personal data. This requires:
Acceptance criteria
A demo that show cases an solution would need to be able to: