Fig 1.
A motivational example.
Fig 2.
An example of salient points extracted from a given sequence.
The blue curve represents the sequence of original health data. The point at which each red line parallel to the y-axis intersects the blue curve corresponds to a salient point.
Fig 3.
An overview of the proposed approach.
The proposed approach can avoid a high expected error caused by the large sequence length by selecting and reporting a small amount of salient points to a data collector.
Fig 4.
Pseudo-code for searching salient points in a given sequence.
Fig 5.
(a) Logistic curve and its symmetric curve for two salient points, and
, and (b) four different curves that are used to rebuild a stream segment depending on the values of μratio and
.
Fig 6.
Relative error ratio for varying privacy budget ϵ and data size.
Fig 7.
Error rate for varying privacy budget ϵ and data size.
Fig 8.
Actual vs. estimated stream of the average heart rates for varying data size (ϵ = 1.0).