Detect periods of gradual decreases in time-series data

I have some time-series data sets in which, in principle, two types of event are possible: the signal can instantaneously jump up or down; or there can be a gradual decrease in the signal. I want to detect the regions featuring only the gradual decreases, without detecting the large jumps in signal strength. Below is an example of this, showing: one gradual decrease of interest from ~392-398 s; a jump back at ~398 s; a pause from ~398-400 s; and a second gradual decrease of interest from ~400-404 s. So far, I have tried various methods to pick out these features, including low-pass filters and matched filters, but I've struggled to get something with enough fidelity to mark the start and end-points accurately. I think the matched filter was the closest I've got, but since I'm only looking for a slight change in gradient of the data the filter wasn't sufficiently discriminatory. My question is similar to that in the thread here , but a) I specifically want to filter out quick changes, unlike in that question; and b) the question there was closed without an answer because the question had insufficient detail, so I'm trying my own here.