Good way for segmenting this signal
I solved this by still using Otsu to find the threshold value. I then just filter the the regions with value == 1 in the thresholded signal (i.e. the region_mask; green line in plot below) by their width.
This is the result, where the rectangular peak on the right will be filtered (see below for the code):

plt.plot(signal_orig)
plt.plot(signal)
plt.plot(region_mask * np.max(signal))
plt.show()



Code:

signal = savgol_filter(signal_orig, 51, 1)  # window size 51, polynomial order 1
threshold = threshold_otsu(signal)

region_mask = signal &gt; threshold
region_list = get_regions_from_mask(region_mask)
region_list = filter_date_regions_by_width(region_list, minimum_region_width=200)


def filter_date_regions_by_width(region_list, minimum_region_width):
    """
    Filters removes data regions from region_list with width &lt; minimum_region_width.

    :param region_list: list of DataRegion objects, that we want to filter.
    :param minimum_region_width: minimum width of a region, so that it is not filtered out.
    :return:
    """
    filtered_list = []
    for region in region_list:
    if region.width &gt;= minimum_region_width:
        filtered_list.append(region)
    return filtered_list


def get_regions_from_mask(region_mask):
    """
    Get list of the DataRegion objects that were found inside region_mask.

    :param region_mask: the np.array of 0 and 1 in which we want find regions of value == 1.
    :return: region_list: a list of DataRegion objects.
    """
    region_list = []  # list that will hold all regions that were found
    region = DataRegion()  # object to hold the start and end values of the region
    inside_region = False  # indicates, if we are currently inside a mask_region with value=1
    for index, value in enumerate(region_mask):
    if value == 1 and not inside_region:
        # entered a region
        inside_region = True
        region.start = index
    if value == 0 and inside_region:
        # left a region
        inside_region = False
        region.end = index
        region.width = region.end - region.start
        region_list.append(region)
        region = DataRegion()
    return region_list


Definition of the DataRegion class:

from dataclasses import dataclass


@dataclass
class DataRegion:
    start: int = None
    end: int = None
    width: int = None