I'm using OSCAR 1.1.1 64-bit on Windows 10 Pro 64-bit, and a Resmed Aircurve 10 V Auto.
The time on my V Auto and computer are correct.
I feel like it didn't do this on a previous version of OSCAR, but I can't say for sure...
My explanation in the first paragraph might be a bit confusing so I'll give last night as an example:
Yesterday was Friday, and I woke up at around 14h10, and took a nap from around 16h00 to 17h00.
At night, I went to sleep at 02h50 and woke up the next day at around 12h25. I went back to sleep around 13h40 until 15:45.
When I imported today, it imports all of the data which happened after 12h00 today, but everything before that is missing - that is from 02h50 until 12h00, which should be displayed on Friday (because of how days work on Resmed machines).
Oscar screenshots after importing today:
Friday - 02h50 until 12h00 is missing (that's 9 hours, the majority of my sleep):
Saturday is showing everything that it should be:
The only way I have found for OSCAR to show the missing data is to go to the Data Menu -> Rebuild CPAP Data. I have to do this every time I import, which is every day. It takes longer and longer every day because my database is growing with each night, and it is becoming very tedious.
After Rebuilding the data, the missing 9 hours now shows on Friday:
Does anyone know why everything before noon never shows up on import? I know that when I import, ALL of the data is imported from the SD card to my computer (it just doesn't all show up in OSCAR), because I only import once, then eject the SD card. Then data is missing for the previous night. Then I do the data Rebuild. Again, this happens for every single day and I have to rebuild the data every time I import in order to see it. Is it because once there is data on a given day, it does not add more data to that day on import, or is it something else?
I'd greatly appreciate any help on this, because having to rebuild the data every day is getting longer and longer each time, and doesn't seem like it's going to work very well in the long run.