non-wear time exclusion

[Spyros Iatropoulos]

Hello, 

1) How can we exclude non-wear periods from the subsequent analysis? From what I understand my output substitutes non-wear time with LPA. My intention is to exclude the non-wear time completely and analyse the rest data available. 

2) Another question is a bit funky but I would appreciate opinions: Since my participants did not wear their monitors during sleeping, the data basically looks like an 8-hr non-wear period and a 16-hr wear period. I understand that part 3,4,5 are not going to be valid (or could they?) so I was thinking to "abuse" the mvpathreshold parameter and assign it as c(30,100) for example to get the MVPA and LPA (>30 TO <100) from part 2 reports. Any thoughts on how bad this might be or any alternatives are welcome!

Thanks

Spyros

[Vincent van Hees]

Hi Spyros,

1) How can we exclude non-wear periods from the subsequent analysis? From what I understand my output substitutes non-wear time with LPA. My intention is to exclude the non-wear time completely and analyse the rest data available.

​

Firstly, non-wear time is not imputed by LPA but by the average of the same timepoint on other days of the recording.

Secondly, we do this because calculating the average over wear-time only time segments would give us a non-representative estimate of a person's behaviour. By excluding non-wear you effectively impute by the average movement of the person during the rest of the recording. This is only meaningful if you can guarantee that all participants did not wear the accelerometer during sleep and never took it off during waking hours, and all output is interpreted as behaviour during waking hours only.

2) Another question is a bit funky but I would appreciate opinions: Since my participants did not wear their monitors during sleeping, the data basically looks like an 8-hr non-wear period and a 16-hr wear period. I understand that part 3,4,5 are not going to be valid (or could they?) so I was thinking to "abuse" the mvpathreshold parameter and assign it as c(30,100) for example to get the MVPA and LPA (>30 TO <100) from part 2 reports. Any thoughts on how bad this might be or any alternatives are welcome!

I think the topic of dealing with large amounts of non-wear requires more research. However, for the time being I would propose:

• Set argument do.imp = FALSE. This will make that non-wear data is not imputed. This would only work if sleep is the dominant activity when the accelerometer is not worn.
  
• Set argument ignorenonwear = TRUE to make that non-wear during the night is detected as sleep.
  
• Set argument relyonguider  = TRUE, to rely on the guider for identifying the largest inactivity period as the sleep period time window.

Best,

Vincent

Dr. Vincent van Hees | Independent consultant | https://accelting.com/

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