PA daytime output analysis

[Ori - Roee Admon Lab]

Hello Vincent,

Attached my outcomes from the main report,

I would like to get the vectors representing day activities and Z angles, with timestamps.

I need to examine the y-axis changes in time of this specific report with the highest time resolution possible (milliseconds/seconds).

Is it something GGIR produce? The reports I got are day-summaries.

*I do not need sleep analysis - only changes in activity by time.

I am using Faros 360 machine with 100HZ configuration - this specific file attached represents 1HZ but we will not use this sf anymore.

I have been able to get output from GGIR only by pasting my raw data into the sample csv format data with the header from ActiLife machine (AS COMES FROM "create_test_acc_csv").

Thank you very much.

regards,

Ori

g.shell func parameters:

mode= c(1,2,3,4,5)

studyname="test"

f0 = 1 

f1 = 2

g.shell.GGIR(#-------------------------------

             # General parameters

             #-------------------------------

             mode=mode, 

             datadir=data, 

             outputdir=output, 

             studyname=studyname, 

             f0=f0, 

             f1=f1,

             overwrite = FALSE, 

             do.imp=TRUE,

             idloc=1, 

             print.filename=FALSE,

             storefolderstructure = FALSE,

             #-------------------------------

             # Part 1 parameters:

             #-------------------------------

             windowsizes = c(5,900,3600),

             do.cal=TRUE, 

             do.enmo = TRUE,

             do.anglez=TRUE,

             chunksize=1,

             printsummary=TRUE,

             #-------------------------------

             # Part 2 parameters:

             #-------------------------------

             strategy = 1,

             ndayswindow=7,

             hrs.del.start = 1,

             hrs.del.end = 1, 

             maxdur = 9,

             includedaycrit = 16, 

             L5M5window = c(0,24),

             M5L5res = 10,

             winhr = c(5,10),

             qlevels = c(c(1380/1440),c(1410/1440)),

             qwindow=c(0,24), 

             ilevels = c(seq(0,400,by=50),8000), 

             mvpathreshold =c(100,120),

             #-------------------------------

             # Part 3 parameters:

             #-------------------------------

             timethreshold= c(5,10),

             anglethreshold=5,

             ignorenonwear = TRUE,

             #-------------------------------

             # Part 4 parameters:

             #-------------------------------

             excludefirstlast = FALSE,

             includenightcrit = 16,

             def.noc.sleep = 1,

             outliers.only = FALSE,

             criterror = 4,

             colid=1, 

             coln1=2, 

             do.visual = TRUE,

             nnights = 9,

             #-------------------------------

             # Part 5 parameters:

             #-------------------------------

             # Key functions: Merging physical activity with sleep analyses

             threshold.lig = c(30,40,50),

             threshold.mod = c(100,120),

             threshold.vig = c(400,500),

             excludefirstlast = FALSE,

             boutcriter = 0.8,

             boutcriter.in = 0.9,

             boutcriter.lig = 0.8,

             boutcriter.mvpa = 0.8,

             boutdur.in = c(10,20,30),

             boutdur.lig = c(1,5,10),

             boutdur.mvpa = c(1,5,10),

             timewindow = c("WW"),

             #-----------------------------------

             # Report generation

             #-------------------------------

             do.report=c(1,2,3,4,5),

             visualreport = TRUE,

             do.part3.pdf=TRUE,

             dofirstpage = TRUE)

             # viewingwindow = 2)

[Vincent van Hees]

Hello Ori,

See documentation for arguments:

read.myacc.csv => to read custom csv file formats

epochvalues2csv => to export epoch level variables in GGIR part 2

save_ms5rawlevels => to export epoch level variables in GGIR part 5

windowsizes => to specify epoch length

https://cran.r-project.org/web/packages/GGIR/GGIR.pdf

Best, Vincent

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[Ori Haran Roee Admon Lab]

Thanks!

What about physical activity analysis by the minute/second/millisecond?

Is there a way to get it from the reports?

[Vincent van Hees]

Hi Ori,

The epochs I referred to in my previous message can be as short as 1 second.

Most GGIR algorithms have been optimised to work with epoch lengths of 5 or more seconds. Therefore, careful interpretation of results is warranted when using 1 second epoch.

I cannot remember whether GGIR can handle sub-second epoch requests. Either way, I would not recommend it as there is no strong scientific basis for it.

Classification of sub-second events such as gait failures or arm gestures where such resolution is critical is currently outside the scope of GGIR.

What kind of benefits do you see in having a version of GGIR that can output its classifications in millisecond resolution?

Cheers,

Vincent

‐‐‐‐‐‐‐ Original Message ‐‐‐‐‐‐‐

[Ori - Roee Admon Lab]

Hi Vincent,

For our research, I need indications for a change in PA in the shortest periods of time,

In order to compare it to changes in HR and other measured physiological data.

As I said, I'm looking for the output related to the report I attached * to see these changes as a vector representing changes in activity trends.

Thank you so much!

Ori

*This report:

[Ori - Roee Admon Lab]

p.s. If there is a report that is reflecting exactly what I'm looking for (in 1 seconds long epochs outputs) - I would love to know how it could be created.

[Ben Maylor]

Hi ori,

 

It sounds like your best option therefore may be to generate the timestamped 1s epoch files as .csv using epochvalues2csv=TRUE, with do.angley=TRUE, and then map them over your HR data. Using those arguments will give you something like this per participant, but with 1s per row:

 

timestamp	ENMO	angley
2018-05-04T16:38:25+0100	0.0608	-17.7308
2018-05-04T16:38:30+0100	0.0512	-46.589
2018-05-04T16:38:35+0100	0.088	-23.2137
2018-05-04T16:38:40+0100	0.1468	-6.8204

 

I would also add that you could also input do.anglez=TRUE and do.anglex=TRUE to get all 3 axes.

You will find these files in output/meta/csv folder that is generated when you run the code.

 

Does that answer your question?

 

Kind regards,

Ben

 

 

 

From: rpacka...@googlegroups.com <rpacka...@googlegroups.com> On Behalf Of Ori - Roee Admon Lab
Sent: 16-11-2021 06:55
To: R package GGIR <Rpacka...@googlegroups.com>
Subject: Re: [GGIR] PA daytime output analysis

 

p.s. If there is a report that is reflecting exactly what I'm looking for (in 1 seconds long epochs outputs) - I would love to know how it could be created.

On Tuesday, November 16, 2021 at 8:50:15 PM UTC+2 Ori - Roee Admon Lab wrote:

Hi Vincent,

For our research, I need indications for a change in PA in the shortest periods of time,

In order to compare it to changes in HR and other measured physiological data.

 

As I said, I'm looking for the output related to the report I attached * to see these changes as a vector representing changes in activity trends.

 

Thank you so much!

Ori

 

*This report:

To view this discussion on the web, visit https://groups.google.com/d/msgid/RpackageGGIR/bd8ff07a-ac7f-4c38-8b74-7b5e4c470de0n%40googlegroups.com.