PA daytime output analysis

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Ori - Roee Admon Lab

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Nov 2, 2021, 7:51:53 AM11/2/21
to R package GGIR
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)

Screenshot 2021-11-02 134557.png

Vincent van Hees

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Nov 9, 2021, 7:58:38 AM11/9/21
to Ori - Roee Admon Lab, R package GGIR
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

Best, Vincent

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Ori Haran Roee Admon Lab

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Nov 16, 2021, 3:09:27 AM11/16/21
to Vincent van Hees, R package GGIR
Thanks!
What about physical activity analysis by the minute/second/millisecond?
Is there a way to get it from the reports?

Vincent van Hees

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Nov 16, 2021, 12:04:46 PM11/16/21
to Ori Haran Roee Admon Lab, R package GGIR
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

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Nov 16, 2021, 1:50:15 PM11/16/21
to R package GGIR
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:
Capture.PNG

Ori - Roee Admon Lab

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Nov 16, 2021, 1:55:08 PM11/16/21
to R package GGIR
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

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Nov 16, 2021, 3:02:50 PM11/16/21
to Ori - Roee Admon Lab, R package GGIR

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:

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