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ChildMindInstitute / Healthy-Brain-Network-wearable-evaluation

tests for HBN wearable analysis
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Wear Time Validation #7

Open shnizzedy opened 7 years ago

shnizzedy commented 7 years ago

Our ActiGraph devices include a wear time sensor "which can be used to detect monitor removal when worn against the skin." image Additionally, the ActiLife software provides the option to use the wear time algorithm defined in

Choi, L., Liu, Z., Matthews, C. E., & Buchowski, M. S. (2011). Validation of Accelerometer Wear and Nonwear Time Classification Algorithm. Medicine and Science in Sports and Exercise, 43(2), 357–364. doi:10.1249/MSS.0b013e3181ed61a

or the one defined in

Troiano, R. P., Berrigan, D., Dodd, K. W., Mâsse, L. C., Tilert, T., & McDowell, M. (2008). Physical activity in the United States measured by accelerometer. Medicine and Science in Sports and Exercise, 40(1), 181. doi:10.1249/mss.0b013e31815a51b3.

The options are:

  1. wear time sensor exclusively
  2. Choi exclusively
  3. Troiano exclusively
  4. wear time sensor and Choi a. accept only agreed-upon non-wear time b. prefer wear time sensor c. prefer Choi d. manually evaluate conflicts
  5. wear time sensor and Troiano a. accept only agreed-upon non-wear time b. prefer wear time sensor c. prefer Troiano d. manually evaluate conflicts
  6. no wear time annotation

My inclination is to use option 1 for the data we share and let researchers apply Choi or Troiano or other algorithms on their own.

binarybottle commented 7 years ago

Can you provide results for all three? Otherwise, I would also go with#1.

On Tue, Oct 17, 2017, 5:29 PM Jon Clucas notifications@github.com wrote:

Assigned #7 https://github.com/ChildMindInstitute/HBN_wearable_evaluation/issues/7 to @binarybottle https://github.com/binarybottle.

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shnizzedy commented 7 years ago

All three as in the first three? We could, but that means doing each subsequent processing step thrice per participant.

binarybottle commented 7 years ago

If it isn't too much of a hassle and the software is available and open, I would provide 1, 4a, 5a, and the consensus of those three, if we are more concerned about retaining activity data than we are about accuracy of activity profile, unless there is a reason to distrust the sensor. Enough caveats there?

On Tue, Oct 17, 2017, 5:54 PM Jon Clucas notifications@github.com wrote:

All three as in the first three? We could, but that means doing each subsequent processing step thrice per participant.

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