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wearables in tranSMART

Data from the L-DOPA response trial
by

Marina Bessarabova

on 21 September 2016

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Transcript of wearables in tranSMART

Standing
Walking
Walking While Counting
Walking Through a Narrow Passage
Going Upstairs
Going Downstairs
Sit to Stand
Sensor Hand Finger-to-Nose
Off Hand Finger-to-Nose
Sensor Hand Alternation
Off Hand Alternation
Typing
Nuts and Bolts (Fine Manipulation)
Pour and Drink
Arrange Papers in a Folder
Fold Towels
Draw on Paper
Sitting
Some tasks elicit predictable activity contrast (e.g. sensor vs offhand tasks)
UPDRS assessment performed (I-IV) and Hoehn and Yahr scores determined

Body morphometrics measured

Demographics
Day 1
Clinical Visit

Prepared for the MJFF
Stephen Wicks, PhD

Subjects are provided with data capture devices and
followed for 4 days

Current and Planned Implementation of Wearable Data
in tranSMART


Manuals and FAQs on Prezi website
YouTube videos
Instructional Prezis, for example Ned Potter's "The how to make a great prezi, prezi" http://prezi.com/_sto8qf_0vcs/the-how-to-make-a-great-prezi-prezi/
For further help
L-DOPA Trial
Abstract "timepoints" vs. actual "timepoints" compete for attention.
Data representation challenges
The L-DOPA trial is a collaborative effort to assess the potential of capturing actigraphy data outside the clinical setting, to inform clinicians of the impact of levodopa self-administration in the home environment.
Tasks sets repeated 6 times
~4 Hour Clinical Visit
Other tasks reflect typical at-home activity (e.g. Fold Towels)
Day 4
Clinical Visit

Days 2 and 3
ad lib
at home

SLEEP
SLEEP
SLEEP
Two-day Continuous Data Capture is split into epochs defined by the reported levodopa administration schedule
65
113
175
197
28
225
56
298
Each epoch begins 30 min prior to the last drug administration

Task list repeated 6+ times at 30 min intervals

Sitting
Sensor Hand to Nose
Off Hand to Nose
Sensor Hand Alternation
Off Hand Alternation

epoch 1
epoch 2
Standing
Walking
Walking While Counting
Walking Through a Narrow Passage
Going Upstairs
Going Downstairs
Sit to Stand
Sensor Hand Finger-to-Nose
Off Hand Finger-to-Nose
Sensor Hand Alternation
Off Hand Alternation
Typing
Nuts and Bolts (Fine Manipulation)
Pour and Drink
Arrange Papers in a Folder
Fold Towels
Draw on Paper
Sitting
Some tasks ellicit predictable activity contrast (e.g. sensor vs offhand tasks)
Tasks sets repeated 6 times
~4 Hour Clinical Visit
Other tasks reflect typical at-home activity (e.g. Fold Towels)
Two-day Continuous Data Capture is split into epochs defined by the reported levodopa administration schedule
15
73
119
143
268
171
325
211
Each epoch is started 30 mins prior to the last drug self-administration

Task list repeated 6+ times at 30 min intervals

Sitting
Sensor Hand to Nose
Off Hand to Nose
Sensor Hand Alternation
Off Hand Alternation

epoch timeline
epoch 1
epoch 2
Actigraphy data
50 Hz acquisition of x,y,z coordinates and a time stamp

Raw data is transformed to a series of measures
Processed Data Measures
5-second Activity Score
Gait Detection
Tremor Score
Movement Level
Step Count


Ordinal data representations
Standing
Walking
Walking While Counting
Walking Through a Narrow Passage
Going Upstairs
Going Downstairs
Sit to Stand
Sensor Hand Finger-to-Nose
Off Hand Finger-to-Nose
Sensor Hand Alternation
Off Hand Alternation
Typing
Nuts and Bolts (Fine Manipulation)
Pour and Drink
Arrange Papers in a Folder
Fold Towels
Draw on Paper
Sitting
Two representations of the 24 hr of data for 1 subject
Averaged activity per hour
Averaged activity per min
epoch 3
Time
Clinical Encounters
Events and Epochs
epoch timeline
To represent time, new data types were defined: timepoint, and datestamp
Timepoint designation specifies special handling in the ETL (tMDataLoader)
Units in "Time" column are converted to base unit (minutes)
X-axis labels are proportional to the numeric value
"datestamp" designations (in development) will parse date stamps and search for the lowest value to determine elapsed minutes for each value in the series
1
2
3
4
5
6
Visit Name
Behavior
Time
The final data is stored to the
i2b2
table in the
c_metadataxml
column, in XML serialized form

| |'<SeriesMeta><Value>' | | series_value | | '</Value>'
| | '<Unit>' | | series_unit_name | | '</Unit>'
| | '<DisplayName>' | | display_name | | '</DisplayName></SeriesMeta>'
| | '</ValueMetadata>'
Currently, epochs are represented as distinct subjects
With improved sample_id support, going forward
epochs can be represented as clinical data samples
each properly associated with subject_id
currently addressed in clinical data file
selecting epoch "Pre" ensures one epoch per subject
yields correct demographics etc. in Summary Stats tab
Simple solution
Each Clinical Visit is a distinct VISIT_NAME value
All data collected between clinic visits gets assigned to a third VISIT_NAME (e.g. "Home")
Use DATA_LABEL or TAG to handle distinct measures
Why is continuous data capture important?
There is potential for parameterization of individual responses
Use these parameters to stratify populations
sensor hand finger-to-nose
unspecified at home
Thanks for your time!
L-DOPA
epoch 3
epoch 4
epoch 5
Full transcript