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Showing posts from March, 2019

Summer - Week 10

This week, I am working to get the dynamic time warping functionality into my program. The process of doing so includes re-processing the features to include the time series, putting each series back together when we construct sequences, and then performing the DTW to generate a number that will be used to compute the kNN of each sequence which can then be used for predictions with the models. The processing time of these activities has gone up significantly since we have been using five different metrics with each of the F phase datasets. I am returning to school next week, and once I've completed the DTW processing all that will remain before we put together our second paper (The date for the reach journal we would like to submit it to is October 1), I am hoping I will have time to look again into the Agglomerative Hierarchical Clustering concept, which I did not successfully complete when we explored it earlier in the summer and then changed focus to the paper. We heard back...
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Week 32

Before I discuss my work this week, I want to include a few definitions to clarify the language I've been using to describe various metrics. Day : While a different 'day' period has been defined throughout the course of our research, we have decided to consistently use the 06:00:00 to 20:59:00 period going forward. Night : Corresponding to 'day', 'night' will be from 21:00:00 to 05:59:00. Baseline : the first three days of a patient's enrollment in the study. For the sake of Dr. Weeks' experiment, this is a significant period because the patients are wearing Actigraphs but not receiving light therapy. For the sake of our experiment, the significance of these days is slightly different. While we are not primarily concerned with the outcome of light therapy, it is valuable to have a point of comparison for a patient's condition. Utilising multiple days for this purpose allows us to wash out any effect that acclimating to the new watch may hav...
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Week 31

This week I finished up the graphs for Dr. Weeks and Dr. Skornyakov and got to work on my idea for sedentary-like activity analysis. I intended to discuss these further here, but I seem to be having an issue uploading pictures with Blogger. Once I have this resolved I will be able to explain them in further detail. Moving on to sedentary-like activity: I want to recap that the idea to identify low-activity instead of high activity was one that stemmed from my reading of several articles on using activity trackers to measure activity levels, most of which relied on periods of textbook sedentary activity (a definition involving both body position and a percentage of metabolism rate). However, for the sake of clarity I am going to begin classifying "high activity" as the number of minutes during the day when the subject's activity level was higher than the median activity level over the first three days. I intend to come up with more concise wording for these definition...
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Week 30

Following our meeting with Dr. Weeks and Dr. Skornyakov, we have a list of tasks to complete to help them out with their projects, as well as some new ideas to consider in light of the difference between the first and second phase actigraphs. Dr. Skornyakov expressed interest in potentially ignoring the first night of data collected for each patient, as there is often an adjustment period associated with sleeping while wearing an unfamiliar device. To get a look at how this might affect our 'baseline' data measurements, Alexa and I are going to calculate what the difference in Coefficient of Variation will be if we choose to only consider days 2 and 3 as the baseline. In addition, I am going to plot out the activity and sleep on the same axes minute-by-minute for the first two days so that we can have a look at how the patient is sleeping. We are also hoping to be able to obtain a few of the phase 1 actigraphs so that Alexa and I can wear them alongside the phase 2 a...
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Week 29

This week, I continued to look at measures of daytime activity and how they may relate to sleep the night before. Upon our realizations about the difference in actigraph sensitivity between subjects, I wanted to look for a way to tailor standards of low (sedentary-like) activity counts to individual patients. I decided to look at the first, second and third quartile thresholds in order to see how counts were distributed across the daytime (lights on to lights off). I also decided to look at the quartiles for nighttime activity. This provided an interesting look at the way the two "phases" of actigraphs were different from one another since there were no patients in the first phase who had median counts of 0 during the night, a characteristic of almost all second phase subjects. Going forward, I want to plot out minutes per day that subjects spent below their baseline Q1 threshold and see if there is correlation between this number and the number of sleep minutes the night b...
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Week 28

Looking to quantify the difference between what we now know to be groups using two unique actigraphs, I calculated the average activity counts per 24 hour day and the average activity counts per minute for each subject, and then took the average of these numbers for the two groups. The results were as follows: Phase 1 (K002-K026) : 181258 counts/day; 123 counts/minute Phase 2 (K027-K037) : 115349 counts/day; 72 counts/minute This demonstrates that there is likely a lower threshold for activity in the first phase vs. the second one. Looking back at the data, this is supported by higher numbers of sleep minutes being recorded in the second phase. This difference suggests that we may want to find different ways to classify sedentary activity for the two different groups. In response to this new information, I intend to spend some more time looking at differences in activity levels between the two groups, as well as revisiting my past explorations to see if there are c...
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