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
In the past week, I managed to finish up my longest-bout calculators for both the longest sleep and longest wake periods. The results for longest sleep bouts were significantly lower than I would have predicted, so I spent some additional time trying to verify my results. According to my calculator, many patients had an average longest bout that was less than a hundred minutes - that is to say, throughout the night they never slept for more than two hours at once! While we expect somewhat irregular sleep patterns from our subjects due to their traumatic brain injuries or strokes, this number seems extreme. However, upon checking the data for a single patient in excel, it did not appear to be incorrect based on our current criteria for sleep/wake. In the next week, I'm going to check on an additional subject's data - one with the lowest average longest sleep bout - to ensure again that I'm not making a mistake. Then, I am going to work on standardizing and modelling the da