mind trainr: how stressed will you be in the next two hours?
TRANSCRIPT
![Page 1: Mind trainr: how stressed will you be in the next two hours?](https://reader035.vdocuments.site/reader035/viewer/2022062412/587448e51a28ab0e6c8b9161/html5/thumbnails/1.jpg)
How stressed will you be in the next two
hours?Xin Chen
Data source: Spire Inc
![Page 2: Mind trainr: how stressed will you be in the next two hours?](https://reader035.vdocuments.site/reader035/viewer/2022062412/587448e51a28ab0e6c8b9161/html5/thumbnails/2.jpg)
What is spire?
Spire wants to be your mindfulness guide!
Tense
Focused Calm
Neutral
![Page 3: Mind trainr: how stressed will you be in the next two hours?](https://reader035.vdocuments.site/reader035/viewer/2022062412/587448e51a28ab0e6c8b9161/html5/thumbnails/3.jpg)
Today16:00 - 18:00
Time to work hard!
predictive model
![Page 4: Mind trainr: how stressed will you be in the next two hours?](https://reader035.vdocuments.site/reader035/viewer/2022062412/587448e51a28ab0e6c8b9161/html5/thumbnails/4.jpg)
00:00:00 24:00:00
calm focused focused tense tense
16:00:00 18:00:00
0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0
16:00:00 18:00:00
# of minutes being tense
![Page 5: Mind trainr: how stressed will you be in the next two hours?](https://reader035.vdocuments.site/reader035/viewer/2022062412/587448e51a28ab0e6c8b9161/html5/thumbnails/5.jpg)
00:00:00 24:00:00
calm focused focused tense tense
16:00:00 18:00:00
16:00:00 18:00:00
Prior information: the past 10 days
Posterior: # of minutes being tense today?
Posterior (# of minutes tense 16:00-18:00 today) = Prior(# of minutes tense 16:00-18:00 in previous 10 days)* Lik(today)
Comparing # of minutes tense 16:00-18:00 today to user’s tense baseline
![Page 6: Mind trainr: how stressed will you be in the next two hours?](https://reader035.vdocuments.site/reader035/viewer/2022062412/587448e51a28ab0e6c8b9161/html5/thumbnails/6.jpg)
Prior
Today16:00 - 18:00
Time to work hard!
mindtrainr.tech
# of minutes being tense 16:00-18:00 (in proportion)
67% accuracy
![Page 7: Mind trainr: how stressed will you be in the next two hours?](https://reader035.vdocuments.site/reader035/viewer/2022062412/587448e51a28ab0e6c8b9161/html5/thumbnails/7.jpg)
Xin ChenComputational Biology Postdoc Computational Biology PhD
![Page 8: Mind trainr: how stressed will you be in the next two hours?](https://reader035.vdocuments.site/reader035/viewer/2022062412/587448e51a28ab0e6c8b9161/html5/thumbnails/8.jpg)
Xin ChenComputational Biology Postdoc Computational Biology PhD
![Page 9: Mind trainr: how stressed will you be in the next two hours?](https://reader035.vdocuments.site/reader035/viewer/2022062412/587448e51a28ab0e6c8b9161/html5/thumbnails/9.jpg)
0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0
Model setup00:00:00 24:00:00
16:00:00 18:00:00
tense
16:00:00 18:00:00
16:00:00 18:00:00
?
1. Within given time range, how many minutes is likely to be tense for this user?
2. Is the total time of being tense within the 120 mins significantly higher/low than the user’s average level?
today
the past 10 days
![Page 10: Mind trainr: how stressed will you be in the next two hours?](https://reader035.vdocuments.site/reader035/viewer/2022062412/587448e51a28ab0e6c8b9161/html5/thumbnails/10.jpg)
Bayesian function and Markov Chain Monte Carlo Posterior Probability(tense between 16:00-18:00) = Prior * LikSearching for the maximum values
for posterior probability
● Multiple chains
● One million generations
● Test convergence
![Page 11: Mind trainr: how stressed will you be in the next two hours?](https://reader035.vdocuments.site/reader035/viewer/2022062412/587448e51a28ab0e6c8b9161/html5/thumbnails/11.jpg)
Convergenceeffective sample size is {'p': 833}effective sample size is {'p': 614}effective sample size is {'p': 579}
Gelman_rubin test:{'p': 0.9997 }{'p': 0.9997 }{'p': 0.9997 }
Geweke test
![Page 12: Mind trainr: how stressed will you be in the next two hours?](https://reader035.vdocuments.site/reader035/viewer/2022062412/587448e51a28ab0e6c8b9161/html5/thumbnails/12.jpg)
Posterior distributionCalm
Focus
Tense