Aspiring to finish the trip my parents had started, I will ride my bicycle from New York City to Alaska in April as I, too, will be 25 years old. There is, however, one key difference between their trip and mine...
My goal is to ultimately advance scientific research. Over the course of the journey, I will collect various health, visual, and geospatial data through a variety of mobile devices to construct "big data" that I will work with during my graduate studies in the field of Statistics. With the advancements of artificial intelligence and cloud computing in recent years, there is a whole untapped arena of interdisciplinary research yet to be explored.
In an era of such prevalent use of mobile technology, my goal is to help contribute to the fields of neuroscience, cardiology, physiology, and navigation systems by developing new methods for analyzing such data. One of the most exciting aspects of this journey will be that you can follow my journey through a live interactive website on schwenck.live
The money raised here will be dedicated to covering the costs associated with the various equipment and services throughout my endeavor. I have estimated the trip to consume a total of 100 days assuming a daily average of 65 miles and a margin of error of 24 days (calculation excluded for brevity). Below is an outline of the main expenses:
- Fitness tracker & heart rate monitor
- Mobile EEG headset
- Service fees for databases and other network related expenses
- Various sensors and equipment for my bicycle
- Computer hardware upgrades
- Any ad hoc camping equipment & bicycle maintenance
- Temporary health insurance costs
- Food and water
- Camping, lodging, and associated fees
100% of all leftover funds will be donated to various medical research initiatives. Feel free to reach out with any questions or comments at [email redacted]
Your donation will not only help my cause, but the research community as a whole. Thank you for your support.
For those curious about the specifics of the study, I will divide the study into 3 phases, each for 100 days, and a final observation phase (also 100 days) for a total of 400 days. The first phase concerns strictly strenuous aerobic exercise (this trip), the second phase concerning a strict diet, and last phase concerning stress management. My research objectives are to:
1) Assess the feasibility of a dynamic Bayesian network to infer latent structure between what I see (via an egocentric camera attached to the bicycle) and how I feel (as determined by a heart rate monitor, fitness tracker watch, mobile EEG headset, etc.)
2) Advance the field of Physiology using Bayesian Inference. This and many medical fields have made great strides to better predict outcomes of exercise routines, but I hope to specifically implement Bayesian approaches to gain a more representative prior distribution through each stage of the study.
3) Uncover relationships through multivariate analysis between brain activity and the environment around me. For example, how does my brain react when I am riding through a picturesque landscape in the mountains compared with a steep ascent in the pouring rain.
4) Assess trends within EEG data as measured through Peak "brain games" as a quantitative comparison.
To overcome the "n of 1" issue, I plan to accumulate data in a structured and standardized manner so that the study can be replicated for future work. All data will be publicly submitted for researchers whose interests align with this study as well.
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