Academy & Industry Research Collaboration Center (AIRCC)

Volume 10, Number 10, July 2020

Apply Modern Statistical Clustering Analysis on Detecting Altitude Sickness and Sports Fatigue Behavior

  Authors

Mason Chen, OHS, Stanford University, USA

  Abstract

This paper will address Altitude Sickness risk when hiking on the high Mountains. It’s very risky if the people are not aware of their altitude sickness symptom such as Fatigue, Headache, Dizziness, Insomnia, Shortness of breath during exertion, Nausea, Decreased appetite. The consequence of altitude sickness could be dangerous on the inconvenient high mountains. Pulse Oximeter was used to monitor the Oxygen% and Heart Beat at different altitude levels from near-sea level in San Jose, Denver (5,000 Feet), Estes Park (8,000 Feet), Rocky Mountains Alpine Center (12,000 Feet). 2.5-mins Jumping Rope exercise was conducted to analyze the fatigue behavior associated with Altitude Sickness. Statistical analysis was conducted to verify several hypotheses to predict the Altitude Sickness Risk as well as the Exercise Fatigue Behavior. This paper has demonstrated how to assess their body strength and readiness before they may take a strenuous hiking on the high mountains.

  Keywords

JMP, Statistics, Altitude Sickness, Data Mining, AI.