ERBAL
- Space Physiology
- Robotics
- …
- Space Physiology
- Robotics
ERBAL
- Space Physiology
- Robotics
- …
- Space Physiology
- Robotics
Machine Learning Enables Modeling of Pathophysiological Adaptations following Musculoskeletal Wasting for Rehabilitation and Predictive Treatment.
By: Drs Walck, Paul, Parida
Prior Works
https://patents.google.com/patent/US9789356B2/en
https://link.springer.com/chapter/10.1007/978-3-031-10015-4_18
Project Description
Muscle atrophy and wasting is a disorder that is experienced by the elderly (> 60 years old), and without adequate exercise and strength loading on muscles, can lead to sarcopenia. Exacerbation of sarcopenia can occur when blood levels of CO2 are elevated, which is a comorbidity in the elderly due to reduced metabolic activity. Elevated blood levels of CO2 can also induce inflammation, contributing to aggravated muscle atrophy. The objective of this project is to design a comprehensive numerical model that defines how different physiological environments cause skeletal muscles to atrophy. Thus, this research aims to assess the pathophysiology of muscular wasting through machine learning data integration, designing a comprehensive numerical model that defines how different physiological environments contribute to skeletal muscle atrophy. The anticipated outcome is a computational integration of diverse, real-time molecular datasets that will develop a comprehensive picture of muscular wasting for enhanced treatments and possible prevention strategies. Ultimately advancing today’s MSK program’s linear differential equations by defining activation and contraction (force) dynamics in terms of real-time response to various stressors. This research may be extended to other disorders that are induced by the age-related stressors hypercapnia and chronic inflammation, including chronic obstructive pulmonary disease (COPD), sleep apnea, glaucoma, brainstem stroke victims, hypothermia, and obesity. Another extended application of this research is related to spaceflight-associated astronaut health.
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