Methods for Physiologic Tremor Characterization, Mitigation, and Modeling

Physiologic tremors exist in all healthy individuals, and occur in moments of excitement, anxiety, or muscle activation. They have been commonly observed in surgeons and other occupations requiring precise movements, but unlike tremors from Parkinson’s disease or Essential Tremor, they are often disregarded in clinical and research settings as they are not linked to any neurological disease, nor disturb one’s daily life. The magnitude of physiologic tremors has been observed to increase through stressful or fatiguing experiences, and decrease through relaxation exercises or medication; however, the combined mechanical, electrical, and physiological changes in the body render it a challenging phenomenon to study. Advancements in physiological monitoring have allowed researchers to characterize tremors. Accelerometry and surface electromyography are often used to measure tremor patterns, both practical methods for measuring surface-level changes. Imaging modalities like ultrasound, on the other hand, are less prevalent techniques for these scenarios. Combining these methods can present a more holistic observation of physiological changes involved in an emerging tremor, potentially guiding research towards a more complete understanding of their cause and impact on the body. This thesis highlights approaches to detect and characterize physiologic tremors in the upper limbs. It describes the methods used to process the signals and images acquired via the various modalities, and relates the changes among modalities to each other. Finally, the results of this analysis are highlighted, presenting strategies to mitigate tremors and a new understanding of the biomechanics behind them.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Mechanical Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Magaña-Salgado, Uriel

Advisor dc:contributor.advisor

• Anthony, Brian

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/150062

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/150062