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Kristin Morgan | The Data Science of Sports Injury

Kristin Morgan | The Data Science of Sports Injury

FromData & Science with Glen Wright Colopy


Kristin Morgan | The Data Science of Sports Injury

FromData & Science with Glen Wright Colopy

ratings:
Length:
71 minutes
Released:
May 10, 2021
Format:
Podcast episode

Description

Description: In the world of biomechanics, engineers continuously aim to innovate and create new models for better understanding of their research. In this episode, Kristin Morgan (University of Connecticut) returns to the show as she explains how they use gait as a form of diagnostic tool in maximizing human performance. Having experiences on sports herself, Morgan presents how they use gait to measure recovery from physical impairment, specifically for ACL-related injuries. Aside from this, however, she also explains how they use the same tool to measure recovery from cognitive impairment. An insightful episode for all!
 
Keywords: biomechanics, models, metrics, gait, engineering, statistics, cognitive impairment, physical impairment
 
0:00 - Intro
03:01 - Creating models for performance optimization
07:23 - Why gait is an effective diagnostic tool
11:38 - Maximizing gait in creating models for post-ACLR
17:35 - Manifestation of different injuries & models
22:01 - Modeling motor control
26:28 - Applying other models in biomechanics
30:50 - Using asymmetric walking for recovery
39:30 - Understanding cognitive impairment recovery
44:19 - Moving forward with gait as diagnostic tool
45:40 - Taking inspiration from other fields / Statistics in Engineering
47:45 - Engineering and statistics hand in hand
52:50 - Limitations of modeling in biomechanics
54:20 - Starting a career in biomechanics
58:20 - Including cognitive impairment
1:00:20 - Tailoring models to specific cases
1:05:33 - Applying the models to injuries other than ACL
Released:
May 10, 2021
Format:
Podcast episode

Titles in the series (88)

Data and Science with Glen Wright Colopy is a podcast covering critical scientific reasoning, particularly from a data science / machine learning / statistics perspective. Episodes typically focus on understanding of how to be better scientists and critical thinkers for the practical purpose of being a better data scientists. Previously called: ”Pod of Asclepius”