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Contributor
Gary Guerra
Digital Publisher
Digital Commons at St. Mary's University
Publication Date
Spring 2025
Keywords
Sit2Stand; AI; AI applications; Biomechanical analysis; Machine learning; Prosthetics; Orthotics
Description
Biomechanical analysis is a tool to evaluate prosthetic and orthotic patient's. These tools offer the clinician capability of understanding the mechanism of injury, gait deviation or prosthesis problem. Video based analysis require expensive hardware, software, and training which sometimes costs $40-100,000.
The recent advent of artificial intelligence (AI) has opened up the possibility of acquiring high speed human motion video analysis using low-cost hardware and open-source machine learning algorithms. Still, free assessments like the Sit2Stand test is a current clinical outcome measure which assesses ability of a patient to stand and sit as fast as possible 5x. The faster the speed, the less likely they are to fall in the future.
One such offering is the Sit2Stand.ai application created by scholars at Stanford University. This application uses machine learning and pose estimation to create a human joint model which is then used to estimate joint kinematics (angle) and velocity of movement. Thus, by combining a clinically relevant measure with AI, the Sit2Stand app offers clinicals a more detailed level of analysis of their patient’s function. This study sought to explore a clinician’s perspective on utility of the application.
Format
Size
1 page
City
San Antonio, Texas
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Included in
Biomedical Commons, Biomedical Devices and Instrumentation Commons, Other Computer Engineering Commons, Robotics Commons
