TY - GEN
T1 - A Pilot Study for Developing Mobile App and Cloud Computing for Upper Extremities Motion Analysis
AU - Kumthekar, Parth S.
AU - Sharma, Abhishek
AU - Malla, Sravani
AU - Richardson, R. Tyler
AU - Morales, Aldo W.
AU - Nguyen, Hien
AU - Agili, Sedig S.
AU - Tran, Truong
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Shoulder and elbow range of motion (ROM) impairment significantly affects an individual's quality of life, yet existing healthcare solutions for evaluating ROMs are often limited by cost, time, and accessibility constraints, particularly in smaller cities. In response, this paper presents a case study on a novel mobile and cloud computing application leveraging Machine Learning and Artificial Intelligence advancements to address these challenges. ROMs calculated by the mobile application are evaluated against a reference standard of motion capture (Qualisys 10-camera system) for specific upper extremity movements. Results demonstrate the proposed mobile and cloud application's accurate ROM measurement, with slight deviations at peak ROM compared to the Qualisys system. By providing a mobile, cost-effective solution, the proposed application aims to enhance diagnostic capabilities and address the critical need for automatic assessment of motions to support clinical and healthcare decision - making.
AB - Shoulder and elbow range of motion (ROM) impairment significantly affects an individual's quality of life, yet existing healthcare solutions for evaluating ROMs are often limited by cost, time, and accessibility constraints, particularly in smaller cities. In response, this paper presents a case study on a novel mobile and cloud computing application leveraging Machine Learning and Artificial Intelligence advancements to address these challenges. ROMs calculated by the mobile application are evaluated against a reference standard of motion capture (Qualisys 10-camera system) for specific upper extremity movements. Results demonstrate the proposed mobile and cloud application's accurate ROM measurement, with slight deviations at peak ROM compared to the Qualisys system. By providing a mobile, cost-effective solution, the proposed application aims to enhance diagnostic capabilities and address the critical need for automatic assessment of motions to support clinical and healthcare decision - making.
UR - http://www.scopus.com/inward/record.url?scp=85202450822&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85202450822&partnerID=8YFLogxK
U2 - 10.1109/Cloud-Summit61220.2024.00011
DO - 10.1109/Cloud-Summit61220.2024.00011
M3 - Conference contribution
AN - SCOPUS:85202450822
T3 - Proceeding - 2024 IEEE Cloud Summit, Cloud Summit 2024
SP - 24
EP - 27
BT - Proceeding - 2024 IEEE Cloud Summit, Cloud Summit 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE Cloud Summit, Cloud Summit 2024
Y2 - 27 June 2024 through 28 June 2024
ER -