Research Article
ShoulderCam: Evaluating the User Experience of a Depth Camera System to Measure Shoulder Range of Motion
@INPROCEEDINGS{10.4108/eai.16-5-2016.2263313, author={Kyle Rector and Alexander Lauder and Peyton Keeling and Arien Cherones and Frederick Matsen III and Julie Kientz}, title={ShoulderCam: Evaluating the User Experience of a Depth Camera System to Measure Shoulder Range of Motion}, proceedings={10th EAI International Conference on Pervasive Computing Technologies for Healthcare}, publisher={ACM}, proceedings_a={PERVASIVEHEALTH}, year={2016}, month={6}, keywords={kinect medical clinic shoulder patient doctor}, doi={10.4108/eai.16-5-2016.2263313} }- Kyle Rector
Alexander Lauder
Peyton Keeling
Arien Cherones
Frederick Matsen III
Julie Kientz
Year: 2016
ShoulderCam: Evaluating the User Experience of a Depth Camera System to Measure Shoulder Range of Motion
PERVASIVEHEALTH
EAI
DOI: 10.4108/eai.16-5-2016.2263313
Abstract
Assessment of patient condition is essential for understanding physical impairment severity and treatment efficacy. It is important that measurements are objective and observer-independent so patient progress can be meaningfully assessed over time. Orthopedic shoulder surgeons typically assess range of motion with a goniometer, a manual measurement tool, which has variability between measurers and techniques. To address these limitations, we developed ShoulderCam, an objective measurement technique utilizing the Microsoft Kinect. ShoulderCam was designed with medical professionals to be integrated into the clinic. After evaluating the utility of ShoulderCam in a qualitative study with 5 medical professionals and 11 patients, we found the majority preferred ShoulderCam due to perceived accuracy, more visual information, and less mental effort. This research can inform future medical clinic assessment technologies.
