학술논문

Posture study for self-training system of patient transfer
Document Type
Conference
Source
2012 IEEE International Conference on Robotics and Biomimetics (ROBIO) Robotics and Biomimetics (ROBIO), 2012 IEEE International Conference on. :842-847 Dec, 2012
Subject
Robotics and Control Systems
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Signal Processing and Analysis
Language
Abstract
Sufficient training with feedback was important for nursing students to learn the techniques. In view of this, we studied the method for measuring and evaluating the performance of nursing students in order to develop a self-training system. Focusing on the training of transferring a patient from a bed to a wheelchair, we defined seven evaluation items related with the postures. In addition, evaluation indexes of each item were determined. Then, we established a prototype system based on two Kinect range cameras. Using the system, first, we recognized the body parts and joints through the color of the markers attached on the bodies. After that, the body joints' spatial locations and body parts' inclination angles were measured via the combination of color and depth information in order to calculate the indexes. We applied Bayes minimum error decision to classify nursing students' performance of each items as correct or incorrect. Ten inexperienced nursing students and five experienced nurses were asked to transfer patient from a bed to a wheelchair at least twice. Every time the patient was transferred, the nursing teacher evaluated the trainee's performance. In addition, proposed system measured and recorded the data. The significant difference between correct and incorrect performance of each item was observed through the determined indexes (P