Development and Validation of a Vision-Based Needling Training System for Acupuncture on a Phantom Model

Abstract

Background: Previous studies have investigated technology-aided needling training systems for acupuncture on phantom models using various measurement techniques. In this study, we developed and validated a vision-based needling training system (noncontact measurement) and compared its training effectiveness with that of the traditional training method. Methods: Needle displacements during manipulation were analyzed using OpenCV to derive three parameters, i.e., needle insertion speed, needle insertion angle (needle tip direction), and needle insertion length. The system was validated in a laboratory setting and a needling training course. The performances of the novices (students) before and after training were compared with the experts. The technology-aided training method was also compared with the traditional training method. Results: Before the training, a significant difference in needle insertion speed was found between experts and novices. After the training, the novices approached the speed of the experts. Both training methods could improve the insertion speed of the novices after 10 training sessions. However, the technology-aided training group already showed improvement after five training sessions. Students and teachers showed positive attitudes toward the system. Conclusion:The results suggest that the technology-aided method using computer vision has similar training effectiveness to the traditional one and can potentially be used to speed up needling training.

Exploring Learning Curves in Acupuncture Education Using Vision-Based Needle Tracking

“…Most studies related to performance tracking in acupuncture needle manipulation have been conducted with few measurements [7,12,15,19]. The number of measurements varies from a few to around 20.…”

“…The needle tracking system in this work is based on computer vision with OpenCV [28]. From the prototype described in [15], we developed a portable system that can be more easily deployed in acupuncture training classes. The software was improved with a graphical user interface (GUI) allowing educators/experimenters to log the needle manipulation performance of novice acupuncturists.…”

“…Traditionally, acupuncture educators manually measure these parameters using rulers. Recently, various sensing technologies have been applied to track the needle during insertion and automatically measure needle manipulation parameters [11,14,15]. These technologies can assist in comprehending each individual's unique learning curve, which depicts how their performance in needle manipulation evolves over time.…”

“…However, attaching sensors to the needle may negatively affect the naturalness of needle manipulation. A more natural needletracking approach is computer vision, in which regular cameras track the needling process [15]. This approach improves the naturalness of needle manipulation with acceptable accuracy for specific acupuncture training lessons.…”