Vision-based needling training system. (A) The experimental setup includes a phantom model, a camera, a white LED light, and a dark background. Images captured by the camera are processed by a computer to determine needle manipulation parameters. (B) Needle manipulation parameters. (C) The needle handle is detected during needle manipulation and visualized by a red bounding rectangle.|@|~(^,^)~|@|Calculation of needle manipulation parameters based on captured frames. The time interval between two consecutive frames is 35 ms.|@|~(^,^)~|@|Laboratory test. (A) An acupuncturist performs needle manipulation skills on the system. (B) The needle manipulation parameters are displayed on the graphical user interface.|@|~(^,^)~|@|Needle manipulation skills of experts and novices. (A) Experts had a higher needle insertion speed than novices before the training. Novices improved their speed after training. (B) No differences were found in the insertion depth error. (C) Statistical differences were found in the insertion angle but were practically negligible. Error bars show the standard deviation.|@|~(^,^)~|@|Training results of the traditional training group (Trad.) and the technology-aided group (Tech.). (A) Both groups showed improvement after 10 training sessions (S10). (B) The technology-aided group had a better improvement after five training sessions (S5). No difference in improvement was found in both groups after 10 sessions (S10). Error bars show the 95% confidence interval.

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