Needle Transportable Semi-Automatic Hair Follicle Implanter and Image-Based Hair Density Estimation for Advanced Hair Transplantation Surgery

Author:

Bae Tae WukORCID,Jung Yong Chul,Kim Kyu Hyung

Abstract

As the number of hair follicles transplanted in a patient is approximately 2000 or more, hair transplantation by a manual implanter requires a considerable amount of time and money and demands a great amount of patience and pain tolerance from both patients and surgeons. In addition, many surgeons frequently experience musculoskeletal disorders owing to the numerous simple repetitive motions of the shoulder and wrist during the procedure. Moreover, the results of the surgery may vary depending on the skill of the surgeon. Although the hair follicle extraction technology has advanced in recent years, the hair follicle transplantation technology still uses a simple hand-held implanter owing to the difficulty of transplanting hair follicles and hair. In this study, a needle transportable semi-automatic hair follicle implanter that can continuously transplant hair follicles is introduced to alleviate the inconvenience of the existing manual implanter. In the developed semi-automatic implanter, a plurality of needles, into which the hair follicles are inserted, are sequentially supplied from the needle supply magazine to the implanter body by the guide groove. The hair follicles in the supplied needles are transplanted to the scalp through the forward and backward movement of the needle gripper and driving motors. The developed implanter can transplant several hair follicles without any replacement, which can shorten surgery time and reduce the fatigue experienced by patients and surgeons. The effectiveness of the proposed implanter was verified through the results of animal and clinical experiments.

Funder

Electronics and Telecommunications Research Institute

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Follicular Unit Registration Based on Binocular Stereo Vision for Hair Transplantation Surgery Robot;2023 6th International Conference on Data Science and Information Technology (DSIT);2023-07-28

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