A Pilot Study on the Evaluation of Physicians' Laser Delivery Performance Using a Laser Beam Detection Kit.

BACKGROUND AND OBJECTIVE: Many laser devices have been developed over the past decades for various skin conditions. However, variations in the technical skill of physicians for laser skin treatment delivery have not yet been evaluated. This study evaluates the differences in omission and overlap percentages during simulated laser hair removal treatments among physicians at two clinics. MATERIALS AND METHODS: A laser beam detection kit was developed to record and collect laser irradiation from a diode laser device. Eight physicians (primary private clinic 4, tertiary referral hospital 4) were recruited to perform 80 trials of laser delivery simulation. The simulation process was captured in video frames by a camera built inside of the detection kit. The laser distribution map was reconstructed, and each physician's performance result was determined by a computer calculation. RESULTS: Various assumption tests showed that each physician had different laser delivery skills. Four physicians from clinic A had an average omission rate of 13.4%, and four physicians from clinic B had an average omission rate of 19.7%. Regarding the average overlap rate of the two clinics, clinic A had a higher rate than clinic B (26.1% vs. 14.6%). CONCLUSIONS: The study's findings confirmed the differences of the technical skills among the physicians and between the two clinics. The proposed computer-assisted evaluation of technical skill is useful for assessing physicians' performance during laser skin treatments.

Development of a Novel Automated Hair Counting System for the Quantitative Evaluation of Laser Hair Removal.

OBJECTIVE: We aimed to develop and validate a novel computer-assisted automated hair counting system for the quantitative evaluation of laser hair removal (LHR). METHODS: We developed a computer-aided image processing system to count hairs on shaved skin and validated its performance through clinical trials. Five volunteers of Fitzpatrick skin type III-IV volunteered and were tested on both thighs. The system automatically detects hair and places a "+" sign on each hair site for every positive detection. This method allows clinicians to check whether a hair has been counted or not. We analyzed the difference in the hair counts between the proposed system (automatic) and those by human observers (manual). RESULTS: The hair counts from the proposed system and the manual counts were compared. The percentage error between automatic and manual counting was <5% in each subject. The data of the two groups were statistically verified with Student's independent t-test. The averages were statistically equivalent between the two groups. The proposed system showed significant time saving in terms of counting. CONCLUSIONS: A dependable, accurate, and fast method of counting hairs on shaved skin through a computer-aided image processing system was developed and validated. The "+" signs on the image to indicate detection allows clinicians to compare with the original image and detect any omission or redundancy. The proposed system is expected to be reliable in analyzing the results of multiple skin-related treatments, including LHR and hair transplantation. Further, it is expected to be widely applicable for use in the clinic.

Improvement in Laser-Irradiation Efficiency of Robot-Assisted Laser Hair Removal Through Pose Measurement of Skin Surface.

OBJECTIVE: This study aims to improve the performance of an automatic laser hair removal (LHR) system by applying an algorithm that considers the curve and slant of the skin surface. BACKGROUND DATA: In an earlier research, a robot-assisted LHR system has been developed and validated for an almost flat skin or a relatively smooth curved part of the skin. For practical clinical applications, the feature of the robot-assisted LHR system is extended for real curved skins. METHODS: A novel pose-measurement algorithm is developed and applied to the LHR system. This system detects a six-degree of freedom (DOF) pose of the skin surface using the pose-measurement algorithm. The main principle of this algorithm is finding the equation of a plane using three noncollinear points, which are obtained by sequential movement of a one dimensional laser sensor. RESULTS: Evaluation of the proposed system was conducted. During the test, we demonstrated that the LHR device automatically and completely contacted the targets along the curved surface. The contact-accuracy test produced satisfactory outcome. The averages of the root mean square (RMS) of the position error and the RMS of the rotation were 1.4437 mm and 1.0982 degrees, respectively. The curvature measurement test produced a satisfactory average result of 0.0006 mm RMS error. CONCLUSIONS: Using the proposed six-DOF pose-measurement algorithm, the performance of the robot-assisted LHR system could be significantly improved from the clinical point of view because most real skins have curved shapes.

Comparison of Efficacy Between Novel Robot-Assisted Laser Hair Removal and Physician-Directed Hair Removal.

OBJECTIVE: This study aimed to evaluate the number of laser irradiation sessions, process duration, and hair removal rate required for robot-assisted automatic versus physician-directed laser hair removal. BACKGROUND DATA: This research group previously developed and tested an automatic laser hair removal (LHR) system to provide uniform laser treatment distribution. METHODS: Six subjects 20-40 years of age, with skin types III-IV completed this study. A home-use LHR device with an 810 nm diode laser was used to treat equal-sized areas of both upper thighs; a random computer generator determined the use of a robot-assisted automatic LHR system or physician-directed LHR on the right or left thigh. The treatment schedule comprised five visits; subjects were photographed and shaved, and received LHR during the first through the fourth visits at 2-week intervals. The fifth visit occurred 1 month after the fourth, and only involved photography. RESULTS: All subjects successfully completed the clinical trial with no noticeable or permanent side effects. The average hair removal rates were 49.0% (standard error of the mean [SEM]: 4.0) and 29.5% (SEM: 4.0) for robot-assisted and physician-directed LHR, respectively. The average treatment duration and number of irradiation shots were 18 min, 30 sec (SEM: 33 sec) and 260 (SEM: 5.7) for robot-assisted LHR and 3 min, 11 sec (SEM: 15 sec) and 73 (SEM: 5.9) for physician-directed LHR. CONCLUSIONS: This clinical study successfully demonstrated the safety and effectiveness of robot-assisted LHR. The proposed novel system will benefit both patients and clinicians.

A study on the development of a robot-assisted automatic laser hair removal system.

UNLABELLED: Abstract Background and Objective: The robot-assisted automatic laser hair removal (LHR) system is developed to automatically detect any arbitrary shape of the desired LHR treatment area and to provide uniform laser irradiation to the designated skin area. METHODS: For uniform delivery of laser energy, a unit of a commercial LHR device, a laser distance sensor, and a high-resolution webcam are attached at the six axis industrial robot's end-effector, which can be easily controlled using a graphical user interface (GUI). During the treatment, the system provides real-time treatment progress as well as the total number of "pick and place" automatically. RESULTS: During the test, it was demonstrated that the arbitrary shapes were detected, and that the laser was delivered uniformly. The localization error test and the area-per-spot test produced satisfactory outcome averages of 1.04 mm error and 38.22 mm(2)/spot, respectively. CONCLUSIONS: RESULTS showed that the system successfully demonstrated accuracy and effectiveness. The proposed system is expected to become a promising device in LHR treatment.

Tool to visualize and evaluate operator proficiency in laser hair-removal treatments.

BACKGROUND: The uniform delivery of laser energy is particularly important for safe and effective laser hair removal (LHR) treatment. Although it is necessary to quantitatively assess the spatial distribution of the delivered laser, laser spots are difficult to trace owing to a lack of visual cues. This study proposes a novel preclinic tool to evaluate operator proficiency in LHR treatment and applies this tool to train novice operators and compare two different treatment techniques (sliding versus spot-by-spot). METHODS: A simulation bed is constructed to visualize the irradiated laser spots. Six novice operators are recruited to perform four sessions of simulation while changing the treatment techniques and the presence of feedback (sliding without feedback, sliding with feedback, spot-by-spot without feedback, and spot-by-spot with feedback). Laser distribution maps (LDMs) are reconstructed through a series of images processed from the recorded video for each simulation session. Then, an experienced dermatologist classifies the collected LDMs into three different performance groups, which are quantitatively analyzed in terms of four performance indices. RESULTS: The performance groups are characterized by using a combination of four proposed indices. The best-performing group exhibited the lowest amount of randomness in laser delivery and accurate estimation of mean spot distances. The training was only effective in the sliding treatment technique. After the training, omission errors decreased by 6.32% and better estimation of the mean spot distance of the actual size of the laser-emitting window was achieved. Gels required operators to be trained when the spot-by-spot technique was used, and imposed difficulties in maintaining regular laser delivery when the sliding technique was used. CONCLUSIONS: Because the proposed system is simple and highly affordable, it is expected to benefit many operators in clinics to train and maintain skilled performance in LHR treatment, which will eventually lead to accomplishing a uniform laser delivery for safe and effective LHR treatment.