Varicose vein treatments range from conventional surgical ligation and sclerotherapy to venous closure using biological adhesives. However, considering ease of procedure, recovery time, and cosmetic outcomes like minimal scarring, minimally invasive techniques employing lasers or radiofrequency are preferred. The efficacy of these methods heavily relies on clinician expertise and ultrasound imaging, with manual catheter retraction during cauterization presenting challenges, such as overlapping or untreated areas, especially in long vessels exceeding 1 meter, leading to increased procedure time and operator fatigue. To address these issues, we propose an automated catheter procedure for varicose veins. This system features a handpiece for energy generation control (laser, radiofrequency) operated near the clinician for convenience. We designed a pullback system that enables constant speed rotation and forward/backward movements of the catheter without moving the handpiece. Through handpiece operation, the catheter rotates at a set speed, and a roller-driven pullback action occurs as it winds on a reel, expanding the diameter of the reel for retraction while remaining stationary. Conversely, reducing the diameter of the reel facilitates forward movement. The length adjustment of the catheter based on winding turns on the reel makes it adaptable for various vascular procedures, enhancing the procedural accuracy and operator convenience.
Climbing stairs places a greater load on lower limb joints compared to walking on level ground. Variations in anatomical structures and muscle characteristics between genders suggest potential differences in the distribution of required mechanical work among the three lower limb joints. This study aimed to identify gender disparities in the allocation of mechanical work to lower limb joints during stair climbing. A total of thirty-six adults (equally divided between men and women) participated in the study. Participants ascended stairs equipped with force plates at their comfortable speeds, while motion was captured using nine cameras. Inverse dynamics analysis was employed to calculate the mechanical work performed by each joint during four phases of stance: weight acceptance, pull-up, forward continuation, and push-up. Male participants exhibited significantly higher mechanical work than females at the hip and ankle joints (p < 0.05) from the 1st- 3rd phases and the 2nd phase, respectively. Conversely, female subjects displayed greater knee joint work during the 2nd- 3rd phases (p < 0.05). Notably, a pronounced gender difference was observed during the 2nd pull-up phase, where body mass is lifted by a single leg. These findings suggest that men and women employ distinct strategies in distributing mechanical work across lower limb joints.
There are no known studies on the changes in walking ability in patients with transfemoral amputations returning to daily activities after prosthetic gait training. The ability to walk after discharge may vary depending on an individual’s physical, psychological, and social factors. This study compared spatiotemporal variables and lower limb coordination ability at the end of training and one year after the end of training in seven unilateral transfemoral amputees and analyzed the factors affecting walking ability. The study results confirmed that there was no significant difference in spatiotemporal parameters such as walking speed and lower limb coordination ability after one year of training, and walking ability was well maintained after training. Five out of seven (71.4%) participants in this study returned to work, and there was a strong correlation between employment and gait improvement (r = 0.806, p < .05). In conclusion, activities such as social participation, employment, and exercise were very important factors in maintaining and improving an individual’s walking ability. The findings are intended to be used as basic data to provide guidelines for maintaining the health of lower limb amputees.
Relative position estimation between body segments is one essential process for inertial sensor-based human motion analysis. Conventionally, the relative position was calculated through a constant segment to joint (S2J) vector and the orientation of the segment, assuming that the segment was rigid. However, the S2J vector is deformed by soft tissue artifact (STA) of the segment. In a previous study, in order to handle the above problem, Lee and Lee proposed the relative position estimation method using time-varying S2J vectors based on inertial sensor signals. Here, time-varying S2J vectors were determined through the joint flexion angle using regression. However, it was not appropriate to consider only the flexion angle as a deformation-related variable. In addition, regression has limitations in considering complex joint motion. This paper proposed artificial neural network models to compensate for the STA by considering all three-axis motion of the joint. A verification test was conducted for lower body segments. Experimental results showed that the proposed method was superior to the previous method. For pelvis-to-foot relative position estimation, averaged root mean squared error of the previous method was 17.38 mm, while that of the proposed method was 12.71 mm.
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Wearable Inertial Sensors-based Joint Kinetics Estimation of Lower Extremity Using a Recurrent Neural Network Ji Seok Choi, Chang June Lee, Jung Keun Lee Journal of the Korean Society for Precision Engineering.2023; 40(8): 655. CrossRef
Gait analysis is the best objective measurement tool for monitoring rehabilitation. However, it has limitations to evaluate gait recovery. Previous studies have evaluated the effect of gait training using continuous relative phase. The objective of this study was to determine the effect of gait recovery by rehabilitation gait training on lower limb coordination. We analyzed spatio-temporal parameters and CRP values of hip and knee joints based on gait analysis data obtained by 3D motion analysis system at 15 days intervals in 24 uni-lateral transfemoral amputees participated in IRP. Our results revealed that walking velocity of uni-lateral transfemoral amputees who participated in the program during a mean of 107.1 days was 49.2% faster than that at initial stage. The walking velocity showed a 46% increase at the end of 30 days after training. In gait coordination, values of CRP-RMS and CRP-SD were increased and maintained in-phase pattern. CRP showed symmetry in both limbs at the end of 90 days after training. Therefore, CRP is a significant factor in the gait recovery process. Effects of various rehabilitation training methods can be determined through CRP analysis.
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A Comparative Study of the Effects of Augmented Reality Application on Movement Accuracy and Subjective Satisfaction in Rehabilitation Training for Individuals with Lower Limb Amputations Yunhee Chang, Jungsun Kang, Hyeonseok Cho, Sehoon Park Applied Sciences.2025; 15(12): 6703. CrossRef
Changes in Gait Characteristics after Completion of Prosthetic Gait Training in Patients with Unilateral Transfemoral Amputation: Follow-Up after 1 Year Bo Ra Jeong, Gyoo Suk Kim, Yun Hee Chang Journal of the Korean Society for Precision Engineering.2022; 39(11): 849. CrossRef
A depth image camera is used for efficient estimation of walking intention of a pedestrian. Three-Dimensional image coordinates of the pedestrian’s joints are obtained from the image data that includes depth information and are converted into the absolute coordinate values. The absolute coordinate data are classified and matched with all 20 joints of a pedestrian and the 9 joints that are corresponding the lower limbs are finally selected. After calculating each three-dimensional area of a triangle that was formed with the adjacent 3 joints of the 9 lower limb joints, the centroid of all triangles along time is obtained. The walking intention, that includes the direction and the speed of walking, can be estimated with the change rate of this centroid. It is experimentally verified by comparing the distance that is measured with inertia moment unit and the distance that the calculated centroid is moving.
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Intelligent robotic walker with actively controlled human interaction Ihn-Sik Weon, Soon-Geul Lee ETRI Journal.2018; 40(4): 522. CrossRef