TY - JOUR
T1 - Exploration of Interventionists' Technical Manipulation Skills for Robot-Assisted Intravascular PCI Catheterization
AU - Du, Wenjing
AU - Omisore, Olatunji Mumini
AU - Duan, Wenke
AU - Zhou, Tao
AU - Lv, Xiaodan
AU - Li, Yifa
AU - Han, Shipeng
AU - Al-Handarish, Yousef
AU - Liu, Qiuhua
AU - Wang, Lei
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant U1713219 and Grant U191320006, in part by the National Key Research and Development Plan under Grant 2019YFB1311700, in part by the Outstanding Youth Science Fund Project of National Natural Science Foundation of China under Grant 61950410618, in part by the Foundation of Public Technology Service Platform of Biomedical Electronics, Shenzhen Natural Science Foundation, under Grant JCYJ20190812173205538, and in part by the Outstanding Youth Innovation Research Fund of Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, under Grant Y8G0381001.
Publisher Copyright:
© 2013 IEEE.
PY - 2020
Y1 - 2020
N2 - Despite the great proven advantages of imaging techniques in percutaneous coronary interventions (PCIs), the recent rapid increase in the number of PCI procedures exposes both surgical experts and patients to more radiation and orthopedic hazards in the intervention room. While patients are minimally exposed, many appearance of interventionists subject them to frequent exposure of the operational hazards. Despite promoting the use of robot-assisted intravascular PCI in the Cath-Labs, cognitive and technical skills of interventionists' are yet to be explored towards reducing procedure time and minimal exposure of surgeon to operational hazards. In this study, a random forest classification framework is developed for proper identification of technical manipulation skills of surgeons along with underlying motion patterns of the flexible intravascular tools (viz. guidewire and catheter) during PCI catheterization. For this purpose, analysis of interventionists' muscular activities and related hand motion were decoded from physiological signals recorded with sensors. Surface electromyography, electromagnetic, and tactile force signals were acquired concurrently from seven interventionists during specified guidewire movement viz. pull, push, rotate-pull (clockwise rotation with pull), rotate-push (counterclockwise rotation with push), CR (clockwise rotation), and CCR (counterclockwise rotation). While relations were established between force and muscle activities in the surgeon groups using Spearman's Rank-Order statistical method, Wilcoxon test and Kruskal-Wallis one-way ANOVA test were employed to identify intra-group and inter-group differences. From the experimental results obtained, guidewire delivery patterns exhibit stable characteristics with overall classification accuracies of 94.11% based on nineteen features subset from muscle activities and hand motion, followed by 88.01% based on twelve features subset from muscle activities, 71.97% based on seven features subset from hand motion, 84.56% based on ten features subset from part muscle activities and hand motion. Thus, this study shows existence of significant correlation (p < 0.05) between force and muscle activity during intravascular catheterization for PCIs, while comparably high tactile force values were experience in vascular model with plaque or stenosis.
AB - Despite the great proven advantages of imaging techniques in percutaneous coronary interventions (PCIs), the recent rapid increase in the number of PCI procedures exposes both surgical experts and patients to more radiation and orthopedic hazards in the intervention room. While patients are minimally exposed, many appearance of interventionists subject them to frequent exposure of the operational hazards. Despite promoting the use of robot-assisted intravascular PCI in the Cath-Labs, cognitive and technical skills of interventionists' are yet to be explored towards reducing procedure time and minimal exposure of surgeon to operational hazards. In this study, a random forest classification framework is developed for proper identification of technical manipulation skills of surgeons along with underlying motion patterns of the flexible intravascular tools (viz. guidewire and catheter) during PCI catheterization. For this purpose, analysis of interventionists' muscular activities and related hand motion were decoded from physiological signals recorded with sensors. Surface electromyography, electromagnetic, and tactile force signals were acquired concurrently from seven interventionists during specified guidewire movement viz. pull, push, rotate-pull (clockwise rotation with pull), rotate-push (counterclockwise rotation with push), CR (clockwise rotation), and CCR (counterclockwise rotation). While relations were established between force and muscle activities in the surgeon groups using Spearman's Rank-Order statistical method, Wilcoxon test and Kruskal-Wallis one-way ANOVA test were employed to identify intra-group and inter-group differences. From the experimental results obtained, guidewire delivery patterns exhibit stable characteristics with overall classification accuracies of 94.11% based on nineteen features subset from muscle activities and hand motion, followed by 88.01% based on twelve features subset from muscle activities, 71.97% based on seven features subset from hand motion, 84.56% based on ten features subset from part muscle activities and hand motion. Thus, this study shows existence of significant correlation (p < 0.05) between force and muscle activity during intravascular catheterization for PCIs, while comparably high tactile force values were experience in vascular model with plaque or stenosis.
KW - Intravascular surgery
KW - percutaneous coronary intervention
KW - recognition accuracy
KW - robotic catheterization
KW - surface electromyography
UR - http://www.scopus.com/inward/record.url?scp=85082707423&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2020.2980579
DO - 10.1109/ACCESS.2020.2980579
M3 - Article
AN - SCOPUS:85082707423
SN - 2169-3536
VL - 8
SP - 53750
EP - 53765
JO - IEEE Access
JF - IEEE Access
M1 - 9035494
ER -