TY - GEN
T1 - Experimental Characterization of Multi-Axis Tissue Resistance Forces for Robot-Assisted Minimally Invasive Spine Surgery
AU - Oiamwong, Panuwat
AU - Chumnanvej, Sorayouth
AU - Suthakorn, Jackrit
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Robot-assisted minimally invasive spinal procedures encounter substantial obstacles due to uncharacterized tissue resistance forces that compromise pedicle screw placement precision. This study developed force-torque characterisation methodologies to enhance robotic surgical control algorithms through biomechanical tissue modelling. The experimental apparatus integrated a custom-designed probe incorporating a 6-axis force/torque sensor with cylindrical guidance components, positioned to align with the spinal instrumentation trajectories. Testing utilized a multi-layered lumbar phantom constructed from biomimetic silicone materials engineered to replicate the mechanical properties of anatomical muscles and soft tissues. The sensor measurements underwent gravitational compensation and filtering protocols to ensure measurement fidelity. Experimental validation revealed vertebral level-dependent force escalation patterns, with a maximum tissue resistance of 27.6 N observed at the L4 level during pitch angular motion. Progressive force amplification from superficial anatomical positions (L1:15.1 N) to deeper insertion sites (L4:27.6 N) demonstrated an 83% resistance increase across vertebral levels. Linear force-depth relationships exhibited gradients of 0.55 N/mm for pitch motions and 0.30 N/mm for roll motions, confirming that angular trajectory deviations at increased insertion depths generated proportionally elevated tissue resistance. Experimental results provide critical parameters for developing adaptive robotic control systems that enhance surgical precision and safety.
AB - Robot-assisted minimally invasive spinal procedures encounter substantial obstacles due to uncharacterized tissue resistance forces that compromise pedicle screw placement precision. This study developed force-torque characterisation methodologies to enhance robotic surgical control algorithms through biomechanical tissue modelling. The experimental apparatus integrated a custom-designed probe incorporating a 6-axis force/torque sensor with cylindrical guidance components, positioned to align with the spinal instrumentation trajectories. Testing utilized a multi-layered lumbar phantom constructed from biomimetic silicone materials engineered to replicate the mechanical properties of anatomical muscles and soft tissues. The sensor measurements underwent gravitational compensation and filtering protocols to ensure measurement fidelity. Experimental validation revealed vertebral level-dependent force escalation patterns, with a maximum tissue resistance of 27.6 N observed at the L4 level during pitch angular motion. Progressive force amplification from superficial anatomical positions (L1:15.1 N) to deeper insertion sites (L4:27.6 N) demonstrated an 83% resistance increase across vertebral levels. Linear force-depth relationships exhibited gradients of 0.55 N/mm for pitch motions and 0.30 N/mm for roll motions, confirming that angular trajectory deviations at increased insertion depths generated proportionally elevated tissue resistance. Experimental results provide critical parameters for developing adaptive robotic control systems that enhance surgical precision and safety.
KW - Force-torque sensor
KW - Minimally invasive spine surgery
KW - Multi-layered lumbar spine phantom
KW - Optical tracking system
KW - Resistive force
KW - torque feedback models
UR - https://www.scopus.com/pages/publications/105037466960
U2 - 10.1109/I-CREATE67590.2025.11478124
DO - 10.1109/I-CREATE67590.2025.11478124
M3 - Conference contribution
AN - SCOPUS:105037466960
T3 - 2025 International Convention on Rehabilitation Engineering and Assistive Technology, i-CREATe 2025 - Conference Proceedings
BT - 2025 International Convention on Rehabilitation Engineering and Assistive Technology, i-CREATe 2025 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th International Convention on Rehabilitation Engineering and Assistive Technology, i-CREATe 2025
Y2 - 24 November 2025 through 26 November 2025
ER -