arXiv subjects

Leo K. Cheng

Publications and source records attributed to Leo K. Cheng.

3 recordsLinked to original sources

arXiv2026

RoSE: A Robotic Soft Esophagus for Endoprosthetic Stent Testing

Soft robotic systems are well suited for developing devices for biomedical applications. A bio-mimicking robotic soft esophagus (RoSE) is developed as an in vitro testing device of endoprosthetic stents for dysphagia management. Endoprosthetic stent placement is an immediate and cost-effective therapy for dysphagia caused by malignant esophageal strictures from esophageal cancer. However, later stage complications, like stent migration, could weaken swallow efficacy in the esophagus. The stent radial force (RF) on the esophageal wall is pivotal in avoiding stent migration. Due to limited randomized controlled trials in patients, stent design and stenting guidelines remain incomplete. To address this knowledge deficit, we investigate RoSE by implanting two stents (A and B) of different radial stiffness characteristics, to measure stent RF and its effect on migration. Endoscopic manometry under peristalsis is also performed to study the impact of stenting and stent dysfunction on intra-bolus pressure signatures (IBPSs) and swallowing efficacy. Each implanted stent undergoes experiments with varied peristalsis velocity, wavelength, and bolus concentrations. The results show that stiffer stent B has a higher RF, whereas stent A maintains a lower RF profile due to lesser stiffness. High RF is necessary to minimize migration under prolonged peristaltic contractions in RoSE. For manometry, stent A slightly increases IBPS, but stiffer stent B significantly decreases IBPS, especially for higher-concentration boluses. If a stiffer stent buckles, it can reduce swallow efficacy and cause recurrent dysphagia. RoSE is therefore an innovative soft robotic platform for testing endoprosthetic stents and addressing clinical challenges in stent evaluation.

cs.RO↗

arXiv2026

Nonlinear Model Predictive Control of a Robotic Soft Esophagus

Strictures caused by esophageal cancer can narrow down the esophageal lumen, leading to dysphagia. Palliation of dysphagia has driven the development of a Robotic Soft Esophagus (RoSE), which provides a novel in vitro platform for esophageal stent testing and food viscosity studies. In RoSE, peristaltic wave generation and control were done in an open-loop manner since the conduit lacked visibility and embedded sensing capability. Hence, in this work, RoSE version 2.0 (RoSEv2.0) is designed with embedded Time Of Flight (TOF) and pressure sensors to measure conduit displacement and air pressure, respectively, for modeling and control. Model Predictive Control (MPC) of RoSEv2.0 is implemented to govern the peristalsis and air pressure profile autonomously. The implemented MPC used Sparse Identification Nonlinear Dynamics with Control (SINDYC) models to estimate the future states of ROSEv2.0. The dynamic models are discovered from the TOF and pressure sensor data. Peristalsis waves of speed 20 mm/s, wavelength 75 mm, and amplitudes 5, 7.5, and 10 mm were successfully generated by the MPC. Additionally, RoSEv2.0 with the MPC was employed to perform stent migration testing with various food bolus consistencies. The major contribution claimed in this paper is the application of SINDYC-based MPC to solve the closed-loop control problem of RoSE for achieving desired peristaltic waves.

cs.RO↗

arXiv2026

Intestinal peristalsis and wrinkling: A novel paradigm

A new computational framework for modeling the intestinal wall as a multi-layered fiber-reinforced continuum is presented. The framework reproduces for the first time physiological motility and overcoming large-displacements limitations (self-contact and volume locking) occurring in classical hyperelastic formulations of soft tissues. We introduce: i) layer-specific functions, segregating active circumferential and longitudinal muscle fibers while maintaining homogeneous passive reinforcement, and ii) a quasi-incompressible volumetric contribution, to handle large peristaltic contractions. Cell electrophysiology is further extended to reproduce both slow waves and spike bursting activities thus mimicking for the first time a localized neural excitation in a three-dimensional geometry of small intestine segment. We introduce a spatio-temporal modulation of contractility to accurately capture activation driven by both slow waves and spike bursts. The overall coupled nonlinear electromechanical boundary valued problem is modeled following the active strain approach. A robust augmented-Lagrangian contact algorithm is also embedded to avoid self-penetration and geometrical instabilities under large displacements. The 8-variables nonlinear governing equations are then discretized using in house P1-P2-P4 finite elements codes implemented within the GetFEM library. Numerical experiments demonstrate the ability of the proposed framework to reproduce physiological peristalsis, i.e., wall contraction greater than 80%, thus allowing full occlusion matching in vivo endoscopic images, and naturally generating wrinkling patterns consistent with experimental observations. We show that an active electromechanics anisotropic heterogeneous modeling strategy is critical for a numerically stable and physiologically accurate representation of gastrointestinal motility.

physics.med-ph↗