Article: Modelling and simulation for biomechanical responses of acupuncture points based on multi-physics field coupling Journal: International Journal of Ad Hoc and Ubiquitous Computing (IJAHUC) 2026 Vol.52 No.5 pp.87 - 100 Abstract: Accurate acupoint localisation is essential for standardised acupuncture therapy and intelligent systems, yet remains challenging due to soft-tissue variability, ambiguous anatomical boundaries, and cross-domain distribution shifts. This study proposes a unified perception framework that integrates multiple complementary mechanisms within a single localisation pipeline. The proposed ACUR-Net incorporates high-resolution feature representation, geometry-aware relational modelling, uncertainty-aware regression, and domain adaptation to address anatomical variability and domain heterogeneity in a coordinated manner. The underlying assumption is that reliable acupoint localisation benefits from the joint modelling of anatomical topology, cross-domain feature alignment, and prediction uncertainty, rather than from isolated architectural modifications. Experiments conducted on the AcuSim-FAcupoint dataset show that the proposed framework achieves improved feature transfer stability and spatial consistency. Comparative evaluations indicate that ACUR-Net outperforms PFLD, PIPNet, HRNet, and ViTPose in terms of NME, PCK@0.05, and OKS-mAP. The results suggest that multi-factor integration is effective for enhancing localisation robustness under realistic conditions. Inderscience Publishers - linking academia, business and industry through research

Title: Modelling and simulation for biomechanical responses of acupuncture points based on multi-physics field coupling

Authors: Xin Xiang; Dongming Li; Songlin Liu; Hongfeng Wang

Addresses: School of Acupuncture-Moxibustion and Tuina, Changchun University of Chinese Medicine, Changchun, Jilin 130117, China ' Baiquan Town Central Health Center, Dongliao County, Liaoyuan, Jilin, 136600, China ' The Third Affiliated Clinical Hospital of Changchun University of Chinese Medicine, Changchun, Jilin 130117, China ' Changchun University of Chinese Medicine, Changchun, Jilin 130117, China

Abstract: Accurate acupoint localisation is essential for standardised acupuncture therapy and intelligent systems, yet remains challenging due to soft-tissue variability, ambiguous anatomical boundaries, and cross-domain distribution shifts. This study proposes a unified perception framework that integrates multiple complementary mechanisms within a single localisation pipeline. The proposed ACUR-Net incorporates high-resolution feature representation, geometry-aware relational modelling, uncertainty-aware regression, and domain adaptation to address anatomical variability and domain heterogeneity in a coordinated manner. The underlying assumption is that reliable acupoint localisation benefits from the joint modelling of anatomical topology, cross-domain feature alignment, and prediction uncertainty, rather than from isolated architectural modifications. Experiments conducted on the AcuSim-FAcupoint dataset show that the proposed framework achieves improved feature transfer stability and spatial consistency. Comparative evaluations indicate that ACUR-Net outperforms PFLD, PIPNet, HRNet, and ViTPose in terms of NME, PCK@0.05, and OKS-mAP. The results suggest that multi-factor integration is effective for enhancing localisation robustness under realistic conditions.

Keywords: acupuncture point recognition; multiphysics modelling; cross-domain adaptation; deep learning.

DOI: 10.1504/IJAHUC.2026.154099

International Journal of Ad Hoc and Ubiquitous Computing, 2026 Vol.52 No.5, pp.87 - 100

Received: 12 Nov 2025
Accepted: 11 Jan 2026
Published online: 12 Jun 2026 *

Title: Modelling and simulation for biomechanical responses of acupuncture points based on multi-physics field coupling

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