Kengo Ohnishi

Background/Objectives: Statistical shape modeling (SSM) is used to describe transtibial residual-limb morphology for prosthetic socket design, simulation, and future structural testing. However, conventional intrinsic metrics such as compactness, generality, and specificity may not directly reflect geometric fidelity to the original shape. This study examined the relationship between geometric fidelity and SSM evaluation and assessed a cross-sectional shape representation framework for transtibial residual limbs. Methods: Residual-limb surfaces were acquired from 62 adults with unilateral transtibial amputation using a structured-light 3D scanner while preserving habitual limb posture. Two surface-based registration methods, non-rigid iterative closest point and Bayesian coherent point drift, were compared with a cross-sectional representation in which proximal and distal regions were sectioned separately and reconstructed by strip triangulation. Geometric fidelity to the original mesh was quantified using average symmetric surface distance (ASSD). SSM performance was evaluated using compactness, generality, and specificity. Results: The optimal cross-sectional configuration was 60 sections × 72 points. The proposed method showed the best geometric fidelity (ASSD, 1.30 ± 0.14 mm), followed by Bayesian coherent point drift (1.33 ± 0.14 mm) and non-rigid iterative closest point (1.48 ± 0.48 mm). Compactness was highest for the proposed method, reaching 95% cumulative variance in four modes, compared with five and seven modes, respectively, for the two surface-based methods. In geometry-space evaluation, the proposed method showed the lowest specificity error, while differences in generality were statistically significant but small in magnitude. Conclusions: Intrinsic SSM metrics alone were insufficient to judge registration quality in transtibial residual-limb modeling. The cross-sectional representation preserved the original surface geometry more faithfully than the evaluated surface-based methods while maintaining competitive SSM performance.

Background: Accurate evaluation of pressure distribution at the socket–limb interface is essential for improving prosthetic fit and comfort in transfemoral amputees. This study aimed to develop a proof-of-concept framework that integrates machine learning–based segmentation with the finite element method (FEM) to explore the feasibility of an initial workflow for residual-limb analysis during socket application. Methods: MRI data from a transfemoral amputee were processed using a custom image segmentation algorithm to extract adipose tissue, femur, and ischium, achieving high F-measure scores. The segmented tissues were reconstructed into 3D models, refined through outlier removal and surface smoothing, and used for FEM simulations in LS-DYNA. Pressure values were extracted at nine sensor locations and compared with experimental measurements to provide a preliminary qualitative assessment of model behaviour. Results: The results showed consistent polarity between measured and simulated values across all points. Moderate correspondence was observed at eight low-pressure locations, whereas a substantial discrepancy occurred at the ischial tuberosity (IS), the primary load-bearing site. This discrepancy likely reflects the combined influence of geometric deviation in the reconstructed ischium and the non-physiological medial boundary condition required to prevent unrealistic tissue displacement. This limitation indicates that the current formulation does not support reliable quantitative interpretation at clinically critical locations. Conclusions: Overall, the proposed framework provides an initial demonstration of the methodological feasibility of combining automated anatomical modeling with FEM for exploratory pressure evaluation, indicating that such an integrated pipeline may serve as a useful foundation for future development. While extensive refinement and validation are required before any quantitative or clinically meaningful application is possible, this work represents an early step toward more advanced computational investigations of transfemoral socket–limb interaction.

Accurate evaluation of pressure distribution at the socket–limb interface is essential for improving prosthetic fit and comfort in transfemoral amputees. This study aimed to develop a data-driven framework that integrates machine learning–based segmentation with finite element method (FEM) to quantitatively assess interface pressure during socket application. MRI data from a transfemoral amputee were processed using a custom image segmentation algorithm to extract adipose tissue, femur, and ischium, achieving high F-measure scores. The segmented tissues were reconstructed into 3D models, refined through outlier removal and surface smoothing, and used for FEM simulations in LS-DYNA. Pressure values were extracted at nine sensor locations and compared with experimental measurements. The results showed consistent polarity between measured and simulated values across all points. Furthermore, at the eight locations excluding the ischial tuberosity (IS) region, a statistically significant and moderately strong positive correlation was observed between measured and simulated pressures (r = 0.7485, p < 0.05). Notably, positive pressure regions demonstrated close agreement between experimental and simulated values, whereas the discrepancy observed at the IS region was likely influenced by the medial boundary conditions introduced to prevent unrealistic tissue displacement. This difference highlights a limitation of the current simulation setup. Overall, the proposed framework demonstrated reliable pressure estimation and offers a promising approach for personalized prosthetic socket design through automated anatomical modeling and simulation.

In this study, we estimated and validated the pressure distribution profile between the residuum and two types of prosthetic sockets for transfemoral amputees by utilizing a finite element analysis. Correct shaping of the socket for an appropriate load distribution is a critical process in the design of lower-limb prosthesis sockets. The pressure distribution profile provides an understanding of the relationship between the socket design and the level of subject comfortability. Estimating the pressure profile is important, as it helps improve the prosthesis through an evaluation of the socket design before it undergoes the fabrication process. This study focused on utilizing a magnetic resonance imaging (MRI)-based three-dimensional (3D) model inside a predetermined finite element simulation. The simulation was predetermined by mimicking the actual socket-fitting environment. The results showed that the potential MRI-based 3D model simulation could be used as an estimation tool for a pressure distribution profile due to the high correlation coefficient value (R² > 0.8) calculated when the pressure profiles were compared to the experiment data. The simulation also showed that the pressure distribution in the proximal area was higher (~30%) than in the distal area of the prosthetic socket for every subject. The results of this study will be of tremendous interest for fabricators through the use of a finite element model as an alternative method for the prefabrication and evaluation of prosthetic sockets. In future prosthetic socket fabrications, less intervention will be required in the development of a socket, and the participation of the subject in the socket-fitting session will not be necessary. The results suggest that this study will contribute to expanding the development of an overall prefabrication evaluation system to allow healthcare providers and engineers to simulate the fit and comfort of transfemoral prosthetics.

Recent technologies have suggested the utilization of three-dimensional (3D) printing technology to enhance the fabrication accuracy of prosthetics. Accordingly, simulations are used to obtain precise parameters for subject-specified prosthetic socket. This study proposes an evaluation system to measure the accuracy of a subject-specific 3D transfemoral residuum model during the interaction with the socket in conjunction with the application of finite element methods. The proposed system can be used in future validations of socket fabrication. The evaluation is based on the measurement of the residuum’s soft tissue deformation inside two types of prosthetic sockets. In comparison with other studies, the 3D models were constructed with magnetic resonance images (MRI) with the aid of computer-aided design (CAD) software. The measurement of soft tissue deformation was conducted based on the measurement of the volumetric value of fat, muscle and skin in the pre- and post-donning phases. The result yielded a promising correlation coefficient value between the simulation and the experiment in the soft tissue deformation evaluation. The relation of the muscle–fat ratio in the residuum is extremely important in the determination of the ability of the prosthetic to deform. The environment during the socket fitting session was similar to that defined by the set boundary conditions in simulations. In view of the promising results of this study, the evaluation system proposed herein is considered reliable and is envisaged to be used in future research.

A prosthetic limb control system to operate powered 2-DOF wrist and 1-DOF hand with environmental information, myoelectric signal, and forearm posture signal is composed and evaluated. Our concept model on fusing biosignal and environmental information for easier manipulation with upper limb prosthesis is assembled utilizing networking software and prosthetic component interlink platform. The target is to enhance the controllability of the powered wrist’s orientation by processing the information to derive the joint movement in a physiologically appropriate manner. We applied a manipulative skill model of prehension which is constrained by forearm properties, grasping object properties, and task. The myoelectric and forearm posture sensor signals were combined with the work plane posture and the operation mode for grasping object properties. To verify the reduction of the operational load with the proposed method, we conducted 2 performance tests: system performance test to identify the powered 2-DOF wrist’s tracking performance and user operation tests. From the system performance experiment, the fusion control was confirmed to be sufficient to control the wrist joint with respect to the work plane posture. Forearm posture angle ranges were reduced when the prosthesis was operated companying environmental information in the user operation tests.

Ground reaction forces (GRF) and pressure beneath the foot prosthesis are the main parameters used in biomechanical analysis to estimate the joint load and evaluate the quality of the prosthesis, especially with transfemoral patient who have amputation that occurs through the femur. The information of ground reaction forces and beneath pressure of foot prosthesis is conventionally achieved using dynamics method or the experimental method. However, these methods have some limitation for a prosthetist and designers to choose the best prosthesis solution for transfemoral patient. In the dynamics method, the deformation of the foot prosthesis and the variation in the shape of the residual limb in the socket is neglected and the center of gravity of the prosthesis component is estimated; thus, the method is less accurate because the prosthesis consists of several parts with different materials and shapes. The experimental method involves time and cost in setting-up the device. Data can be acquired only after the patient wears the prosthesis. In this study, the authors were implemented a finite element (FE) method for computing the GRF, and the pressure beneath the foot prosthesis and its distribution. The finite element model of all components of transfemoral of the prosthesis was created. The ground reaction forces, beneath pressure of foot prosthesis and other parameters were disclosed after solving by explicit solver of LS-Dyna software. The results of the vertical ground reaction forces exhibit consistently similar data between the simulation and the measurement. A correlation coefficient of 0.91 between them denotes their correspondence. The reaction force at knee joint, distribution of beneath pressure of foot prosthesis were included in results and discussion. These results can be used for prosthesis design and optimization; they can assist the prosthetist in selecting a comfortable prosthesis for the patient and in improving the rehabilitation training.

This paper reports on the development of a 2 degree-of-freedom swaying motion platform and a basic experiment on measurement and evaluation of the driving posture stability. A motion base with pneumatic cylinders to rotationally accelerate the subject in the driver's seat was made. With this motion base, an experiment was conducted to evaluate the indices of driver's posture stability placing a mannequin in the seat. Accelerometer was attached to the mannequin and inclination sensors were mounted on the motion base. Two postural conditions were set and tested on unidirectional swaying motion on each axis. Motion base's angular velocity and of the mannequin's velocity were computed from the sensor signals and the relation is plotted for each situation. Results showed feature points in the axes and directions that are to be evaluated in human subjects.