In musculoskeletal simulation, individualized joint axes enhance the accuracy and reliability of kinematic and kinetic simulation results. We investigated the correctness and performance of an analytical method for identifying the instantaneous axis of rotation between two bodies based on motion data in OpenSim. The instantaneous center of rotation is the point at which two bodies have the same velocity. The relative linear and angular velocity between the two bodies, as well as their relative position to each another, are required as inputs to calculate it. Using the instantaneous center of rotation, fixed or moving joint centers of rotation can be identified. To prove the general applicability of the method, the instantaneous centers of rotation of a revolute joint of a simple double pendulum model and the hip and knee joint of a more complex musculoskeletal model were investigated. The hip joint is defined as a ball joint. The knee joint is defined as an OpenSim custom joint which describes the motion of the child segment in relation to the parent segment as a function of generalized coordinates. To verify the correctness of the approach in OpenSim, the moving centers of rotation were calculated using synthetic noisefree data. The results were compared to the implementation of the respective joints in the model which act as the ground truth. White Gaussian noise was added to the synthetic data to analyze its effect on the quality of the calculated centers of rotation. We were able to correctly identify the center of rotation of each joint using noisefree data. In the case of noisy data, joint centers of rotation can be determined by applying additional filtering or optimization methods to the calculated instantaneous centers of rotation. Consequently, we are able to determine the center of rotation for arbitrary joints based on noisy synthetic data. This approach is applicable for both fixed and moving centers of rotation which distinguishes it from commonly used methods in the field of biomechanical simulation.Supplementary InformationThe online version contains supplementary material available at 10.1186/s42490-025-00102-7.

The mechanical properties of tumor tissue differ from those of healthy tissue. Therefore, surgeons palpate accessible surgical sites to determine tumor boundaries prior to resection. However, palpation is not possible during minimally invasive surgery, so instrumented palpation is required instead. This study investigates the suitability of an engineering method that combines mechanical object scanning and indentation to determine Young’s modulus of soft, tissue-like materials. To establish a defined reference, we tested our concept on silicone phantoms containing stiff tumor-like inclusions. We used a sensor consisting of a load cell connected to a rigid probe with a spherical indenter tip. Young’s modulus was calculated by measured force, indentation depth, and indenter geometry. These results were compared with those of a palpation experiment on the same specimens, conducted with surgeons. Validation results reflect the accuracy of the method. Error in estimation of Young’s modulus is: soft material 6.7%, stiff material 44.9%. Repeatability is high, with a standard deviation < 7%. By scanning a phantom and creating a stiffness image, we were able to identify the location and shape of the inclusion more clearly than experienced surgeons could using manual palpation. Looking ahead, the prospect of miniaturizing the presented technique for localizing tumor boundaries during surgery seems promising.Supplementary InformationThe online version contains supplementary material available at 10.1186/s42490-025-00100-9.

Diabetic retinopathy (DR) stands as a leading cause of global blindness. Early identification and prompt treatment are crucial in preventing vision impairment caused by diabetic retinopathy (DR). Manual screening of retinal fundus images is challenging and time-consuming. Additionally, there is a significant gap between the number of DR patients and the number of medical experts. Integrating machine learning (ML) and deep learning (DL) techniques is becoming a viable alternative to traditional DR screening techniques. However, the absence of a retinal dataset with standardized quality, the complexity of DL models, and the need for high computational resources are challenges. Therefore, in this study, we studied and analyzed the research landscape in integrating ML techniques in DR screening. In this regard, our work contributes significantly in several aspects. Initially, we identify and characterize images of the retinal fundus that are readily available. Then, we discuss commonly used preprocessing techniques in DR screening. In addition, we analyze the progress of ML techniques in DR screening. Lastly, we discussed existing challenges and showed future directions.Supplementary InformationThe online version contains supplementary material available at 10.1186/s42490-025-00098-0.

BackgroundStiff-knee gait is a common movement disorder in individuals with stroke; however, standardized criteria for its identification remain lacking. This study aimed to examine suitable criteria for identifying stiff-knee stroke survivors to facilitate comparisons across studies. Twenty-four stroke survivors (45.2±13.7 years old) and 24 age- and sex-matched controls (45.5±13.5 years old) with no known gait impairment participated in this study. Participants walked along a 10-m walkway at a self-selected comfortable speed. A motion capture system recorded the trajectories of retroreflective markers placed on specific body landmarks. The following knee flexion parameters during gait cycle were analyzed: (1) peak knee flexion during the swing period, (2) total range of motion (RoM cycle), calculated as the difference between maximum and minimum knee excursion during gait cycle, (3) RoM from toe-off to peak knee flexion (“RoM swing”), and (4) timing of peak flexion. Comparisons were made among control, paretic, and non-paretic limbs.ResultsAmong the 21 stroke survivors identified with stiff-knee gait, the paretic limb showed reduced peak swing, RoM swing, and RoM cycle compared to both the control and non-paretic limbs, as well as earlier timing compared to the non-paretic limb only.ConclusionsAmong the four examined criteria to identify stiff-knee gait in stroke survivors, the most suitable are peak knee flexion during the swing period of less than 40°, and knee range of motion from toe-off to peak knee flexion of less than 12°.

Healthcare practitioners in low and middle-income countries encounter numerous challenges, including insufficient staffing, an unreliable electrical infrastructure, and constrained resources. Unstable availability of electricity constitutes a significant impediment to the efficacy of public health initiatives that depend on technology requiring electrical power. More than 95% of medical apparatus is procured from developed nations, with an only 13% of medical device manufacturers situated within LMIC. Non-profit organizations have developed innovative medical technologies that offer life-saving solutions previously inaccessible in the developing world. The device is designed to be cost-effective, made from local resources, compact, portable, and operated without electricity. The device is designed to have replaceable parts, a waste container cut off, and be compatible with standard suction catheter/tubing. It includes user and maintenance training, displayed parameters, corrosion-resistant components, and pump pedal spring loading. A combination concept was created by combining the manufacturing capabilities of a diaphragm with the efficiency of a piston cylinder. The final design chosen uses a piston-cylinder assembly with a trash bag diaphragm for the seal, eliminating the need for exact tolerances and costly machining. A prototype was built on top of this combined design concept. The design concept involves the implementation of locally accessible resources for the pressure-generating mechanisms, as well as the adaptability and ease of assembly of the device. The ideal length of the cylinder assembly was determined through pressure readings using a digital manometer differential pressure sensor. Changing the capacity of the cylinder can adjust the pressure range. The ideal cylinder length was found to be 12.75 inches as it provided the desired pressure range, although longer cylinders were inconsistent and difficult for users to operate. The Foot-Operated Suction Unit is particularly well suited for usage in distant places without power supply, rural health facilities, home care, field emergencies, and brief power outages due to its compact size, low weight, and simplicity of operation. Hospitals of all levels typically employ foot-operated suction units to execute abortions and to draw blood, pus, sputum, and other mucus during surgical operations.