journal: Biomedical Engineering / Biomedizinische Technik

Impact Factor: 1.8

Zeitschrift Open Access

Biomedical Engineering / Biomedizinische Technik

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering and the German Society of Biomaterials

Editor-in-Chief:
Herausgegeben von: , , , , , , , und

Sprache: Englisch

Erstveröffentlichung: 1. Januar 1956

Erscheinungsweise: 6 Hefte pro Jahr

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Über diese Zeitschrift

Objective
Biomedical Engineering / Biomedizinische Technik (BMT) is a high-quality forum for the exchange of knowledge in the fields of biomedical engineering, medical information technology and biotechnology/bioengineering. As an established journal with a tradition of more than 60 years, BMT addresses engineers, natural scientists, and clinicians working in research, industry, or clinical practice. All articles are peer-reviewed. All manuscripts must be submitted in English.

Starting 2025, the journal will be transferred to Diamond Open Access on a year-by-year basis. All articles will thus immediately appear under the Creative Commons license CC-BY. There will be no publication costs for the authors. The Open Access transformation is based on Subscribe-to-Open, an alternative model that enables the full Open Access transformation of journals through the continuation of existing subscriptions. The prerequisite for successful transformation is that subscriptions are continued to the same extent as before. The editors of the Biomedical Engineering / Biomedizinische Technik and the publisher De Gruyter would therefore like to thank all subscribers for their support, to make the transformation to Open Access possible.

Topics

diagnostic imaging
image processing
biosignal processing
modelling and simulation
biomechanics
information and communication in medicine
telemedicine and e-health
surgery
minimum invasive interventions
endoscopy and image-guided therapy
diagnostic and therapeutic instrumentation
clinical engineering
micro- and nanosystems in medicine
active implants
biosensors
neuro-engineering
neural systems
rehabilitation and prosthetics
biomaterials
cellular and tissue engineering
artificial organs
biomedical engineering for audiology, ophthalmology, emergency and dental medicine
general subjects (e.g., education and training, health technology assessment)
special topics (e.g., linking proteomics and genomics with biomedical engineering, emergency medicine)

Article formats
Reviews, Research Articles, Short Communications

Ihre Vorteile

Your benefits:Imperative topicApplicative approach to engineering facilities and methodsNew areas of application of cutting-edge technologies in modern medicineState-of-the-art solutions for requirements in current medical practiceAhead-of-print online publicationHistoryThe Journal was founded in 1956 as the official journal of the German Society of Biomedical Engineering Biomedizinische Technik and published firstly in German. In a transition period as of 2004 publication in German and English was possible, but since 2010 the journal appears only in English. Consistently the title was changed to Biomedical Engineering – Biomedizinische Technik.

Open Access
Robust ventricular segmentation in cardiac MRI via fused attention and capsule networks

17. März 2026

Yuguang Ye, Taisheng Zeng, Kavimbi Chipusu, Bijiao Ding, Yifeng Huang, Jingwei Guo, Jianlong Huang

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Objectives An effective automatic system for ventricular segmentation from MRI is vital for diagnosing cardiovascular diseases, yet challenges persist due to anatomical variations and artifacts. Methods We preprocess cardiac MRI with min-max normalization, then propose a hybrid segmentation network (ResFAU-net) integrating residual blocks, attention gates, and a Fused Accumulation Bridge module to delineate ventricle boundaries. The segmented regions are classified by the HAMC3 model, which combines cascaded capsule networks, CNNs, and hierarchical attention, with parameters optimized via the Coati Optimization Algorithm (COA). Results Rigorous assessment on our CMRI dataset using metrics (Dice, IoU, accuracy, precision, etc.) demonstrates the model’s high performance in segmenting and classifying the left and right ventricles achieving an IoU of 96.29 % and accuracy of 99.03 %. Conclusions The proposed ResFAU-net and HAMC3 framework offers a robust, end-to-end solution for precise ventricular cardiac analysis, demonstrating strong potential to automate and enhance the efficiency of cardiovascular diagnosis in clinical MRI workflows.
Open Access
Tetrakaidecahedron-inspired porous custom insoles for enhanced diabetic foot decompression

12. März 2026

Yan Zheng, Changsheng Yang, Jing Wang, Yaping Yang, Jiantao Yang

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Objectives Diabetic foot is a prevalent and severe complication among diabetic patients, usually caused by sensory neuropathy and chronic mechanical stress overload. The structural characteristics of the tetrakaidecahedron porous structure are applied to insoles to optimize plantar pressure distribution, thereby minimizing abnormal plantar pressure in diabetic feet. Methods Integrating plantar pressure zoning, finite element analysis, Grasshopper parametric modeling, and 3D printing technology, a customized pressure-relief insole for diabetic feet has been designed and validated using static standing plantar-pressure measurements. The insole employs a porous structure with adjustable porosity and specified regional elastic modulus to achieve customized plantar pressure relief. Results The designed insole (NPSI) increases the plantar contact area by approximately 30 % and reduces peak contact pressure by over 47 % in the high-pressure regions of M and H zones. Conclusions The method proposed in this study effectively customizes pressure-relief insoles for diabetic feet, reducing the incidence and progression of diabetic foot ulcers. This approach is also applicable to the design of other assistive medical devices that require specific support and pressure relief.
Open Access
CT-based hybrid deep learning–radiomics framework for predicting postoperative rebleeding in hypertensive intracerebral hemorrhage

12. März 2026

Weiwei Lu, Feng Wang, Li Li, Dan Chen, Peng Ji

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Objectives Hypertensive intracerebral hemorrhage (HICH) is a frequently encountered and highly lethal cerebrovascular disorder, and postoperative rebleeding remains one of its most feared complications. Methods We developed a nomogram featuring a hybrid architecture that integrates radiomics-derived signatures and deep learning representations from CT imaging together with routine clinical parameters, with the goal of enhancing the individualized prediction of rebleeding risk following surgical intervention in HICH patients. A total of 151 individuals diagnosed with HICH were prospectively enrolled and randomly assigned to a training set (n=105) and a validation set (n=46) following a 7:3 ratio. Results The resulting model outperformed single-domain approaches relying solely on traditional clinical indicators or deep learning features. In the training cohort, the nomogram yielded an AUC of 0.993 (95 % CI: 0.982–1.000), while in the internal testing cohort, the AUC reached 0.860 (95 % CI: 0.745–0.974). The model highlighted several key predictors associated with postoperative rebleeding. Conclusions Overall, the integrated nomogram, embedding clinical data, radiomic phenotypes, and deep learning markers, exhibited robust predictive capability in assessing rebleeding risk among patients with HICH. Ongoing research is needed to further refine and validate the model in broader clinical settings.
Open Access
LLM-guided multimodal attention network for robust multiclass Parkinson’s disease diagnosis

3. März 2026

Taisheng Zeng, Yuguang Ye, Bijiao Ding, Yifeng Huang, Muhammad Ibrahim Umar, Kavimbi Chipusu, Jianlong Huang

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Objectives Accurate identification of Parkinson’s disease (PD), particularly during its prodromal stage, remains a major clinical challenge due to heterogeneous symptom presentation and overlapping neurological patterns. This study proposes an LLM-Guided Multimodal Attention Network (LLM-MAN) to improve PD staging by jointly modeling structural MRI and clinical/cognitive metadata. Methods We develop a unified multimodal framework that encodes structural MRI using a ResNet-18 backbone enhanced with Convolutional Block Attention Modules (CBAM) for discriminative neuroimaging feature extraction, and represents clinical/cognitive metadata using an LLM-based text encoder (pre-trained BERT) for contextualized semantic modeling. A Meta-Guided Cross-Attention (MGCA) module is introduced to align clinical semantic knowledge with imaging features, enabling robust cross-modal fusion for multiclass classification (Normal Control, prodromal PD, and diagnosed PD). The model is evaluated on the Parkinson’s Progression Markers Initiative (PPMI) dataset and further validated on an independent external cohort. Results On the PPMI dataset, LLM-MAN achieved an accuracy of 95.68 % for distinguishing Normal Control, prodromal PD, and diagnosed PD. External validation on an independent cohort yielded 94.10 % accuracy, indicating strong generalization performance across datasets. Conclusions LLM-guided multimodal fusion via MGCA provides reliable and interpretable approach for PD staging, substantially improving prodromal PD identification by integrating semantic clinical knowledge with neuroimaging representations.
Open Access
Influence of Sr²⁺ doping and phase composition on the physicochemical properties and cytocompatibility of biphasic calcium phosphate for bone graft applications

2. März 2026

Ravathi Marathandi, Adlisa Abdul Samad, Murfiqah Taufiqiah Mohd Amin, Zatul Faqihah Mohd Salaha, Norhana Jusoh, Ardiyansyah Syahrom, Dian Agustin Wahjuningrum

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Objectives To investigate how phase composition influences the physicochemical properties, Sr 2+ ion release behavior, and cytocompatibility of Strontium (Sr)-doped calcium phosphate (CaP) materials, focusing on Sr-HA, Sr- β -TCP, and three Sr-BCP compositions. Methods This work focuses on Sr-HA, Sr- β -TCP, and Sr-BCP powders with HA/ β -TCP ratios (60:40 (BCP1), 30:70 (BCP2), and 20:80 (BCP3)) that were synthesized by wet chemical precipitation followed by calcination. The effect of CaP phase compositions on physicochemical characteristics, Sr 2+ release, and cytocompatibility was investigated by using ICP-OES, FTIR, XRD, SEM-EDX, and MTT assays. Results EDX confirmed the Ca/P ratios, and both FTIR and XRD indicated successful phase formation without secondary phases. The Sr-BCP samples demonstrated enhanced cell viability after 48 h in MTT assays, highlighting biological responses associated with the biphasic structure. ICP-OES analysis indicated composition-dependent Sr 2+ release, with Sr-BCP1 showing the highest initial and sustained ion release. Conclusions Sr-BCP1 offers a promising balance between structural stability, favorable cytocompatibility, and controlled Sr 2+ ion delivery, supporting its potential for bone applications.
Open Access
Arm support as hidden assistance during Sit-To-Stand movement: a systematic review

26. Februar 2026

Musfirah Abd Aziz, Nur Azah Hamzaid, Haidzir Manaf, Noreha Abdul Malik

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Sit-To-Stand (SitTS) training is often performed by patients who may require arm assistance to perform it successfully. This study examines the role of arms in performing the SitTS maneuver to better understand their contribution and clinical significance. This review synthesizes the reported outcome measures of arm-assisted SitTS exercise programs in people with physical impairments. Web of Science (WoS) and Scopus™ databases were searched for relevant studies up to May 2025. Inclusion and exclusion criteria were used to screen the titles and abstracts of articles identified using key search terms related to SitTS activity and arm support. Only articles that met the key terms were extracted and analyzed in this study. A total of 47 studies reported arm support measures during SitTS, either in clinical or biomechanical contexts. These studies highlighted various methods and tools used to assess the body’s state during the rising movement. Joint angle and SitTS duration are clinically applicable and more easily measured compared to seat, foot, and arm forces which require specialized instrumentation. Balancing clinical measures with detailed biomechanical assessments is important in enabling practitioners and researchers to evaluate and enhance SitTS interventions that involve arm assistance, ultimately improving rehabilitation outcomes.
Open Access
Standing up to neurodegeneration: evaluating autonomic stress and safety in sit-to-stand using heart rate variability analysis

24. Februar 2026

Sorfina Ilham Rozman, Nur Azah Hamzaid, Einly Lim, Norhamizan Hamzah, Jade P. Guan, Sakinah Sabirin, Nazirah Hasnan, Nortina Shahrizaila

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Objectives Sit-to-stand (STS) exercises are commonly incorporated in functional rehabilitation due to their simplicity, relevance to daily mobility and more recently, cardiac fitness. While generally considered safe for most clinical populations, its effect on autonomic stability remains underexplored – particularly in those with autonomic vulnerability such as individuals with amyotrophic lateral sclerosis (ALS). This study investigates the suitability of STS exercises for individuals with ALS, with specific focus on establishing baseline heart rate variability (HRV) data during rest and transient STS movement. Methods Heart rate (HR) and HRV (RMSSD and HF) were assessed across three cohorts; healthy young adults (n=29), individuals living with ALS (n=8), and their age-matched controls (n=9), under resting condition and two STS protocols: Timed up and go (TUG) and five times sit-to-stand test (FTSST). Results All groups exhibited significant increase in mean HR during STS compared to rest (p<0.05), whereas no statistically significant differences were observed in RMSSD and HF. These results indicate that STS exercises elicit measurable cardiovascular exertion without triggering acute autonomic dysfunction in ALS individuals, supporting its role in safe rehabilitation for early-mid stages ALS. Conclusions HRV serves as a potential tool for non-invasive monitoring and assessment of autonomic function during physical therapy.
Open Access
Blood pressure estimation using single photoplethysmography signal based on ResNet-BiGRU

20. Februar 2026

Gongwei Fan, Yuhao Pang, Wei Zheng, Min Wang

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Objectives Conventional cuff-based blood pressure (BP) measurement provides only intermittent readings, whereas photoplethysmography (PPG)-based methods enable continuous and noninvasive monitoring. This study aims to develop a deep learning framework for accurate, cuffless BP estimation using a single PPG signal. Methods A hybrid deep neural network, termed ResNet-BiGRU, was developed by integrating residual convolutional blocks with bidirectional gated recurrent units to jointly capture morphological and temporal features. The UCI Cuff-Less Blood Pressure Estimation Dataset (a subset of MIMIC-II), which contains synchronized PPG and arterial blood pressure (ABP) signals from 942 subjects, was used for model training and validation. After applying a 0.5–8 Hz bandpass filter and segmenting into 5 s windows, the data were split 80/20 for training and validation. External evaluation was conducted using the VitalDB dataset, which provides synchronized PPG and ABP recordings from surgical patients under diverse physiological conditions. Results The model achieved mean absolute errors (MAE) of 4.78 mmHg for systolic BP (SBP) and 2.98 mmHg for diastolic BP (DBP) on UCI, and 8.15 mmHg for SBP and 4.59 mmHg for DBP on VitalDB. Conclusions The ResNet-BiGRU model demonstrates accurate, robust, and generalizable cuffless BP estimation, showing strong potential for wearable health monitoring applications.
Open Access
Optimizing arteriovenous fistula (AVF) configurations: a computational study of radial artery deviation and reimplantation (RADAR) and conventional techniques in hemodynamics

18. Februar 2026

Ning Zhang, Hongtao Zhang, Xiaofeng Wang, Yang Lu, Jiawei Li, Shujie Yan, Jianhua Hou, Guo Pan, Qian Li

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Objectives Anastomotic stenosis in arteriovenous fistulas (AVFs) is a significant issue for hemodialysis patients. This study uses computational fluid dynamics (CFD) simulations to evaluate the effects of different AVF configurations, comparing the RADAR technique with conventional AVF configurations in terms of hemodynamics, flow disturbances, and wall shear stress (WSS). Methods Echo-color Doppler (ECD) imaging and CFD simulations assessed disturbed hemodynamics in different AVF configurations. Large eddy simulations (LES) captured turbulence transition at the anastomosis. Hemodynamic parameters, including velocity distribution, vortex formation, WSS, wall displacement, and stress distribution, were analyzed. A one-way fluid-structure interaction (FSI) approach was used to compute fluid-induced wall forces and assess stress distribution and deformation. Results The RADAR configuration showed superior hemodynamic performance with higher blood flow velocity, reduced turbulence, and a more favorable WSS environment, potentially reducing stenosis risk and improving long-term patency. Higher venous inner wall stress in RADAR configurations may aid vascular remodeling. Conclusions Optimizing AVF configurations and anastomosis angles can enhance AVF functionality, reduce complications, and improve hemodialysis outcomes for patients with end-stage renal disease. The RADAR technique may improve AVF maturation and reduce complications.
Open Access
Optimizing the load capacity of a compliant-mechanism-based microplate gripper for biomedical lab automation

17. Februar 2026

Leon Budde, Leonhard Häberle, Thomas Seel, Daniel O. M. Weber

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Objectives Laboratory automation enhances repeatability and throughput in scientific and industrial applications. An important aspect of automation is transportation of standardized components, such as microplates (MPs). Previously, we developed the compliant-mechanism-based gripper (“CrocoGrip”), enabling secure and contamination-free MP transport. However, we have yet to optimize the gripping jaws to increase the gripper’s maximum load capacity (LC). In this paper, we optimize the design and surface of CrocoGrip’s jaws to optimize its LC. CrocoGrip works like a torsion spring, so its opening width, which defines the CrocoGrip’s deformation, its jaw arm length, and the jaw’s surface material affect its LC. Methods We tested the LC of six different jaw materials at different opening widths. The best-performing jaw surface was further evaluated at a second jaw arm length. Results Jaws equipped with silicone inserts performed the best (LC=2.93 N). Aluminum with different surface smoothness performed the worst (0.68 N≤LC≤1.56 N). Decreasing the jaw arm length from 81 mm to 66 mm increased the LC of the silicone-insert jaws to 3.71 N. Conclusions The improved LC allows the safe handling of MP (weight ≤127 g), enabling the use of the CrocoGrip for a broader range of tasks.
Open Access
Multi-encoder U-Net benchmarking for LiTS17 Liver–Tumor segmentation: accuracy–efficiency trade-offs across training durations

17. Februar 2026

Yuguang Ye, Kavimbi Chipusu, Taisheng Zeng, Yusi Chen, Bijiao Ding, Yifeng Huang, Jingwei Guo, Jianlong Huang

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Objectives Accurate liver and tumor segmentation from CT is fundamental for diagnosis, treatment planning, and longitudinal monitoring of liver cancer. Although U-Net variants with popular encoder backbones are widely used, the coupled effects of encoder selection, training duration, and computational cost, as well as comparisons against volumetric architectures such as V-Net, remain insufficiently standardized. Methods We propose a unified benchmarking framework that evaluates a family of multi-encoder 2D U-Net models together with an optional 3D V-Net baseline under the same preprocessing, input construction, and 3-fold cross-validation protocol on LiTS17. Multiple backbones (VGG16/VGG19/ResNet34/ResNet50/ResNet101/MobileNetV2) are assessed under 15/50/100-epoch schedules, and performance is reported using overlap and detection metrics (Dice, IoU, precision, recall) alongside efficiency indicators (training time and model complexity when available) to characterize the accuracy–efficiency trade-off. Results Results show liver segmentation rapidly reaches near-ceiling performance across models, while tumor segmentation benefits markedly from longer training and stronger encoders, especially for small or low-contrast lesions. Conclusions Overall, the study provides a reproducible protocol and practical guidance for selecting segmentation models that balance accuracy, robustness, and deployment cost.
Open Access
Patient-specific 3D-Printed jigs for high tibial osteotomy: a preclinical simulation study using affordable 3D printing

6. Februar 2026

Kunal Verma, Shagun Sharma, Chander Sen, Sarbjit Singh, Siddhartha Sharma

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Objectives Patient-specific 3D-printed jigs improve surgical outcomes, yet their use in high tibial osteotomy (HTO) lacks widespread acceptance due to cost-related scepticism and workflow adaptation challenges. This work aims to facilitate the adoption of 3D printed patient-specific instrumentation by demonstrating the precision of jigs produced using affordable resin 3D printing. Methods Full-length tibial CT scans were used for 3D modelling, virtual HTO planning and designing of patient-specific jigs. The jigs were 3D printed using a ∼$550 resin printer, whereas the bones were printed in a ∼$600 filament printer. Achieved vs. planned corrections were compared using the 3D scanning superimposition method. Accuracy was assessed with paired t-tests, Bland-Altman plots, linear regression, and two one-sided t-tests (TOST). Results For Medial Proximal Tibial Angle (MPTA), the mean error was −0.05° ± 1.32° with no systematic bias (p=0.912), whereas for Posterior Proximal Tibial Angle (PPTA), it was 0.57° ± 0.38°, having a significant over-correction (p=0.004). Strong to excellent correlations were observed (R 2 : 0.77 for MPTA, 0.99 for PPTA). Corrections were equivalent within ±1° (TOST: p=0.042 and p=0.007). Conclusions Affordable 3D-printed jigs could achieve acceptable corrections in a preclinical simulation setting, offering cost-effective preoperative planning and surgical training.
Open Access
Perspectives on biomechanical data: a cross-disciplinary survey of current practices, challenges, and future needs

2. Februar 2026

Jonas Borsch, David Schnur, Sebastian Roth, Ulrich Hartmann, Daniel Friemert

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Objectives The objective of this study was to assess the current usage, challenges, and specific needs regarding biomechanical data, with a focus on gait analysis, across a diverse field such as sports performance, clinical rehabilitation, and occupational health. Methods We conducted a survey among more than 300 institutions in the DACH region (Germany, Austria, Switzerland). Of 49 individuals who began the survey, 24 submitted complete responses. Results Findings indicate that participants recognize the value of biomechanical data, yet adoption of publicly available datasets is hindered by inconsistent formats, limited metadata, and strict privacy regulations. Respondents emphasized standardized documentation and clearer guidelines to facilitate sharing and collaboration. Many institutions are overwhelmed by legal compliance, with data proception laws posing significant hurdles to effective usage. Conclusions The results highlight the need to (1) establish standardized file formats, (2) improve metadata quality, (3) develop transparent, consistent data-sharing protocols, and (4) clarify legal frameworks for compliance.
Open Access
Polymeric micro- and nanoparticle release from cardiopulmonary bypass and extracorporeal membrane oxygenation circuits

28. Januar 2026

Lars Saemann, Markus Stiller, Hardik Vaghasiya, Meet Gadara, Susanne Gramsall, Anne Großkopf, Andreas Simm, Gábor Szabó, Paul-Tiberiu Miclea

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Objectives Cardiopulmonary bypass (CPB) and extracorporeal membrane oxygenation (ECMO) or life support (ECLS) circuits are built from polymers and might release polymeric micro- and nanoparticles (MNP) into the circulation. MNPs seem to provoke inflammation, oxidative stress, and apoptosis, which are also side effects of extracorporeal circulation. Thus, we investigated the MNP release from CPB and ECMO/ECLS circuits. Methods A CPB and ECMO/ECLS circuit was filled with saline solution, and circulation was initiated for 5 h and 7 d, respectively. Samples were taken from both circuits and filtered through a silicon membrane. MNPs were detected and quantified using optical microscopy and micro Raman spectroscopy. Results During circulation, polyvinyl chloride (PVC) and polymethyl methacrylate (PMMA) were detected in the CPB perfusate. After 5 h of circulation, polyethylene terephthalate (PET) was detected. In the ECMO/ECLS circuit, time-dependent accumulation of polymeric fragments was detected. Finally, particles of polyethylene (PE), polystyrene (PS), PET, and PVC were identified. The particle-size distribution extended from initially <2 µm to finally >10 µm with increasing circulation time. Conclusions CPB and ECMO/ECLS circuits release MNPs. The number of MNPs increases over the period of use. A larger number of circuits and of health effects of identified MNPs, should be investigated.
Open Access
Numerical modeling and prediction of late estimated glomerular filtration rate in kidney transplant recipients based on machine learning models and the Monte Carlo simulation method

22. Januar 2026

Ivan R. Pavlović, Nikola Stefanović, Nikola Despenić, Dragana R. Pavlović, Maša Jović, Radmila Velicković-Radovanović, Branka Mitić, Tatjana P. Cvetković

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Objectives This paper presents an experimental numerical method for modeling and analyzing stochastic systems. For this purpose, various machine prediction models are trained using the Monte Carlo simulation method. This method is presented using experimental data of a kidney transplantation with an immunosuppressive protocol based on tacrolimus. Methods A multivariate regression model was constructed by previous authors based on a clinical study in which key independent physiological parameters such as serum creatinine and estimated glomerular filtration rate (eGFR) six months after transplantation, as well as the pharmacokinetics of tacrolimus, including the dose-adjusted trough concentration of tacrolimus (C0/D) and intrastation variability (IPV), and eGFR between 13 and 36 were the dependent variable. Using the Monte Carlo simulation method, this model is further applied to obtain the essential data for the optimization of the prediction models. To determine the optimal prediction model, the DecisionTreeClassifier, Random Forest Classifier, and XGBClassifier were trained and compared. Results The results indicate that XGBoost is the most accurate, reliable and generalizable model among the classifiers tested, while Monte Carlo simulation represents a significant methodological advance in the field of kidney transplantation. Conclusions Advanced numerical methods for kidney transplant patients’ therapy are step forward in optimization of current immunosuppressive protocols.
Open Access
Advanced deep learning framework for breast cancer detection using digital breast tomosynthesis images

12. Januar 2026

G. Bharatha Sreeja, S. Sudha, T. M. Inbamalar

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Objectives Early and accurate detection of breast cancer is critical for improving patient survival outcomes. This study proposes a robust deep learning–based framework for breast cancer detection using digital breast tomosynthesis (DBT) images, leveraging both single-slice and multi-slice inputs. Methods The proposed work includes image normalization, resizing and Laplacian Pyramid Enhancement (LPE). Various features were extracted and fused in different combinations. To retain the most discriminative features Exhaustive Feature Selection (EFS) is used. A hybrid model integrated using ResNet V2, MobileNet V3 and Inception V3+ for classification. Finally ensemble learning with XGBoost was applied and Hyperparameters were optimized using a grid search strategy. Results The hybrid model with multi-slice DBT inputs achieved better improvements with accuracy, sensitivity, specificity and area under the curve (AUC). While applying LPE, feature fusion and EFS substantially enhanced the hybrid model’s diagnostic performance. Conclusions The findings demonstrate the strong potential of advanced methods in enhancing performance. Future research work will focus on integrating this pipeline with clinical decision support systems, multi-center datasets and extending to other breast imaging modalities.
Open Access
Evaluation of an adaptive system for breathing control in closed-loop diaphragm pacing

15. Dezember 2025

Xiaoyu Gu, Zifu Huang, Zhihao Mao, Wei Zhong, Yixuan Wang, Yan Shi

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Objectives Existing diaphragm pacing (DP) system use an open-loop control method with a fixed stimulation mode to control breathing. It requires doctors to manually adjust stimulation parameters to meet the patient’s ventilation needs. Methods A neural network adaptive controller was tested to control breathing in DP system. For the diaphragm motion model, the respiratory airflow of healthy adults and rabbits was collected and compared with the simulation calculation results to verify the accuracy of the model. The performance of the adaptive controller was evaluated comparatively with that of the PID controller. Adaptive controller consists of a neural network and adaptively adjusts stimulation parameters to produce the desired respiratory volume waveform. Superiority of the output performance of the adaptive controller was further studied by setting various diaphragm model parameters. We further verified the feasibility of the adaptive controller through animal testing. Results The adaptive controller is better than the PID controller in maintaining the stability of the desired breath volume. Application of the adaptive controller can reduce the root mean square (RMS) error between the desired breath volume and the actual value to less than 6 %. Conclusions This study demonstrates the potential application of adaptive controllers in closed-loop DP systems.
Open Access
AI in healthcare: mapping Romania’s transition from research to intellectual property & industry solutions

20. November 2025

Giovani M. Goron, Razvan M. Chereches

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Objectives Romania is aligning its healthcare AI ecosystem with the European Union’s AI Act (2024/1689), through its own National AI Strategy. Despite a growing volume of research in medical AI, significant gaps remain in translating this output into patents and domestically developed high-risk medical devices. This study assesses Romania’s research productivity, patenting activity, and commercial solutions in medical AI. Methods We conducted an analysis combining bibliometric data, patent information, and medical device databases, and analyzed 619 Romanian-authored articles on medical AI, 272 patent records, and identified domestic AI-powered software providers. Results Romania’s publication output in medical AI has surged post-2018, primarily driven by academic institutions in Bucharest and Cluj. Patents are predominantly filed by multinationals, indicating a potential disconnect between research and industrial output. Six AI medical software solutions were identified, most under the low-risk classifications. Conclusions While Romania is expanding its medical AI research, it faces barriers in converting academic output into innovation. The dominance of foreign corporations in patent filings, reliance on international funding for high-impact research, and the scarcity of domestically developed high-risk medical AI solutions highlight important gaps. Addressing these disparities is essential for national alignment in the AI medical innovation space.

Abstracts of the 2025 Joint Annual Conference of the Austrian (ÖGBMT), German (VDE DGBMT) and Swiss (SSBE) Societies for Biomedical Engineering

Abstracts of the 58th Annual Meeting of the German Society of Biomedical Engineering, 18 – 20 September 2024, Stuttgart

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Abstracts of the 2024 Annual Meeting of the Austrian Society for Biomedical Engineering (ÖGBMT)

Abstracts of the 2023 Annual Meeting of the Austrian Society for Biomedical Engineering (ÖGBMT)

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Abstracts of the 57th Annual Meeting of the German Society of Biomedical Engineering 26 – 28 September 2023, Duisburg, including: The Artificial Vision Symposium – The International Symposium on Visual Prosthetics

Special Issue: Medical Flow and Dosing Measurement Metrology in Drug Delivery; Guest Editors: Elsa Batista, Hugo Bissig and Stephan Klein

Abstracts of the 2022 Joint Annual Conference of the Austrian (ÖGBMT), German (VDE DGBMT) and Swiss (SSBE) Societies for Biomedical Engineering, including the 14th Vienna International Workshop on Functional Electrical Stimulation

Abstracts of the 55th Annual Meeting of the German Society of Biomedical Engineering (5 – 7 October 2021, Hannover)

Abstracts of the 2020 Annual Meeting of the German Society of Biomedical Engineering (29 September – 1 October 2020, Leipzig)

Abstracts of the 2019 Annual Meeting of the German Society of Biomedical Engineering (25–26 September 2019, Frankfurt am Main)

Abstracts of the 2018 Annual Meeting of the German Society for Biomaterials

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Special Issue: Optical Imaging Methods in Medicine / Guest Editors: Werner Nahm, Christoph Hornberger, Ute Morgenstern and Stephan B. Sobottka

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Highlight: Textile Engineering & Regenerative Medicine

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Highlight: Biosignal Analysis

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Special Issue: OR.NET – Secure Dynamic Networks in Operating Room and Clinic

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Highlight: Imaging & Image Analysis

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Highlight: Tissue Engineering & Scaffolds

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Highlight: Passive Implants & Biomaterials

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Special Issue: Smart Life Support, Issue Editor: Steffen Leonhardt

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Highlight issue: Biosignal Analysis

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Highlight Issue: Implants, Surgery and Interventions

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Highlight: Imaging and Image Analysis

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Highlight issue: Biomaterials and Artificial Tissue

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Special issue: Risk Management in Medical Human-Machine Systems / Guest Editors: Wolfgang Lauer and Klaus Radermacher

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Special Issue: Biosignal Processing / Guest Editors: Jens Haueisen and Tilmann Sander-Thömmes

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Highlight issue: Biomechanic Models and Image Guided Interventions

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Special Issue: Magnetic nanoparticles for biomedical applications / Guest Editor: Lutz Trahms

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Special Issue: Low Liquid Flows in Medical Technology / Guest Editors: Stephan Klein and Peter Lucas

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Special Issue: Technically Assisted Rehabilitation – TAR 2013 / Guest Editor: Thomas Stieglitz

Special Issue: Neuroprobes / Guest Editor: Thomas Stieglitz, Herc Neves and Patrick Ruther

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Special Issue: Patient Customized Engineering / Guest Editor: Thomas Schmitz-Rode, Robert Farkas and Fridtjof Nüsslin

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Special Issue: Magnetic Particle Imaging / Guest Editor: Thorsten M. Buzug

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Special Issue: Bioresorbable Implants / Guest Editors: Axel Haverich and Klaus-Peter Schmitz

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Proceedings BMT (Biomedizinische Technik) 2013 - Dreiländertagung der Deutschen, Schweizerischen und Österreichischen Gesellschaft für Biomedizinische Technik, Graz - Table of Contents

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Track A. FES Workshop - Functional Electro Stimulation & Neuroprosthetics

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Track B. Advanced Therapeutic Concepts

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Track C. Biomaterials & Biocompatibility

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Track D. Biomechanics

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Track E. Biomedical Instrumentation

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Track F. Biosensors & Bioanalytics

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Track G. Biosignal Processing

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Track H. Cellular & Tissue Engineering

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Track I. Clinical and Ambulatory Monitoring

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Track J. Usability, Risk Management & Regulatory Affairs

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Track K. Home Health Care & AAL

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Track L. Imaging, Image Based Interventions & Image Processing

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Track M. Medical Informatics & Bioinformatics

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Track N. Modeling & Simulation

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Track O. Prosthetics, Implants & Artificial Organs

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Track P. Rehabilitation Technology

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Track Q. Surgical Technique, Robotics & Endoscopy

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Track R. Education & Training

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Track S. Miscellaneous & Special Sessions

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Special issue: Innovations in the processing of biolelectric and biomagnetic signals

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Technically assisted rehabilitation – TAR 2011

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Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Table of contents / Inhaltsverzeichnis

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Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track A Training and Further Education

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Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track B. Imaging and Image Processing

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Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track C. Image Based Intervention

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Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track D. Biomaterials and Biocompatibility

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Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track E. Biosensors and Bioanalytics

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Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track F. Biosignal Processing

Heft SI-1-Track-G

Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track G. Cellular-, Tissue- und Bioengineering

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Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track H. Surgical Technique and Endoscopy

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Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track I. Clinical Engineering

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Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track J. Ergonomics and Risk Management

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Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track K. Home health care and AAL

Heft SI-1-Track-L

Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track L. Clinical and Ambulatory Monitoring

Heft SI-1-Track-M

Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track M. Magnetic Methods in Medicine

Heft SI-1-Track-N

Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track N. Medical Information Systems, Telemedicine, eHealth, mHealth

Heft SI-1-Track-O

Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track O. Modelling and Simulation

Heft SI-1-Track-P

Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track P. Ophthalmology Techniques, Optical and Photonic Processes

Heft SI-1-Track-Q

Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track Q. Personalized Medical Technology

Heft SI-1-Track-R

Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track R. Prevention and Rehabilitation Engineering

Heft SI-1-Track-S

Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track S. Prosthetics and Implants

Heft SI-1-Track-Z

Proceedings BMT 2012, 46. DGBMT Jahrestagung, Jena - Track Z. Special Sessions

Proceedings BMT 2011, 45. DGBMT Jahrestagung, Freiburg

Special Issue: Technically Assisted Rehabilitation

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Special Issue: Oral Implantology

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Proceedings BMT 2010, 44. DGBMT Jahrestagung, 3-Länder-Tagung D-A-CH, Rostock

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Special Issue: NeuroMath

Special Issue: Smart Life Support

Special Issue: Biomechanics and Biomaterials in Oral Rehabilitation and Dental Treatment

to be implemented...

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Die Zeitschrift Biomedical Engineering / Biomedizinische Technik veröffentlicht Sonder- und Themenhefte, die sich auf wichtige und neu aufkommende Themen im Bereich der Forschung konzentrieren. Die Zeitschrift hat ein strenges Verfahren eingeführt, um sicherzustellen, dass alle Manuskripte für Sonderausgaben denselben Qualitätsstandards und Peer-Review-Verfahren unterliegen wie reguläre Manuskripte. Weitere Informationen über die Peer-Review-Politik der Zeitschrift finden Sie in den "Hinweisen für Autoren".

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Jens Haueisen (Ilmenau, Germany)

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Associate Editors
Peter Augat (Institut für Biomechanik, Germany)
Daniel Baumgarten (Institut für Elektrotechnik und Biomedizinische Technik, Austria)
Thomas Deserno (Peter L. Reichertz Instituts für Medizinische Informatik, Technische Universität Braunschweig, Germany)
Frédéric Heim (Laboratoire de Physique et Mécanique Textiles
Universite de Haute-Alsace, France)
Steffen Leonhardt (Helmholtz Institute of Biomedical Engineering, RWTH Aachen University, Germany)
Klaus Radermacher (Helmholtz-Institute for Biomedical Engineering,
RWTH Aachen University)
Erik Schkommodau (Institute for Medical Technologies, University of Applied Sciences Northwestern Switzerland, Switzerland)
Thomas Stieglitz (Department of Microsystems Engineering (IMTEK) University of Freiburg, Germany)
Gudrun Wagenknecht (Forschungszentrum Jülich GmbH, Germany)

Editorial Board
†Ulrich Boenick (Berlin, Germany)
Olaf Dössel (Karlsruhe, Germany)
Pamela Habibovic (Maastricht, Netherlands)
Branislav Jaramaz (Pittsburgh, PA, United States)
Marc Kraft (Berlin, Germany)
Thomas Lenarz (Hannover, Germany)
Harry van Lenthe (Leuven, Belgium)
Benny Lo (London, UK)
Luca Mainardi (Milano, Italy)
Silvestro Micera (Lausanne, Switzerland & Pisa, Italy)
Thomas Penzel (Berlin, Germany)
Andrea Robitzki (Karlsruhe, Germany)
Klaus-Peter Schmitz (Rostock, Germany)
Tobias Schaeffter (Berlin, Germany)
Jess G. Snedeker (Zurich, Switzerland)
Leif Sörnmo (Lund, Sweden)
Nobuhiko Sugano (Osaka, Japan)
Jürgen Werner (Bochum, Germany)
Werner Wolf (Neubiberg, Germany)

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0013-5585

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Erstveröffentlichung:

1. Januar 1956

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6 Hefte pro Jahr

eISSN: 1862-278X

ISSN: 0013-5585

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