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Robust adaptive filtering algorithms based on (inverse)hyperbolic sine function

Sihai Guan, Qing Cheng, Yong Zhao, Bharat Biswal

Retention and promotion of women and underrepresented minority faculty in science and engineering at four large land grant institutions

Marcia Gumpertz, Raifu Durodoye, Emily Griffith, Alyson Wilson

How do research faculty in the biosciences evaluate paper authorship criteria?

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The value of CCTA combined with machine learning for predicting angina pectoris in the anomalous origin of the right coronary artery

Authors: Ying Wang, MengXing Wang, Mingyuan Yuan and Wenxian Peng

In vivo video microscopy of the rupturing process of thin blood vessels to clarify the mechanism of bruising caused by blunt impact: an animal study

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Ferroptosis in radiation-induced brain injury: roles and clinical implications

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Tissue engineering strategies hold promise for the repair of articular cartilage injury

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A personalized clinical assessment: multi-sensor approach for understanding musculoskeletal health in the frail population

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How smartphones are changing the face of mobile and participatory healthcare: an overview, with example from eCAALYX

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Automated system for lung nodules classification based on wavelet feature descriptor and support vector machine

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Organ-on-a-chip: recent breakthroughs and future prospects

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Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model

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Modern Trends and Applications of Intelligent Methods in Biomedical Signal and Image Processing

Jan kubicek.

1 Department of Cybernetics and Biomedical Engineering, VŠB-Technical University of Ostrava, 17. listopadu 15, 70 833 Ostrava-Poruba, Czech Republic; [email protected]

Marek Penhaker

Ondrej krejcar.

2 Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Rokitanskeho 62, 50 003 Hradec Kralove, Czech Republic; [email protected]

Ali Selamat

3 Malaysia Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, Kuala Lumpur 54100, Malaysia; ym.mtu@tamalesa

There are various modern systems for the measurement and consequent acquisition of valuable patient’s records in the form of medical signals and images, which are supposed to be processed to provide significant information about the state of biological tissues. Therefore, in the modern age of digital technologies in the healthcare sector, we are surrounded with big data of clinical patients containing valuable information about actual state and future prediction, which needs to be extracted from biomedical signals and images. Thus, the current trends in this area of biomedical engineering are focused on the design and development of intelligent methods, containing elements of artificial intelligence, allowing the extraction, classification, and optimization of clinical information from various medical data. Such methods significantly facilitate the workload of medical staff, and at the same time, serve to provide effective feedback for clinicians as decision-making systems. Particularly, such intelligent methods are employed for data smoothing, feature extraction, segmentation, identification, and classification. Such tasks require participation clinical specialists, mathematicians, and information experts, who together develop the intelligent systems which can be employed in the health care sector as a support to medical staff.

The Special Issue “Modern Trends and Applications of Intelligent Methods in Biomedical Signal and Image Processing” is aimed at the new proposals and intelligent solutions that constitute the state of the art of the intelligent methods for biomedical data processing from selected areas of signal and image processing. This Special Issue brings together research works from various fields that are related to the area of biomedical engineering to describe the recent trends and advances in this area.

For this Special Issue, we received 20 contributions in total. After judging scientific impact and novelty, we selected the 10 contributions included herein. The published papers include nine research papers and one review.

We appreciate all the authors who have decided to publish their research in this Special Issue. Thanks to these authors, we could provide the state of the art of the recent research of intelligent techniques in applications of biomedical engineering. Below, we summarize the individual contributions published in this Special Issue.

In recent years, image-guided navigation systems (IGNS) have become an important tool for various surgical operations. In the preparations for planning a surgical path, verifying the location of a lesion, etc., it is an essential tool; in operations such as bronchoscopy, which is the procedure for the inspection and retrieval of diagnostic samples for lung-related surgeries, it is even more so. In Reference [ 1 ], the authors propose a novel registration method to match real bronchoscopy images with virtual bronchoscope images from a 3D bronchial tree model built using computed tomography (CT) image stacks in order to obtain the current 3D position of the bronchoscope in the airways. This method represents a combination of a novel position-tracking method using the current frames from the bronchoscope and the verification of the position of the real bronchoscope image against an image extracted from the 3D model using an adaptive-network-based fuzzy inference system (ANFIS)-based image matching method. Experimental results show that the proposed method performs better than the other methods used in the comparison.

Heart problems are responsible for the majority of deaths worldwide. The use of intelligent techniques to assist in the identification of existing patterns in these diseases can facilitate treatments and decision making in the field of medicine. In Reference [ 2 ], authors extract knowledge from a dataset based on heart noise behaviors in order to determine whether heart murmur predilection exists or not in the analyzed patients. A heart murmur can be pathological due to defects in the heart, so the use of an evolving hybrid technique can assist in detecting this comorbidity team, and at the same time, extract knowledge through fuzzy linguistic rules, facilitating the understanding of the nature of the evaluated data. Heart disease detection tests were performed to compare the proposed hybrid model’s performance with the state of the art for the subject. The results obtained showed 90.75% accuracy, in addition to great assertiveness in detecting heart murmurs.

In recent years, research has focused on generating mechanisms to assess the levels of subjects’ cognitive workload when performing various activities that demand high concentration levels, such as driving a vehicle. These mechanisms have involved the implementation of several tools for analyzing the cognitive workload, and electroencephalographic (EEG) signals have been most frequently used due to their high precision. In Reference [ 3 ], the authors present a new feature selection model that is focused on pattern recognition using information from EEG signals based on machine learning techniques called GALoRIS (Genetic algorithms and logistic regression). This method utilizes genetic algorithms and logistic regression with the aim to make a new fitness function that identifies and selects the critical EEG features that contribute to recognizing high and low cognitive workloads and structures.

In the area of medical data processing, wavelet transformation is frequently used for various applications, including data decomposition, smoothing, feature extraction, and image segmentation. One of the essential steps is the selection of suitable wavelet settings, including the mother wavelet and the decomposition level. Since wavelet transformation offers plenty of settings, it is usually a complicated task to select the most appropriate settings. In Reference [ 4 ], the authors propose a novel scheme that is able to simultaneously evaluate the effectivity of selected wavelet settings via the form of the spatial 2D maps. The authors also study the effect of dynamical noise influence within wavelet smoothing by using the volumetric mapping. The authors report of the testing of these techniques on both 1D EMG signals and 2D medical images from various imaging modalities.

In Reference [ 5 ], the authors present a novel approach intended for the periodical testing of the function evaluation of fetal heart rate monitors. The proposed simulator was designed to be compliant with the standard requirements for the accurate assessment and measurement of medical devices. The accuracy of the simulated signals was evaluated, and it was shown to be stable and reliable. The generated frequencies showed an error of about 0.5% with respect to the nominal one, while the accuracy of the test equipment was within ±3% of the test signal set frequency. The proposed device ensures easy and fast testing of fetal heart rate monitors. Hence, it provides an effective way to evaluate and test the correlation of commercial devices.

The invasive method of fetal electrocardiogram (fECG) monitoring is widely used, with electrodes directly attached to the fetal scalp. There are potential risks, such as infection, and thus it is usually carried out during labor when required. Recent advances in electronics and technologies have enabled fECG monitoring from the early stages of pregnancy through fECG extraction from the combined fetal/maternal ECG (f/mECG) signal recorded noninvasively in the abdominal area of the mother. In Reference [ 6 ], the authors propose an end-to-end deep learning model which is aimed at the detection of fetal QRS complexes. The proposed model also contains the residual network (resNet) architecture. This net is able to adopt a novel 1D octave convolution (OctConv), which is focused on multiple temporal frequency features. This fact predetermines the memory reduction and computational demands.

Time-of-flight (ToF) sensors are the source of various errors, including the multicamera interference artifact caused by the parallel scanning mode of the sensors. In Reference [ 7 ], the authors present a novel importance map, which is based on the median filtration algorithm with the aim of suppressing interference artifacts. The proposed method is based on the processing of multiple depth frames. This method uses the interference region and application of the interpolation. Performance of the algorithm was evaluated on a dataset consisting of the real-world objects with different textures and morphologies against popular filtering methods based on neural networks and statistics.

In Reference [ 8 ], the authors present a proposal of using electrodes for the continual measurement of the glucose concentration for the purpose of specifying further hemodynamic parameters. The proposal includes the design of the electronic measuring system, the construction of the electrodes themselves, and the functionality of the entire system, verified experimentally using various electrode materials. The proposed circuit works based on the microammeter measuring the size of the flowing electric current, and the electrochemical measurement method is used for specifying the glucose concentration. The electrode system is comprised of two electrodes embedded in a silicon tube. The authors present testing indicating that even if the Ag/AgCl electrode appears to be the most suitable, showing high stability, gold-plated electrodes showed stability throughout the measurement, similarly to Ag/AgCl electrodes, but did not achieve the same qualities in sensitivity and readability of the measured results.

The next study [ 9 ] proposes a novel multinetwork intelligent architecture, containing a multiscale convolutional neural network (MSCNN) with a fully connected graph convolution network (GCN), named MSCNN-GCN, for the detection of musculoskeletal abnormalities via musculoskeletal radiographs. The effectiveness of this model was verified by comparing the performance of radiologists and three popular CNN models (DenseNet169, CapsNet, and MSCNN) with three evaluation metrics (accuracy, F1 score, and kappa score) using the MURA dataset (a large dataset of bone X-rays).

The intake of microbially contaminated food poses severe health issues due to outbreaks of serious foodborne diseases. Therefore, there is a need for the precise detection and identification of pathogenic microbes and toxins in food to prevent these concerns. Thus, understanding the concept of biosensing has enabled researchers to develop nano-biosensors with different nanomaterials and composites to improve the sensitivity as well as the specificity of pathogen detection. In Reference [ 10 ], the authors publish a review that summarizes various sensing methods used in foodborne pathogen detection; in addition, the authors focus on the design, technical principles, and advances in sensing systems.

Author Contributions

Conceptualization, J.K.; methodology, M.P.; validation, O.K.; formal analysis, A.S. All authors have read and agreed to the published version of the manuscript.

The work and the contributions were supported by the project SV450994 Biomedical Engineering Systems XV’. This study was supported by the research project The Czech Science Foundation (TACR) ETA No. TL01000302 Medical Devices development as an effective investment for public and private entities.

Conflicts of Interest

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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• Published: 01 February 2023

An engineering makeover of biomedical research

• Vasilis Ntziachristos 1 , 2 ,
• Stephen R. Quake 3 , 4 &
• Matthias Tschöp 5 , 6  

Nature Reviews Bioengineering volume  1 ,  pages 154–155 ( 2023 ) Cite this article

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The clinical translation of research findings into improvements in human health can take decades. Engineers perform biomedical research with a solution-oriented mind-set, generating tools and concepts that enable the transformation of knowledge into medical solutions. In this light, bioengineering becomes the driving force for accelerating clinical translation and introducing new concepts in validation, prevention, diagnostics and precision therapy.

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Acknowledgements

We acknowledge the advice of T. Schwarz-Romond in developing this article; several EU and German research programs that have funded research to advance bioengineering concepts, including the European Research Council (ERC), the Horizon 2020 program, the German Research Foundation (DFG) and the German Federal Ministry of Education and Research (BMBF); and the support of bioengineering concepts from the presidents of the Technical University of Munich, T. Hofmann and W. Herrmann, and O. Wiestler of the Helmholtz Association.

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Vasilis Ntziachristos

Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Munich, Germany

Department of Bioengineering and Applied Physics, Stanford University, Stanford, CA, USA

Stephen R. Quake

Chan Zuckerberg Biohub, San Francisco, CA, USA

Helmholtz Munich, Neuherberg, Germany

Matthias Tschöp

School of Medicine, Technical University of Munich, Munich, Germany

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V.N. is a founder and shareholder of the medical technology companies iThera Medical GmbH, sThesis GmbH, I3 Inc. and Spear UG.

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Ntziachristos, V., Quake, S.R. & Tschöp, M. An engineering makeover of biomedical research. Nat Rev Bioeng 1 , 154–155 (2023). https://doi.org/10.1038/s44222-022-00015-3

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• Published: 30 January 2019

BMC Biomedical Engineering: a home for all biomedical engineering research

• Alexandros Houssein   ORCID: orcid.org/0000-0001-6993-4301 1 ,
• Alan Kawarai Lefor 2 ,
• Antonio Veloso 3 ,
• Zhi Yang 4 ,
• Jong Chul Ye 5 ,
• Dimitrios I. Zeugolis 6 &
• Sang Yup Lee 7  

BMC Biomedical Engineering volume  1 , Article number:  1 ( 2019 ) Cite this article

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This editorial accompanies the launch of BMC Biomedical Engineering , a new open access, peer-reviewed journal within the BMC series, which seeks to publish articles on all aspects of biomedical engineering. As one of the first engineering journals within the BMC series portfolio, it will support and complement existing biomedical communities, but at the same time, it will provide an open access home for engineering research. By publishing original research, methodology, database, software and review articles, BMC Biomedical Engineering will disseminate quality research, with a focus on studies that further the understanding of human disease and that contribute towards the improvement of human health.

Introduction

Biomedical engineering is a multidisciplinary field that integrates principles from engineering, physical sciences, mathematics and informatics for the study of biology and medicine, with the ultimate goal of improving human health and quality of life.

Biomedical engineering is not a new concept; however, it was not until the 1900s when rapid technological advancements in the chemical, physical and life sciences influenced breakthroughs in the prevention, diagnosis and treatment of disease. The invention of the electrocardiograph, the concept of x-ray imaging, the electron microscope, the mechanical heart valve and human genome sequencing, are just a few examples of technological innovations that revolutionised science and medicine and changed the approach to human healthcare. Current biomedical engineering technologies are a growing part of clinical decision making, which can now be influenced from multiscale observations, ranging from the nano to the macro-scale.

Today, the need for innovation in health technologies is ever more prominent. The annual global healthcare spending has seen continued growth and is projected to reach a staggering $8.7 trillion by 2020 [ 1 ]. Global health challenges are becoming more complex, wide spread and difficult to control. Resources are scarce and with a growing population, our society has a need for affordable, portable and sustainable solutions. The World Health Organisation has pledged to make a billion lives healthier by 2023 [ 2 ], a goal that will require widespread commitment by governments, funding agencies, researchers and clinicians. Biomedical engineers will be at the heart of this movement and face a responsibility for continuous innovation. Biomedical engineering research is expected to create health technologies that will drastically improve the prevention, diagnosis and treatment of disease, as well as patient rehabilitation. As an example, the NIH 2016–2020 strategic plan focuses on point of care and precision medicine technologies including genetic engineering, microfluidics, nanomedicine, imaging, digital/mobile-Health and big data [ 3 ].

BMC Biomedical Engineering will strive to complement these efforts and provide an open access venue for the dissemination of all biomedical engineering research. As part of the BMC series, a portfolio of journals serving communities across all sciences, the Journal will act as a resource for a wide range of disciplines. It aims to support scientists, engineers and clinicians by making their research openly and permanently available, irrespective of their location or affiliation.

Aims and scope

BMC Biomedical Engineering considers articles on all aspects of biomedical engineering, including fundamental, translational and clinical research. It combines tools and methods from biology and medicine with mathematics, physical sciences and engineering towards the understanding of human biology and disease and the improvement of human health. The Journal will publish a range of article types, including research, methodology, software, database and review articles.

As part of the BMC series, a collection of open access, peer-reviewed and community focused journals covering all areas of science, editorial decisions will not be made on the basis of the interest of a study or its likely impact. Studies must be scientifically valid. For research articles this includes a scientifically sound research question, the use of suitable methods and analysis, and following community-agreed standards relevant to the research field.

BMC Biomedical Engineering aims to publish work that undergoes a thorough peer review process by appropriate peer-reviewers and is deemed to be a coherent and valid addition to the scientific knowledge. It aims to provide an open access venue which allows for immediate and effective dissemination of research and enables our readers to explore and understand the latest developments, trends and practices in biomedical engineering. We believe that open access and the Creative Commons Attribution License [ 4 ] are essential to this, allowing universal and free access to all articles published in the Journal and allowing them to be read and the data re-used without restrictions. BMC Biomedical Engineering will work closely with the rest of the journals in the BMC series portfolio [ 5 ] to help authors find the right home for their research. We will highlight selected journal content through various promotional channels to ensure the research reaches its target audience and receives the attention it deserves.

Editorial sections

Many new technologies that have revolutionised biomedical engineering require the coalition of previously independent communities. 3D bioprinting of tissues and organs brings together methods from cell biology, biomaterials, nanotechnology and engineering and is being used for the transplantation of tissues, including skin, bone, muscle, soft tissue, cartilage and others [ 6 , 7 ]. The concept of tissue and disease modelling is being driven towards drug discovery and toxicology studies, aiming to increase the yield of drug testing by tackling limitations of current cell and animal models [ 8 ].

New approaches in natural and synthetic biomaterials have redefined bioelectronics. Silk fibroins and other unconventional interfaces can form flexible electronics and challenge the use of silicon-based technologies. For biomedical applications, these new approaches present advantages not only due to their biocompatibility and low cost, but also for their electromechanical and optical virtues [ 9 ]. Implantable probes are being redesigned so that they facilitate long term stability and high resolution, without perturbing the biological system or creating an immune response. Such technologies are now able to facilitate recordings of single neurons in vivo, in a chronically stable manner, with applications to the restoration of vision and retinal prosthetics [ 10 ].

For many years biomedical imaging has been connecting microscopic discoveries with macroscopic observations. Photoacoustic tomography (PAT) is now able to image large spatial scales, from organelles to small animals, at very high speeds [ 11 ]. In fact, single-shot real-time imaging can operate at 10 trillion frames per second and is finding applications in breast cancer diagnosis [ 12 , 13 ].

In the field of medical robotics, new approaches combine machine learning and artificial intelligence to strengthen the clinician’s decision making. Others are leveraging augmented reality (AR) to facilitate better immersion and more natural surgical workflows for computer assisted orthopaedic surgery [ 14 ].

BMC Biomedical Engineering celebrates the interdisciplinary nature of the field. In order to navigate the wide range of biomedical engineering research, the Journal is structured in six editorial sections.

Biomaterials, nanomedicine and tissue engineering

Medical technologies, robotics and rehabilitation engineering

Biosensors and bioelectronics

Computational and systems biology

Biomechanics

Biomedical Imaging

We are delighted to welcome our founding Section Editors along with a growing international group of Editorial board Members [ 15 , 16 ]. The Journal is supported by an expert Editorial Advisory group of senior engineers and scientists, which is chaired by Distinguished Professor Sang Yup Lee. Together with the in-house Editor, this group will provide academic leadership and expertise and will work together to transverse into multiple clinical and engineering disciplines. The Editorial Board will keep growing and developing to reflect and adapt to the nature of this diverse community.

Biomaterials, nanomedicine and tissue engineering section

This section primarily focuses on the development of biofunctional tissue substitutes, which possess the highest level of biomimicry, through recapitulation of nature’s innate sophistication and thorough processes. It considers research, methods, clinical trials, leading opinion and review articles on the development, characterisation and application of nano- and micro- biofunctional biomaterials, cell-assembled tissue substitutes, diagnostic tools, microfluidic devices and drug/gene discovery and delivery methods. Manuscripts focusing on permanently differentiated, engineered and stem cell biology and application are welcome. This section will place a substantial focus on clinical translation and technologies that advance the current status-quo. As such, articles that enhance the scalability and robustness of tissue engineering methodologies, or that enable new and improved industrial or clinical applications of biomedical engineering discoveries, tools and technologies are strongly encouraged.

Medical technologies, robotics and rehabilitation engineering section

This section seeks to represent research in engineering that encompasses a wide range of interests across medical specialties, including orthopaedic, cardiovascular, musculoskeletal, craniofacial, neurological, urologic and other medical technologies. It will consider research on medical robotics, computer assisted technologies, medical devices, e/m-health and other medical instrumentation. It aims to improve the prevention, diagnosis, intervention and treatment of injury or disease and it welcomes articles that represent new approaches to engineering that may be useful in the care of patients. Technical and practical aspects of rehabilitation engineering, from concept to clinic and papers on improving the quality of life of patients with a disability are encouraged. The section also seeks to represent clinically important research that is based on new and emerging technologies. This could include clinical studies of new approaches to robotic-assisted surgery, clinical studies of new devices, or other studies that are close to patient care or rehabilitation.

Biosensors and bioelectronics section

This section considers articles on the theory, design, development and application on all aspects of biosensing and bioelectronics technologies. The section will consider approaches that combine biology and medicine with sensing and circuits and systems technologies on a wide variety of subjects, including lab-on-chips, microfluidic devices, biosensor interfaces, DNA chips and bioinstrumentation. It also considers articles on the development of computational algorithms (such as deep learning, reinforcement learning, etc.) that interpret the acquired signals, hardware acceleration and implementation of the algorithms, brain-inspired or brain-like computational schemes, and bioelectronics technologies that can have a wide impact in the research and clinical community. Articles on implantable and wearable electronics, low-power, wireless and miniaturised imaging systems, organic semiconductors, smart sensors and neuromorphic circuits and systems are strongly encouraged.

Computational and systems biology section

Computational, integrative and systemic approaches are at the heart of biomedical engineering. This section considers papers on all aspects of mathematical, computational, systems and synthetic biology that result in the improvement of patient health. Integrative and multi-scale approaches, in the network and mechanism-based definition of injury and disease, or its prevention, diagnosis and treatment are welcome. Papers on high precision, interactive and personalised medicine, on digital/mobile health, on complex/big data analytics and machine learning, or on systemic and informatics approaches in a healthcare or clinical setting are encouraged.

Biomechanics section

This section represents the interdisciplinary field of biomechanics and investigates the relationship of structure with function in biological systems from the micro- to the macro- world. It considers papers on all aspects of analytical and applied biomechanics at all scales of observation, that improve the diagnosis, therapy and rehabilitation of patients or that advance their kinetic performance. The topics of interest range from mechanobiology and cell biomechanics to clinical biomechanics, orthopaedic biomechanics and human kinetics. Articles on the mechanics and wear of bones and joints, artificial prostheses, body-device interaction, musculoskeletal modelling biomechanics and solid/fluid computational approaches are strongly encouraged.

Biomedical imaging section

Biomedical imaging has been connecting microscopic discoveries with macroscopic observations for the diagnosis and treatment of disease and has seen considerable advances in recent years. This section will consider articles on all biomedical imaging modalities including medical imaging (MRI, CT, PET, ultrasound, x-ray, EEG/MEG), bio-imaging (microscopy, optical imaging) and neuroimaging across all scales of observation. Its primary focus will be to foster integrative approaches that combine techniques in biology, medicine, mathematics, computation, hardware development and image processing. Articles on new methodologies or on technical perspectives involving novel imaging concepts and reconstruction methods, machine learning, sparse sampling and statistical analysis tool development are encouraged.

The motivation for the launch of BMC Biomedical Engineering is to create an authoritative, unbiased and community-focused open access journal. We are committed to working together with our authors, editors and reviewers to provide an inclusive platform for the publication of high-quality manuscripts that span all aspects of biomedical engineering research. We welcome articles from all over the world and we will devote our efforts to ensure a robust and fair peer-review process for all. We believe in continuous improvement and we encourage the community to get in touch with us to provide ideas and feedback on how to improve the Journal and serve the community better.

We hope you will find the first group of articles an interesting and valuable read, and we look forward to working with you all to disseminate research into the exciting field of biomedical engineering.

Abbreviations

Augmented Reality

Computed Tomography

Electroencephalogram

Magnetoencephalography

Photoacoustic Tomography

Positron Emission Tomography

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Springer Nature, 4 Crinan Street, London, N1 9XW, UK

Alexandros Houssein

Department of Surgery, Jichi Medical University, Shimotsuke, Tochigi, Japan

Alan Kawarai Lefor

Laboratory of Biomechanics and Functional Morphology, Faculty of Human Kinetics, Lisbon, Portugal

Antonio Veloso

Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA

Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea

Jong Chul Ye

Regenerative, Modular and Developmental Engineering Laboratory (REMODEL), Biomedical Sciences Building, National University of Ireland Galway (NUI Galway), Galway, Ireland

Dimitrios I. Zeugolis

Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea

Sang Yup Lee

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AH wrote the introduction, aims and scope and conclusion. AH, AKL, AV, ZY, JCY, DIZ and SYL wrote the editorial sections. All authors read and approved the final version of the manuscript.

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Houssein, A., Lefor, A.K., Veloso, A. et al. BMC Biomedical Engineering: a home for all biomedical engineering research. BMC biomed eng 1 , 1 (2019). https://doi.org/10.1186/s42490-019-0004-1

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DOI : https://doi.org/10.1186/s42490-019-0004-1

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Biomedical Engineering

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Close the gap between engineering and medicine. This program integrates principles of engineering with the biological and medical sciences to develop better ways to diagnose illnesses, treat health problems and enhance health. It is is designed to equip students with the skills and knowledge necessary to develop innovative technologies and solutions for the healthcare industry, improving patient care and advancing medical research.

In our Biomedical Engineering program, you'll develop knowledge in engineering fundamentals, biomechanics, physics, physiology and design. Hands-on labs will give you experience modelling, prototyping and testing biomedical systems. By graduation, you'll be ready to design and build tomorrow's innovative healthcare technologies - from bionic limbs and implantable biomaterials to laser-guided surgical devices and wearable tech.

Courses in Biomedical Engineering

In your first year, you'll take foundational courses combining biology with applied sciences and engineering. You will begin to think about how to best approach solving health-related problems and gain the science and math skills to develop tools for medical diagnosis, treatment, and prevention. Utilizing engineering solutions, you will design innovative technologies – from new diabetic monitoring and cancer-imaging systems to the design of rehabilitation equipment.

Sample first-year courses

This is a sample schedule. Courses are subject to change.

Fall Term (September to December)	Winter Term (January to April)
- Communications in Biomedical Engineering - Digital Computation  - Introduction to Biomedical Design - Physics 1: Statics - Calculus 1 - Elementary Engineering Mathematics	- Seminar - Data Structures and Algorithms - Human Factors in the Design of Biomedical and Health Systems - Chemistry Principles - Calculus 2 - Matrices and Linear Systems One approved elective

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For information about courses past your first year, check out the Undergraduate Academic Calendar.

Customize your degree with options and specializations

Options are a way to provide you with a path to expand your degree and get a secondary emphasis in another subject or area. They are available to any student within the Faculty of Engineering (excluding Architecture). Students should decide if they are interested in taking options as they enter second year. Some available options are:

• Artificial Intelligence
• Biomechanics
• Computer Engineering
• Entrepreneurship
• Environmental Engineering
• Life Sciences
• Management Sciences
• Mechatronics
• Physical Sciences
• Quantum Engineering
• Software Engineering

Specializations

A specialization is recognition of selected elective courses within your degree. Specialization offerings are unique to your engineering program and are listed on your diploma. Specializations that are available to Biomedical Engineering students include:

• Biomaterials & Tissues Specialization
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You’ll have an unrivalled opportunity to gain paid work experience before you even graduate. We’ll help you navigate job applications, résumés, and interviews; you’ll have the added benefit of trying out different roles and/or industries to find the one that fits you while building your work experience and reinforcing your in-class learning out in the real world. It all adds up to a competitive advantage after graduation.

Starting in first year, you'll normally alternate between school and work every four months, integrating your classroom learning with real-world experience. You can return to the same employer for a couple of work terms to gain greater knowledge and responsibility or work for different employers to get a broad range of experience.

Year	September to December (Fall)	January to April (Winter)	May to August (Spring)
First	Study	Study
Second	Study		Study
Third		Study
Fourth	Study
Fifth	Study	Study	-

Your first work term will be at the end of first year.  Learn more about co-op .

Example co-op positions for Biomedical Engineering students

• Junior biomedical engineer
• Medical device software developer
• Robotics and embedded sensor research assistant
• Signal processing algorithm developer
• Bioengineering research assistant
• Medical device designer

2022 Engineering co-op student of the year

Jennifer tsai, biomedical engineering student.

As a computational neuroscience researcher at the Cembrowski Lab , Jennifer mastered experimental methods, microscope processes and computational modelling. Her accomplishments included:

• Discovering a new, separate sub-division of the brain region involved in episodic memory.
• Developing visualizations and presentations, coding with bioinformatic packages and studying data science principles.
• Continuing her research outside of work through lectures, networking and reading.
• Awarded the 2022 Experiential & Work-Integrated Learning Ontario (EWO) Co-op Student of the Year Award.

Example careers for Biomedical Engineering graduates

• Brain-computer interface designer
• Clinical application developer
• Medical device product designer
• Biomedical data analyst
• Systems integration engineer
• Product development specialist
• Clinical application analyst

Capstone design projects in Biomedical Engineering

Capstone Design is the culmination of the engineering undergraduate student experience, creating a blueprint for innovation in engineering design.

Supported by numerous awards, Capstone Design provides Waterloo Engineering students with the unique opportunity to conceptualize and design a project related to their chosen discipline.

A requirement for completion of their degrees, Capstone Design challenges students teams to push their own boundaries, and apply the knowledge and skills learned in the classroom and on co-op work terms.  It reinforces the concepts of teamwork, project management, research and development. 

For a full list of previous capstone design projects, see our Capstone Design website .

SATURN (Capstone 2024)

Sam Burke, Kate Harvey, Amanda Johnson, Ceili Minten

Despite impressive advances in the control of modern myoelectric prosthetic devices, the current lack of sensory feedback remains a challenge, often cited as the primary cause of user dissatisfaction and device abandonment. The Sensory Awareness of Touch Upper-limb Radial Network (SATURN) aims to improve users' ability to interact with objects in their surrounding environment by sensing force at the fingertips and delivering pressure information to the user's phantom hand map via inflatable air bladders placed inside the socket. SATURN incorporates customized design elements, and is compatible with a range of prosthetic devices.

CACHA Clinic Manager (Capstone 2024)

Ethan Alvizo, Valerie Liu, Hannah Tario, Duru Uluk

Canada Africa Community Health Alliance (CACHA), our Capstone partner, is a nonprofit organization that sends volunteer doctors and pharmacists to provide healthcare through clinics in rural communities of Tanzanian and Uganda. Their largest concerns are patient identification and communication with low medical illiteracy patients resulting in drug non-adherence. The CACHA Clinic Manager (CCM) is a full system solution with three components: (1) a biometrics-integrated patient identification system, (2) secure medical records keeping, (3) culturally sensitive translated labeling. This solution aims to improve the efficiency and effectiveness of CACHA clinics operations, and ultimately save lives.

The Sedra Student Design Centre consists of over 20,000 square feet of space dedicated to design teams and student projects. There are more than two dozen design teams , all of which are student-led, and many of which represent Waterloo internationally.

Some examples include:

BIOMOD Team

The University of Waterloo BIOMOD team aims to solve real-world problems using biomolecular technology, from molecular robots to nanoscale therapeutics. Team members use software-aided design, wet-lab experiments, and engineering design to take great strides in health technology.

MedTechResolve

MedTechResolve aims to automate the process of diagnosis, treatment, and prognosis, both inside and outside of the emergency room (ER). The team participates in the John Hopkins Healthcare Design Competition annually.

Alternative Protein Project

The Waterloo Alternative Protein Project is the first chapter of the Good Food Institute’s Alt. Protein Project in Canada. The project aims to create a sustainable and secure food system through research, entrepreneurship, and innovation.

Biomedical Engineering alumni

Zoey (class of 2024) was named in The Logic publication as a rising star for her work solving challenges and championing initiatives that advance inclusion in engineering. 

Zoey’s time at Waterloo Engineering reflects her commitment to fostering a more inclusive engineering ecosystem. As the vice president of advocacy for the Canadian Federation of Engineering Students and co-chair of the 2023 Conference on Diversity in Engineering, she worked with faculty to launch the university’s first mental wellness survey and to improve diversity and inclusion in the university’s engineering school. She was awarded the Pearl Sullivan Emerging Global Leaders Award for her efforts to advance representation in engineering.   

Zoey has been hired by Nvidia as a technical marketing engineer focused on advancing their machine learning tools. Zoey previously spent two co-op terms working with the Silicon Valley semiconductor giant, where she helped build the company’s first hands-on lab for medical imaging.  

Frequently Asked Questions (FAQ)

What’s the difference between biomedical sciences and biomedical engineering.

Biomedical Sciences  is the study of life from a medical perspective. You’ll learn about the body, disease, healing processes, genetics, physiology – the knowledge of how the body works and responds to stimuli.

Biomedical Engineering is the application of that scientific knowledge to develop medical technology. For instance, a surgeon needs to understand biomedical science to operate on a patient – and might use laser-guided surgical devices, artificial internal organs, or replacements for body parts developed by a biomedical engineer. The two work in tandem, but their approach is different. Biomedical Engineering has more mandatory courses than Biomedical Sciences.

Is Biomedical Engineering a path to become a doctor?

In theory, yes, although it’s not recommended because it can be difficult to take the courses required to apply to medical school. The decision is whether you want to be a doctor or an engineer. Biomedical Sciences is a good  route to becoming a doctor or other health care professional . Biomedical Engineering leads to becoming an engineer, usually in the medical field and biotechnology field.

Interested in Biomedical Engineering?