Technological Offer

Biomedical signals are recorded and analyzed in order to collect information about the patient's health status or to know the activity and functioning of an organ.

Sometimes the methodology for analyzing these signals is widely documented and constitutes almost a standard, such as the determination of the heart rate from the electrocardiogram.

However, if you want to obtain additional information than usual or work with unconventional signals, new techniques are necessary for the characterization of the signals or for the elimination of possible interferences.

In our research group, special emphasis has been placed on the processing of bioelectric signals captured on the body surface originating from smooth muscle such as uterine, intestinal, gastric, etc0;. origin of skeletal striated muscle such as pelvic floor, swallowing, cadiac, respiratory, or extremities; and of cerebral origin.

The group's capabilities cover both the pre-processing of bioelectrical signals to improve signal quality and eliminate interference; such as the subsequent characterization of the signals using parameters with physiological interpretation that help to assess the electrophysiological state of the organ under study in different aspects.

Key People:

• Garcia Casado, Francisco Javier
• Martínez De Juan, José Luís
• Prats Boluda, Gema
• Ye, Yiyao

Responsible:

• Garcia Casado, Francisco Javier

1. Medical diagnosis : Biomedical signal processing is used to analyze data from electrocardiograms (ECG), electroencephalograms (EEG), electromyograms (EMG) of different organs and muscles and other clinical records. These techniques help detect abnormal patterns, identify diseases, and evaluate patients' health .
2. Telemedicine : Biomedical signal processing enables remote transmission and analysis of medical data. This is especially useful in rural areas or when real-time access to specialists is needed .
3. Continuous monitoring : Biomedical signals can be processed to constantly monitor patients' health. For example, wearable devices (such as smartwatches) use signal processing to measure heart rate, blood pressure, and other parameters .
4. Automatic diagnostic systems : Signal processing is applied in systems that automate the diagnosis of diseases. These systems can detect specific patterns in biomedical signals and alert doctors to potential problems .
5. Biomedical research : Signal processing is used in research studies to analyze data from experiments and clinical trials. This helps to better understand physiological mechanisms and develop new therapies . .

1. Precision and early detection : These techniques allow subtle patterns in signals to be detected, making it easier to identify diseases or abnormalities early.
2. Personalization of treatment : By analyzing a patient's biomedical signals, doctors can tailor treatments on an individualized basis. This improves effectiveness and reduces side effects.
3. Continuous monitoring : Biomedical signals can be monitored continuously, allowing for constant health assessment. This is especially useful in chronic patients or during surgical procedures.
4. Automation and efficiency : Signal processing algorithms can automate tasks such as detecting anomalous patterns or segmenting medical signals. This saves time and resources.
5. Research and development : The analysis of biomedical signals is fundamental for research in areas such as neuroscience, genomics and biomechanics. It helps to better understand biological processes and develop new therapies.

Improving the quality of weak signals and low signal-to-noise ratio, signal-to-interference.

Obtaining more robust biomedical signal characteristic parameters.

Obtaining additional and covert information in biomedical signals.

Added value in biomedical devices.

Direct impact on clinical practice

The research group has extensive experience in the processing of biomedical signals in a multitude of techniques, both linear in the temporal, spectral, time-frequency and non-linear domains; all this both for signal characterization and for the elimination of unwanted components.

The scope of application is very broad, covering signals of cardiac, uterine, swallowing, intestinal, cerebral, respiratory muscle, balance, etc. origin.

We have worked on both basic and applied research projects, in projects in collaboration with multiple clinical entities and international research groups. Likewise, there is also extensive experience in research contracts with companies in the biomedical and clinical field.

Our projects highlight the use of advanced technology to address relevant clinical problems, providing innovative tools to improve medical care and reduce associated costs.

In the past, “label free” biosensors have been mainly used in the pharmaceutical industry, the main drawback being their high costs and the need for expert user personnel to manage and interpret the data. However, the new challenges facing research mean that companies and R&D centers are demanding more sensitive “label free” biosensors with real-time analysis capacity, at a reduced cost and with easy handling and interpretation of information

In this area, researchers from CI2B are working on the development of new piezoelectric biosensors, based on the use of quartz crystal microbalances (QCM). The microgravimetric technique has allowed the implementation of a quantitative, direct and real-time detection method of biomolecular interactions such as antigen-antibody, detection of pathogens, cell adhesion, adsorption and hybridization of oligonucleotides and interactions of complementary DNA sequences, characterization of the absorption of proteins, and detection of bacteria and viruses, among others.

Recently, this team has made important advances both in characterization techniques and in the sensor support technology and associated fluidics, which can allow us to address the pending challenges for their application to the development of biochemical sensors, and in particular piezoelectric biosensors. “label free”.

The group led by Professor Antonio Arnau has recently managed to develop a new generation of very high frequency QCM sensor arrays, with sensitivities much higher than those currently existing, which have allowed an increase of more than 1000 times (3 orders of magnitude). the detection limit of these sensors in relation to conventional microbalances, reaching, and even exceeding, the limits of current “label free” optical systems. All of this, together with the group's advances in the characterization techniques of these sensors, has provided the basis for a new generation of microbalances called “High Resolution QCM”.

Key people:

•  Antonio Arnau Vives
• Juan José Manclús Ciscar
• Román Fernánez Díaz
• José Vicente García Narbón
• María Isabel Rocha Gaso
• Augusto Juste Dolz
• Yolanda Jiménez Jiménez

Responsible:

• Yolanda Jimenéz Jiménez

• Medical diagnostic:

  - Fast and accurate detection of pathogens such as bacteria and viruses.

  - Diagnosis and monitoring of chronic diseases.

  - Analysis of antigen-antibody reactions for the diagnosis of autoimmune diseases.

  Biotechnology industry:

  - Characterization of protein absorption.

  - DNA and RNA interactions with complementary sequences.

  - Cell adhesion and oligonucleotide hybridization studies.

  Pharmaceutical industry:

  - Evaluation of biomolecular interactions for drug development.

  - Quality control in biotechnological and pharmaceutical products.

  - Activity tests of pharmaceutical compounds.

  Food industry

  - Detection of pesticides and antibiotics in Food.

  - Detection of adulterant substances in Foods.

  Agricultural industry:

  - Detection of pathogens and diseases in livestock to prevent outbreaks

  Environmental industry:

  - Detection of pathogenic microorganisms in water and soil.

Direct Detection: reduces costs and sample preparation time.

Real-time analysis: Provides instant data for rapid diagnosis and immediate decision-making.

High Sensitivity and Resolution.

Sensor regeneration capacity: They can be regenerated without significant loss of sensitivity, allowing their reuse and reducing costs.

Versatility in applications: medical diagnosis, biotechnology, pharmaceutical industry, food industry, environment, scientific research

Cost Reduction: the development of the sensor has a cost and also has regeneration capacity.

Ease of use: reduces dependence on expert data interpretation personnel.

High precision and efficiency: provides fast diagnoses, crucial in urgent medical situations

In 2009, the group created the company Advanced Wave Sensors (AWSensors), a spin-off of the UPV, to transfer the results of its research and which is specialized in the design, development, production and marketing of high-precision detection instrumentation based on quartz crystal microbalance (QCM). The company's QCMD instruments, sensors and accessories are of interest in research fields in which extremely high precision is required with measurement at the frontiers of detection (wear, corrosion, swelling of new materials, study of DNA, infectious diseases , clinical diagnosis in health...).

The group has participated in various projects at regional, national and European level for the development of biosensors as alternative analytical methods to traditional ones, for different applications in the agri-food, environmental and biomedical fields. Ci2B has the appropriate infrastructure, experience and network of collaborations to address the development of both enzymatic (those whose bioactive component is an enzyme) and immunological (those based on antibodies) biosensors, with different transduction mechanisms: electrochemical, optical, piezoelectric. , etc.

Cardiac arrhythmias are one of the main causes of morbidity and mortality in developed countries. Despite the intense research carried out, the mechanisms of generation, maintenance and termination of these arrhythmias are not completely clear. Furthermore, its treatment is not entirely satisfactory. Although today a large amount of information is available at different levels: sub-cellular, cellular, tissue, organ and system, the prediction, prevention and treatment of cardiac arrhythmias continues to be one of the greatest scientific challenges. .

A new and promising technology based on the integration of different levels of information in computational models allows research in this field. Within this line, researchers from Ci2B of the Universitat Politècnica de València work on the study of the causes of cardiac arrhythmias through modeling and simulation.

Realistic three-dimensional models of the heart have been developed that include, with a high degree of detail, genetic characteristics of ionic currents and their mutations, the electrophysiological characteristics of the different types of cardiac cells and the anatomical structure of the different cardiac tissues, in addition of an anatomical model of the torso.

Using these models, situations that generate and perpetuate complex pathological rhythms and their relationship with the electrical signals used in clinical diagnosis (ECG) are studied. These integrated multi-scale models are used to improve the prevention and diagnosis of cardiac pathologies, surgical procedures related to radiofrequency ablation and knowledge of the pro-arrhythmic effects of different antiarrhythmic drugs.

Key People:

• Ferrero De Loma-Osorio, José María
• Gomis-Tena Dolz, Julio
• Romero Perez, Lucia
• Saiz Rodríguez, Francisco Javier
• Trénor Gomis, Beatriz Ana

Responsible:

• Trénor Gomis, Beatriz Ana

Medical Device Development

- Design and Optimization of Pacemakers and Defibrillators: Modeling cardiac electrical activity allows for the design of more effective and safe devices. Simulations help optimize electrode placement and electrical pulse configuration.

- Virtual Testing: Before manufacturing, devices can be tested on virtual models of the heart, reducing development time and costs and improving the safety of the final product.

Research and Development in Cardiology

- Study of Arrhythmias: Simulations allow us to study the origin and spread of cardiac arrhythmias, improving the understanding of these disorders and facilitating the development of new treatments.

- Drug Development: Evaluate the effect of new medications on the electrical activity of the heart, identifying possible side effects and optimizing dosage.

Medical Training and Education

- Training Simulators: Virtual cardiac models are used in simulators to train doctors and healthcare personnel in interpreting electrocardiograms (ECG) and performing cardiac interventions.

Personalization of Treatments

- Personalized Therapies: Simulation models can be customized according to each patient's data, allowing doctors to plan specific treatments and predict the results of different interventions.

- Computer-Assisted Cardiac Surgery: Facilitates preoperative planning, helping surgeons visualize and rehearse procedures before performing them on the patient.

Monitoring and Diagnosis

- Development of Remote Monitoring Systems: Improves the design of remote monitoring systems for cardiac activity, allowing early detection of anomalies and intervention.

- Improvement of Diagnostic Algorithms: Optimization of the algorithms used in portable devices and hospital monitoring systems to detect and classify arrhythmias and other cardiac conditions with greater precision.

Regulation and Certification

- Evaluation and Certification of New Medical Devices: Models and simulations can be used to meet the requirements of regulatory agencies, providing data on the safety and effectiveness of new medical devices.

Telemedicine and Remote Medical Care

- Remote Diagnosis: Use of simulations to improve the precision of diagnoses made remotely, facilitating telemedicine.

- Continuous Monitoring: Helps in the development of continuous monitoring systems for patients with heart disease, allowing early interventions and reduction of hospitalizations.

Multi-Scale Simulation:

Integration of data at the sub-cellular, cellular, tissue and organ levels, allowing a holistic understanding of cardiac function and arrhythmias.

Personalized and realistic heart models:

Creation of realistic three-dimensional cardiac models based on specific genetic and anatomical characteristics, improving the accuracy of simulations.

Advanced Prediction and Prevention:

Ability to predict the appearance of arrhythmias and their progression, facilitating more effective preventive interventions.

Optimization of Medical Procedures:

Simulation of procedures to improve techniques and results, reducing risks and recovery times.

- Improvement of the prevention and diagnosis of cardiac pathologies

- Improvement of surgical procedures related to radiofrequency ablation

- More information about pro-arrhythmic effects of different antiarrhythmic drugs.

The research group has extensive experience in:

- Computational simulation and modeling: to predict and study cardiac arrhythmias.

- Personalized and multi-scale technologies: for the treatment of cardiac pathologies.

- In silico optimization and certification: of cardiac devices and medications.

- Early detection and genetics: developing platforms for predisposition to arrhythmias.

- Electrical activity studies: focused on atrial fibrillation.

These experiences span both competitive research projects and significant international and funded collaborations, highlighting their ability to address critical problems in cardiology through innovative and advanced methods. Some projects are:

pCardioTreat: Optimization of personalized therapies for atrial and ventricular pathologies through multi-scale computational models. Focused on atrial fibrillation, myocardial infarction and heart failure, with personalization methods based on clinical data.

V-Heart SN: Summary: Advanced computer simulation for the study of the electrical activity of the heart, allowing a detailed analysis of arrhythmias and the effect of various treatments.

PFarma: Development of computational platforms for the simulation of drugs and medical devices applied to the treatment of heart diseases, improving the efficiency and effectiveness of treatments.

Prometeo: Project focused on advanced research into the electrical activity of the heart, with special attention to the improvement of ablation techniques and other interventional treatments.

MY-ATRIA: Multidisciplinary training network for the management of atrial fibrillation, integrating various disciplines and approaches to improve the understanding and treatment of this pathology.

MeHeart: Focus on modeling and simulation of cardiac electrical activity to improve the accuracy of medical treatments and the prediction of therapeutic outcomes.

SimCardioTest: Project that develops in silico simulations for the certification of cardiac devices and drugs, with the aim of reducing costs and improving the safety and effectiveness of treatments.

PCarTrialsM&S: The overall objective of this project is to develop, validate and test a tool for conducting in silico clinical trials for precision medicine using populations of electrophysiological and electromechanical models to improve the efficacy and safety of therapies.

These projects reflect the group's extensive experience in the use of computational models and simulations for the study and treatment of cardiac pathologies, collaborating with various international institutions and focusing on the personalization and optimization of therapies.

Electrical tissue stimulation is a medical technique that applies electrical impulses to influence the biological activity of various tissues. It is essential in the treatment of conditions such as neurological disorders, cardiovascular diseases and muscle problems, helping to restore physiological functions, relieve symptoms and improve the quality of life of patients.

Currently, electrical tissue stimulation is performed using various technologies with their own advantages and limitations. Deep brain stimulation (DBS) implants electrodes in the brain to treat neurological diseases such as Parkinson's and epilepsy; Although effective, it is invasive and carries surgical risks. Transcutaneous electrical nerve stimulation (TENS) uses electrodes in the skin to relieve muscle and nerve pain, being less invasive but limited in depth and precision. Pacemakers and defibrillators, which regulate cardiac activity using implantable electrodes, are essential for cardiac patients, but their implantation is invasive and requires long-term maintenance.

Our research group focuses on advanced tissue electrical stimulation systems. These systems use electrodes, which can be implanted or applied superficially, to provide precise and controlled stimulation. They include nervous, sensory and cortical stimulation systems using electrodes implanted in the cerebral cortex to treat neurological disorders. In addition, they have transthoracic stimulation systems that apply electrodes to the skin of the chest to improve effectiveness in the treatment of cardiac arrhythmias and other cardiovascular problems.

Key People:

• Gomis-Tena Dolz, Julio
• Saiz Rodríguez, Francisco Javier

Responsible:

• Saiz Rodríguez, Francisco Javier

• Medicine and health- Treatment of Chronic Pain: Systems such as peripheral nerve stimulators (PNS) and spinal cord stimulators (SCS) are used to relieve chronic pain in patients who do not respond to other treatments.- Neuromodulation for Neurological Disorders: They are used to treat diseases such as epilepsy, Parkinson's and other movement disorders, providing electrical stimuli to improve neurological function.

  - Neurological Rehabilitation: They help in the rehabilitation of patients who have suffered strokes or spinal cord injuries, stimulating the nerves and muscles to recover mobility and function.

  - Treatment of Psychiatric Disorders: Transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) are used to treat disorders such as treatment-resistant depression and obsessive-compulsive disorder (OCD).

  Physical Rehabilitation and Therapy:

  - Use of functional electrical stimulation (FES) to improve mobility in patients with partial paralysis, helping them to perform daily activities and rehabilitation exercises.

  - Treatment of sports injuries and musculoskeletal problems by stimulating muscles and nerves to reduce inflammation, relieve pain and speed recovery.

  Sports and Physical Performance:

  - Optimization of sports training, improving muscle strength and endurance.

  - Post-Intense Exercise Recovery, reducing fatigue and accelerating tissue repair.

  Personal Health and Wellbeing

  - Integration into wearable devices for pain, stress and fatigue management, providing relief through electrical stimulation.

  - Development of electrical stimulation devices for massage and relaxation, improving circulation and relieving muscle tension.

  Aesthetics Industry

  - Anti-aging Treatments: Use of electrical stimulation to improve skin tone and reduce wrinkles, promoting cell regeneration.

  - Body Remodeling Therapies: Use in non-invasive fat reduction and muscle toning procedures.

Stimulation Precision:

Electrical stimulation systems are designed to provide precise and controlled stimulation of specific tissues, allowing for targeted and effective therapeutic intervention.

Adaptability to Different Fabrics:

These systems can be adapted to stimulate a variety of tissues, including nerves, sensory and cortical tissue, as well as for transthoracic applications, making them versatile and useful in a wide range of medical applications.

Control of Stimulation Parameters:

They allow stimulation parameters to be adjusted and controlled, such as the intensity, frequency and duration of the electrical pulses, allowing for personalization of treatment according to the patient's specific needs and medical condition.

Electrode Compatibility:

They can be used with a variety of electrodes designed for different applications and anatomical areas, providing flexibility in system design and allowing adaptation to the specific needs of each patient or procedure.

Intuitive User Interface:

Stimulation systems typically have intuitive and friendly user interfaces that make it easy for healthcare professionals to configure and operate them, contributing to an efficient and safe user experience.

Monitoring and Feedback:

Some systems may include real-time monitoring and feedback functions, allowing tissue response to stimulation to be assessed and treatment parameters adjusted as necessary, thereby improving treatment effectiveness.

Improvement in Treatment Efficacy:

The precision and adaptability of these systems allow for precise and controlled stimulation of specific tissues, which can result in a significant improvement in treatment efficacy for a variety of medical conditions, such as neurological disorders, chronic pain, among others.

Reduction of Side Effects:

By allowing precise adjustments of stimulation parameters, these systems can minimize the occurrence of unwanted side effects, improving treatment tolerability and patient quality of life.

Personalization of Treatment:

The ability to tailor stimulation parameters to the patient's specific needs allows for personalization of treatment, which can lead to better clinical outcomes and more individual-centered care.

Greater security:

Intuitive user interfaces and real-time monitoring features help ensure patient safety during the stimulation procedure, reducing the risk of complications and improving the overall treatment experience.

Long-Term Cost Reduction:

By improving the effectiveness of treatment and reducing the incidence of side effects and complications, these systems can help reduce costs associated with long-term medical care, both for patients and for health systems as a whole.

Advances in Biomedical Research:

The use of these systems in biomedical research can contribute to the advancement of knowledge in fields such as neuroscience and regenerative medicine, which can lead to the development of new therapies and innovative medical technologies.

The research group at has extensive experience in the development and application of electrical tissue stimulation systems. His main areas of focus include:

Tissue stimulation systems

- Deep Brain Stimulation (DBS). Related projects: PARK1 and VTA1.

They develop and optimize deep brain stimulation techniques, which involve the use of electrodes implanted in the brain to treat neurological diseases such as Parkinson's. This type of stimulation allows the direct modulation of neuronal functions through electrodes in contact with brain tissues.

Nervous, sensory and cortical stimulation systems

- Sensory and cortical stimulation. Related projects: REO2.

It involves rehabilitation and stimulation through biological signal feedback systems, including nerve and sensory stimulation. This type of work is essential for the recovery of motor and sensory functions in patients with neurological damage.

This capability focuses on the development and implementation of artificial intelligence (AI) systems designed to assist in clinical decision making. These systems use advanced algorithms and machine learning to analyze clinical data sets and generate accurate, personalized recommendations.

Automatic decision support systems can address a variety of clinical applications, from disease diagnosis and prognosis to optimization of treatment plans. These systems are capable of processing and analyzing complex, multidimensional information that can be difficult to interpret manually, such as biomedical signals, electronic health records, and clinical data.

Additionally, these systems can learn and improve over time as they are exposed to more data, which can lead to greater accuracy and effectiveness in clinical decision making. This can result in more efficient and effective patient care, and can help doctors make more informed decisions.

Importantly, these systems are designed to complement, not replace, human clinical judgment. They provide an additional tool that physicians can use to inform their decision making and improve patient care.

Key People:

• Garcia Casado, Francisco Javier
• Martínez De Juan, José Luís
• Prats Boluda, Gema
• Ye, Yiyao

Responsible:

• Garcia Casado, Francisco Javier

1. AI-assisted diagnosis : AI systems can quickly analyze large amounts of patient data, such as medical records, biomedical diagnostic signals, and laboratory results, to identify patterns and aid in the diagnosis of diseases.
2. Disease prognosis : By analyzing patient data over time, AI systems can help predict disease progression and provide accurate prognoses.
3. Treatment optimization : AI systems can analyze patient and previous treatment data to recommend the most effective treatment plan for each individual patient.
4. Early disease detection : By analyzing real-time health data, such as that collected by wearable devices, AI systems can help detect early signs of disease.
5. Clinical research : AI systems can analyze large sets of research data to identify patterns and correlations that may not be evident to human researchers.
6. Population health management : By analyzing population-level health data, AI systems can identify community-level health trends and risks, which can inform public health strategies.
7. Personalization of healthcare : AI systems can use patient data to personalize health interventions and improve the effectiveness of care.

1. Improved efficiency : AI systems can quickly analyze large amounts of data, which can lead to faster diagnosis and treatment.
2. Greater accuracy : AI systems can identify patterns and correlations in data that may be difficult for humans to detect, which can result in more accurate diagnoses and prognoses.
3. Personalized care : AI systems can use patient data to personalize health interventions and improve the effectiveness of care.
4. Reducing the workload of medical staff : By taking on data analysis and recommendation generation tasks, AI systems can free up time for medical staff to focus on other important tasks.
5. Continuous improvement : AI systems can learn and improve over time as they are exposed to more data, which can lead to greater accuracy and effectiveness in clinical decision making.
6. Proactive prevention : AI systems can help detect early signs of disease, which can allow for early interventions and potentially prevent the development of serious diseases.

1. 1. Improving patient health outcomes : By providing more accurate diagnoses and personalized treatment recommendations, AI systems can directly improve patient health outcomes.
   2. Cost savings : By improving the efficiency and accuracy of diagnosis and treatment, AI systems can help reduce costs associated with medical errors and ineffective treatments.
   3. Access to healthcare : AI systems can facilitate access to healthcare in areas where medical resources are limited, by enabling remote diagnosis and treatment.
   4. Medical training : AI systems can be a valuable tool for medical training, providing medical students and doctors in training the opportunity to learn from complex and rare cases.
   5. Research and development : AI systems can accelerate research and development in the medical field by quickly identifying patterns and correlations in large research data sets.

   Equity in healthcare : By providing diagnoses and treatment recommendations based on data and not assumptions or biases, AI systems can help promote equity in healthcare.

The research group has extensive experience in the development of automatic systems to help clinical diagnosis and decision making; mainly based on biomedical signals from different areas combined with other types of clinical information.

For example, systems have been developed that help predict premature birth or imminent birth, the success of labor induction, the success of treatments for chronic pelvic pain, the diagnosis of neurodegenerative diseases, the presence of hemophilic arthropathy, etc

Also for the automatic segmentation of signal sections that are artifacted, identifying contractile events and rest sections, etc.

In our developments we use both machine learning techniques such as neural networks, support vector machines, advanced decision trees, k-nearest Neighbors... when the amount of data is 'medium'. When a large volume of data is available we have experience in techniques such as convolutional neural networks, recurrent neural networks, autoencoders, transformers...

We have worked on both basic and applied research projects, in projects in collaboration with multiple clinical entities and international research groups. Likewise, there is also extensive experience in research contracts with companies in the biomedical and clinical field.

Our projects highlight the use of advanced technology to address relevant clinical problems, providing innovative tools to improve medical care and reduce associated costs.

We develop customized and compact systems for remote monitoring and recording of a wide range of biological signals, both common and uncommon. These systems, designed by researchers from Ci2B of the UPV, can acquire between 1 and 16 signal channels, including intestinal pressure, intestinal myoelectric signal, uterine myoelectric signal, intrauterine pressure, respiration, maternal and fetal electrocardiography, among others.

Based on generic biosignal amplifiers with adaptable configuration, we select the most appropriate sensors for each application, even developing our own sensors if necessary. Its user interface, based on PC with specialized software, allows the acquisition, storage and visualization of signals, as well as the generation of databases, all customizable to meet the specific needs of each case.

These compact, low-power systems are capable of synchronizing the acquisition and digital conversion of signals using a microcontroller, subsequently transmitting them, both by guided means and wirelessly, to mobile devices or PCs. This facilitates remote monitoring of bioelectric signals in non-hospital environments, providing a comprehensive solution for the recording and analysis of biological signals in different clinical and research contexts.

Key People:

• Garcia Casado, Francisco Javier
• Gomis-Tena Dolz, Julio
• Martínez De Juan, José Luís
• Prats Boluda, Gema
• Ye, Yiyao

Responsible:

• Julio Gomis-Tena Dolz

Diagnosis and Clinical Monitoring

- Maternal and Fetal Health: Continuous and non-invasive monitoring of maternal and fetal electrocardiographic signals, and signals of the uterine muscles, improving prenatal surveillance and early detection of possible complications.

- Gastroenterology: Monitoring gastric and intestinal pressure and myoelectric signals to diagnose and manage gastrointestinal diseases such as irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), or intestinal ischemia.

- Gynecology and Obstetrics: Evaluation of uterine myoelectric activity and intrauterine pressure to predict and monitor labor and other uterine conditions.

Intensive and Hospital Care

- Intensive Care Units (ICU): Implementation in ICUs for the monitoring of critical patients, allowing continuous monitoring of multiple vital signs and rapid medical intervention.

- Remote monitoring of patients with chronic diseases, reducing the need for hospitalizations and improving quality of life.

Telemedicine and Remote Monitoring

- Integration into telemedicine platforms for remote patient monitoring, facilitating remote medical care and allowing doctors to perform diagnoses and follow-ups without the need for in-person visits.

- Development of Portable devices that allow patients to monitor their biological signals from home, sending data in real time to their doctors.

Medical Technology and Devices

- Innovation in Medical Devices: Development of new medical devices based on multichannel monitoring technology, providing innovative solutions for diagnosis and treatment.

- Optimization of Existing Devices: Improvement of current medical devices through the integration of advanced biological signal acquisition and processing systems.

Rehabilitation and Physiotherapy

- Biofeedback: Using biological signals to provide real-time feedback during rehabilitation sessions, helping patients improve muscle control and neurological function.

- Personalized Rehabilitation Programs: Design of rehabilitation programs based on continuous monitoring of biological signals, optimizing treatment for each patient.

Customization and adaptability:

These systems can be designed and configured specifically to meet the needs of a wide range of biomedical and industrial applications, allowing complete customization of signal acquisition parameters and the selection of appropriate sensors for each case.

Flexibility in the number of channels:

The ability to acquire between 1 and 16 signal channels provides flexibility to accommodate different monitoring requirements, from simple applications to complex studies requiring the simultaneous collection of multiple biological signals.

Compactness and low consumption:

These systems are designed to be compact and low-power, making them suitable for use in environments where space and power are limited, such as in wearable or implantable devices.

Intuitive user interface:

The PC-based user interface with specialized software provides an intuitive and easy-to-use user experience, allowing signal acquisition, storage and display, as well as database generation, in an efficient and customizable manner.

Synchronization and data transmission:

The ability to synchronize the acquisition and digital conversion of signals using a microcontroller, as well as the transmission of data to mobile devices or PCs, allows remote and real-time monitoring of biological signals, facilitating access to information from any location. .

Reduced cost:

The devices are inexpensive compared to other solutions available on the market, making them accessible to a wide range of users and applications. This feature is especially relevant for industrial and healthcare applications where you seek to maximize efficiency and reduce operating costs.

• Improvement in diagnosis and treatment:

  By allowing continuous and remote monitoring of various biological signals, these systems can facilitate early diagnosis of diseases, as well as monitoring patient progress during treatment, which can lead to better medical care and more favorable outcomes.

  Greater comfort for patients:

  The ability to monitor remotely reduces the need for patients to travel to the hospital or clinic for testing, providing greater convenience and flexibility, especially in cases of long-term follow-up or chronic diseases.

  Optimization of industrial processes:

  In industrial settings, these systems can contribute to the improvement of production processes by providing accurate, real-time data on relevant biological variables, allowing for more efficient optimization and higher quality of the final product.

  Costs reduction:

  By enabling early detection of health problems, these systems can contribute to the reduction of costs associated with more complex medical treatments or prolonged hospital stays. Additionally, in industrial settings, process optimization can lead to increased efficiency and reduced operating costs.

  Normative compliance:

  In sectors where compliance with strict health and safety regulations is required, such as the medical or food industry, these systems can help ensure regulatory compliance by providing accurate data and detailed records of monitoring conditions.

  Advances in research:

  These systems can facilitate data collection in scientific and clinical studies, contributing to the advancement of knowledge in areas such as medicine, biology, and biomedical engineering."

The research group has relevant experience in the development of ad hoc systems for the monitoring and recording of biological signals, especially in the following projects:

1. Electrohysterography for clinical use in obstetrics
2. Systems for the capture and analysis of gastric and intestinal myoelectric signals
3. Personalized computational models to optimize diagnosis and treatment of cardiac arrhythmias
4. Development of a system for measuring efforts and electromechanical actuation for prostheses of lower limb amputees
5. Development of a prototype based on Doppler ultrasound and artificial intelligence for non-invasive and non-bloody diagnosis and assistance of female urinary incontinence
6. Intelligent platform for early detection, helps diagnose and monitor sarcopenia

These projects demonstrate the group's experience in the development of ad hoc systems for the monitoring and recording of biological signals, including electrohysterography, computational simulation, analysis of myoelectric signals, the development of stress measurement systems and electromechanical actuation, and the use of Doppler ultrasound and artificial intelligence for diagnosis and medical assistance.

The goal of tissue engineering is to restore, maintain, improve or replace biological tissues. Ideally, tissue-engineered constructs should be designed considering that they biodegrade over time to be simultaneously replaced by autologous tissue that can adapt in vivo under multiple changing conditions. In particular, cardiac structures created for this purpose are subjected to electrical stimulations, hemodynamic loads and mechanical loads that evolve over time. This is why functional cardiac models must incorporate the ability to grow with the patient and adapt to these loads to prevent complications that can lead, for example, to heart failure.

With unprecedented spatial control, 3D bioprinting offers a means to create complex, functional structures. Recent research has demonstrated the ability to bioprint heart models (or its parts) in 3D using bioinks formed by hydrogels that include different cardiac cells, in particular, cardiomyocytes, being able to recapitulate both electrophysiological function and dynamic pressure-volume cycles.

On the other hand, an important goal in the design of bioengineered scaffolds is the reliable prediction of the impact of specific scaffold materials, including their degradation, and cell types. Extensive exploration of such effects through purely experimental and clinical studies is cost and time prohibitive. Mathematical modeling and computational simulation can accelerate these studies to push the boundaries of tissue engineering. However, current computational frameworks are limited and often rely on inadequate constitutive descriptions of these complex structures.

The study of this problem necessarily requires a combined theoretical, computational and experimental approach. Theoretical developments are needed to understand the underlying mechanical and mechanobiological behavior, guide experiments, and synthesize results; Computational models and simulations are needed to analyze the data and solve initial and boundary value problems; Furthermore, the construction of these theoretical and computational models requires the analysis of experimental and clinical data to parameterize them and thus accurately describe the behavior of the bioartificial heart.

In this inter- and multidisciplinary field, CI2B researchers are working on the design and manufacturing of a cardiac ventricular chamber created through 3D bioprinting with cardiomyocytes derived from induced pluripotent stem cells (iPS), as well as on the characterization, modeling and simulation of the Contributions of growth and remodeling to neotissue formation and the establishment of cardiac function.

Key People:

• Latorre Ferrús, Marcos

Responsible:

• Latorre Ferrús, Marcos

• Assemble functional constructs that restore, maintain or improve damaged cardiac chambers or tissues.
• Understand how heart disease progresses and how it can be treated.
• Combine tissue engineering and regenerative medicine techniques to repair tissue in the body.
• Design and optimization of three-dimensional scaffolds that support the growth, remodeling and maturation of pluripotent stem cells differentiated into cardiomyocytes.
• Study the normal and pathological development of cardiac tissue.
• Test therapies and medications in disease models.
• Evaluation of cell adhesion of implanted cells and its long-term effects.
• Design and optimization of personalized transplants.
• Engineering cardiac ventricles for newborns with alterations due to congenital heart disease.

• Combination of established methods and state-of-the-art hydrogels that allow the proper adaptation and maturation of cardiomyocytes derived from human iPS cells.
• Creation of more realistic and higher fidelity ventricular geometries through 3D bioprinting.
• Separate investigation of flow- and/or pressure-induced wall growth and remodeling.
• Advanced simulation of simultaneous degradation and regeneration of cardiac tissue.
• Synergy of experimental and computational techniques to design optimal functional constructs.

• Reduction of costs, time and risk with respect to purely experimental and clinical studies.
• Restoration, maintenance, improvement and/or replacement of personalized biological tissues on demand.
• Improvement of the biocompatibility of the implant and reduction of rejection by the body.

The research group has extensive experience in:

• Computational simulation and modeling of coupled solid and fluid mechanics problems.
• Experimental and computational studies on the treatment of cardiovascular pathologies.
• Design of biomaterials for tissue engineering applications through 3D bioprinting.
• Culture of healthy and pathological human iPS cell lines and differentiation into cardiac cells.
• Mechanical, electrical and imaging characterization of native and bioartificial cardiac tissue.