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The Biomedical Data Science Lab (BDSLab) of ITACA Institute and the institute of mathematics “Instituto Universitario de Matemática Pura y Aplicada IUMPA”, both at Universitat Politècnica de València (UPV), have developed a new mobile application that facilitates continuous monitoring of the quality of life of cancer patients and that is being tested in the Oncology Service of the Doctor Peset University Hospital in Valencia. Called Lalaby, the app allows the monitoring of the patients’ day-to-day life. It does so from the information collected by the sensors of their mobiles and from other sources stored in them that allow calculating their physical activity (movement and movement), social interaction (voice frequencies) and activity on the network (amount of data used ).

In addition, Lalaby allows the integration of questionnaires, such as the EORTC QLQ-C30 (European Organization for Research and Treatment of Cancer- QLQ-C30) widely used to assess quality of life, as well as for the patient to directly record the activities carried out (household chores, personal hygiene, watching TV,…), your symptoms (vomiting, shortness of breath, tiredness…) and your level of pain.

“To guide the patient in his interaction with the app, Lalaby includes a notification system that reminds him of what information to report at any given time and directs him to the screen to use with a click”, adds Ángel Sánchez García, researcher of BDSLab.

From all this information, Lalaby makes it possible to obtain user behavior patterns and relate them to quality of life indicators. “These patterns can be of great help, for example, to monitor possible changes in mood, activity, symptoms, and so on, in people starting cancer treatment, which offers doctors valuable information to make the best possible decisions for the patient’s day-to-day life ”, explains Juan Miguel García-Gómez, director of the BDSLab group.

One of the most remarkable aspects of the Lalaby app, in addition to the integration and recording of all patient information that doctors can consult in the Dashboard, is its user-centered graphic design and its intuitive nature, “which it greatly facilitates its use and acceptance by patients ”, adds Sabina Asensio-Cuesta, researcher of the BDSLab group.

The graphic design of the Lalaby app is the result of a contest in which students from the UPV’s Higher Technical School of Design Engineering submitted 44 proposals. From this contest came the name Lalaby and the germ of his graphic design.

In collaboration with the Doctor Peset University Hospital of Valencia

In the validation of the Lalaby app, the UPV team has had the advice and collaboration of Inmaculada Maestu, Head of the Medical Oncology Service of the Doctor Peset University Hospital in Valencia, Maria Martín, also from the aforementioned hospital, and Teresa Soria, an oncologist and collaborator of the project. It is precisely with patients from this hospital – specifically, patients with lung cancer – with whom the first trials of the validation and improvement of the app are being carried out.

Among the advantages of continuous monitoring, the UPV team and the Doctor Peset University Hospital point out that it contributes to observing the evolution of the patient in the course of active cancer treatment, in which it is essential to make decisions aimed at maintaining its functionality and quality of life.

Dr. Inmaculada Maestu points out that “the Lalaby app allows us to have more information regarding the patient’s symptoms, both the disease itself and that derived from the treatments applied. This contributes to better control of the disease and can help us in making therapeutic decisions. It helps patients to maintain better communication with the medical team, being able to express their health status in real time, which leads to the adoption of appropriate interventions aimed at improving their quality of life ”.

Valid for other chronic diseases

In addition to cancer patients, Lalaby could also be adapted for the study of quality of life in people with migraine headaches or chronic covid patients, among other pathologies.

“The app makes it possible to correlate the data stored by mobile phones with questionnaires used to evaluate these and other chronic diseases, hence its potential,” concludes Sabina Asensio-Cuesta.

More information about Lalaby available at www.lalaby.es

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News on UPV TV

 

Source: UPV’s Information Office


ITACA’s Biomedical Data Science Lab (BDSLab) of Universitat Politècnica de València (UPV) has developed a new mobile application that facilitates continuous monitoring of the quality of life of cancer patients.
 
This app, called Lalaby, allows the monitoring of the patients’ day-to-day life. It does so from the information collected by the sensors of their mobiles and from other sources stored in them that allow calculating their physical activity (movement and displacement), social interaction (voice frequencies) and activity on the network (amount of data used).
 
Source: UPVTV


The medical imaging area (IBIME-MI) of the ITACA institute has been working for the last 20 years in the processing and analysis of medical images, with special emphasis on magnetic resonance images of the human brain.
 
IBIME-MI has developed and transferred many state-of-the-art methods for quantitative neuroimaging. Volbrain is an online system for automatically analyzing MRI brain data to provide volumetric information of different brain structures. It has already been used to analyze more than 300,000 brains worldwide from almost 2,000 different universities and hospitals.
 
Currently IBIME-MI is focused on developing new deep learning methods for brain analysis with special interest both in normal brain development and in different pathological conditions such as Alzheimer’s or Parkinson’s disease, among others.


The group SEN (Smart Electronics and Networks) from ITACA institute has extensive experience in the design and implementation of intelligent monitoring and control systems, the development of hardware devices, their embedded applications, and their integration through various communication technologies in Cloud IoT platforms.
 
SEN experience covers multiple fields, among which we can mention smart cities, environmental care, green energy, smart hospitals, underwater deployments and high reliability embedded systems applied to multiple areas, such as electronic injection systems for heat engines, mechatronics, drones, and other electronic systems.
 
SEN firmly believes that these advances in technology result in great benefits for society, helping to achieve the Sustainable Development Goals proposed by the United Nations.


ITACA’s Microwave Area (DIMAS) is dedicated to scientific and applied research, technological development and technology transfer initiatives in the field of microwave engineering.
 
DIMAS’ main research lines focus on numerical modelling, design of microwave circuits and components, microwave measurements, non-invasive microwave sensors, and the use of high-power microwaves for materials processing.
 
For example, DIMAS applies microwaves in electrochemical applications to produce green hydrogen.


PM4H is dedicated to scientific and applied research, technological development and technology transfer initiatives in the field of Process Mining for Health. Born within the SABIEN group of ITACA, PM4H is the result of the experience garnered by SABIEN in healthcare as the fruit of years of hard work with multitude of European, National and local health entities.
 
PM4H is divided into three main areas: 1) PM4H Lab, 2) PM4H Consultancy and 3) PM4H Training
 
PM4HLab is the Academic part of PM4H and is in charge to provide the best research available by collaborating with universities, hospitals and research centres around the world. PM4H Lab is also the incubator for new ideas and the testbed for new research for which PM4H has a mainframe.
 
PM4H Consultancy is based on an analytic solution powered by process mining and specially designed for healthcare PM4H has developed a tool, called PMApp, for supporting process miners in the creation of Interactive Process Mining Dashboards in the healthcare Domain.
 
PM4H Training is centred on generating material for developers, and health and process experts to develop, customize and understand the analytic solution, looking for innovative ways to teaching digital skills especially to healthcare professionals.


Everyday thousands of aircrafts fly in the sky. In the mid-term, a huge number of unmanned aircraft will share the airspace with manned ones. To guarantee a safe, ordered and environmentally friendly use of such a scarce resource, specific technologies and procedures must be defined.
 
The ITACA Air Navigation Systems group (SNA) contributes to this global goal by developing research and knowledge transfer in navigation and surveillance technologies and concepts for Air Traffic Management and Unmanned Traffic Management. SNA research activities are focused on two main lines: Performance based surveillance and navigation systems.
 
SNA is currently improving state-of-the-art surveillance monitoring systems by introducing Artificial Intelligence to associate target reports to multitracks and to identify Modes of Flight.
 
SNA also develops research activities to optimise the flight operations and to guarantee safety in contingency situations, including the development of a new concept of operations for conflict management of drones and manned aviation in the U-space, always considering the optimal use of airspace.


Cardiac arrhythmias affect to one in three adults: more than 10 million Europeans do suffer a cardiac arrhythmia. In 2021, almost 70% of heart arrhythmias cannot be cured, and they cost more than two hundred thousand millions of euros to the European Union each year. Nowadays, fundamental mechanisms of initiation and maintenance of arrhythmias remain unknow. Antiarrhythmic drugs fail in more than sixty percent of patients.
 
The goal of ITACA–COR research group is to achieve that cardiac arrhythmias become a curable disease. COR is a team of electronic and biomedical engineers developing technology to understand cardiac arrhythmias, to provide valuable tools to clinicians and to ensure that its knowledge arrives to all patients.
 
ITACA-COR collaborates with biologists in the development and characterization of human cell cultures from pluripotent stem cells. These cell cultures improve the understanding of the ionic currents interactions that affect cardiac tissue. These will be the target of novel biological antiarrhythmic treatments.
 
Today, all patients are receiving the same surgery, pulmonary vein isolation, although it fails in more than forty percent of cases. Closer to the patients, ITACA-COR also develops electrocardiographic imaging technology, studying regularization techniques that allow the estimation of the origin of the arrhythmia without the need of surgical interventions and applying machine learning techniques to predict the most appropriate treatment for each patient by putting together different clinical variable and electrophysiological information.


One of the WSN team’s areas of work is LPWANs, a specific approach for Internet of Things (IoT) implementation. It allows the development of devices able to operate for years without battery replacement and to transfer data over long distances.
 
IoT and specifically LPWAN technologies are a perfect complement to other conventional technologies such as Bluetooth, Wi-Fi or 4G/5G. They enable edge applications in many fields such as smart cities, tourism, industry 4.0, smart farming, natural resources monitoring, etc.
 
One of WSN’s ongoing projects is focused on cultural heritage conservation. Cultural objects can be affected by environmental conditions, as they can trigger different degradation mechanisms. The use of wireless sensors is increasingly an option to address the continuous monitoring of environmental conditions. However, conventional wireless technologies may not be adequate in many of the buildings housing these collections as they have thick walls and long distances to cover. WSN can develop electronics and software especially suited to solve this type of problems.


The Biomedical Data Science Lab (BDSLab) is a multidisciplinary research group committed to developing a technology based on data science & artificial intelligence for real health problems. BDSLab expertise includes machine learning, predictive modelling, data quality and variability, multiparametric tissue signatures, decision support systems, and medical imaging.
 
Aiming to a trustworthy data use, BDSLAb conducts research in methods and tools to help profile and control data quality. The goal is to achieve reliable data science and artificial intelligence, being robust to data quality and variability in real-world data.
 
BDSLab investigates innovative Deep Learning solutions to extract valuable knowledge from MRI images to address complex clinical problems, for example, glioblastoma, which is the most aggressive brain tumour.
 
Another of BDSLab research lines focuses on the development of predictive models and Clinical Decision Support Systems Ther goal is to provide reliable tools to physicians and health experts concerning several health issues; our latest work is a system to assess palliative care needs on hospital admitted patients.
 
BDSLab also focuses its research on mHealth, mobile applications for health care. Such as the Wakamola chatbot to collect data from users about their lifestyle and calculate their obesity risk.