ABSTRACT  

Recently it has been demonstrated that specific miRNAs can indicate and characterize a haemorrhagic condition of the patient. Unfortunately, the miRNA detection requires many hours nullifying the stroke minimization actions that are needed within five hours in most patients.
Electronic sensing through large area CMOS sensors could be able, starting from a biological fluid of the patient, to detect the miRNA generated fluorescence allowing a significant reduction of time, cost, and difficulty of the diagnosis.
The research activity focuses on the development of the algorithms, and the design of the related digital circuitry, for measurement of the minute fluorescence generated on large area CMOS sensors.

No More Available

Already assigned to a PhD student of cycle XXXV

OBJECTIVES 

The research activity aims at designing a lab on chip based on a large area customized CMOS sensor, surrounding circuitry, and human interface for the detection of the miRNA fluorescence signal.
The chip should diagnose the haemorrhagic condition exploiting the photoluminescence signal arising from the specific recognition between complementary nucleotides’ sequences and labelling with fluorescent tags as the transduction principle. The extended sensor’s surface will permit to carry out an efficient data integration and to reduce the electronic noise. Dedicated algorithms will be needed to carry out the challenging task of extracting the limited signal from the noisy environment counteracting chip derating, temperature, and chip to chip variability.

ABSTRACT 

The investigation on the use of High Permittivity Materials (HPM) is a hot topic in ultra high field Magnetic Resonance Imaging (MRI) because it allows improving the signal to noise ratio in many scenarios. A physical based explanation of this phenomenon is still an open problem. The PhD Students are expected to contribute to the advancement of knowledge on this field. They will be called to develop electromagnetic models and to implement numerical tools to find, at least in simple geometries, the optimum configuration for the HPMs.  

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVES

o Comprehension of the physical mechanisms that govern the RF field distribution in MRI scanner.
o Comprehension of the effects of a HPM layer on the SNR.
o Identification of optimal configurations for a HPM-array of antennas case

Instrumentation and Measurements for Brain Computer interface in health care

ABSTRACT 

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVES

ABSTRACT 

In this activity, the PhD candidate will develop a nanophotonic biosensor aimed at the detection of circulating non-coding RNAs (miRNAs).  The sensor will be based on novel anomalous electromagnetic scattering effects emerging at the nanoscale. The PhD candidate will design the electromagnetic properties of the nanophotonic substrate under the guidance of Prof. Forestiere; then he will fabricate and characterize the device under the supervision of Dr. De Stefano. Eventually, he will test the optical sensors under the guidance of Prof. Caraglia, M.D.

No More Available

Already assigned to a PhD student of cycle XXXV

OBJECTIVES

The objective of this proposal is to develop a nanostructured nano-biophotonic able to accurately detect circulating miRNAs, that is at same time cheaper and have limited invasiveness compared to the methods currently used for screening.

Optical Tomography, digital holography, microfluidics, numerical algorithms, fast processing, cell characterization.

ABSTRACT 

Recently, the Tomographic flow cytometry by digital holography has been established as the new tomographic principle to recover the 3D refractive index mapping of circulating cells. The main goal is the development of new diagnostic systems and computational tools for single Circulating Tumor Cells analysis, through the high-throughput tomographic imaging in a microfluidic platform. The PhD research activity will be hosted by the laboratories of ISASI-CNR located in Pozzuoli, within the Pietro Ferraro’s research group.

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVES

Development of new lab on a chip devices, algorithms and computational tools for phase contrast tomography of circulating tumor cells with the aim to implement the liquid biopsy paradigm.

ABSTRACT

Inflammation, oxidative stress are pre-conditions to neurodegenerative diseases from early to terminal stages. In the central nervous system (CNS), oxidative damage occurs much more easily than in other tissues, it notes the greater metabolic activity, generating a consequent greater quantity of oxidants and consequently its disposal. Thus the identification and use of new markers of oxidative stress, and the technique to detect them, represent a promising strategy to establish if/how molecular targets are damaged, identify such mechanisms in pathological events associated with neurodegeneration. In this program we plan to study disease related to neurodegenerative disorders [e.i. Alzhaimer (AD), Multiple Sclerosis (MS), Parkinson (PD)]. The activity is mainly focused to the definition of optic fiber biosensor activated by antibodies/target detection using new biomarkers to detect both in-vitro and in-vivo the initiation of oxidative stress, a sign for neuronal degeneration. The assay will be assembled in a prototype with use of a biosensor in detecting in vivo the disease in small rodents. We aim to build the bases for the development of a diagnostic instrument to detect initiation of neurodegeneration for the use in medical practice in patients affected. 

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVES

Functional genomics has identified those propitiatory mechanisms of the initial state of neurodegenerative disease. Analysis technologies of these phenomena, based on fibre optic detection platforms, will be extensively investigated. In fact, the close collaboration of the partner of the proposal that well balance the necessary skills, will put the student to face the issues with solid bases both technological and life science related questions as devoted to neuroscience and diagnostic biomarker discoveries.

ABSTRACT

In the last years there has been an increasing interest to try to reduce the collateral effects in any kind of clinical therapy. In particular, the precision medicine has become a strategical target in oder to reduce the quantity of drug to be delivered to the patient. This approach is becoming almost a golden rule in any oncology threatment. On this line of argument and taking advantage on the tremendous progress made in the field of optical fiber sensors a new idea came out the lab on fiber from which the most natural extension for medical application was the hospital in the needle.
The Hospital in the Needle is a large research strategy finalized to realize a single needle able to simultaneously perform, with only one insertion, all the following operations:
• Detection of cancer markers and MIRNA
• High resolution localized ecography totally integrated inside the needle
• Optical recognition of sick areas by linear and non linear optical spectroscopy
• Ultrasound selective destructions of sick tissue
• Localized drug delivery
• System for automatic guidance of the needle
• Laser surgery

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVES

The objective of this proposal is to develop a nanostructured nano-biophotonic able to accurately detect circulating miRNAs, that is at same time cheaper and have limited invasiveness compared to the methods currently used for screening.

ABSTRACT

The proposed project aims at the development and the experimental validation of a lowcomplexity microwave imaging device capable of addressing currently unmet clinical needs arising in brain stroke diagnosis and treatment, namely early diagnosis and monitoring in the post-acute stage. The project will be developed within an international intersectoral (academic/medical/enterprise) consortium of partners with a background in electromagnetic engineering, medical sciences and imaging technologies.

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVES

The project aims at improving the effectiveness of brain stroke diagnosis and treatment by introducing an innovative technological solution capable of performing early-stage diagnosis and continuous monitoring at the patient’s bedside.

ABSTRACT

The research aims to design and develop small and lightweight sensors for non-invasive, ubiquitous patient monitoring. The continuous acquisition of vital parameters such as cardiac rhythm, respiratory rate, cardiac mechanics, blood pressure in addition to the activity level provides doctors with additional information on the patient's health and may supports more prompt diagnoses and therapies. Sensors wireless connectivity with mobile devices will allow to provide telemedicine applications. 

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVES

Design of innovative sensors for continuous patient monitoring. Development of prototype devices easily wearable, low-power and with wireless connectivity. implementation of data analysis and an integrated  telemedicine system.

Accelerator-based HPC for Genomic computational building blocks

ABSTRACT

Over the past two decades, genomic has paved the way for new breakthroughs in biology and medicine. The ability to effectively handle and process genomic information, e.g. for activities like analysing and aligning DNA and protein sequences as well as generating 3D models of protein structures, is by all means crucial. The activity is focused on understanding the computational implications of next-generation sequencing approaches as well as investigating developments at the algorithm and implementation level matching the opportunities of emerging high-performance computing (HPC) accelerator-based technologies.

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVE

The main objectives of the activity will include:

• studying the computational building blocks in current genomic applications;
• investigating efficient implementation approaches based on emerging accelerator-based architectures, including GPU and FPGA devices;
• demonstrating the proposed approaches on next-generation HPC platforms, including large scale HPC facilities and/or small-scale innovative prototypes.

AI-supported modeling for retrospective and prospective health-related studies (e.g. infectious diseases due to COVID-19).

ABSTRACT

Health-related analyses generate huge amounts of heterogeneous data. Obtaining knowledge from these “big data” is both challenging and promising for data-driven medicine, that can benefit from AI tools to infer models for such complex problems. The PhD research activities will include model design, optimization, and validation, applied to prospective and retrospective studies, with the support of the MS partner (including data sanitization operations, and resulting analysis and validation). The PhD student will spend at least six months abroad working under the guidance of one or both our foreign partners, University of Warwick (UK) and University of Saint Louis (US).

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVES

Main goals include the development and application of innovative approaches to prospective and retrospective studies, aimed at modeling the complexity of infectious diseases. The approaches will be supported by AI and Big Data technologies.

Delivery Manager of Cognitive Computing for Neuroncology 

No More Available

Already assigned to a PhD student of cycle XXXV

From Metanalysis to the Cognitive Computing approach in Brain Tumors / Rare Tumors

ABSTRACT

Starting from structured and structured medical data, cognitive computing approaches has the aim to derive results and correlations that can be used later with widely validated statistical strategies such as standard and network meta-analysis.  The Standard Metanalysis and the most advanced Network Metanalysis, was used in an original research conducted at the Operative Unit of Neuroncology / Rare Tumor Regional Center of the AOU Federico II

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVE

Acquire structured and unstructured data, and implement flows and components shown in the architecture above

ABSTRACT

Multidisciplinary Prostate Cancer Units are designed to facilitate cross consultation and joint decision-making based upon diagnostic evidence to patients. At present, substantial gaps exist in their ability to accurately predict outcome and to counsel patients on short-mid and long-term treatment options. We propose to derive a Quality of Life factor through artificial intelligence and Big Data analytics, collecting, and analyzing data from 3 National Institutions, to understand how a patient’s quality of life changes over time according to type of treatment received and disease progression, also taking into account comorbidities and their own progression.

Available

Can be assigned to one doctoral student of cycle XXXVI

OBJECTIVES

Derive a Quality of Life factor through artificial intelligence and big data analytics, to create a comprehensive patient profile that will ultimately save time, consolidate knowledge, give emotional support, provide measurement of physical and mental health, and personalized treatment.

ABSTRACT

Nowadays electronic medical records, billing, clinical systems data from wearables and various pieces of research provide huge amount of healthcare information. Careful analysis of these data can lead to smarter decisions, better patient care and cost savings. In this context the development and usage of analytics and data science techniques represent a valuable decision support tool for the improvement of the clinical care activities and prevention of disease or health incidents.

Available

Can be assigned to one doctoral student of cycle XXXVI

OBJECTIVES

Main objectives are the processing and development of data science techniques for: i) drug discovery and quick/precise diagnosis by the processing of clinical and laboratory reports; ii) healthcare cost reduction and resource exploitation optimization (room usage, personnel scheduling, device maintenance, etc.).

Giovanni Poggi

Development of a Remote Ecosystem for implanted Neuromodulator to realize real-time Adaptive Therapy for Neurological Diseases.

Marco Lops

ABSTRACT

The usage of adaptive neuromodulation devices with simultaneous sensing and stimulation is the most recent advance in clinical neurological therapy. Sensing and stimulating specific areas in the nervous system will lead to maximize global knowledge about disease model, minimize time delays for therapy actuation and investigate the instantaneous response to a stimulation, enabling thus the deployment of a medical artificial intelligence as real-time therapy controller. The capability to grant a viable, low-energy communication layer between Implanted devices and computing resources is essential to allow the flourishing of neuromodulation as a continuous bioelectronic medicine

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVES

Develop a remote controller system that could enable a use case involving end-to-end adaptive-loop neuromodulation, in order to:

• minimize energy expenditure in the implanted pulse generator;
• fulfil therapeutic task (e.g. damping oscillating behaviour in neurological disease like Parkinson, essential tremor, bypass damaged nervous areas, forecast seizures) while minimizing potential side-effects;
• providing data exposure to third-parties in order to provide data for analytics and AI system;
• enable a reliable and non-invasive patient-centric monitoring system for chronical disease.
• allow interoperability with other medical use-cases related to tele-health system

Paolo Bifulco

ABSTRACT

The research aims to improve knowledge on the electrical potential generated by neurons in the brain in physiological condition and in some diseases such as epilepsy. Acquisition of biopotentials by means of electrode matrices placed directly on the brain cortex combined with anatomical information obtained by CT and MRI can provide more accurate information about the functioning of various brain areas. This can enrich our knowledge about neuroscience issues, support more specific diagnoses and treatments of pathologies and design new brain computer interfaces.

Available

Can be assigned to one doctoral student of cycle XXXVI

OBJECTIVES

To obtain accurate anatomical localization of neuronal population that generate specific EEG waves by means of biomedical signals and images processing. Interpretation of some brain functions in healthy and pathological subjects. Development of diagnosis and therapy support tools.

ABSTRACT

Our lives depend more and more on the correct functioning of computer-based medical devices, ranging from wearable appliances to surgical robots. Nevertheless, as also witnessed by recent studies, software malfunctions and cyber attacks targeting such devices may harm patient health or cause sensitive data leakages.  With the collaboration of Italian and foreign partners, the aim of the research is to analyse the potential threats in current and future medical applications and define/experiment actionable countermeasures.

Available

Can be assigned to one doctoral student of cycle XXXVI

OBJECTIVES

- Analyze the current practice for patient data treatment and data collection from real equipment
- leverage real-time data analytics solutions for on-line fault or attack detection
- experiment with real-time software containerization to isolate critical components

Francesco Amato

ABSTRACT

Cardiovascular diseases represent, to date, the major cause of mortality worldwide. Diagnosis of the most frequent of such disease, Acute Myocardial Infarction (AMI), requires the evaluation of time-series measurements of specific cardiac biomarkers. The project will develop novel dynamical models, which synthetically describes the basic mechanisms underlying cardiac troponin release into the plasma, after the onset of AMI. The aim of the project is to provide the clinicians with a quantitative tool to analyze such timeseries, to enhance the diagnostic procedures 

OBJECTIVES

An experimental campaign will be performed versus a dataset of AMI patients treated at the Interventional Cardiology unit of the Catanzaro University Hospital, to show the potentially relevant implications on both the quality and cost of diagnosis and prognosis of the AMI pathology.

ABSTRACT

The goal of this research activity is the development of computational tools and algorithms for diagnostics at the single cell level by using holographic imaging in opto-fluidic environments. Recently, optical imaging and microfluidics was used synergistically to synthesize novel functionalities for biological samples characterization. Among optical imaging modalities, the label-free quantitative phase imaging by digital holography has been demonstrated as one of the most powerful method to investigate biological samples for diagnostic purposes. The digital holography research unit at the Istituto di Scienze Applicate e Sistemi Intelligenti “E. Caianiello”, Consiglio Nazionale delle Ricerche (ISASI-CNR), has been recognized as worldwide leader in the aforementioned fields, especially for applications in blood diseases diagnostics.

Available

Can be assigned to one doctoral student of cycle XXXVI

OBJECTIVES

The PhD research activity will focus on the development of new algorithms and computational tools for:

• Fast and accurate identification of rare cells in blood samples though suitable label-free biomarkers.
• Speeding up the holographic processing with the aim to implement the real-time point-of-care diagnostics paradigm.
• Design and implementation of new opto-fluidics solutions.

The possibility to employ deep learning based strategies to achieve the proposed goals will be considered

ABSTRACT

Understanding when a patient with bladder cancer is in a real progression of disease requires a great deal of interpretation of a huge amount of data that often may not be analyzed effectively by the oncologist when a decision must be taken. The aim of the research is to develop an appropriate classification of cancer that indicates, through machine learning techniques and statistical analysis of patients’ clinical variables, the status of the bladder cancer, how it is progressing and if a change of therapy is needed. The research will be in cooperation with Clinical Research Technology S.r.l. (IT), European Institute of Oncology (IT) and Klinik Sankt Moritz (CH).

Available

Can be assigned to one doctoral student of cycle XXXVI

OBJECTIVES

The aim is to help the oncologist to better understand when a change of therapy is needed through machine learning methodologies and statistical analysis of clinical variables such as the patient's medical condition, the aggressiveness of the cancer, the effectiveness of the treatments.

ABSTRACT

In subjects with autoimmunity (i.e., multiple sclerosis), an important aspect of the immune system is how T lymphocytes respond to T cell receptor (TCR) stimulation. This is a key event controlling the fate of naïve T lymphocytes impacting on activation, differentiation and regulation of the immune response, which has been shown to be impaired in subjects with autoimmunity. T cell responsiveness is inherently stochastic (i.e., it cannot be predicted a priori) due to different sources of noise that are intrinsically produced by the underlying biochemical reactions. Such a noise may influence T cell activation grade by degrading the information transmission from the TCR.

Available

Can be assigned to one doctoral student of cycle XXXVI

OBJECTIVES

The main focus of this research activity is to develop specific mathematical models to understand the kinetic and dynamic issues regulating the TCR stimulation process and its possible alterations during autoimmunity. Results from this study could help to identify the relevant molecular targets and pave the way for the development of novel therapies aimed at restoring T cell responsiveness in autoimmunity.

Oncological Pain Automatic Assessment

ABSTRACT

In oncological patients, pain is one of the most disabling symptoms. The correct approach to pain treatment has a positive impact on her prospectives to afford other therapies for recovery. Therapist defines treatment based on subjective pain scales and continuously refine drug dosages, based on the patient responses, in a loop that sometimes hardly converging. This project aims at creating an automatic pain assessment protocol, based on the collection of multimodal data generated during a patient's life. Patients will be remotely monitored, recording texts (questionnaires), video (self-report), biometric parameters (recorded via personal devices), drug timing scheduling, etcetera. This project falls in the area of big data technologies for health. Physicians will cooperate with computer scientists and data analysts to design, process, and evaluate this flux of data to be used both for real-time monitoring and training of AI systems.

Available

Can be assigned to one doctoral student of cycle XXXVI

OBJECTIVES

• the creation of a dataset for pain assessment substituting subjective scale for self-evaluation;
• the definition of an interventionist protocol in the field of refining treatments and drug dosages ;
• the design of AI-based decision making systems in the field of big data for oncological purposes.

ABSTRACT

A key challenge for the development of personalized therapies is the ability of delivering drugs in situ and avoid unwanted side effects to the patients. A promising approach is the use of synthetically engineered cell populations with advanced functionalities whose collective behavior can be carefully controlled so that they can move to the target area and release some drug. This proposal focuses on the development of multicellular control strategies to create microbial consortia in which cell populations cooperate to realize this challenging goal. The project will be supervised by the proponent together with prof Brunetti and prof Surace at the Dept. of Translational Medicine and will involve active collaboration with leading groups at ETH and Bristol and the start-up companies at TIGEM.  

No More Available

Already assigned to a PhD student of cycle XXXV

OBJECTIVES

- Develop synthetic biology approaches for drug delivery based on multicellular consortia;
- Synthesize gene regulatory networks to implement the desired functions in vivo;
- Adopt and develop methods from ICT to achieve multicellular control of bacterial and mammalian cell populations;
- Carry out in-vivo validation using optogenetics and microfluidics platforms.

ABSTRACT

The need of having advanced tools for data analysis is one of the most important trends in the current economic, technological and social scenario and, nowadays, it is mainly based on methodologies and techniques of artificial intelligence and BigData. One of the goals of modern medicine is the "precision medicine", whose purpose is to offer personalized treatments based on the specific characteristics of patients and pathologies. In this context, new analysis techniques such as Radiomics is becoming a novel research field. The analysis of the large number of data derived from medical images allows to recognize many characteristics of cancers and they can be integrated with other molecular and genomic characteristics by obtaining further correlations.

Available

Can be assigned to one doctoral student of cycle XXXVI

OBJECTIVES 

The implementation of a decision support system based on a sematic multimedia bigdata to support the analysis of medical images represented by novel radiomics descriptors and texture analysis.

ABSTRACT

Software applications for the Health care are becoming more and more widespread and complex, as they can rely on the most modern ICT technologies. To cite a few, they can be developed as event-based and context-aware mobile systems, can be integrated with distributed software architectures for data collection, use machine learning techniques to support decision-making processes, or exploit virtual or augmented reality technologies. To manage the complexity of developing this type of system and assure their quality, acceptability and dependability, it is increasingly necessary to invest in the search for new development paradigms, architectures and techniques that simplify their development and validation.

Available

Can be assigned to one doctoral student of cycle XXXVI

OBJECTIVES

- Develop innovative model driven solutions for the development, testing, validation and certification of mobile, sensor-based and context-aware solutions for health care domain;
- Carry out experimental validation of the proposed approaches by case studies in selected health care fields

ABSTRACT

Sentinel node (SLN) biopsy is used to stage patients with early-stage breast cancer with clinically negative axillary nodes, but it is invasive and with complications. To overcome such issues this research aims to predict SLNs metastasis using radiomics on T1w-MRI of the native tumor, even in combination with histological features and patients clinical data, supporting treatment decision by providing a non-invasive approach in clinical routine.

No More Available

Already assigned to a PhD student of cycle XXXV

OBJECTIVES

Development of  a radiomic platform to predict sentinel nodes metastasis in a non-invasive ways using artificial intelligence-based methods extracting information from T1w-MR scans and patient clinical data.

ABSTRACT

What we release into the environment can come back to us, often with negative effects. At high exposure levels, environmental pollution can cause adverse health effects. There are no doubts on the negative effects of environmental pollution on human health, what can still be verified is the correlation between implicated variables (lifestyle, pollutant, social context) and the appearance of many diseases (respiratory, oncological, etc.).
This project aims to integrate a huge amount of health, socio-economic and environmental data in order to determine the cause-effects relationships between environmental pollution and human health. In particular, the goal is to propose the study and the development of a forecast model related to the spread of pollutants in a given area and of a correlation model between the concentration of the very same pollutants and health data of people living in the analysed geographical area.
It’s of utmost importance to ensure the semantic interoperability between different databases, i.e. the capability of a computer system to cooperate and exchange data with other systems, in a more or less complete and error-free way, with reliability and resource efficiency. Interoperability’s purpose is to ease interaction between different systems as well as data exchange and reuse between not homogenous information systems.

Available

Can be assigned to one doctoral student of cycle XXXVI

OBJECTIVES

The increase in pollution-related diseases turned science’s attention to the correlation between man-environment to safeguard the living condition of the planet and its inhabitants. Starting from the concentration maps of the pollutants taken into consideration it will be possible to identify impact areas and/or the ones with higher pollutants concentrations. Information obtained will support the acknowledgment of a correlation with health data regarding patients suffering respiratory, oncologic, etc. The development of knowledge on the relationship between environment and human health is mandatory to develop programs useful in protecting environment and in preventing related diseases.

ABSTRACT

The project consists on the development of an innovative m-Health system based on wearable devices in e-textile technology. M-Health means the provision of healthcare services supported by "mobile" devices which the most recent studies identify as the ICT sector with the greatest future potential expansion; while for e-textile we mean the integration of electronic components directly into washable and sensorized garments, commercially available at low and decreasing costs and  suitable for home care based applications.

No More Available

Already assigned to a PhD student of cycle XXXV

OBJECTIVES

Project, development and experimental setting of e-textile based prototyping t-shirt and socks for biomedical physiological signals and movement analysis' indexes processing

ABSTRACT

The Covid-19 pandemic has dramatically pointed out the next urgent challenges of digital medical technologies: telemedicine, e-health, m-health, smart hospitals, digital homecare. Expectations about the potential driving role played by 5G technologies are great. After exploring the medical requirements of the considered scenarios, the PhD student is expected to develop technological solutions based on next generation 5G networks, in the context of telemedicine (e.g., digital homecare and monitoring) and smart hospitals (e.g., monitoring of isolated patients).

Available

Can be assigned to one doctoral student of cycle XXXVI

OBJECTIVES

• Comprehensive analysis of medical requirements of e-health systems in an epidemic scenario
• Comprehensive analysis of ICT requirements in the context of telemedicine and smart hospitals
• Development of m-health technological solutions fruitfully exploiting the features of 5G networks

ABSTRACT

One of the fundamental challenges in healthcare management is to achieve an efficient utilization of expensive resources, while maintaining or increasing the quality of care. Quantitative decision tools, extensively used in the industry, are not yet widely applied in the health care sector. In this context the development and usage of of decision support tools for planning and management is a challenging task.

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVES

The main objective of the research activity is the development of new support tool for solving decision operational and tactical healthcare management problems, mainly related to personnel scheduling, timetabling and scheduling and utilization of the limited resources (rooms and facilities) of an hospital.

ABSTRACT 

In the last years logistics has gained a strategic role in the management of hospitals. Managers are moving towards the use of various optimization tools, software and methods to achieve improvements in the offered services, and significant results were obtained in reducing errors, improving process quality and reducing waiting times. However, internal and external activities still require a significant effort to be re-designed and optimized for the complexity of the hospital system, the variability and unpredictability of the patient profile and the high demand for care.

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVES 

Main aim is the development of decision support tools for: designing and optimizing the healthcare integrated supply chain or parts of it; analyzing the relationship between workplace characteristics and health care cost containment practices.

ABSTRACT 

The replacement of the real world with a simulated one has found, in recent years, thanks to the innovations of ict technologies, wide spaces in different application fields ranging from micro-simulation of medical procedures to the support of cognitive rehabilitation techniques through serious games.
Application areas, apparently very distant, have in common many technologies and methodologies that represent the baggage of skills that the student will have to enrich in his training 

Available

Can be assigned to one doctoral student of cycle XXXVI 

OBJECTIVES 

A professional able to design software applications and contributing to research and technological innovation in order to reproduce real world events related to clinical procedures, healthcare organizational models or rehabilitation contexts for the education of health professionals or young people with cognitive or communication disorders .

Abstract

The goal of the proposal is to apply Hyper Accuracy 3D (HA3DTM) technology in the Gynaecological surgery (endometriosis, endometrial cancer and so on) to reconstruct, form diagnostic imaging (RM, TC, ANGIOTC), three-dimensional model of the patient anatomy to improve pre-operative planning and consequently perform faster, more precise and safer robot-guided surgery.  The study will reveal specific indications of pathologies and surgical procedures for which HA3DTM technology is more effective. 

 Available

Can be assigned to one doctoral student of cycle XXXVI 

Objectives

The objectives are: to develop a tool to improve pre-operative planning; to improve robot-guided surgery towards enhanced robot autonomy; to understand the usefulness of the new technology compared to the state of the art.

The research aims to realize a semi-autonomous robotic system to assist dental implant surgery. The student will work closely with dental surgeons to understand their needs with the goal of overcoming surgical and treatment challenges. The developed robotic system will be manually guided by the surgeon to perform surgery exactly as it has been planned preoperatively, relative to the patient’s CT scan, by using haptic cues, visual guidance and multisensory feedback in a shared control framework.

 No More Available

Already assigned to a PhD student of cycle XXXV

Objectives

The goal is to develop a robotic system that helps surgeons to increase the accuracy of implant placement in the bone, to speed up the process and to promote less invasive procedures, improving patient outcomes and surgeon comfort.

Abstract

Computer assisted surgery has many advantages (minimized post-operative pain; sped up recovery; increased comfort for the surgeon; improved surgery's performance; reduced haemorrhaging; reduced risk of infections). There is however still a long way to go towards partial or full automation surgical interventions while the actual research activity is based on automating basic surgery.
The research activity will develop the hardware accelerators and the interfaces that will improve speed and accuracy of the atomic surgery tasks devised by other research groups that are part of the project. These tasks are based on the video elaboration of the Da Vinci stereo camera (the Da Vinci robot is available for the research group). Processing intensive tasks for video processing, feature extraction and tracking, will be leveraged through the use of high performance dedicated circuits.

 Available

Can be assigned to one doctoral student of cycle XXXVI 

Objectives

The research activity will assist in the automation of atomic surgical actions that joint together form a complete surgery activity. As an example, the actions of cutting, suturing, tissue repositioning, bone drilling, and tool exchange. The project aims at developing (i) real-time visual sensing and elaboration of the scene (ii) to track laparoscopic instruments, (iii) to automatically move the camera with no explicit human direction and finally (iii) to start performing simple autonomous tasks. The considered test scenario will be the urological surgeries.

The research activity is expected to deploy hardware accelerators implemented on FPGA to assist the control and tracking algorithms. The initial steps will be the extraction of stereo data from the cameras (not an easy task due to the reduced volume of the laparoscopic surgical field) and the track of the tools.

Abstract

Assistive robotics is a research field meant to help impaired individuals recovering motor functions or coping with Activities of Daily Living (ADL). The rehabilitation devices considered in the proposed research are upper-limb exoskeletons. Interaction control is the main core topic in this scenario as well as adaptive control, multimodal perception, sensory fusion and smart/friendly user control interface. The goals of the proposed activity are the development of a multi-joint dynamics model for upper-limb exoskeleton and the development of assistive control systems that can customize the amount of assistance according to the patient recovery advancement as well as the development of friendly control interfaces using multimodal sensory feedback. Open problems are related to sensitive and robust adaptation of the robotic system to the patient and safety issues.

Available

Can be assigned to one doctoral student of cycle XXXVI 

Objectives

The scientific research goals of the proposed PhD activity are: (i) to develop a multi-joint dynamics model for upper-limb exoskeleton for rehabilitation purposes; (ii) to develop adaptive control algorithms for automatic tuning of the level of assistance of upper-limb exoskeletons according to the patient recovery advancement; (iii) to optimize the assistive profile delivered by an exoskeleton through techniques of human-in-the-loop optimization and AI techniques.

Abstract

Remote Surgical Training (ReST) on Da Vinci platforms consist in dislocating tutor and second console in an operation room (OR) adiacentent to the Operation Room where the trainee is. 

Main Steps: 1.Use the environmental video camera of the main Operation Room also connecting it to the tutor console in the adjacent room so that (s)he can see and monitor everything that happens. 2.Perform remotely training tests. 3.Evaluate the data and performance by the whole OR team. 4.Make a statistical study of the data collected and prepare a detailed report on the results.

Available

Can be assigned to one doctoral student of cycle XXXVI 

Objectives

The research focuses on human factors and pedagogical effects of remotely training. The intent is to evaluate how the human-machine relationship for the trainee changes without the physical presence of tutor in the main OR. Methods to facilitate communication between tutor and trainee with respect to the operating room environment willbe explored. The trainee’s performance score will be evaluated.

Abstract

A socially Assistive Robot is intended as an assistive tool which can complement the therapist in training and rehabilitation, can be used for remote monitoring and assisting the user, and constitutes a playful agent to better engage the participants and relief from anxiety. In order to achieve these goals, it requires the ability of multi-modal perception, emotion expression, verbal and non-verbal communication, adaptive control, decision-making, and learning mechanisms.

Available

Can be assigned to one doctoral student of cycle XXXVI 

Objectives

The aim of the research activity is to develop, validate, and test in hospitals and homes interaction strategies for socially assistive robots in healthcare and home environments and adapt to each individual’s capabilities. Goal of the interaction is defined by considering the assistive role the robot has to play with respect to the patient.