Matjaz Gams

• PhD
• Head of Department at Jožef Stefan Institute

Background The importance of computational psychotherapy is increasing due to the record high prevalence of mental health issues worldwide. Despite advancements, current computational psychotherapy systems lack advanced prediction and behavior change mechanisms using conversational agents. Purpose This work presents a computational psychotherapy s...

With the rapid advancement of artificial intelligence technologies, the integration of AI concepts into educational curricula represents an increasingly important issue. This paper presents a comparative analysis of four AI large language models, ChatGPT (now GPT-4o), Bard (now Gemini), Copilot, and Auto-GPT, in the last year, progressing from the...

To address the growing need for advanced tools that enable urban policymakers to conduct comprehensive cost-benefit analyses of traffic management changes, the Urbanite H2020 project has developed innovative artificial intelligence methods. Among them is a robust decision support system that assists policymakers in evaluating and selecting optimal...

As urban populations rise globally, cities face increasing challenges in managing urban mobility. This paper addresses the question of identifying which modifications to introduce regarding city mobility by evaluating potential solutions using city-specific, subjective multi-objective criteria. The innovative AI-based recommendation engine assists...

Cardiovascular diseases (CVDs) are a leading cause of mortality worldwide, responsible for 32% of all deaths, with the annual death toll projected to reach 23.3 million by 2030. The early identification of individuals at high risk of CVD is crucial for the effectiveness of preventive strategies. In the field of deep learning, automated CVD-detectio...

ChatGPT has shown high performance in medical diagnosis, with various enhancement strategies proposed. However, national-level applications remain limited. This study explores integrating a personal medical chatbot into home environments nationwide, using knowledge from the Insieme platform, a robust electronic and mobile health system developed th...

In this study, we explore the integration of ChatGPT with the Insieme platform, a robust electronic and mobile health system designed as an Italian and Slovenian project. This integration provides a novel way in which users access medical information, offering online support from healthcare professionals and enabling interactions with a sophisticat...

This study explores the capabilities of ChatGPT, specifically in relation to consciousness and its performance in the Turing Test. The article begins by examining the diverse perspectives among both the cognitive and AI researchers regarding ChatGPT’s ability to pass the Turing Test. It introduces a hierarchical categorization of the test versions,...

Falls by the elderly pose considerable health hazards, leading not only to physical harm but a number of other related problems. A timely alert about a deteriorating gait, as an indication of an impending fall, can assist in fall prevention. In this investigation, a comprehensive comparative analysis was conducted between a commercially available m...

The objective of the URBANITE project is to design an open-data, open-source, smart-city framework to enhance the decision-making processes in European cities. The framework's basis is a robust and user-friendly simulation tool that is supplemented with several innovative service modules. One of the modules, a multi-output, machine-learning unit, i...

With the development of technology allowing for a rapid expansion of data science and machine learning in our everyday lives, a significant gap is forming in the global job market where the demand for qualified workers in these fields cannot be properly satisfied. This worrying trend calls for an immediate action in education, where these skills mu...

One key task in the early fight against the COVID-19 pandemic was to plan non-pharmaceutical interventions to reduce the spread of the infection while limiting the burden on the society and economy. With more data on the pandemic being generated, it became possible to model both the infection trends and intervention costs, transforming the creation...

Non-pharmaceutical interventions against COVID-19 and other infectious diseases seek good trade-offs between reducing the number of infections and their socioeconomic costs. We propose a framework that establishes these costs from data on interventions implemented in real life for each country taking into consideration its culture and economy. The...

Hidradenitis suppurativa (HS) is a recurrent inflammatory skin disease with a complex etiopathogenesis whose treatment poses a challenge in the clinical practice. Here, we present a novel integrated pipeline produced by the European consortium BATMAN (Biomolecular Analysis for Tailored Medicine in Acne iNversa) aimed at investigating the molecular...

From 2018 to 2021, the Sussex-Huawei Locomotion-Transportation Recognition Challenge presented different scenarios in which participants were tasked with recognizing eight different modes of locomotion and transportation using sensor data from smartphones. In 2019, the main challenge was using sensor data from one location to recognize activities w...

Implementing information and communications technology (ICT) at scale requires evaluation processes to capture the impact on users as well as the infrastructure into which it is being introduced. For older adults living with cognitive impairment, this requires evaluation that can accommodate different levels of cognitive impairment, alongside input...

The EU PlatformUptake project’s main goal is to investigate the usage of EU open and partly-open platforms in active and healthy aging (AHA) and ambient-assisted living (AAL) domains, from a software viewpoint. The aim of the project was to provide tools for a deeper interpretation and examination of the platforms, gather user feedback, and use it...

One key task in the early fight against the COVID-19 pandemic was to plan non-pharmaceutical interventions to reduce the spread of the infection while limiting the burden on the society and economy. With more data on the pandemic being generated, it became possible to model both the infection trends and intervention costs, transforming the creation...

Covid-19 has so far affected every country in the world. The Non-Pharmaceutical Interventions (NPIs) by governments have proven themselves quite effective at stopping the spread of infections, but when applied in a very strict and long-lasting manner could have devastating consequences for the economic and social well-being of the population. XPRIZ...

Data Science and Machine learning are increasingly important in the world's economy and there is an increasing gap in the job market of skilled workers. To address this the Valence project proposes the design and implementation of a Data Science and Machine Learning focused curriculum in VET high schools. As a precursor to this, we designed a surve...

To further extend the applicability of wearable sensors, methods for accurately extracting subtle psychological information from the sensor data are required. However, accessing subjective information in everyday life, such as cognitive load, remains challenging. To bring consensus on methods for cognitive load monitoring, a machine learning challe...

The COVID-19 pandemic affected the whole world, but not all countries were impacted equally. This opens the question of what factors can explain the initial faster spread in some countries compared to others. Many such factors are overshadowed by the effect of the countermeasures, so we studied the early phases of the infection when countermeasures...

Intelligent cognitive assistant (ICA) technology is used in various domains to emulate human behavior expressed through synchronous communication, especially written conversation. Due to their ability to use individually tailored natural language, they present a powerful vessel to support attitude and behavior change. Behavior change support system...

Artificial intelligence (AI) and its sister ambient intelligence (AmI) have in recent years become one of the main contributors to the progress of digital society and human civilization [...]

bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">The increasing trend of mental health issues, especially among younger people, is not a new phenomenon. World organizations, leaders, and decision-makers are recognizing its devastating effect, resulting in mental health well-being appearing in goal 3 of...

In many ambient-intelligence applications, including intelligent homes and cities, awareness of an inhabitant’s presence and identity is of great importance. Such an identification system should be non-intrusive and therefore seamless for the user, especially if our goal is ubiquitous and pervasive surveillance. However, due to privacy concerns and...

This paper presents relations between information society (IS), electronics and artificial intelligence (AI) mainly through twenty-four IS laws. The laws not only make up a novel collection, currently non-existing in the literature, but they also highlight the core boosting mechanism for the progress of what is called the information society and AI...

Finding the best classifiers according to different criteria is often performed by a multi-objective machine learning algorithm. This study considers two criteria that are usually treated as the most important when deciding which classifier to apply in practice: comprehensibility and accuracy. A model that offers a broad range of trade-offs between...

To further extend the applicability of wearable sensors in various domains such as mobile health systems and the automotive industry, new methods for accurately extracting subtle physiological information from these wearable sensors are required. However, the extraction of valuable information from physiological signals is still challenging-smartph...

Falls are a significant threat to the health and independence of elderly people and represent an enormous burden on the healthcare system. Successfully predicting falls could be of great help, yet this requires a timely and accurate fall risk assessment. Gait abnormalities are one of the best predictive signs of underlying locomotion conditions and...

This paper describes the design for a personal mental health virtual assistant with novel ambient intelligence integration-PerMEASS. It is specifically designed to provide help for three mental health issues: stress, anxiety, and depression. Its assistance in these issues is based on two very closely related and trending multidisciplinary computer...

This study introduces two datasets for multimodal research on cognitive load inference and personality traits. Different to other datasets in Affective Computing, which disregard participants’ personality traits or focus only on emotions, stress, or cognitive load from one specific task, the participants in our experiments performed seven different...

Short-term load forecasting is integral to the energy planning sector. Various techniques have been employed to achieve effective operation of power systems and efficient market management. We present a scalable system for day-ahead household electrical energy consumption forecasting, named HousEEC. The proposed forecasting method is based on a dee...

Home energy-management systems can optimize performance either by computing the next step dynamically – online, or rely on a precomputed strategy used to introduce the next decision – offline. Further, such systems can optimize based on only one or several objectives. In this paper, the multi-objective optimization of offline strategies for home en...

It is only a matter of time until autonomous vehicles become ubiquitous; however, human driving supervision will remain a necessity for decades. To assess the driver’s ability to take control over the vehicle in critical scenarios, driver distractions can be monitored using wearable sensors or sensors that are embedded in the vehicle, such as video...

The Sussex-Huawei Locomotion-Transportation Recognition Challenge presented a unique opportunity to the activity-recognition community to test their approaches on a large, real-life benchmark dataset with activities different from those typically recognized. The goal of the challenge was to recognize, as accurately as possible, eight locomotion act...

Human falls are common source of injury among the elderly, because often the elderly person is injured and cannot call for help. In the literature this is addressed by various fall-detection systems, of which most common are the ones that use wearable sensors. This paper describes the winning method developed for the Challenge Up: Multimodal Fall D...

Chronic heart failure (CHF) affects over 26 million of people worldwide, and its incidence is increasing by 2% annually. Despite the significant burden that CHF poses and despite the ubiquity of sensors in our lives, methods for automatically detecting CHF are surprisingly scarce, even in the research community. We present a method for CHF detectio...

The Sussex-Huawei Locomotion-Transportation Recognition Challenge presented a unique opportunity to the activity-recognition community to test their approaches on a large, real-life benchmark dataset with activities different from those typically being recognized. The goal of the challenge was to recognize eight locomotion activities (Still, Walk,...

The Sussex-Huawei Locomotion Challenge 2019 was an open competition in activity recognition where the participants were tasked with recognizing eight different modes of locomotion and transportation. The main difficulty of the challenge is that the training data was recorded with a smartphone that was placed in a different body location than the te...

In the past decade, public institutions and private entities have launched large campaigns of digitization of cultural artefacts leading to the creation of massive digital collections like Europeana, Europe's digital cultural library, museum, and archive. It offers public access to millions of digital objects from thousands of contributing heritage...

Chronic heart failure (CHF) affects over 26 million of people worldwide and represents a significant societal, logistic and financial burden both for the patients and for the healthcare system, necessitating novel management approaches of this patient population. In this paper, we explore the possibilities of detecting heart failure worsening based...

Ambient intelligence (AmI) is intrinsically and thoroughly connected with artificial intelligence (AI). Some even say that it is, in essence, AI in the environment. AI, on the other hand, owes its success to the phenomenal development of the information and communication technologies (ICTs), based on principles such as Moore's law. In this paper we...

Virtual assistants and similar software tools are gaining importance among phone and computer users. The most well-known assistants (Siri, Cortana, Google, etc.) provide general information to users and cannot be adapted to specific needs. Custom implementations usually cover specific domains and are specialized to provide a comprehensive set of in...

In recent years, activity recognition (AR) has become prominent in ubiquitous systems. Following this trend, the Sussex-Huawei Locomotion-Transportation (SHL) recognition challenge provides a unique opportunity for researchers to test their AR methods against a common, real-life and large-scale benchmark. The goal of the challenge is to recognize e...

The Sussex-Huawei Locomotion-Transportation recognition challenge presents a unique opportunity to the activity-recognition community - providing a large, real-life dataset with activities different from those typically being recognized. This paper describes our submission (team JSI Classic) to the competition that was organized by the dataset auth...

People with Profound Intellectual and Multiple Disabilities (PIMD) stand for a broad and very heterogeneous spectrum of people that are characterised by some common aspects like an severe intellectual disability usually in combination with a lack of conventional and symbolic communication abilities, coupled with the need for high levels of support...

Person identification is a process through which a person is recognized using some information about him-/herself. Usually this is performed by asking the user to perform some action, e.g., to apply a token (card), enter a PIN code, scan a finger, or something similar. This paper describes an approach for recognizing a person entering a room using...

Blood pressure is one of the most valuable vital signs. Recently, the use of bio-sensors has expanded, however, the blood pressure estimation still requires additional devices. We proposed a method based on complexity analysis and machine learning techniques for blood pressure estimation using only ECG signals. Using ECG recordings from 51 differen...

Extensive skill training using simulations for improving decision making has become a common practice in a multitude of domains and professions due to the expense or danger of training in real-life circumstances, or to speed up the learning process. In this work we propose a novel approach called PATDS (Performance Analysis of Training through Data...

We present a web application to inform users about different types of viral hepatitises. The core of the application is a questionnaire about past behavior and risk factors. Based on the answers, it produces a personalised overview of any risky actions that the user might have taken in the past. The site also contains general information about thes...

A rapidly ageing population in the developed world brings a necessity and opportunity for the AI-based ICT solutions. We present a system, developed within the scope of an EU H2020 project IN LIFE, which aims to prolong the age at which individual can still live at home independently while at the same time increasing comfort and safety. In this dem...

In this paper, we present the European H2020 project INLIFE (INdependent LIving support Functions for the Elderly). The project brought together 20 partners from nine countries with the goal of integrating into a common ICT platform a range of technologies intended to assist community-dwelling older people with cognitive impairment. The majority of...

Background: Blood pressure (BP) measurements have been used widely in clinical and private environments. Recently, the use of ECG monitors has proliferated; however, they are not enabled with BP estimation. We have developed a method for BP estimation using only electrocardiogram (ECG) signals. Methods: Raw ECG data are filtered and segmented, a...

Arousal recognition from physiological signals is a task with many challenge remaining, especially when performed in several different domains. However, the need for emotional intelligent machines increases day by day, starting with timely detection and improved management of mental disorders in mobile health, all the way to enhancing user experien...

We present the concept of an Intelligent Assistant Carer system for the elderly, designed to help with active aging and to facilitate the interactions with carers. The system is modular, allowing the users to choose the appropriate functions according to their needs, and is built on an open platform in order to make it compatible with third-party p...

Affect recognition is an important task in ubiquitous computing, in particular in health and human-computer interaction. In the former, it contributes to the timely detection and treatment of emotional and mental disorders, and in the latter, it enables indigenous interaction and enhanced user experience. We present an inter-domain study for affect...

The recent advances in machine learning (ML) and sound processing have considerably expanded the possibilities provided by such techniques. The next step are open-access tools in existing ML toolkits for general sound ML tasks. We present JSI Sound, one of the first tools of this kind, developed within the Orange data mining software. The input for...

Being able to detect stress as it occurs can greatly contribute to dealing with its negative health and economic consequences. However, detecting stress in real life with an unobtrusive wrist device is a challenging task. The objective of this study is to develop a method for stress detection that can accurately, continuously and unobtrusively moni...

Refrigeration systems have been a vital component of our lives for more than a century. Apart from storing food, they are used to store sensitive goods such as pharmaceutical products or reactive chemicals. The deterioration of the refrigeration system performance due to aging or malfunction directly affects the quality of stored goods. Therefore,...

We present a web application to detect risks related to sexually transmitted infections (STIs). The application works as a questionnaire about sexual behaviour and risk factors for STIs and, based on the answers, calculates the risk of being infected. The application also works as an informational tool with educating about STIs and prevention. It u...

Increasing demand of resources has driven research towards design of mechanisms that address resourcedemand management, which usually focus on balancing peak demand and optimal device scheduling. While balancing homogeneous sources is well known, the goal of this paper is to balance the demand of heterogeneous resources with a convex cost function...

Training in simulators through serious games is widely used in domains where it is too dangerous to train in a real environment. Simulations can help to model complex social and psychological aspects and can enable repetitiveness during game-based learning, which is especially important when opposing or cooperating humans can get hurt. When a train...

Continuous exposure to stress is harmful for mental and physical health, but to combat stress, one should first detect it. In this paper we propose a method for continuous detection of stressful events using data provided from a commercial wrist device. The method consists of three machine-learning components: a laboratory stress detector that dete...

While turning attention to the fantastic technical AI progress is no doubt a reasonable orientation, distancing from predicting the future seems strange, in particular in the land of the free and brave. Nevertheless, AI is changing our everyday life and future at a pace unbelievable even for AI experts.

The paradox in the question originates from the well-known children story of Pinocchio, starring a wooden boy whose nose grows whenever he is lying. The paradox stems from his statement: "My nose is growing". In real life, a statement that a person's nose grows should not cause any problems, since noses have the property of growing; however, the st...

Purpose In this paper, the authors aim to propose a method for learning robotic assembly sequences, where precedence constraints and object relative size and location constraints can be learned by demonstration and autonomous robot exploration. Design/methodology/approach To successfully plan the operations involved in assembly tasks, the planner...

Although wearable accelerometers can successfully recognize activities and detect falls, their adoption in real life is low because users do not want to wear additional devices. A possible solution is an accelerometer inside a wrist device/smartwatch. However, wrist placement might perform poorly in terms of accuracy due to frequent random movement...

Classification trees are attractive for practical applications because of their comprehensibility. However, the literature on the parameters that influence their comprehensibility and usability is scarce. This paper systematically investigates how tree structure parameters (the number of leaves, branching factor, tree depth) and visualisation prope...

We present a study of buzzing sounds of several common species of bumblebees, with the focus on automatic classification of bumblebee species and types. Such classification is useful for bumblebee monitoring, which is important in view of evaluating the quality of their living environment and protecting the biodiversity of these important pollinato...

In buildings, classical heating controllers are based on user-preferred settings of the indoor temperature at particular times of day. The controllers alter the heating or cooling to achieve a desired temperature. Since comfort also relates to other factors, such as human activity rate and indoor air humidity, we developed a novel comfort regulator...

The paper describes an approach for recognizing a person entering a room using only door accelerations. The approach analyzes the acceleration signal in time and frequency domain. For each domain two types of methods were developed: (i) feature-based – use features to describe the acceleration and then uses classification method to identify the per...

In this paper we present a machine learning approach to activity recognition using a wristband device. The approach includes: data acquisition, filtering, feature extraction, feature selection, training a classification model and finally classification (recognizing the activity). We evaluated the approach using a dataset consisting of 10 everyday a...

The rapid aging of the population drives the development of pervasive solutions for the care of the elderly, which often involve fall detection with accelerometers. These solutions are very accurate in laboratory conditions, but can fail in some real-life situations. To overcome this, we present the Confidence system, which detects falls mainly wit...

This paper presents a novel approach to the adaptation of multidimensional data models to user-specific needs. The multidimensional data models used in contemporary business-intelligence systems are inherently complex. In order to reduce the complexity of these models, we propose using a qualitative multiple-criteria decision modelling method that...

This paper describes a novel system for identification of a person entering a room using only the door acceleration data. The main hypothesis is that each user has a unique way of opening and closing the door, and that the differences are sufficient to enable accurate identification of a limited set of people. In particular, two approaches are prop...