About the project
Objective
The objective of the project is to identify and characterize clusters of patients and their dynamics over time such that the patients respond optimally to medical caregivers’ interventions and medications. In collaboration with Karolinska Institute and Region Stockholm, we will focus on dementia patients for personalized treatments and develop an advanced AI-based predictive analysis method to help medical caregivers for their decisions.
Background
It has been observed that patients suffering of a same disease can respond differently to the same medication. This can slow down medical treatments and even worsen the disease prognoses. How can we then make medical treatments personalized to improve the disease progression of patients over time?
Dementia patients have multiple follow-ups over time, generating longitudinal data. In a large patient pool, there can be several clusters, some representing patients who are more receptive and doing better with interventions and medications, and other clusters representing a more limited scope. Individual patients may also change clusters over time. Predictive analysis is required to make treatment decisions based on a patient’s personalized profile and the patient’s similarity across other patients over time. Modern sequence-based AI-methods are useful to make predictions on this type of data, and topological data analysis can give insights about characteristics and relations between patients by studying the shape of the data. These methods can help us find clusters of patients, characterize their disease progression and develop a decision care system for personalized treatments.
About the Digital Futures Postdoc Fellow
Belén García Pascual completed her PhD in biomathematics in October 2024 at the University of Bergen (Norway). She developed mathematical and computational models to explore questions in evolutionary and cell biology, with a focus on mitochondrial genes and evolutionary progression pathways of antimicrobial resistance. During the PhD, Belén did an industry internship at DNV in Oslo (Norway) researching how large language models can generate realistic synthetic data in healthcare. Before, she took her master in topology at the University of Bergen, and her bachelor in mathematics at Complutense University of Madrid (Spain).
Main supervisor
Martina Scolamiero
Co-supervisor
Saikat Chatterjee
About the project
Objective
The main objective is to develop a Content-Based Image Retrieval (CBIR) system using a large database of longitudinal brain Magnetic Resonance Imaging (MRI) of patients with dementia. By using artificial intelligence, the system will detect patterns and similarities in the longitudinal images, empowering healthcare professionals to predict treatment outcomes and deliver personalized care. Eventually, this tool aims to simplify decision making, improve patient care and make healthcare more efficient and cost-effective.
Background
As the global population ages, dementia diseases are becoming increasingly prevalent, currently affecting approximately 47 million individuals and imposing an economic burden of around $2.8 trillion. Innovative computer-aided diagnosis techniques, particularly CBIR, have been transformed by enhancing the retrieval of relevant images for patients with or at risk of dementia. Scientific evidence suggests that spatio-temporal patterns from longitudinal recordings can significantly improve outcomes in cross-sectional studies. However, progress in this field has been hindered by limited access to longitudinal databases, small dataset sizes, and ineffective analytical methods.
About the Digital Futures Postdoc Fellow
Félix received his PhD in Electronic Engineering from the Universitat Politècnica de València. His research has centered on applying artificial intelligence and signal processing techniques to biomedical data analysis. His thesis focused on developing a state-of-the-art preterm labor prediction system using Electrohysterography (EHG), successfully addressing challenges such as low incidence rates and limited data availability.
His work spanned the entire research process, from clinical data acquisition and signal preprocessing to the design of an automated decision-making system. Building on this foundation, he has expanded his proficiency in medical imaging modalities, and gained experience with modern deep learning architectures.
Main supervisor
Rodrigo Moreno, Associate Professor, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), KTH Royal Institute of Technology
Co-supervisor
Chunliang Wang, researcher with Docent title at School of Technology and Health (STH), KTH Royal Institute of Technology
About the project
Objective
The research aims to fill the gap in women’s health by designing and studying the use of digital health technologies for intimate care and the tacit interpersonal relationships associated with intimate care. At the personal level, the research aims to improve awareness of intimate care by co-designing and developing innovative interactions with the technology using innovative design methods such as Soma Design. At the interpersonal level, the research aims to study the shared and domestic use of intimate health technologies between partners, such as fertility tracking, and how better care structures can be developed outside the home, such as in the workplace. The research aims to understand the trust factors in using algorithmic services for intimate health at the system level.
Background
Despite making important progress in women’s health, severe gaps prevail in how women’s health is understood and represented. Social and cultural taboos associated with the female body have long affected education, treatment, and access to healthcare. Digital approaches to women’s health similarly have been limited in their focus such that they fail to respond to the broad, bodily, and taboo challenges that women’s health brings.
About the Digital Futures Postdoc Fellow
Deepika Yadav is a postdoctoral research fellow in Stockholm Technology & Interaction Research (STIR) group. Her research lies at the intersection of Human-Computer Interaction and global development with specific interests in working for underrepresented groups in resource-constrained settings, women’s health, and well-being. Her latest research studies sociological contexts of interpersonal relationships of care in the workplace setting for lactating mothers.
Main supervisor
Airi Lampinen, Associate Professor, Department of Computer and Systems Sciences (DSV), Stockholm University.
Co-supervisor
Madeline Balaam, Associate Professor, Division of Media Technology and Interaction Designs, KTH.
Watch the recorded presentation at Digitalize in Stockholm 2022 event.
About the project
Objective
This research project aims to design and develop an AI prototype that strengthens the collaborative work in the sighted guiding partnership. In sighted guiding, the guide bends and offers its arm to the person being guided. Their physical connection allows companions to accomplish navigation collaboratively.
This project will advance perspectives that stress how access and independence are achieved through interdependence, opening up new opportunities to design AI-AT that supports cooperation between people through/with AI, better responds to people’s capacities, and therefore empowers people with VI in social life. Results will be technically innovative because of the increasing adaptability of AI-based AT to contextual, situational and personal factors and the capabilities of people with VI. This differs from previous approaches focused on object recognition and discrete tasks where the end-to-end scenario is easily defined.
Background
Over 30 million people live with Visual Impairments (VI) in Europe. Often this medical condition interferes with the individual’s abilities to perform activities of everyday life since in a world with a predominance of visual content, information access can be hard, tiring and frustrating. Nowadays, people with VI still suffer from exclusion, such as marginalisation and powerlessness, in an increasingly digitalised society. People with VI are early adopters of Assistive Technology (AT), and AI-based AT (e.g., smartphone applications) plays an increasing part in their daily lives. In Human-Computer Interaction (HCI) research, increased attention has been given to independent navigation. Here, AI technologies aim to solve a functional task, where the user follows turn-by-turn instructions to successfully reach a destination and receive physical spatial information, such as the identification and proximity of obstacles and landmarks. A promising alternative approach builds on the interdependence framework that sees AT as a way to extend the relations between one another, focusing on how actors are made more or less able, relationally, through other actors and through AT.
About the Digital Futures Postdoc Fellow
Beatrice Vincenzi, University of London, is a postdoc in the Interaction Design research group at KTH Royal Institute of Technology. She is interested in inclusivity and designing AI assistive technology for/with people with disabilities. She is passionate about exploring design methods which make space for accessibility, interdependence, and AI.
Main supervisor
Marianela Ciolfi Felice, KTH.
Co-supervisor
Sanna Kuoppamäki, KTH.
About the project
Objective
With over 1 billion people over 60 worldwide, creating technology that supports the aged to live independently for longer by assisting them in everyday tasks became essential. While companion robots are aimed toward this need, current technology falls short in maintaining engagement over long-term interactions. Among the reasons is the inability to learn from users and adapt, known as lifelong learning, especially in open-domain dialogue that is not limited to any topic.
This project aims to develop a long‐term memory model for open‐domain dialogue such that a robot can learn and recall a person’s attributes, preferences, and shared history to provide personalized assistance in a variety of tasks, such as performing preferred activities, adaptive collaboration in chores, and providing reminders based on their schedule and needs.
About the Digital Futures Postdoc Fellow
Bahar Irfan is a Postdoctoral researcher at KTH Digital Futures. Her research focuses on creating personal robots that can continually learn and adapt to assist everyday life. Previously, she was a Research and Development Associate at Evinoks Service Equipment Industry and Commerce Inc., developing customizable software for industrial robots and smart buffets. Before that, she worked as an R&D Lab Associate at Disney Research Los Angeles on emotional language adaptation in multiparty interactions.
She has a diverse background in robotics, from personalization in long-term human-robot interaction during her PhD at the University of Plymouth and SoftBank Robotics Europe as a Marie Skłodowska-Curie Actions fellow to user-centred task planning for household robotics during her MSc in computer engineering, and building robots for BSc in mechanical engineering at Boğaziçi University.
Main supervisor
Gabriel Skantze, Professor in Speech Communication and Technology, KTH.
Co-supervisor
Sanna Kouppamäki, Assistant Professor, Division of Technology in Health Care, KTH.
Watch the recorded presentation at the Digitalize in Stockholm 2023 event.
About the project
Objective
This project has two parts – the feminist design part is about reflecting on how feminist ideas can influence social robot design, firstly ensuring that robots do not propagate harmful norms, e.g. about women, but then actually going beyond that to see if we can actively challenge such norms with the design decisions we make. The part on working with children is about exploring how children can be invited to co-design robots designed for their use, and particularly whether we can use human-in-the-loop automation approaches to have them ‘teach’ robots how to support them best.
Background
Involvement in robotics research and development is typically limited to a privileged few who generally lack diversity with regards to, e.g. gender, cultural background, etc., yet are expected to develop systems that work for all. These projects are both fundamentally concerned with trying to bring different perspectives into robotics, motivated by a desire to avoid some of the harms we already see in technology development (biased systems, inappropriate use of gender cues) but also build better systems from the beginning – who better craft robot behaviours than those who are ultimately supposed to benefit from that robot’s deployment?
About the Digital Futures Postdoc Fellow
Katie Winkle, after originally studying to be a mechanical engineer, undertook a PhD in social robotics at the Bristol Robotics Laboratory in the UK. She also undertook work on responsible robotics with partners from the University of Oxford. She defended her thesis ‘Expert-Informed Design and Automation of Persuasive, Socially Assistive Robots’ in Summer 2020. Now, Katie is a Digital Futures Postdoctoral Research Fellow at KTH, based in the Social Robotics group at the Division of Robotics, Perception and Learning. Her research is hugely interdisciplinary, drawing on psychology and the social sciences and the latest in robotics and AI to engineer effective, meaningful, impactful human-robot interactions.
Main supervisor
Iolanda Leite, Associate professor, Department of Robotics, Perception and Learning, KTH.
Co-supervisor
Donald McMillan, Associate professor, Department of Computer and Systems Sciences, Stockholm University.
About the project
Objective
Arzu’s future research focus is co-designing and developing gamified robot-enhanced interventions for children and adolescents with neurodevelopmental disorders (NDDs). The research will be based on an iterative design approach to develop interventions for and with the target user groups tailored to the individual to enhance the functional recovery of sensorimotor, social, or cognitive functions in children with NDDs. She aims to investigate what the best roles for robots are in different inclusive practices, including neurodivergent and neurotypical groups where they play and learn together, how to involve children in the design process of robot-mediated activities, and how to design inclusive gamified practices to enhance social interaction between the neurotypical and neurodivergent children as well as their families.
Background
Neurodevelopmental disorders (NDDs) result in different degrees of emotional, physical, social, academic and economic consequences for individuals and in turn, families and society [1, 2]. Upon diagnosis, families report significant delays in treatment initiation and unsatisfactory levels of treatment monitoring. [2, 3].There is a need to establish effective easy-to-access strategies for assessing, treating and monitoring NDD.
Rapid progress in the area of robotics offers excellent chances for innovation in the treatment of children with NDDs, thanks to robots allowing the execution of specific and repetitive tasks which can be tailored according to the particular needs of the individuals. Robots thus offer the opportunity to deliver automated and independent interventions that enable therapy to be delivered over a distance in inclusive and collaborative education environments [4,5] and personalise treatment procedures [6,7]. Combined with gamification, which improves the learning rate and ensures effective improvement in the pedagogical, social and behavioural sense [8,9], robot-enabled therapy becomes a highly promising avenue for research.
About the Digital Futures Postdoc Fellow
Arzu Guneysu Ozgur is a Postdoctoral researcher at Digital Futures. Arzu got a PhD in Robotics on “Designing Gamified Activities with Haptic-Enabled Tangible Robots for Therapy and Assistance” from EPFL in 2021. Her research interests include various topics in Human-Robot Interaction, Adaptive Robot-Enhanced Therapy, Iterative Design, Participatory Design, Neurodevelopmental Disorders, Gamified Therapeutic Technologies, Healthy Aging, Intergenerational Practices for Elderly and Children, and Special Education.
Main supervisor
Iolanda Leite, Associate professor, Department of Robotics, Perception and Learning, KTH.
Co-supervisor
Ali Reza Majlesi, Associate Professor, Department of Education, Stockholm University.
Watch the recorded presentation at Digitalize in Stockholm 2022 event.