About the project
Objective
The project aims to develop a self-powered biodegradable pressure sensor with the potential for wireless data transmission that is tested in vitro under conditions that mimic the in vivo environment of physiological blood flow. The pressure sensor is based on the self-powered triboelectric nanogenerator technology and will combine components that enable high performance and on-demand biodegradation. Sensor validation will be enabled by a hybrid mock circulatory loop: an in vitro system that simulate the dynamics of the healthy and pathological patient’s circulatory system. The method will enable to validate sensor-generated pressure signals against reference pressures generated by a digital patient representation.
Objective
The project aims to develop a self-powered biodegradable pressure sensor with the potential for wireless data transmission that is tested in vitro under conditions that mimic the in vivo environment of physiological blood flow. The pressure sensor is based on the self-powered triboelectric nanogenerator technology and will combine components that enable high performance and on-demand biodegradation. Sensor validation will be enabled by a hybrid mock circulatory loop: an in vitro system that simulate the dynamics of the healthy and pathological patient’s circulatory system. The method will enable to validate sensor-generated pressure signals against reference pressures generated by a digital patient representation.
- Erica Zeglio, Assist. Prof. in organic bioelectronics / materials chemistry at the Department of Chemistry at SU, is an expert in materials with ionic and electronic conductivity and their application in bioelectronic devices.
- Seraina Dual, Assist. Prof. in Intelligent Health Technologies at the Department of Biomedical Engineering and Health Systems at KTH, is an expert in implantable sensors and robotic systems for prevention and treatment of cardiovascular disease.
About the project
Objective
The project aims to develop analysis and synergy mechanisms for complex systems consisting of high-order interactions, with a particular focus on opinion and societal-scale dynamics on hypernetworks. The ultimate goal is to apply the methodology and insight derived from collective behaviors of social dynamics on hypernetworks and moment-based approaches in societal-scale networked systems to design more efficient and sustainable infrastructures. These include transportation systems, smart grids, and smart buildings, where human decisions and group interactions are pivotal.
Background
In recent years, there has been a growing interest in studying the collective behavior of systems with higher-order interactions. The motivation stems from a practical need in real-world applications where the phenomena observed in complex systems cannot be adequately captured by considering only pairwise interactions between agents. Instead, these systems require the inclusion of higher-order interactions, often represented by hypergraphs or simplicial complexes. Such a need is evident in numerous applications, ranging from neuron dynamics to protein interaction networks, and from ecological systems to social systems. Understanding how these high-order interactions affect collective behaviors in social dynamics and incorporating their effects into human-involved infrastructures is greatly needed.
Crossdisciplinary collaboration
Our research team is formed by PIs from two KTH Schools, Angela Fontan (KTH/EECS) and Silun Zhang (KTH/SCI). The project team will also include a postdoctoral researcher with a strong background and interest in networked systems, control and systems theory, optimization, and large-scale system modeling.
About the project
Objective
The project creates opportunities for a new form of public performances where the line between artists and audience is blurred. We work with mixed and augmented reality together with immersive participation and new mobile communication technology. We will demonstrate this in an interactive performance in a public environment.
The project aims at:
- Creating a completely novel arena for immersive, participatory and creative cultural events using mobile communications and 3D/Mixed Reality (MR) innovations
- Allowing artists and audience to participate in real-time performative events like theatre, music and dance, both indoors and outdoors in public spaces
- Developing an experimental mobile AR and MR visualizing and auditive platform allowing creation of new types of participatory artistic performances, utilizing cutting edge colocation and spatial map/digital twin technologies
Background
We focus on the creation of a completely new form of public performances where physical actors can interact with virtual actors, and with physical and virtual objects. The project develops and studies both artistic creative processes and new wireless communication technology such as WiFi7 and 6G. We also use a number of prototypes developed in collaboration between Stockholm University and Ericsson Research during 2023–2024.
Central to the SECE project is the use of mixed reality (MR), enabling us to mix physical and virtual actors, objects and environments. The goal is to enable performances also outdoors, which is a big challenge with today’s technology.
The project involves expertise from many different directions and areas such as mobile communication, augmented and mixed reality, artistry and choreography.
Project webpage on Stockholm University website
Crossdisciplinary collaboration
The SECE project is a collaboration between the Department of Computer and Systems Sciences (DSV) at Stockholm University, Ericsson Research and Kulturhuset Stadsteatern.
About the project
Objective
A Lego-inspired design framework called SiLago (Silicon Lego) enables automation from the system level to ready-to-manufacture solutions for high-performance Edge AI applications. This framework bridges the gap between ease of use and performance by providing ASIC-comparable efficiency while achieving significantly improved energy efficiency—10X to 100X better than commercial off-the-shelf (COTS) solutions such as GPUs and FPGAs. The research project aims to enhance the SiLago framework to support comprehensive system-level implementation by addressing computation, storage, and interconnect requirements. These enhancements will enable SiLago to streamline the synthesis of complex applications, such as those required in industrial use cases. Finally, the improved system-level capabilities will be seamlessly integrated with the existing application-level synthesis flow, creating a unified, automated design process from applications to manufacturable silicon.
Background
The field of electronics and VLSI has driven transformative advancements in computing, enabling the development of increasingly powerful and efficient hardware systems. System architecture plays a crucial role in defining the structure and interaction of hardware components, ensuring efficient computation, storage, and communication. Despite these advancements, designing high-performance and energy-efficient hardware, such as ASICs, remains a complex, resource-intensive process requiring specialized expertise. The SiLago framework builds on these foundations, combining principles of VLSI, hardware modeling, system architecture, and design automation to provide a modular, automated solution for ASIC design.
About the Digital Futures Postdoc Fellow
Nooshin Nosrati completed her doctoral research in Digital Electronic Systems at the University of Tehran (UT). Her doctoral thesis was on hybrid reliability provisions in embedded systems with a focus on Computational Elements. Her research interests encompass hardware design and modeling, computer architectures, reliability and testability of embedded systems.
Main supervisor
Ahmed Hemani, Full Professor, Department of Electrical Engineering, KTH.
Co-supervisor
Artur Podobas, Associate Professor, Division of SCS, School of EECS, KTH.
About the project
Objective
To develop a mobile application that leverages advanced 3D pose estimation technology for tracking and analyzing a person’s movement outside traditional laboratory settings. This app aims to complement the clinician’s work by enabling remote monitoring and interaction between patients and healthcare providers, thus facilitating data-driven physiotherapy and rehabilitation sessions.
The benefits of such an approach include:
- Adaptive, personalized therapy to each patient’s progress and needs
- Progress tracking highlighting achievements and areas needing attention
- Assisting in correct execution by providing immediate feedback
Background
The need for innovative tools that offer quantitative insights into patients’ movements has become increasingly apparent, particularly for remote or home-based physiotherapy and rehabilitation. Traditional methods often rely on in-person assessments that may not fully capture the nuances of a patient’s progress or challenges.
An app that provides accurate, quantitative movement analysis can significantly enhance the clinician’s ability to tailor treatments, monitor progress remotely, and ensure patients perform exercises correctly while reducing the need for frequent in-person visits.
Status
The current app demo utilizes a single smartphone or tablet to capture a person’s 3D movement using the device’s depth camera capabilities. To ensure high accuracy and reliability, the app employs a machine learning model to refine and improve pose estimation based on data collected from a wide range of users. The current implementation primarily targets the lower extremities, focusing on walking. Efforts are underway to broaden the model’s scope to encompass a broader range of movements.
Crossdisciplinary collaboration
The project partners are Innovations Office Region Stockholm and Danderyd University Hospital.
Watch the recorded presentation at the Digitalize in Stockholm 2023 event:
About the project
Objective
The QB-ACT project aims to develop and evaluate an Internet-based psychological intervention integrating Question-Based Learning (QBL) and Acceptance and Commitment Therapy (ACT). It seeks to create an engaging, user-friendly platform for delivering therapy to improve mental health outcomes, reduce dropout rates, and enhance treatment adherence. By conducting a randomized controlled trial, the project will assess its effectiveness in addressing anxiety, depression, and overall well-being. Additionally, it aims to promote accessibility and scalability, providing an innovative alternative to traditional mental health care while supporting broader adoption through stakeholder dissemination and integration into healthcare systems.
Background
The QB-ACT project addresses critical challenges in mental health care: the growing demand for services and insufficient accessibility. Internet-based psychological interventions offer scalable solutions but often face issues like low engagement and high dropout rates. To overcome these barriers, the project integrates the evidence-based framework of Acceptance and Commitment Therapy (ACT) with Question-Based Learning (QBL), a proven methodology from e-learning. ACT fosters mindfulness and value-driven action to improve mental health, while QBL enhances engagement and learning through interactive, problem-solving techniques. By uniting these approaches, QB-ACT seeks to create a transformative digital platform, making therapy more accessible, personalized, and effective.
Crossdisciplinary collaboration
The proposed research project unites a multidisciplinary team with expertise spanning clinical psychology, Internet-based psychological treatments, large-scale e-learning technology, instructional design, online education, and the OLI Torus e-learning platform, ensuring a comprehensive and innovative approach to digital mental health interventions.
About the project
Objective
The project aims to develop a model-based decision-making tool for planning, designing and improving patient flows at the Karolinska University Hospital. The tool will include a prediction model, integrating clinical data, production data, and expert knowledge of the patient flows through the emergency department and the hospital. In addition, a network-based simulation model will be integrated to facilitate capacity and resource planning to improve patient care, decisions on handling and resource utilisation.
Background
Hospital emergency departments play a central role in healthcare systems and patient flow logistics throughout the system. Delivery of emergency care is resource and knowledge-intensive and requires close alignment with all other hospital functions and departments. Emergency healthcare is a complex system with high variability in patient characteristics, disease profile, processes and outcomes. This is a challenge for change work aimed at improving efficiency.
Little or no work has combined clinical and production data into process models to inform healthcare planning. Current models treat the emergency department as an independent leverage point without considering downstream bottlenecks in hospital wards. Overcoming these methodological limitations is important for informing hospital resource planning.
Crossdisciplinary collaboration
The project partners are Karolinska University Hospital, Region Stockholm, and KTH.
Watch the recorded presentation at the Digitalize in Stockholm 2023 event: