Currently, I have been working on the following innovative projects:

Integrating Persuasive Educational Intervention in Health Education to reduce Antimicrobial Resistance: Antimicrobial Resistance (AMR) is a growing global concern with exponentially rising rates of drug-resistant infections. AMR occurs when bacteria, viruses, fungi and parasites no longer respond to medicines effectively, making infections in humans, animals and plants more difficult to treat. This threatens global health security, food safety and security, economic growth, poverty alleviation and the environment. AMR has been described as a silent pandemic, further progressing in the shadows of the COVID-19 pandemic. In 2019, AMR was responsible for 1.27 million deaths alone, more than HIV/AIDs and malaria; and contributed to 4.95 million deaths.  It is estimated that by 2050, the number of deaths could reach up to 10 million. AMR is directly impacting the society by high number of patients suffering from resistance, implying more people not contributing to economy, thus increasing economical pressure on the health care system. Due to over-prescription practices among human, veterinary care and agriculture, the environment is getting polluted by all three critical sources that impacts the overall well-being of the people globally. A significant factor contributing to the spread of AMR is lack of knowledge about the use of antibiotics. Studies have found that the use of games show promising results for helping improve students’ knowledge about health and may be used to boost knowledge about AMR. A playful educational support will be developed to make the health problem of bacterial resistance and the action of antibiotics more understandable among young people, who will be leaders in medicine, veterinary science and agriculture in the near future.

Team: Dr. Avis Anya Nowbuth, Dr. Akwi W. Asombang, MD MPH 

Decision support platform to diagnose Cerebral Palsy in early stage: Cerebral palsy (CP) is a condition of altered motor function caused by a brain injury before age 2, resulting in a lifelong need for specialised services and treatment interventions (Rosenbaum 2006, Novak 2017). Treatment and care for individuals with CP result in a lifetime cost of €800,000 per child, approximately four times higher than in typically developing children. The condition leads to significant personal challenges for the child and their families and reduced social participation (Blencowe 2013, Kruse 2009). Annually, 5 Million babies are born in the EU. Of these, 0.2% (10 000) will get a non-curable Cerebral Palsy (CP) diagnosis. Today CP-diagnosis is typically set at age 1-2 years and sometimes as late as 4-5 years. This decision support system is based on nearly 20 years of national and international clinical research studies, where video recordings of spontaneous movements in infants and their CP status at 3-5 years of age were collected. These studies have been led by researchers at St. Olavs Hospital and NTNU in Trondheim, and data has been collected from the USA, India, Norway, Denmark, Belgium, Turkey, and China (Støen Groos 2022), resulting in a unique research database. Together with AI researchers at the Norwegian Open AI Lab at NTNU, neonatologists, paediatricians, and physiotherapists from St. Olavs Hospital have developed an AI algorithm for motion tracking in infant videos, which is currently considered state-of-the-art internationally. A machine learning model for predicting CP based on motion data has recently been published in the prestigious journal JAMA Network Open, receiving significant international recognition (Groos 2022). The automatic motion tracker and the CP risk prediction model are new research innovations that can be developed into commercial AI products. 

Team: Dr. Lars Adde PT PhD, Kjell Arne Jacobsen

A Digital Decision Support system for accelerated return from overtraining/burnout (in athletes) : The overtraining condition is defined as a prolonged maladaptation leading to a decrease in the ability to perform at established levels for a prolonged period. The overtraining condition is associated with a range of symptoms and research suggests that 20-60% of athletes experience overtraining syndrome at some point, which in many cases can do career-ending damage. After conducting interviews with key stakeholders from the national and international sports federations, we identified an urgent need for a Digital Decision Support (DDS) system that could help avoid, screen, and treat athletes experiencing overtraining conditions. The general Health Tech market is growing exponentially worldwide, which also implies that the potential market (both as B-2-C and B-2-B solutions) for the DDS developed in this project will be growing. In this context, it is assumed that the overall market part of the sports and health technology branch is estimated to be €55 billion by 2024. If we succeed in sports, the burnout aspect is not limited to athletic performance but could also be further developed and adapted to other high-stress environments of the society.

Team: Prof. Øyvind Sandbakk, Dr. Guro Strøm Solli

Digital Wheelchair: The main goal of this project is to develop an algorithm that validly measures Physical Activity and estimates energy expenditure of wheelchair users during exercise as well as free-living activities. This will be achieved through utilizing the data and knowledge gained from an ongoing research project on: The feasibility of using the individual VO₂-HR relationship to measure energy expenditure during wheelchair propulsion and free-living activities across the entire fitness spectrum in this population. We aim for a new patent in the area of wearable health devices. The results from the studies conducted together with the algorithm will be used to develop a business case for possible commercialization.

Team: Dr. Julia Baumgart, Prof. Øyvind Sandbakk,

Tracking the Menstrual Cycle of Female Athletes: Progressing education and performance- The sporting industry provides commodities for the most minute aspects of athletic performance, yet the menstrual cycle (MC), which represents the most striking difference between male and female physiology, remains virtually unacknowledged. Considering the growing participation of female athletes in sports, the interest in female-specific products and services (fem-tech) is growing rapidly. Research is beginning to suggest that the hormonal fluctuations associated with the MC can affect response to training, athletic performance and may even be linked to increased injury risk amongst female athletes. While scientific research in this field continues to gain interest, recent polls suggest that most athletes still do not talk with their coaches about their MC, indicating that this topic continues to be seen as taboo and highlights the importance of educating coaches and athletes about this topic. Based on these findings, we perceive the need for a female athlete specific mobile platform for tracking and reporting on the MC in order to create a safe space to explore, discuss, and destigmatize this important aspect of female physiology and optimize athletic performance.

Team: Prof. Øyvind Sandbakk, Dr. Ashis Jalote Parmar

Smartphone-based Self-tests of Functional Fitness: The overall aim is to develop a fitness calculator, that allows seniors to self-assess functional fitness by use of a smartphone. We also see a potential for the end-user to share the test results with health care workers or GPs remotely, making risk assessment more convenient and cost-effective. The goal of the app is to empower seniors and motivate them to do necessary life-style changes.

Team: Prof. Jorunn L. Helbostad

Older projects: Before joining NTNU, he has designed and implemented two projects at NID namely, UP 100 (emergency service that has been launched in Uttar Pradesh), and the Smart Police Uniform for BPR&D.