Dr. Mevludin Memedi

Assistant Professor, Department of Operations & Project Management

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Short bio, education, projects and awards, and publications

Mevludin Memedi is working as an Assistant Professor at the Department of Operations and Project Management, College of Business, Alfaisal University in Riyadh. He received his PhD degree in Information Technology in 2014 at Örebro University, Sweden. After his PhD degree he has held a tenure track position at the Computer Engineering department, Dalarna University, Sweden. After that he worked as Assistant Professor at the Informatics department, Business School, Örebro University, Sweden. He was also affiliated with the department of Information Systems and Operations Management, Vienna University of Economics and Business in Vienna, Austria.

 

Dr. Memedi taught several courses in English and Swedish for undergraduate and graduate courses at Dalarna University and Örebro University in database systems, machine learning, programming, information security, and quantitative methods. His teaching expertise includes planning, implementing, and evaluating teaching. He has been involved in developing courses in collaboration with different stakeholders for a new Master program in Information Security Management at Örebro University. Together with his colleagues at Örebro University he has received a pedagogical award 2023 from the Swedish Information Systems Academy regarding a student-centered learning model called “Walkshop model” implemented for teaching programming-related courses. In 2015, together with colleagues at Dalarna University he presented the findings from a study on flipped classroom approach at the Next Generation Learning Conference in Falun, Sweden. In addition to teaching in undergraduate and graduate levels, Dr. Memedi has experience in supervising PhD students: 2 graduated in 2020 and 2022, and two ongoing. He has also taken courses in pegagogical teaching in higher education at Mälardalen University and Dalarna University and research supervision at Örebro University.

 

His research interests primarily focus on developing information systems for sustainable healthcare. The research interests focus on developing machine-learning based methods/systems for improving patient care and providing novel insights to health institutions. More specifically, Dr. Memedi’s research focused on leveraging techniques from machine learning, sensor technologies, statistics, signal processing, data visualization, and user-centered design in developing information systems for patients to follow-up their health and symptoms and clinicians to support them with new insights during decision-making. Some of the projects Dr. Memedi worked are monitoring and quantification of motor symptoms of patients with Parkinson’s disease using sensors such as wearables and smartphones, objective assessment of pain using biosensors, empowering patients with their own health-related data via digital tools, and management and prevention of social isolation of elderly. Through the interdisciplinary research Dr. Memedi has established and maintained collaboration with university hospitals, companies, and patient organizations. He has experience in managing externally funded projects in collaboration with different stakeholders. He authored more than 40 peer reviewed articles and submitted 1 patent application. In addition, Dr. Memedi is involved in the following professional activities. He is acting as member of the editorial board of the Informatics in Medicine Unlocked journal and as a review editor at the Frontiers in Aging Neuroscience journal. He has also served as special guest editor for special issues at the Sensors and Informatics in Medicine Unlocked journals. He has published papers in multidisciplinary outlets such as Artificial Intelligence in Medicine, Journal of Medical Internet Research, Computer Methods and Programs in Biomedicine, and is a regular reviewer for IEEE Journal of Biomedical and Health Informatics and Sensors journal. Furthermore, Dr. Memedi acted as an external reviewer for funding agencies in Luxemburg and Slovenia.

 

Education

PhD in Information Technology, 2014, Örebro University, Örebro, Sweden.

Licentiate in Information Technology, 2011, Örebro University, Örebro, Sweden.

Master of Science in Computer Engineering, 2008, Dalarna University, Borlänge, Sweden.

 

Projects

- Behaviours and beyond: Investigating information security policy compliance among IT professionals in Saudi Arabia

- Controlled treatment of opiate-requiring pain using biosensors

- Remote monitoring of Parkinson's disease - empowerment of patients and improved treatment using ICT-based tools

- Multimodal motor symptoms quantification platform for individualized Parkinson's disease

 

Awards/patents

- Teaching award from Swedish Information Systems Academy, 2023

- "Young scientist" from North Macedonian Islamic Youth Forum, 2018

- Best Master thesis degree from Teknikdalen Foundation in Borlänge, Sweden, 2009

- US patent application 16617088, Systems for evaluating dosage parameters.

 

List of journal publications

Thangavel, G., Memedi, M., & Hedström, K (2024). Information and communication technology for managing social isolation and loneliness among people with Parkinson disease: qualitative study of barriers and facilitators. Journal of Medical Internet Resarch, 26.

 

Thangavel, G. , Memedi, M. & Hedström, K. (2022).Customized information and communication technology for reducing social isolation and loneliness among older adults: Scoping review. JMIR Mental Health, 9(3).

 

Karni, L. , Jusufi, I. , Nyholm, D. , Klein, G. O. & Memedi, M. (2022). Toward improved treatment and empowerment of individuals with Parkinson's disease: Design and evaluation of an Internet of Things system. JMIR Formative Research, 6(6).

 

Aghanavesi, S. , Westin, J. , Bergquist, F. , Nyholm, D. , Askmark, H. , Aquilonius, S. M. , Constantinescu, R. , Medvedev, A. & et al. (2020). A multiple motion sensors index for motor state quantification in Parkinson's disease. Computer Methods and Programs in Biomedicine, 189.

 

Karni, L. , Dalal, K. , Memedi, M. , Kalra, D. & Klein, G. O. (2020). Information and communications technology-based interventions targeting patient empowerment: Framework development. Journal of Medical Internet Research, 22(8).

 

Aghanavesi, S. , Bergquist, F. , Nyholm, D. , Senek, M. & Memedi, M. (2020). Motion sensor-based assessment of Parkinson's disease motor symptoms during leg agility tests: results from levodopa challenge. IEEE Journal of Biomedical and Health Informatics, 24(1).

 

Johansson, D. , Thomas, I. , Ericsson, A. , Johansson, A. , Medvedev, A. , Memedi, M. , Nyholm, D. , Ohlsson, F. & et al. (2019). Evaluation of a sensor algorithm for motor state rating in Parkinson's disease. Parkinsonism & Related Disorders, 64.

 

Thomas, I. , Alam, M. , Bergquist, F. , Johansson, D. , Memedi, M. , Nyholm, D. & Westin, J. (2019). Sensor-based algorithmic dosing suggestions for oral administration of levodopa/carbidopa microtablets for Parkinson's disease: a first experience. Journal of Neurology, 266(3).

 

Thomas, I. , Memedi, M. , Westin, J. & Nyholm, D. (2019). The effect of continuous levodopa treatment during the afternoon hours. Acta Neurologica Scandinavica, 139(1).

 

Thomas, I. , Westin, J. , Alam, M. , Bergquist, F. , Nyholm, D. , Senek, M. & Memedi, M. (2018). A treatment-response index from wearable sensors for quantifying Parkinson's disease motor states. IEEE Journal of Biomedical and Health Informatics, 22(5).

 

Memedi, M. , Tshering, G. , Fogelberg, M. , Jusufi, I. , Kolkowska, E. & Klein, G. O. (2018). An interface for IoT: feeding back health-related data to Parkinson's disease patients. Journal of Sensor and Actuator Networks, 7(1).

 

Aghanavesi, S. , Nyholm, D. , Senek, M. , Bergquist, F. & Memedi, M. (2017). A smartphone-based system to quantify dexterity in Parkinson's disease patients. Informatics in Medicine Unlocked, 9.

 

Sadikov, A. , Groznik, V. , Možina, M. , Žabkar, J. , Nyholm, D. , Memedi, M. & Georgiev, D. (2017). Feasibility of spirography features for objective assessment of motor function in Parkinson's disease. Artificial Intelligence in Medicine, 81.

 

Senek, M. , Aquilonius, S. , Askmark, H. , Bergquist, F. , Constantinescu, R. , Ericsson, A. , Lycke, S. , Medvedev, A. & et al. (2017). Levodopa/carbidopa microtablets in Parkinson's disease: a study of pharmacokinetics and blinded motor assessment. European Journal of Clinical Pharmacology, 73(5).

 

Aghanavesi, S. , Memedi, M. , Dougherty, M. , Nyholm, D. & Westin, J. (2017). Verification of a method for measuring Parkinson's disease related temporal irregularity in spiral drawings. Sensors, 17(10).

 

Memedi, M. , Sadikov, A. , Groznik, V. , Zabkar, J. , Mozina, M. , Bergquist, F. , Johansson, A. , Haubenberger, D. & et al. (2015). Automatic spiral analysis for objective assessment of motor symptoms in Parkinson's disease. Sensors, 15(9).

 

Memedi, M. , Nyholm, D. , Johansson, A. , Pålhagen, S. , Willows, T. , Widner, H. , Linder, J. & Westin, J. (2015). Validity and responsiveness of at-home touch screen assessments in advanced Parkinson's disease. IEEE Journal of Biomedical and Health Informatics, 19(6).

 

Memedi, M. , Khan, T. , Grenholm, P. , Nyholm, D. & Westin, J. (2013). Automatic and objective assessment of alternating tapping performance in Parkinson's disease. Sensors, 13(12).

 

Memedi, M. , Westin, J. & Nyholm, D. (2013). Spiral drawing during self-rated dyskinesia is more impaired than during self-rated off. Parkinsonism & related Disorders, 19(5).

 

Westin, J. , Schiavella, M. , Memedi, M. , Nyholm, D. , Dougherty, M. & Antonini, A. (2012). Validation of a home environment test battery for supporting assessments in advanced Parkinson's disease. Neurological Sciences, 33(4).

 

Memedi, M. , Westin, J. , Nyholm, D. , Dougherty, M. & Groth, T. (2011). A web application for follow-up of results from a mobile device test battery for Parkinson's disease patients. Computer Methods and Programs in Biomedicine, 104(2).

 

Westin, J. , Ghiamati, S. , Memedi, M. , Nyholm, D. , Johansson, A. , Dougherty, M. & Groth, T. (2010). A new computer method for assessing drawing impairment in Parkinson's disease. Journal of Neuroscience Methods, 190(1).

 

Published conference proceedings

Thangavel, G., Memedi, M., Moll, J. & Hedström, K (2023). Management of social isolation and loneliness in Parkinson's disease: design principles. Forty-fourth International Conference on Information Systems (ICIS), Hyderabad, India.

 

Memedi, M. , Miclescu, A. , Katila, L. , Claesson, M. , Essermark, M. , Holm, P. , Klein, G. O. , Spira, J. & et al. (2022). Sensor-based measurement of nociceptive pain: An exploratory study with healthy subjects. In: Hadas Lewy; Refael Barkan, Pervasive Computing Technologies for Healthcare 15th EAI International Conference 2021, December 6-8, 2021, virtual event.

 

Memedi, M. & Aghanavesi, S. (2020). A partial least squares regression model to measure Parkinson's disease motor states using smartphone data. In: Proceedings of the 53rd Hawaii International Conference on Systems Sciences (HICSS), January 7-10, 2020, Maui, Hawaii, USA.

 

Memedi, M. , Aghanavesi, S. , Bergquist, F. , Nyholm, D. & Senek, M. (2019). A multimodal sensor fusion platform for objective assessment of motor states in Parkinson's disease. In: IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), May 19-22, 2019, Chicago, Illinois, USA.

 

Thangavel, G. , Memedi, M. & Hedström, K. (2019). A systematic review of Social Internet of Things: Concepts and application areas. In: Americas Conference on Information Systems (AMCIS), August 15-17, 2019, Cancun, Mexico.

 

Karni, L. , Memedi, M. & Klein, G. O. (2019). Targeting patient empowerment via ICT interventions: An ICT-specific analytical framework. In: Americas Conference on Information Systems (AMCIS), August 15-17, 2019, Cancun, Mexico.

 

Matić, T. , Aghnavesi, S. , Memedi, M. , Nyholm, D. , Bergquist, F. , Groznik, V. , Žabkar, J. & Sadikov, A. (2019). Unsupervised learning from motion sensors data to assess the condition of patients with Parkinson's disease. In: Conference of Artificial Intelligence in Medicine (AIME), June 26-29, 2019, Poznan, Poland.

 

Javed, F. , Thomas, I. & Memedi, M. (2018). A comparison of feature selection methods when using motion sensors data: a case study in Parkinson's disease. In: International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), July 17-21, 2018, Honolulu, Hawaii, USA.

 

Memedi, M. , Lindqvist, J. , Tunedal, T. & Duvåker, A. (2018). A study on pre-adoption of a self-management application by Parkinson's disease patients. In: International Conference on Information Systems (ICIS), December 13-16, 2018, San Francisco, California, USA.

 

Kolkowska, E. , Scandurra, I. , Avatare Nöu, A. , Sjölinder, M. & Memedi, M. (2018). A user-centered ethical assessment of welfare technology for elderly. In: International Conference on Human Computer Interaction (HCI), July 15-20, 2018, Las Vegas, Nevada, USA.

 

Karni, L. , Memedi, M. , Kolkowska, E. & Klein, G. O. (2018). EMPARK: Internet of Things for empowerment and improved treatment of patients with Parkinson's disease. In: International Congress of Parkinson's Disease, October 5-9, 2018, Hong Kong.

 

Jusufi, I. , Memedi, M. & Nyholm, D. (2018). TapVis: A data visualization approach for assessment of alternating tapping performance in patients with Parkinson's disease. In: European Conference on Visualization (EuroVis), June 4-18, 2018, Brno, Czech Republic.

 

Thomas, I. , Bergquist, F. , Constantinescu, R. , Nyholm, D. , Senek, M. & Memedi, M. (2017). Using measurements from wearable sensors for automatic scoring of Parkinson's disease motor state: Results from 7 patients. In: International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), July 11-15, 2017, Jeju island, South Korea.

 

Memedi, M. , Aghanavesi, S. & Westin, J. (2016). A method for measuring Parkinson's disease related temporal irregularity in spiral drawings. In: IEEE International Conference on Biomedical and Health Informatics (BHI), February 24-27, 2016, Las Vegas, Nevada, USA.

 

Memedi, M. , Aghanavesi, S. & Westin, J. (2015). Digital spiral analysis for objective assessment of fine motor timing variability in Parkinson's disease. In: International Congress of Parkinson's disease and Movement Disorders, June 14-18, 2015, San Diego, California, USA.

 

Sadikov, A. , Žabkar, J. , Možina, M. , Groznik, V. , Nyholm, D. & Memedi, M. (2015). Feasibility of spirography features for objective assessment of motor symptoms in Parkinson's disease. In: 15th Conference on Artificial Intelligence in Medicine (AIME), June 17-20, 2015, Pavia, Italy.

 

Memedi, M. , Aghanavesi, S. & Westin, J. (2015). Objective quantification of Parkinson's disease upper limb motor timing variability using spirography. In: 37th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), August 25-29, 2015, Milan, Italy.

 

Khan, T. , Memedi, M. , Song, W. W. & Westin, J. (2014). A case study in healthcare informatics: a telemedicine framework for automated Parkinson's disease symptom assessment. In: Smart Health International Conference (ICSH), July 10-11, 2014, Beijing, China.

 

Jusufi, I. , Nyholm, D. & Memedi, M. (2014). Visualization of spiral drawing data of patients with Parkinson's disease. In: 18th International Conference on Information Visualization (IV), July 16-18, 2014, Paris, France.

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