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Memedi, Mevludin, PhDORCID iD iconorcid.org/0000-0002-2372-4226
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Publications (10 of 58) Show all publications
Thangavel, G., Memedi, M. & Hedström, K. (2024). Information and Communication Technology for Managing Social Isolation and Loneliness Among People Living With Parkinson Disease: Qualitative Study of Barriers and Facilitators. Journal of Medical Internet Research, 26, Article ID e48175.
Open this publication in new window or tab >>Information and Communication Technology for Managing Social Isolation and Loneliness Among People Living With Parkinson Disease: Qualitative Study of Barriers and Facilitators
2024 (English)In: Journal of Medical Internet Research, E-ISSN 1438-8871, Vol. 26, article id e48175Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Parkinson disease (PD) is a complex, noncurable, and progressive neurological disease affecting different areas of the human nervous system. PD is associated with both motor and nonmotor symptoms, which negatively affect patients' quality of life and may cause changes in socialization such as intentional social withdrawal. This may further lead to social isolation and loneliness. The use of information and communication technology (ICT) plays an important role in managing social isolation and loneliness. Currently, there is a lack of research focusing on designing and developing ICT solutions that specifically address social isolation and loneliness among people living with PD.

OBJECTIVE: This study addresses this gap by investigating barriers and social needs in the context of social isolation, loneliness, and technology use among people living with PD. The insights gained can inform the development of effective ICT solutions, which can address social isolation and loneliness and improve the quality of life for people living with PD.

METHODS: A qualitative study with 2 phases of data collection were conducted. During the first phase, 9 health care professionals and 16 people living with PD were interviewed to understand how PD affects social life and technology use. During the second phase, 2 focus groups were conducted with 4 people living with PD in each group to gather insights into their needs and identify ways to manage social isolation and loneliness. Thematic analysis was used to analyze both data sets and identify key themes.

RESULTS: The results showed that the barriers experienced by people living with PD due to PD such as "fatigue," "psychological conditions," "social stigma," and "medication side effects" affect their social life. People living with PD also experience difficulties using a keyboard and mouse, remembering passwords, and navigating complex applications due to their PD-related physical and cognitive limitations. To manage their social isolation and loneliness, people living with PD suggested having a simple and easy-to-use solution, allowing them to participate in a digital community based on their interests, communicate with others, and receive recommendations for social events.

CONCLUSIONS: The new ICT solutions focusing on social isolation and loneliness among people living with PD should consider the barriers restricting user's social activities and technology use. Given the wide range of needs and barriers experienced by people living with PD, it is more suitable to adopt user-centered design approaches that emphasize the active participation of end users in the design process. Importantly, any ICT solution designed for people living with PD should not encourage internet addiction, which will further contribute to the person's withdrawal from society.

Place, publisher, year, edition, pages
JMIR Publications, 2024
Keywords
ICT, Parkinson disease, information and communication technology, loneliness, social isolation
National Category
Human Aspects of ICT
Identifiers
urn:nbn:se:oru:diva-111017 (URN)10.2196/48175 (DOI)38231548 (PubMedID)2-s2.0-85182768739 (Scopus ID)
Funder
EU, Horizon 2020
Note

This project received funding from the European Union’s Horizon 2020 research and innovation program under the MarieSklodowska-Curie.

Available from: 2024-01-26 Created: 2024-01-26 Last updated: 2024-02-05Bibliographically approved
Thangavel, G., Memedi, M., Moll, J. & Hedström, K. (2023). Management of social isolation and loneliness in Parkinson’s disease: Design principles. In: ICIS 2023 Proceedings: . Paper presented at 2023 International Conference on Information Systems (ICIS 2023), Hyderabad, India, December 10-13, 2023. AIS eLibrary, Article ID 2169.
Open this publication in new window or tab >>Management of social isolation and loneliness in Parkinson’s disease: Design principles
2023 (English)In: ICIS 2023 Proceedings, AIS eLibrary , 2023, article id 2169Conference paper, Published paper (Refereed)
Abstract [en]

Persons with Parkinson’s disease (PwPs) may have difficulty participating in social activities due to motor and non-motor symptoms that may lead to social isolation and loneliness. This paper addresses how to manage social isolation and loneliness among PwPs using digital solutions. Information and Communication Technologies (ICT) have the potential to address social isolation and loneliness, but there are no current solutions that specifically target these issues among PwPs. In this paper, we present an ongoing project based on design science research (DSR) combined with a user-centered approach to identify challenges, requirements, and design objectives. The empirical work includes data from interviews and focus groups with PwPs and healthcare professionals. Based on the empirical material, we formulated design principles on identified challenges and requirements, which were instantiated into a high-fidelity prototype. This initial cycle serves as a foundation for ongoing improvements and evaluations in a continuous DSR process.

Place, publisher, year, edition, pages
AIS eLibrary, 2023
Keywords
Social isolation, loneliness, Information and Communication Technologies, design science research, user-centered design, design principles
National Category
Gerontology, specialising in Medical and Health Sciences Interaction Technologies
Research subject
Informatics; Human-Computer Interaction
Identifiers
urn:nbn:se:oru:diva-111049 (URN)9781958200070 (ISBN)
Conference
2023 International Conference on Information Systems (ICIS 2023), Hyderabad, India, December 10-13, 2023
Funder
EU, Horizon 2020, 754285
Available from: 2024-01-25 Created: 2024-01-25 Last updated: 2024-01-31Bibliographically approved
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), Article ID e34221.
Open this publication in new window or tab >>Customized Information and Communication Technology for Reducing Social Isolation and Loneliness Among Older Adults: Scoping Review
2022 (English)In: JMIR Mental Health, E-ISSN 2368-7959, Vol. 9, no 3, article id e34221Article, review/survey (Refereed) Published
Abstract [en]

BACKGROUND: Advancements in science and various technologies have resulted in people having access to better health care, a good quality of life, and better economic situations, enabling humans to live longer than ever before. Research shows that the problems of loneliness and social isolation are common among older adults, affecting psychological and physical health. Information and communication technology (ICT) plays an important role in alleviating social isolation and loneliness.

OBJECTIVE: The aim of this review is to explore ICT solutions for reducing social isolation or loneliness among older adults, the purpose of ICT solutions, and the evaluation focus of these solutions. This study particularly focuses on customized ICT solutions that either are designed from scratch or are modifications of existing off-the-shelf products that cater to the needs of older adults.

METHODS: A scoping literature review was conducted. A search across 7 databases, including ScienceDirect, Association for Computing Machinery, PubMed, IEEE Xplore, PsycINFO, Scopus, and Web of Science, was performed, targeting ICT solutions for reducing and managing social isolation and loneliness among older adults. Articles published in English from 2010 to 2020 were extracted and analyzed.

RESULTS: From the review of 39 articles, we identified 5 different purposes of customized ICT solutions focusing on reducing social isolation and loneliness. These were social communication, social participation, a sense of belonging, companionship, and feelings of being seen. The mapping of purposes of ICT solutions with problems found among older adults indicates that increasing social communication and social participation can help reduce social isolation problems, whereas fulfilling emotional relationships and feeling valued can reduce feelings of loneliness. In terms of customized ICT solution types, we found the following seven different categories: social network, messaging services, video chat, virtual spaces or classrooms with messaging capabilities, robotics, games, and content creation and management. Most of the included studies (30/39, 77%) evaluated the usability and acceptance aspects, and few studies (11/39, 28%) focused on loneliness or social isolation outcomes.

CONCLUSIONS: This review highlights the importance of discussing and managing social isolation and loneliness as different but related concepts and emphasizes the need for future research to use suitable outcome measures for evaluating ICT solutions based on the problem. Even though a wide range of customized ICT solutions have been developed, future studies need to explore the recent emerging technologies, such as the Internet of Things and augmented or virtual reality, to tackle social isolation and loneliness among older adults. Furthermore, future studies should consider evaluating social isolation or loneliness while developing customized ICT solutions to provide more robust data on the effectiveness of the solutions.

Place, publisher, year, edition, pages
JMIR Publications, 2022
Keywords
ICT, customization, loneliness, mobile phone, older adults, review, social isolation
National Category
Human Aspects of ICT
Identifiers
urn:nbn:se:oru:diva-97847 (URN)10.2196/34221 (DOI)000787096500013 ()35254273 (PubMedID)2-s2.0-85126100204 (Scopus ID)
Funder
European Commission, 754285
Available from: 2022-03-08 Created: 2022-03-08 Last updated: 2024-01-11Bibliographically approved
Memedi, M., Miclescu, A., Katila, L., Claesson, M., Essermark, M., Holm, P., . . . Kalrsten, R. (2022). Sensor-based Measurement of Nociceptive Pain: An Exploratory Study with Healthy Subjects. In: Hadas Lewy; Refael Barkan (Ed.), Pervasive Computing Technologies for Healthcare: 15th EAI International Conference, Pervasive Health 2021, Virtual Event, December 6-8, 2021, Proceedings. Paper presented at 15th EAI International Conference on Pervasive Computing Technologies for Healthcare (EAI PervasiveHealth 2021), (Virtual conference), December 6-8, 2021 (pp. 88-95). Springer, 431
Open this publication in new window or tab >>Sensor-based Measurement of Nociceptive Pain: An Exploratory Study with Healthy Subjects
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2022 (English)In: Pervasive Computing Technologies for Healthcare: 15th EAI International Conference, Pervasive Health 2021, Virtual Event, December 6-8, 2021, Proceedings / [ed] Hadas Lewy; Refael Barkan, Springer, 2022, Vol. 431, p. 88-95Conference paper, Published paper (Refereed)
Abstract [en]

Valid assessment of pain is essential in daily clinical practice to enhance the quality of care for the patients and to avoid the risk of addiction to strong analgesics. The aim of this paper is to find a method for objective and quantitative evaluation of pain using multiple physiological markers. Data was obtained from healthy volunteers exposed to thermal and ischemic stimuli. Twelve subjects were recruited and their physiological data including skin conductance, heart rate, and skin temperature were collected via a wrist-worn sensor together with their selfreported pain on a visual analogue scale (VAS). Statistically significant differences (p< 0.01) were found between physiological scores obtained with the wearable sensor before and during the thermal test. Test-retest reliability of sensor-based measures was good during the thermal test with intraclass correlation coefficients ranging from 0.22 to 0.89. These results support the idea that a multi-sensor wearable device can objectively measure physiological reactions in the subjects due to experimentally induced pain, which could be used for daily clinical practice and as an endpoint in clinical studies. Nevertheless, the results indicate a need for further investigation of the method in real-life pain settings.

Place, publisher, year, edition, pages
Springer, 2022
Series
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, ISSN 1867-8211, E-ISSN 1867-822X ; 431
Keywords
pain, sensors, physiological data, healthy subjects
National Category
Information Systems, Social aspects
Identifiers
urn:nbn:se:oru:diva-96422 (URN)10.1007/978-3-030-99194-4_7 (DOI)000790610600007 ()2-s2.0-85127858196 (Scopus ID)9783030991937 (ISBN)9783030991944 (ISBN)
Conference
15th EAI International Conference on Pervasive Computing Technologies for Healthcare (EAI PervasiveHealth 2021), (Virtual conference), December 6-8, 2021
Funder
Vinnova
Available from: 2022-01-12 Created: 2022-01-12 Last updated: 2022-05-17Bibliographically approved
Karni, L., Jusufi, I., Nyholm, D., Klein, G. O. & Memedi, M. (2022). Toward Improved Treatment and Empowerment of Individuals With Parkinson Disease: Design and Evaluation of an Internet of Things System. JMIR Formative Research, 6(6), Article ID e31485.
Open this publication in new window or tab >>Toward Improved Treatment and Empowerment of Individuals With Parkinson Disease: Design and Evaluation of an Internet of Things System
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2022 (English)In: JMIR Formative Research, E-ISSN 2561-326X, Vol. 6, no 6, article id e31485Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Parkinson disease (PD) is a chronic degenerative disorder that causes progressive neurological deterioration with profound effects on the affected individual's quality of life. Therefore, there is an urgent need to improve patient empowerment and clinical decision support in PD care. Home-based disease monitoring is an emerging information technology with the potential to transform the care of patients with chronic illnesses. Its acceptance and role in PD care need to be elucidated both among patients and caregivers.

OBJECTIVE: Our main objective was to develop a novel home-based monitoring system (named EMPARK) with patient and clinician interface to improve patient empowerment and clinical care in PD.

METHODS: We used elements of design science research and user-centered design for requirement elicitation and subsequent information and communications technology (ICT) development. Functionalities of the interfaces were the subject of user-centric multistep evaluation complemented by semantic analysis of the recorded end-user reactions. The ICT structure of EMPARK was evaluated using the ICT for patient empowerment model.

RESULTS: Software and hardware system architecture for the collection and calculation of relevant parameters of disease management via home monitoring were established. Here, we describe the patient interface and the functional characteristics and evaluation of a novel clinician interface. In accordance with our previous findings with regard to the patient interface, our current results indicate an overall high utility and user acceptance of the clinician interface. Special characteristics of EMPARK in key areas of interest emerged from end-user evaluations, with clear potential for future system development and deployment in daily clinical practice. Evaluation through the principles of ICT for patient empowerment model, along with prior findings from patient interface evaluation, suggests that EMPARK has the potential to empower patients with PD.

CONCLUSIONS: The EMPARK system is a novel home monitoring system for providing patients with PD and the care team with feedback on longitudinal disease activities. User-centric development and evaluation of the system indicated high user acceptance and usability. The EMPARK infrastructure would empower patients and could be used for future applications in daily care and research.

Place, publisher, year, edition, pages
JMIR Publications Inc., 2022
Keywords
Internet of Things, Parkinson disease, objective measures, patient empowerment, self-assessment, self-management, wearable technology, web interface
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Identifiers
urn:nbn:se:oru:diva-99507 (URN)10.2196/31485 (DOI)000854080300009 ()35679097 (PubMedID)2-s2.0-85132037074 (Scopus ID)
Note

Funding agencies:

General Electric 20160176  

Höganäs AB Statisticon AB

Nethouse Sverige AB

Newbreed EU Cofund doctoral program within the focus area of Successful Ageing at Örebro University

 

Available from: 2022-06-14 Created: 2022-06-14 Last updated: 2022-10-17Bibliographically approved
Aghanavesi, S., Westin, J., Bergquist, F., Nyholm, D., Askmark, H., Aquilonius, S. M., . . . Memedi, M. (2020). A multiple motion sensors index for motor state quantification in Parkinson's disease. Computer Methods and Programs in Biomedicine, 189, Article ID 105309.
Open this publication in new window or tab >>A multiple motion sensors index for motor state quantification in Parkinson's disease
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2020 (English)In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 189, article id 105309Article in journal (Refereed) Published
Abstract [en]

Aim: To construct a Treatment Response Index from Multiple Sensors (TRIMS) for quantification of motor state in patients with Parkinson's disease (PD) during a single levodopa dose. Another aim was to compare TRIMS to sensor indexes derived from individual motor tasks.

Method: Nineteen PD patients performed three motor tests including leg agility, pronation-supination movement of hands, and walking in a clinic while wearing inertial measurement unit sensors on their wrists and ankles. They performed the tests repeatedly before and after taking 150% of their individual oral levodopa-carbidopa equivalent morning dose.Three neurologists blinded to treatment status, viewed patients’ videos and rated their motor symptoms, dyskinesia, overall motor state based on selected items of Unified PD Rating Scale (UPDRS) part III, Dyskinesia scale, and Treatment Response Scale (TRS). To build TRIMS, out of initially 178 extracted features from upper- and lower-limbs data, 39 features were selected by stepwise regression method and were used as input to support vector machines to be mapped to mean reference TRS scores using 10-fold cross-validation method. Test-retest reliability, responsiveness to medication, and correlation to TRS as well as other UPDRS items were evaluated for TRIMS.

Results: The correlation of TRIMS with TRS was 0.93. TRIMS had good test-retest reliability (ICC=0.83). Responsiveness of the TRIMS to medication was good compared to TRS indicating its power in capturing the treatment effects. TRIMS was highly correlated to dyskinesia (R = 0.85), bradykinesia (R=0.84) and gait (R=0.79) UPDRS items. Correlation of sensor index from the upper-limb to TRS was 0.89.

Conclusion: Using the fusion of upper- and lower-limbs sensor data to construct TRIMS provided accurate PD motor states estimation and responsive to treatment. In addition, quantification of upper-limb sensor data during walking test provided strong results.

Place, publisher, year, edition, pages
Elsevier, 2020
National Category
Computer and Information Sciences
Research subject
Informatics
Identifiers
urn:nbn:se:oru:diva-78860 (URN)10.1016/j.cmpb.2019.105309 (DOI)000533562800005 ()31982667 (PubMedID)2-s2.0-85078170133 (Scopus ID)
Funder
Knowledge Foundation
Available from: 2020-01-05 Created: 2020-01-05 Last updated: 2020-05-29Bibliographically approved
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 System Sciences | 2020: . Paper presented at HICSS 53, Grand Wailea, Maui, January 7-10, 2020 (pp. 1056-1062). Maui, Hawaii: HCSS
Open this publication in new window or tab >>A partial least-squares regression model to measure Parkinson’s disease motor states using smartphone data
2020 (English)In: Proceedings of the 53rd Hawaii International Conference on System Sciences | 2020, Maui, Hawaii: HCSS , 2020, p. 1056-1062Conference paper, Published paper (Refereed)
Abstract [en]

Design choices related to development of data- driven models significantly impact or degrade predictive performance of the models. One of the essential steps during development and evaluation of such models is the choice of feature selection and dimension reduction techniques. That is imperative especially in cases dealing with multimodal data gathered from different sources. In this paper, we will investigate the behavior of Partial Least Squares (PLS) regression for dimension reduction and prediction of motor states of Parkinson’s disease (PD) patients, using upper limb motor data gathered by means of a smartphone. The results in terms of correlations between smartphone-based and clinician-derived scores were compared to a previous study using the same data where principal component analysis (PCA) and support vector machines (SVM) were used. The findings from this study show that PLS is superior in terms of prediction performance of motor states in PD than combining PCA and SVM. This indicates that PLS could be considered as a useful methodology in problems where data-driven analysis is needed.

Place, publisher, year, edition, pages
Maui, Hawaii: HCSS, 2020
National Category
Computer and Information Sciences Probability Theory and Statistics
Research subject
Informatics
Identifiers
urn:nbn:se:oru:diva-78958 (URN)
Conference
HICSS 53, Grand Wailea, Maui, January 7-10, 2020
Funder
Knowledge Foundation
Available from: 2020-01-11 Created: 2020-01-11 Last updated: 2022-06-22Bibliographically approved
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), Article ID e17459.
Open this publication in new window or tab >>Information and Communications Technology-Based Interventions Targeting Patient Empowerment: Framework Development
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2020 (English)In: Journal of Medical Internet Research, E-ISSN 1438-8871, Vol. 22, no 8, article id e17459Article, review/survey (Refereed) Published
Abstract [en]

BACKGROUND: Empowerment of patients is often an explicit goal of various information and communications technology (ICT) (electronic, digital) interventions where the patients themselves use ICT tools via the internet. Although several models of empowerment exist, a comprehensive and pragmatic framework is lacking for the development of such interventions.

OBJECTIVE: This study proposes a framework for digital interventions aiming to empower patients that includes a methodology that links objectives, strategies, and evaluation.

METHODS: This study is based on a literature review and iterated expert discussions including a focus group to formulate the proposed model. Our model is based on a review of various models of empowerment and models of technology intervention.

RESULTS: Our framework includes the core characteristics of the empowerment concept (control, psychological coping, self-efficacy, understanding, legitimacy, and support) as well as a set of empowerment consequences: expressed patient perceptions, behavior, clinical outcomes, and health systems effects. The framework for designing interventions includes strategies to achieve empowerment goals using different ICT services. Finally, the intervention model can be used to define project evaluations where the aim is to demonstrate empowerment. The study also included example indicators and associated measurement instruments.

CONCLUSIONS: This framework, which includes definitions, can be useful for the design and evaluation of digital interventions targeting patient empowerment and assist in the development of methods to measure results in this dimension. Further evaluation in the form of interventional studies will be needed to assess the generalizability of the model.

Place, publisher, year, edition, pages
JMIR Publications, 2020
Keywords
ICT intervention, ICT patient empowerment model (ICT4PEM), digital health, eHealth, empowerment, framework model
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:oru:diva-85327 (URN)10.2196/17459 (DOI)000575053600001 ()32845245 (PubMedID)2-s2.0-85090078337 (Scopus ID)
Funder
EU, Horizon 2020Knowledge Foundation
Available from: 2020-09-08 Created: 2020-09-08 Last updated: 2024-01-17Bibliographically approved
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), 111-118
Open this publication in new window or tab >>Motion sensor-based assessment of Parkinson's disease motor symptoms during leg agility tests: results from levodopa challenge
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2020 (English)In: IEEE journal of biomedical and health informatics, ISSN 2168-2194, E-ISSN 2168-2208, Vol. 24, no 1, p. 111-118Article in journal (Refereed) Published
Abstract [en]

Parkinson's disease (PD) is a degenerative, progressive disorder of the central nervous system that mainly affects motor control. The aim of this study was to develop data-driven methods and test their clinimetric properties to detect and quantify PD motor states using motion sensor data from leg agility tests. Nineteen PD patients were recruited in a levodopa single dose challenge study. PD patients performed leg agility tasks while wearing motion sensors on their lower extremities. Clinical evaluation of video recordings was performed by three movement disorder specialists who used four items from the motor section of the Unified PD Rating Scale (UPDRS), the treatment response scale (TRS) and a dyskinesia score. Using the sensor data, spatiotemporal features were calculated and relevant features were selected by feature selection. Machine learning methods like support vector machines (SVM), decision trees and linear regression, using 10-fold cross validation were trained to predict motor states of the patients. SVM showed the best convergence validity with correlation coefficients of 0.81 to TRS, 0.83 to UPDRS #31 (body bradykinesia and hypokinesia), 0.78 to SUMUPDRS (the sum of the UPDRS items: #26-leg agility, #27-arising from chair and #29-gait), and 0.67 to dyskinesia. Additionally, the SVM-based scores had similar test-retest reliability in relation to clinical ratings. The SVM-based scores were less responsive to treatment effects than the clinical scores, particularly with regards to dyskinesia. In conclusion, the results from this study indicate that using motion sensors during leg agility tests may lead to valid and reliable objective measures of PD motor symptoms.

Place, publisher, year, edition, pages
IEEE Computer Society, 2020
Keywords
Legged locomotion, Diseases, Foot, Feature extraction, Machine learning, Standards, Acceleration, Leg agility, Parkinson's disease, support vector machines, stepwise regression, predictive models
National Category
Computer and Information Sciences Neurology
Research subject
Informatics
Identifiers
urn:nbn:se:oru:diva-72361 (URN)10.1109/JBHI.2019.2898332 (DOI)000506642000012 ()2-s2.0-85077669455 (Scopus ID)
Funder
Knowledge FoundationVinnova
Note

Funding Agencies:

Acreo  

Cenvigo  

Sensidose  

Uppsala University  

Örebro University  

Dalarna University 

Available from: 2019-02-09 Created: 2019-02-09 Last updated: 2020-03-17Bibliographically approved
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 19): . Paper presented at IEEE Conference on Biomedical and Health Informatics 2019, Chicago, IL, USA, 19-22 May, 2019.
Open this publication in new window or tab >>A multimodal sensor fusion platform for objective assessment of motor states in Parkinson's disease
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2019 (English)In: IEEE-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH INFORMATICS (BHI 19), 2019Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

This study proposes a platform to objectively assess motor states in Parkinson’s disease (PD) using sensor technology and machine learning. The platform uses sensor information gathered during standardized motor tasks and fuses them in a data-driven manner to produce an index representing motor states of the patients. After investigating clinimetric properties of the platform it was found that the platform had good validity and responsiveness to treatment, which are essential for developing systems to individualize treatments.

National Category
Computer and Information Sciences Information Systems
Research subject
Informatics
Identifiers
urn:nbn:se:oru:diva-74621 (URN)
Conference
IEEE Conference on Biomedical and Health Informatics 2019, Chicago, IL, USA, 19-22 May, 2019
Funder
Knowledge Foundation
Available from: 2019-06-07 Created: 2019-06-07 Last updated: 2019-06-10Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2372-4226

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