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Thangavel G, Memedi M, Hedström K. Information and Communication Technology for Managing Social Isolation and Loneliness Among People Living With Parkinson Disease: Qualitative Study of Barriers and Facilitators. J Med Internet Res 2024; 26:e48175. [PMID: 38231548 PMCID: PMC10831595 DOI: 10.2196/48175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 08/17/2023] [Accepted: 11/20/2023] [Indexed: 01/18/2024] Open
Abstract
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.
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Affiliation(s)
- Gomathi Thangavel
- Centre for Empirical Research on Information Systems, Örebro University School of Business, Örebro, Sweden
| | - Mevludin Memedi
- Centre for Empirical Research on Information Systems, Örebro University School of Business, Örebro, Sweden
- College of Business, Alfaisal University, Riyadh, Saudi Arabia
| | - Karin Hedström
- Centre for Empirical Research on Information Systems, Örebro University School of Business, Örebro, Sweden
- Department of Communication, Quality Management and Information Systems, Mid Sweden University, Sundsvall, Sweden
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Karni L, Jusufi I, Nyholm D, Klein GO, Memedi M. Toward Improved Treatment and Empowerment of Individuals With Parkinson Disease: Design and Evaluation of an Internet of Things System. JMIR Form Res 2022; 6:e31485. [PMID: 35679097 PMCID: PMC9227793 DOI: 10.2196/31485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 03/08/2022] [Accepted: 03/18/2022] [Indexed: 11/13/2022] Open
Abstract
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.
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Affiliation(s)
- Liran Karni
- Centre for Empirical Research on Information Systems, Örebro University School of Business, Örebro, Sweden
| | - Ilir Jusufi
- Department of Computer Science and Media Technology, Linnaeus University, Växjö, Sweden
| | - Dag Nyholm
- Department of Medical Sciences, Neurology, Uppsala University, Uppsala, Sweden
| | - Gunnar Oskar Klein
- Centre for Empirical Research on Information Systems, Örebro University School of Business, Örebro, Sweden
| | - Mevludin Memedi
- Centre for Empirical Research on Information Systems, Örebro University School of Business, Örebro, Sweden
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The internet of medical things and artificial intelligence: trends, challenges, and opportunities. Biocybern Biomed Eng 2022. [DOI: 10.1016/j.bbe.2022.05.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
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Asemi A, Asemi A, Tahaei H. Non-empirical ISO 9241-210:2019-based usability evaluation using fuzzy inference analyser: a special issue on interactive social robots. LIBRARY HI TECH 2022. [DOI: 10.1108/lht-02-2022-0091] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
PurposeThe objective of this research was to develop a new and highly accurate approach based on a fuzzy inference system (FIS) for the evaluation of usability based on ISO 9241-210:2019. In this study, a fully automated method of usability evaluation is used for interactive systems with a special look at interactive social robots.Design/methodology/approachFuzzy logic uses as an intelligent computing technique to deal with uncertainty and incomplete data. Here this system is implemented using MATLAB fuzzy toolbox. This system attempted to quantify four criteria that correlate highly with ISO 9241-210:2019 criteria for the evaluation of interactive systems with maximum usability. Also, the system was evaluated with standard cases of computer interactive systems usability evaluation. The system did not need to train various data and to check the rules. Just small data were used to fine-tune the fuzzy sets. The results were compared against experimental usability evaluation with the statistical analysis.FindingsIt is found that there was a high strong linear relation between the FIS usability assessment and System Usability Scale (SUS) based usability assessment, and authors’ new method provides reliable results in the estimation of the usability.Research limitations/implicationsIn human-robot systems, human performance plays an important role in the performance of social interactive systems. In the present study, the proposed system has considered all the necessary criteria for designing an interactive system with a high level of user because it is based on ISO 9241-210:2019.Practical implicationsFor future research, the system could be expanded with the training of historical data and the production of rules through integrating FIS and neural networks.Originality/valueThis system considered all essential criteria for designing an interactive system with a high level of usability because it is based on ISO 9241-210:2019. For future research, the system could be expanded with the training of historical data and the production of rules through integrating FIS and neural networks.
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Riggare S, Stamford J, Hägglund M. A Long Way to Go: Patient Perspectives on Digital Health for Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2022; 11:S5-S10. [PMID: 33682728 PMCID: PMC8385497 DOI: 10.3233/jpd-202408] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Digital health promises to improve healthcare, health, and wellness through the use of digital technologies. The purpose of this commentary is to review and discuss the field of digital health for Parkinson’s disease (PD) focusing on the needs, expectations, and wishes of people with PD (PwP). Our analysis shows that PwP want to use digital technologies to actively manage the full complexity of living with PD on an individual level, including the unpredictability and variability of the condition. Current digital health projects focusing on PD, however, does not live up to the expectations of PwP. We conclude that for digital health to reach its full potential, the right of PwP to access their own data needs to be recognised, PwP should routinely receive personalised feedback based on their data, and active involvement of PwP as an equal partner in digital health development needs to be the norm.
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Affiliation(s)
- Sara Riggare
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Jon Stamford
- Gentleman Neuroscientist and Independent Parkinson's Patient Advocate, UK
| | - Maria Hägglund
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
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Kristoffersson A, Lindén M. A Systematic Review of Wearable Sensors for Monitoring Physical Activity. SENSORS 2022; 22:s22020573. [PMID: 35062531 PMCID: PMC8778538 DOI: 10.3390/s22020573] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 12/27/2021] [Accepted: 01/05/2022] [Indexed: 01/01/2023]
Abstract
This article reviews the use of wearable sensors for the monitoring of physical activity (PA) for different purposes, including assessment of gait and balance, prevention and/or detection of falls, recognition of various PAs, conduction and assessment of rehabilitation exercises and monitoring of neurological disease progression. The article provides in-depth information on the retrieved articles and discusses study shortcomings related to demographic factors, i.e., age, gender, healthy participants vs patients, and study conditions. It is well known that motion patterns change with age and the onset of illnesses, and that the risk of falling increases with age. Yet, studies including older persons are rare. Gender distribution was not even provided in several studies, and others included only, or a majority of, men. Another shortcoming is that none of the studies were conducted in real-life conditions. Hence, there is still important work to be done in order to increase the usefulness of wearable sensors in these areas. The article highlights flaws in how studies based on previously collected datasets report on study samples and the data collected, which makes the validity and generalizability of those studies low. Exceptions exist, such as the promising recently reported open dataset FallAllD, wherein a longitudinal study with older adults is ongoing.
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Asemi A, Asemi A. A judgment-based model for usability evaluating of interactive systems using fuzzy Multi Factors Evaluation (MFE). Appl Soft Comput 2022. [DOI: 10.1016/j.asoc.2022.108411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Desai D, Shende P. Integration of Internet of Things with Quantum Dots: A State-of-the-art of Medicine. Curr Pharm Des 2021; 27:2068-2075. [PMID: 33618640 DOI: 10.2174/1381612827666210222113740] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 01/25/2021] [Indexed: 11/22/2022]
Abstract
Internet of Things (IoT) emerges as disruptive innovation and development in the fields of drug delivery and biomedical sciences using on-target active transportation, sensors, wearable devices, real-time diagnostics, etc. Semiconducting fluorescence emitting material, quantum dots on integration with IoT displayed interesting results in the healthcare sector, especially in hospitals and pathological laboratories. Presently, the integrated system is used to improve productivity without the interference of human and offer a cost-effective system. This integrated system can be used for the detection of various diseases like epilepsy, cancer, diabetes, etc., and various biomedical applications like energy storage, lights, sensor technology, light filters, etc. The integrated technology is implemented into the field of medicine for simplifying the approaches in therapeutics and diagnostic applications. The collected and analyzed data are further useful for healthcare professionals to find patient-centric solutions. Artificial Intelligence-aided IoT emerges as a novel technology for transmitting and securing health data. Despite some of the limitations like e-waste and the risk of hacking, an IoT-based QD system will be considered as a modern healthcare provider with life-saving products for enriching the medical quality and real-time accessibility.
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Affiliation(s)
- Drashti Desai
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM'S NMIMS, Vile Parle (W), Mumbai, India
| | - Pravin Shende
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM'S NMIMS, Vile Parle (W), Mumbai, India
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The Internet of Things in Geriatric Healthcare. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:6611366. [PMID: 34336163 PMCID: PMC8313366 DOI: 10.1155/2021/6611366] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 06/27/2021] [Accepted: 07/09/2021] [Indexed: 11/17/2022]
Abstract
There is a significant increase in the geriatric population across the globe. With the increase in the number of geriatric people and their associated health issues, the need for larger healthcare resources is inevitable. Because of this, healthcare service-providing industries are facing a severe challenge. However, technological advancement in recent years has enabled researchers to develop intelligent devices to deal with the scarcity of healthcare resources. In this regard, the Internet of things (IoT) technology has been a boon for healthcare services industries. It not only allows the monitoring of the health parameters of geriatric patients from a remote location but also lets them live an independent life in a cost-efficient way. The current paper provides up-to-date comprehensive knowledge of IoT-based technologies for geriatric healthcare applications. The study also discusses the current trends, issues, challenges, and future scope of research in the area of geriatric healthcare using IoT technology. Information provided in this paper will be helpful to develop futuristic solutions and provide efficient cost-effective healthcare services to the needy.
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A Network Architecture and Routing Protocol for the MEDIcal WARNing System. JOURNAL OF SENSOR AND ACTUATOR NETWORKS 2021. [DOI: 10.3390/jsan10030044] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The MEDIcal WARNing (MEDIWARN) system continuously and automatically monitors the vital parameters of pre-intensive care hospitalized patients and, thanks to an intelligent processing system, provides the medical teams with a better understanding of their patients’ clinical condition, thus enabling a prompt reaction to any change. Since the hospital units generally lack a wired infrastructure, a wireless network is required to collect sensor data in a server for processing purposes. This work presents the MEDIWARN communication system, addressing both the network architecture and a simple, lightweight and configurable routing protocol that fits the system requirements, such as the ability to offer path redundancy and mobility support without significantly increasing the network workload and latency. The novel protocol, called the MultiPath Routing Protocol for MEDIWARN (MP-RPM), was therefore designed as a solution to support low-latency reliable transmissions on a dynamic network while limiting the network overhead due to the control messages. The paper describes the MEDIWARN communication system and addresses the experimental performance evaluation of an implementation in a real use-case scenario. Moreover, the work discusses a simulative assessment of the MEDIWARN communication system performance obtained using different routing protocols. In particular, the timeliness and reliability results obtained by the MP-RPM routing protocol are compared with those obtained by two widely adopted routing protocols, i.e., the Ad-hoc On-demand Distance Vector (AODV) and the Destination-Sequenced Distance-Vector Routing (DSDV).
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Wannheden C, Revenäs Å. How People with Parkinson's Disease and Health Care Professionals Wish to Partner in Care Using eHealth: Co-Design Study. J Med Internet Res 2020; 22:e19195. [PMID: 32955448 PMCID: PMC7536604 DOI: 10.2196/19195] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Revised: 07/04/2020] [Accepted: 07/26/2020] [Indexed: 01/26/2023] Open
Abstract
Background Worldwide, the number of people with Parkinson’s disease (PD) is predicted to double between the years 2005 and 2030. Chronic care management requires active collaboration and knowledge exchange between patients and health care professionals (HCPs) for best possible health outcomes, which we describe as co-care. eHealth services have the potential to support the realization of co-care between people with PD (PwP) and HCPs. Objective This study aimed to explore how co-care could be operationalized in PD care, supported by eHealth. More specifically, this study explores PwP's and HCPs' expectations and desired eHealth functionalities to achieve co-care. Methods Principles of participatory design were used to enable the identification of co-care needs and design ideas, in a series of 4 half-day co-design workshops. The sample included 7 (4 women) PwP and 9 (4 women) HCPs, including 4 neurologists, 3 nurses, and 2 physiotherapists. The co-design process resulted in a functional prototype that was evaluated by the co-design participants in the last workshop. Data were collected through note cards produced by the participants during the first 3 workshops and focus group discussions during the 3rd and 4th workshops. The data were analyzed using qualitative thematic analysis. After the workshop series, the prototype was demonstrated at a Mini Fair for ongoing PD research and evaluated using a self-developed questionnaire with 37 respondents: 31 PwP (14 women) and 6 informal caregivers (3 women). Descriptive statistics are reported. Results The qualitative analysis of data resulted in 2 main themes. The first theme, core eHealth functionalities and their expected values, describes 6 desired eHealth functionalities for supporting PD co-care between PwP and HCPs: (1) self-tracking, (2) previsit forms, (3) graphical visualization, (4) clinical decision support, (5) self-care recommendations, and (6) asynchronous communication. The second theme, individual and organizational constraints, describes constraints that need to be addressed to succeed with an eHealth service for co-care. Individual constraints include eHealth literacy and acceptance; organizational constraints include teamwork and administrative workload. The majority of the questionnaire respondents (31/37, 84%) perceived that they would benefit from an eHealth service similar to the demonstrated prototype. All prototype functionalities were rated as very important or important by the majority of respondents (ranging from 86% to 97% per functionality). Conclusions This study adds to our knowledge on how PD co-care could be operationalized. Co-care implies a shift from episodic routine-driven care to more flexible care management that is driven by the mutual needs of patients and HCPs and supported by active information exchange between them, as well as automated information processing to generate patient-specific advice. More research is needed to further explore the concept of co-care in chronic care management and what it means for self-care and health care. International Registered Report Identifier (IRRID) RR2-10.2196/11278
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Affiliation(s)
- Carolina Wannheden
- Medical Management Centre, Department of Learning, Informatics, Management and Ethics (LIME), Karolinska Institutet, Stockholm, Sweden
| | - Åsa Revenäs
- Centre for Clinical Research, County of Västmanland, Uppsala University, Västerås, Sweden.,School of Health, Care and Social Welfare, Division of Physiotherapy, Mälardalen University, Västerås, Sweden
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Karni L, Dalal K, Memedi M, Kalra D, Klein GO. Information and Communications Technology-Based Interventions Targeting Patient Empowerment: Framework Development. J Med Internet Res 2020; 22:e17459. [PMID: 32845245 PMCID: PMC7481871 DOI: 10.2196/17459] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 05/04/2020] [Accepted: 06/03/2020] [Indexed: 01/22/2023] Open
Abstract
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.
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Affiliation(s)
- Liran Karni
- Centre for Empirical Research on Information Systems, Örebro University School of Business, Örebro, Sweden
| | - Koustuv Dalal
- Centre for Empirical Research on Information Systems, Örebro University School of Business, Örebro, Sweden.,School of Health Sciences, Mid Sweden University, Sundsvall, Sweden
| | - Mevludin Memedi
- Centre for Empirical Research on Information Systems, Örebro University School of Business, Örebro, Sweden
| | - Dipak Kalra
- European Institute for Innovation through Health Data, Gent, Belgium
| | - Gunnar Oskar Klein
- Centre for Empirical Research on Information Systems, Örebro University School of Business, Örebro, Sweden
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Aghanavesi S, Westin J, Bergquist F, Nyholm D, Askmark H, Aquilonius SM, Constantinescu R, Medvedev A, Spira J, Ohlsson F, Thomas I, Ericsson A, Buvarp DJ, Memedi M. A multiple motion sensors index for motor state quantification in Parkinson's disease. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2020; 189:105309. [PMID: 31982667 DOI: 10.1016/j.cmpb.2019.105309] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 12/22/2019] [Accepted: 12/29/2019] [Indexed: 06/10/2023]
Abstract
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.
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Affiliation(s)
| | - Jerker Westin
- Department of Computer Engineering, Dalarna University, Falun, Sweden.
| | - Filip Bergquist
- Department of Pharmacology at Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden.
| | - Dag Nyholm
- Department of Neuroscience, Neurology at Uppsala University, Uppsala, Sweden.
| | - Håkan Askmark
- Department of Neuroscience, Neurology at Uppsala University, Uppsala, Sweden.
| | | | - Radu Constantinescu
- Department of Clinical Neuroscience, University of Gothenburg, Gothenburg, Sweden.
| | - Alexander Medvedev
- Department of Information Technology, at Uppsala University, Uppsala, Sweden.
| | | | | | - Ilias Thomas
- Department of Statistics, Dalarna University, Falun, Sweden.
| | | | - Dongni Johansson Buvarp
- Department of Clinical Neuroscience and Rehabilitation, University of Gothenburg, Gothenburg, Sweden.
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Kristoffersson A, Lindén M. A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis. SENSORS 2020; 20:s20051502. [PMID: 32182907 PMCID: PMC7085653 DOI: 10.3390/s20051502] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Revised: 02/26/2020] [Accepted: 03/05/2020] [Indexed: 12/19/2022]
Abstract
The use of wearable body sensors for health monitoring is a quickly growing field with the potential of offering a reliable means for clinical and remote health management. This includes both real-time monitoring and health trend monitoring with the aim to detect/predict health deterioration and also to act as a prevention tool. The aim of this systematic review was to provide a qualitative synthesis of studies using wearable body sensors for health monitoring. The synthesis and analysis have pointed out a number of shortcomings in prior research. Major shortcomings are demonstrated by the majority of the studies adopting an observational research design, too small sample sizes, poorly presented, and/or non-representative participant demographics (i.e., age, gender, patient/healthy). These aspects need to be considered in future research work.
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Internet of things in medicine: A systematic mapping study. J Biomed Inform 2020; 103:103383. [PMID: 32044417 DOI: 10.1016/j.jbi.2020.103383] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 01/28/2020] [Accepted: 02/01/2020] [Indexed: 12/26/2022]
Abstract
CONTEXT The current studies on IoT in healthcare have reviewed the uses of this technology in a combination of healthcare domains, including nursing, rehabilitation sciences, ambient assisted living (AAL), medicine, etc. However, no review study has scrutinized IoT advances exclusively in medicine irrespective of other healthcare domains. OBJECTIVES The purpose of the current study was to identify and map the current IoT developments in medicine through providing graphical/tabular classifications on the current experimental and practical IoT information in medicine, the involved medical sub-fields, the locations of IoT use in medicine, and the bibliometric information about IoT research articles. METHODS In this systematic mapping study, the studies published between 2000 and 2018 in major online scientific databases, including IEEE Xplore, Web of Science, Scopus, and PubMed were screened. A total of 3679 papers were found from which 89 papers were finally selected based on specific inclusion/exclusion criteria. RESULTS While the majority of medical IoT studies were experimental and prototyping in nature, they generally reported that home was the most popular place for medical IoT applications. It was also found that neurology, cardiology, and psychiatry/psychology were the medical sub-fields receiving the most IoT attention. Bibliometric analysis showed that IEEE Internet of Things Journal has published the most influential IoT articles. India, China and the United States were found to be the most involved countries in medical IoT research. CONCLUSIONS Although IoT has not yet been employed in some medical sub-fields, recent substantial surge in the number of medical IoT studies will most likely lead to the engagement of more medical sub-fields in the years to come. IoT literature also shows that the ambiguity of assigning a variety of terms to IoT, namely system, platform, device, tool, etc., and the interchangeable uses of these terms require a taxonomy study to investigate the precise definition of these terms. Other areas of research have also been mentioned at the end of this article.
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Morgan C, Rolinski M, McNaney R, Jones B, Rochester L, Maetzler W, Craddock I, Whone AL. Systematic Review Looking at the Use of Technology to Measure Free-Living Symptom and Activity Outcomes in Parkinson's Disease in the Home or a Home-like Environment. JOURNAL OF PARKINSON'S DISEASE 2020; 10:429-454. [PMID: 32250314 PMCID: PMC7242826 DOI: 10.3233/jpd-191781] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 01/31/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND The emergence of new technologies measuring outcomes in Parkinson's disease (PD) to complement the existing clinical rating scales has introduced the possibility of measurement occurring in patients' own homes whilst they freely live and carry out normal day-to-day activities. OBJECTIVE This systematic review seeks to provide an overview of what technology is being used to test which outcomes in PD from free-living participant activity in the setting of the home environment. Additionally, this review seeks to form an impression of the nature of validation and clinimetric testing carried out on the technological device(s) being used. METHODS Five databases (Medline, Embase, PsycInfo, Cochrane and Web of Science) were systematically searched for papers dating from 2000. Study eligibility criteria included: adults with a PD diagnosis; the use of technology; the setting of a home or home-like environment; outcomes measuring any motor and non-motor aspect relevant to PD, as well as activities of daily living; unrestricted/unscripted activities undertaken by participants. RESULTS 65 studies were selected for data extraction. There were wide varieties of participant sample sizes (<10 up to hundreds) and study durations (<2 weeks up to a year). The metrics evaluated by technology, largely using inertial measurement units in wearable devices, included gait, tremor, physical activity, bradykinesia, dyskinesia and motor fluctuations, posture, falls, typing, sleep and activities of daily living. CONCLUSIONS Home-based free-living testing in PD is being conducted by multiple groups with diverse approaches, focussing mainly on motor symptoms and sleep.
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Affiliation(s)
- Catherine Morgan
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- School of Computer Science, Electrical and Electronic Engineering, and Engineering Mathematics, Faculty of Engineering, University of Bristol, Bristol, UK
- Movement Disorders Group, Bristol Brain Centre, Southmead Hospital, North Bristol National Health Service Trust, Bristol, UK
| | - Michal Rolinski
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Movement Disorders Group, Bristol Brain Centre, Southmead Hospital, North Bristol National Health Service Trust, Bristol, UK
| | - Roisin McNaney
- School of Computer Science, Electrical and Electronic Engineering, and Engineering Mathematics, Faculty of Engineering, University of Bristol, Bristol, UK
| | - Bennet Jones
- Library and Knowledge Service, Learning and Research, Southmead Hospital, North Bristol National Health Service Trust, Bristol, UK
| | - Lynn Rochester
- Institute of Neuroscience, Newcastle University, Newcastle Upon Tyne, UK
- Newcastle Upon Tyne Hospitals National Health Service Foundation Trust, Newcastle Upon Tyne, UK
| | - Walter Maetzler
- Department of Neurology, Christian-Albrechts University, Kiel, Germany
| | - Ian Craddock
- School of Computer Science, Electrical and Electronic Engineering, and Engineering Mathematics, Faculty of Engineering, University of Bristol, Bristol, UK
| | - Alan L. Whone
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Movement Disorders Group, Bristol Brain Centre, Southmead Hospital, North Bristol National Health Service Trust, Bristol, UK
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Special Issue: Empowering eHealth with Smart Internet of Things (IoT) Medical Devices. JOURNAL OF SENSOR AND ACTUATOR NETWORKS 2019. [DOI: 10.3390/jsan8020033] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The use of Internet of Things (IoT) with medical devices within a connected health environment promotes the quick flow of information and enables easy access to it [...]
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VisKit: Web-Based Interactive IoT Management with Deep Visual Object Detection. JOURNAL OF SENSOR AND ACTUATOR NETWORKS 2019. [DOI: 10.3390/jsan8010012] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Various technologies and standards for the Internet of Things (IoT) have defined the way devices should interact with each other to provide an intelligent IoT service to users in an efficient manner. Although the usability of system interface between the platform and users is one of the key factors for the success of IoT ecosystems, the manner in which IoT platforms should interact with users has not been well studied. Current IoT platforms provide a simple list-based interface to manage devices, which result in the degradation of their usability as the number of devices increases. In this paper, we propose an interactive web-based IoT management system where deep object detection techniques are adopted to facilitate user’s device selection and management. The proposed system automatically recognizes the device type from video streams and accordingly generates smart controllers. The users can choose a device by touching an object in the video stream and use a smart controller to control the selected device. Finally, we show the feasibility of the proposed system through the implementation of a prototype which demonstrates a set of user scenarios.
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