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Hobson E, McDermott C. Advances in symptom management and in monitoring disease progression in motor neuron disease. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2024; 176:119-169. [PMID: 38802174 DOI: 10.1016/bs.irn.2024.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
The aim of supportive management of motor neuron disease is to improve survival, promote good quality of life and patient independence and autonomy whilst preparing for future progression and the end of life. Multidisciplinary specialist care aims to address the multifaceted and interacting biopsychosocial problems associated with motor neuron disease that leads to proven benefits in both survival and quality of life. This chapter will explore principles, structure and details of treatment options, and make recommendations for practice and for future research.
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Affiliation(s)
- Esther Hobson
- Sheffield Institute for Translational Neuroscience, Division of Neuroscience, School of Medicine and Population Health, University of Sheffield, Sheffield, United Kingdom
| | - Christopher McDermott
- Sheffield Institute for Translational Neuroscience, Division of Neuroscience, School of Medicine and Population Health, University of Sheffield, Sheffield, United Kingdom.
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He J, Luo A, Yu J, Qian C, Liu D, Hou M, Ma Y. Quantitative assessment of spasticity: a narrative review of novel approaches and technologies. Front Neurol 2023; 14:1121323. [PMID: 37475737 PMCID: PMC10354649 DOI: 10.3389/fneur.2023.1121323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 06/19/2023] [Indexed: 07/22/2023] Open
Abstract
Spasticity is a complex neurological disorder, causing significant physical disabilities and affecting patients' independence and quality of daily lives. Current spasticity assessment methods are questioned for their non-standardized measurement protocols, limited reliabilities, and capabilities in distinguishing neuron or non-neuron factors in upper motor neuron lesion. A series of new approaches are developed for improving the effectiveness of current clinical used spasticity assessment methods with the developing technology in biosensors, robotics, medical imaging, biomechanics, telemedicine, and artificial intelligence. We investigated the reliabilities and effectiveness of current spasticity measures employed in clinical environments and the newly developed approaches, published from 2016 to date, which have the potential to be used in clinical environments. The new spasticity scales, taking advantage of quantified information such as torque, or echo intensity, the velocity-dependent feature and patients' self-reported information, grade spasticity semi-quantitatively, have competitive or better reliability than previous spasticity scales. Medical imaging technologies, including near-infrared spectroscopy, magnetic resonance imaging, ultrasound and thermography, can measure muscle hemodynamics and metabolism, muscle tissue properties, or temperature of tissue. Medical imaging-based methods are feasible to provide quantitative information in assessing and monitoring muscle spasticity. Portable devices, robotic based equipment or myotonometry, using information from angular, inertial, torque or surface EMG sensors, can quantify spasticity with the help of machine learning algorithms. However, spasticity measures using those devices are normally not physiological sound. Repetitive peripheral magnetic stimulation can assess patients with severe spasticity, which lost voluntary contractions. Neuromusculoskeletal modeling evaluates the neural and non-neural properties and may gain insights into the underlying pathology of spasticity muscles. Telemedicine technology enables outpatient spasticity assessment. The newly developed spasticity methods aim to standardize experimental protocols and outcome measures and enable quantified, accurate, and intelligent assessment. However, more work is needed to investigate and improve the effectiveness and accuracy of spasticity assessment.
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Affiliation(s)
- Jian He
- Research Academy of Grand Health, Faculty of Sports Sciences, Ningbo University, Ningbo, China
| | - Anhua Luo
- Research Academy of Grand Health, Faculty of Sports Sciences, Ningbo University, Ningbo, China
| | - Jiajia Yu
- Research Academy of Grand Health, Faculty of Sports Sciences, Ningbo University, Ningbo, China
| | - Chengxi Qian
- Research Academy of Grand Health, Faculty of Sports Sciences, Ningbo University, Ningbo, China
| | - Dongwei Liu
- School of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou, China
| | - Meijin Hou
- National Joint Engineering Research Centre of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China
- Key Laboratory of Orthopaedics and Traumatology of Traditional Chinese Medicine and Rehabilitation (Fujian University of TCM), Ministry of Education, Fuzhou, China
| | - Ye Ma
- Research Academy of Grand Health, Faculty of Sports Sciences, Ningbo University, Ningbo, China
- National Joint Engineering Research Centre of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China
- Key Laboratory of Orthopaedics and Traumatology of Traditional Chinese Medicine and Rehabilitation (Fujian University of TCM), Ministry of Education, Fuzhou, China
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Kwasnicka D, Keller J, Perski O, Potthoff S, Ten Hoor GA, Ainsworth B, Crutzen R, Dohle S, van Dongen A, Heino M, Henrich JF, Knox L, König LM, Maltinsky W, McCallum C, Nalukwago J, Neter E, Nurmi J, Spitschan M, Van Beurden SB, Van der Laan LN, Wunsch K, Levink JJJ, Sanderman R. White Paper: Open Digital Health - accelerating transparent and scalable health promotion and treatment. Health Psychol Rev 2022; 16:475-491. [PMID: 35240931 DOI: 10.1080/17437199.2022.2046482] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
In this White Paper, we outline recommendations from the perspective of health psychology and behavioural science, addressing three research gaps: (1) What methods in the health psychology research toolkit can be best used for developing and evaluating digital health tools? (2) What are the most feasible strategies to reuse digital health tools across populations and settings? (3) What are the main advantages and challenges of sharing (openly publishing) data, code, intervention content and design features of digital health tools? We provide actionable suggestions for researchers joining the continuously growing Open Digital Health movement, poised to revolutionise health psychology research and practice in the coming years. This White Paper is positioned in the current context of the COVID-19 pandemic, exploring how digital health tools have rapidly gained popularity in 2020-2022, when world-wide health promotion and treatment efforts rapidly shifted from face-to-face to remote delivery. This statement is written by the Directors of the not-for-profit Open Digital Health initiative (n = 6), Experts attending the European Health Psychology Society Synergy Expert Meeting (n = 17), and the initiative consultant, following a two-day meeting (19-20th August 2021).
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Affiliation(s)
- Dominika Kwasnicka
- NHMRC CRE in Digital Technology to Transform Chronic Disease Outcomes, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.,Faculty of Psychology, SWPS University of Social Sciences and Humanities, Wrocław, Poland
| | - Jan Keller
- Department of Education and Psychology; Freie Universität Berlin, Berlin, Germany
| | - Olga Perski
- Department of Behavioural Science and Health, University College London, London, UK
| | - Sebastian Potthoff
- Department of Social Work, Education and Community Wellbeing, Northumbria University, Newcastle upon Tyne, UK
| | - Gill A Ten Hoor
- Department of Work & Social Psychology, Maastricht University, Maastricht, The Netherlands
| | - Ben Ainsworth
- Department of Psychology, University of Bath, Bath, UK
| | - Rik Crutzen
- Department of Health Promotion, Maastricht University/CAPHRI, Maastricht, the Netherlands
| | - Simone Dohle
- Department of Psychology, University of Cologne, Cologne, Germany and Institute of General Practice and Family Medicine, University Hospital Bonn, University of Bonn, Bonn, Germany
| | - Anne van Dongen
- Department of Psychology, Health, and Technology, University of Twente, Enschede, the Netherlands
| | - Matti Heino
- Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Julia F Henrich
- Faculty of Social and Behavioural Sciences, Leiden University, Institute of Psychology, Unit of Health-, Medical- and Neuropsychology, Leiden, The Netherlands
| | - Liam Knox
- Sheffield Institute for Translational Neuroscience, The University of Sheffield, Sheffield, UK
| | - Laura M König
- Faculty of Life Sciences, University of Bayreuth, Bayreuth, Germany
| | - Wendy Maltinsky
- Faculty of Natural Sciences, Division of Psychology, University of Stirling, Stirling, UK
| | - Claire McCallum
- Centre for Digital Health and Care, Faculty of Engineering, University of Bristol, Bristol, UK
| | - Judith Nalukwago
- Center for Communication Programs, USAID-Social and Behavior Change Activity, Johns Hopkins University Bloomberg School of Public Health, Kampala, Uganda
| | - Efrat Neter
- Department of Behavioral Sciences, Ruppin Academic Center, Emeq Hefer, Israel
| | - Johanna Nurmi
- Faculty of Social Sciences, University of Helsinki, Helsinki, Finland.,University of Cambridge, Behavioural Science Group, Primary Care Unit, Institute of Public Health, Forvie Site, Cambridge, UK
| | - Manuel Spitschan
- TUM Department of Sport and Health Sciences (TUM SG), Technical University of Munich, Munich, Germany and Translational Sensory and Circadian Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | | | - L Nynke Van der Laan
- Department of Communication and Cognition, Tilburg University, Tilburg, The Netherlands
| | - Kathrin Wunsch
- Karlsruhe Institute of Technology, Institute of Sports and Sports Science, Karlsruhe, Germany
| | - Jasper J J Levink
- Levink Life Sciences BV & Stichting Feniks Ontwikkelingsbegeleiding, Utrecht, The Netherlands
| | - Robbert Sanderman
- Department of Psychology, Health, and Technology, University of Twente, Enschede, the Netherlands.,Department of Health Psychology, University Medical Center Groningen University of Groningen, Groningen, The Netherlands
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