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Grijalvo M, Ordieres-Meré J, Villalba-Díez J, Aladro-Benito Y, Martín-Ávila G, Simon-Hurtado A, Vivaracho-Pascual C. Sufficiency for PSS tracking gait disorders in multiple sclerosis: A managerial perspective. Heliyon 2024; 10:e30001. [PMID: 38707444 PMCID: PMC11066638 DOI: 10.1016/j.heliyon.2024.e30001] [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: 09/27/2023] [Revised: 04/15/2024] [Accepted: 04/18/2024] [Indexed: 05/07/2024] Open
Abstract
This study primarily aimed to explore the capabilities of digitalisation in the healthcare context, focusing on a specific disease. In this case, the study examined the potential of remote monitoring of gait to address the sensitivity of multiple sclerosis progression to gait characteristics by adopting a non-invasive approach to remotely quantify gait disturbances in a patient's daily life. To better understand the managerial aspects associated with this approach, the researchers conducted a literature review along with a set of semi-structured interviews. The target population included MS patients as well as the key agents involved in their care: patients' family members, neurologists, MS nurses, physiotherapists, medical directors, and pharmacist. The study identifies the perceived barriers and drivers that could contribute to the successful deployment of PSS remote gait monitoring as a healthcare service: i) At mega-level governance. Implications on privacy and security data are notable barriers missing on the speech. ii) At macro level, funding is highlighted as main barrier. The cost and lack of health system subsidies may render initiatives unsustainable, as emphasised by the interviewees. iii) At meso level, useable data is recognised as a driver. The data collection process can align with diverse interests to create value and business opportunities for the ecosystem actors, enhance care, attract stakeholders, such as insurers and pharma, and form partnerships. iv) At micro-level processes, we find two potential barriers: wearable device and app usability (comfort, navigation, efficiency) and organisational/behavioural aspects (training, digital affinity, skills), which are crucial for value creation in innovation ecosystems among patients and healthcare professionals. Finally, we find an interesting gap in the literature and interviews. Stakeholders' limited awareness of technological demands, especially from information technologies, for a successful long-term service, can be consider two key barriers for PSS.
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Affiliation(s)
- Mercedes Grijalvo
- Department of Organizational Engineering, Business Administration and Statistics, Universidad Politécnica de Madrid, Madrid, Spain
| | - Joaquín Ordieres-Meré
- Department of Organizational Engineering, Business Administration and Statistics, Universidad Politécnica de Madrid, Madrid, Spain
| | | | - Yolanda Aladro-Benito
- Department of Neurology, Getafe University Hospital, Madrid, Spain
- Faculty of Biomedical and Health Sciences, European University of Madrid, Madrid, Spain
| | | | - Arancha Simon-Hurtado
- Departamento de Informática, Escuela de Ingeniería Informática de Valladolid, Universidad de Valladolid, Paseo de Belén 15, 47011, Valladolid, Spain
| | - Carlos Vivaracho-Pascual
- Departamento de Informática, Escuela de Ingeniería Informática de Valladolid, Universidad de Valladolid, Paseo de Belén 15, 47011, Valladolid, Spain
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Gervasoni E, Anastasi D, Di Giovanni R, Solaro C, Rovaris M, Brichetto G, Confalonieri P, Tacchino A, Carpinella I, Cattaneo D. Uncovering Subtle Gait Deterioration in People with Early-Stage Multiple Sclerosis Using Inertial Sensors: A 2-Year Multicenter Longitudinal Study. SENSORS (BASEL, SWITZERLAND) 2023; 23:9249. [PMID: 38005634 PMCID: PMC10674176 DOI: 10.3390/s23229249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 11/09/2023] [Accepted: 11/14/2023] [Indexed: 11/26/2023]
Abstract
Limited longitudinal studies have been conducted on gait impairment progression overtime in non-disabled people with multiple sclerosis (PwMS). Therefore, a deeper understanding of gait changes with the progression of the disease is essential. The objective of the present study was to describe changes in gait quality in PwMS with a disease duration ≤ 5 years, and to verify whether a change in gait quality is associated with a change in disability and perception of gait deterioration. We conducted a multicenter prospective cohort study. Fifty-six subjects were assessed at baseline (age: 38.2 ± 10.7 years, Expanded Disability Status Scale (EDSS): 1.5 ± 0.7 points) and after 2 years, participants performed the six-minute walk test (6MWT) wearing inertial sensors. Quality of gait (regularity, symmetry, and instability), disability (EDSS), and walking perception (multiple sclerosis walking scale-12, MSWS-12) were collected. We found no differences on EDSS, 6MWT, and MSWS-12 between baseline and follow-up. A statistically significant correlation between increased EDSS scores and increased gait instability was found in the antero-posterior (AP) direction (r = 0.34, p = 0.01). Seventeen subjects (30%) deteriorated (increase of at least 0.5 point at EDSS) over 2 years. A multivariate analysis on deteriorated PwMS showed that changes in gait instability medio-lateral (ML) and stride regularity, and changes in ML gait symmetry were significantly associated with changes in EDSS (F = 7.80 (3,13), p = 0.003, R2 = 0.56). Moreover, gait changes were associated with a decrease in PwMS perception on stability (p < 0.05). Instrumented assessment can detect subtle changes in gait stability, regularity, and symmetry not revealed during EDSS neurological assessment. Moreover, instrumented changes in gait quality impact on subjects' perception of gait during activities of daily living.
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Affiliation(s)
- Elisa Gervasoni
- IRCCS Fondazione Don Carlo Gnocchi Onlus, 20148 Milan, Italy; (E.G.); (D.A.); (M.R.); (D.C.)
| | - Denise Anastasi
- IRCCS Fondazione Don Carlo Gnocchi Onlus, 20148 Milan, Italy; (E.G.); (D.A.); (M.R.); (D.C.)
| | - Rachele Di Giovanni
- Department of Rehabilitation, Centro di Recupero e Rieducazione Funzionale (CRRF) “Mons. Luigi Novarese”, 13040 Moncrivello, Italy;
| | | | - Marco Rovaris
- IRCCS Fondazione Don Carlo Gnocchi Onlus, 20148 Milan, Italy; (E.G.); (D.A.); (M.R.); (D.C.)
| | - Giampaolo Brichetto
- Italian Multiple Sclerosis Foundation, Scientific Research Area, 16126 Genoa, Italy; (G.B.); (A.T.)
| | - Paolo Confalonieri
- IRCCS Foundation “Carlo Besta” Neurological Institute, 20133 Milan, Italy;
| | - Andrea Tacchino
- Italian Multiple Sclerosis Foundation, Scientific Research Area, 16126 Genoa, Italy; (G.B.); (A.T.)
| | - Ilaria Carpinella
- IRCCS Fondazione Don Carlo Gnocchi Onlus, 20148 Milan, Italy; (E.G.); (D.A.); (M.R.); (D.C.)
| | - Davide Cattaneo
- IRCCS Fondazione Don Carlo Gnocchi Onlus, 20148 Milan, Italy; (E.G.); (D.A.); (M.R.); (D.C.)
- Department of Physiopathology and Transplants, University of Milan, 20122 Milan, Italy
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Woelfle T, Bourguignon L, Lorscheider J, Kappos L, Naegelin Y, Jutzeler CR. Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective. J Med Internet Res 2023; 25:e44428. [PMID: 37498655 PMCID: PMC10415952 DOI: 10.2196/44428] [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: 11/18/2022] [Revised: 12/19/2022] [Accepted: 05/04/2023] [Indexed: 07/28/2023] Open
Abstract
BACKGROUND Wearable sensor technologies have the potential to improve monitoring in people with multiple sclerosis (MS) and inform timely disease management decisions. Evidence of the utility of wearable sensor technologies in people with MS is accumulating but is generally limited to specific subgroups of patients, clinical or laboratory settings, and functional domains. OBJECTIVE This review aims to provide a comprehensive overview of all studies that have used wearable sensors to assess, monitor, and quantify motor function in people with MS during daily activities or in a controlled laboratory setting and to shed light on the technological advances over the past decades. METHODS We systematically reviewed studies on wearable sensors to assess the motor performance of people with MS. We scanned PubMed, Scopus, Embase, and Web of Science databases until December 31, 2022, considering search terms "multiple sclerosis" and those associated with wearable technologies and included all studies assessing motor functions. The types of results from relevant studies were systematically mapped into 9 predefined categories (association with clinical scores or other measures; test-retest reliability; group differences, 3 types; responsiveness to change or intervention; and acceptability to study participants), and the reporting quality was determined through 9 questions. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines. RESULTS Of the 1251 identified publications, 308 were included: 176 (57.1%) in a real-world context, 107 (34.7%) in a laboratory context, and 25 (8.1%) in a mixed context. Most publications studied physical activity (196/308, 63.6%), followed by gait (81/308, 26.3%), dexterity or tremor (38/308, 12.3%), and balance (34/308, 11%). In the laboratory setting, outcome measures included (in addition to clinical severity scores) 2- and 6-minute walking tests, timed 25-foot walking test, timed up and go, stair climbing, balance tests, and finger-to-nose test, among others. The most popular anatomical landmarks for wearable placement were the waist, wrist, and lower back. Triaxial accelerometers were most commonly used (229/308, 74.4%). A surge in the number of sensors embedded in smartphones and smartwatches has been observed. Overall, the reporting quality was good. CONCLUSIONS Continuous monitoring with wearable sensors could optimize the management of people with MS, but some hurdles still exist to full clinical adoption of digital monitoring. Despite a possible publication bias and vast heterogeneity in the outcomes reported, our review provides an overview of the current literature on wearable sensor technologies used for people with MS and highlights shortcomings, such as the lack of harmonization, transparency in reporting methods and results, and limited data availability for the research community. These limitations need to be addressed for the growing implementation of wearable sensor technologies in clinical routine and clinical trials, which is of utmost importance for further progress in clinical research and daily management of people with MS. TRIAL REGISTRATION PROSPERO CRD42021243249; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=243249.
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Affiliation(s)
- Tim Woelfle
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Lucie Bourguignon
- Department of Health Sciences and Technology, ETH Zurich, Zürich, Switzerland
| | - Johannes Lorscheider
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Ludwig Kappos
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Yvonne Naegelin
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Basel, Switzerland
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Mestanza Mattos FG, Luciano F, Lencioni T, Gervasoni E, Jonsdottir J, Anastasi D, Pavei G, Clerici M, Cattaneo D. Complementary use of statistical parametric mapping and gait profile score to describe walking alterations in multiple sclerosis: a cross-sectional study. Sci Rep 2023; 13:10465. [PMID: 37380732 DOI: 10.1038/s41598-023-36916-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 06/12/2023] [Indexed: 06/30/2023] Open
Abstract
Gait analysis is often used to study locomotor alterations in people with multiple sclerosis (PwMS), but the large number of extracted variables challenges the interpretability. In this paper, we analysed gait alterations by combining the Gait Profile Score (GPS), which summarizes kinematic locomotor deviations, and Statistical Parametric Mapping (SPM), which compares kinematics and kinetics over the whole gait cycle. Eleven PwMS and 11 speed-matched Healthy Controls (HC) underwent overground gait analysis. GPS were compared through independent-samples t-tests; sagittal-plane kinematics and power at hip, knee, and ankle were compared through SPM Hotelling's-T2 and SPM t-tests. Spearman's correlation coefficients (r) between GPS and clinical outcomes were also calculated. PwMS had higher GPS than HC (PwMS = 8.74 ± 2.13°; HC = 5.01 ± 1.41°;p < 0.001). Multivariate SPM found statistically significant differences at 0-49%, 70-80%, and 93-99% of stride (p < 0.05) and univariate analysis showed reduced ankle dorsiflexion, and lower knee flexion during pre-swing and swing. GPS correlated with Expanded Disability Status Scale (r = 0.65; 95%C.I.[0.04,0.91]; p = 0.04) and 2-Minute Walking Test (r = -0.65; 95%C.I.[-0.91,-0.04]; p = 0.04). GPS in conjunction with SPM revealed multi-joint kinematic alterations on sagittal plane involving distal joint angles, ankle and knee, during the stance phase with no changes at the proximal level. Gait deviations were more pronounced in PwMS with higher disability and walking limitations.
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Affiliation(s)
| | - Francesco Luciano
- Department of Pathophysiology and Transplantation, Università Degli Studi di Milano, 20100, Milan, Italy
| | - Tiziana Lencioni
- IRCCS Fondazione Don Carlo Gnocchi, Via Capecelatro 66, 20148, Milan, Italy
| | - Elisa Gervasoni
- IRCCS Fondazione Don Carlo Gnocchi, Via Capecelatro 66, 20148, Milan, Italy.
| | - Johanna Jonsdottir
- IRCCS Fondazione Don Carlo Gnocchi, Via Capecelatro 66, 20148, Milan, Italy
| | - Denise Anastasi
- IRCCS Fondazione Don Carlo Gnocchi, Via Capecelatro 66, 20148, Milan, Italy
| | - Gaspare Pavei
- Department of Pathophysiology and Transplantation, Università Degli Studi di Milano, 20100, Milan, Italy
| | - Mario Clerici
- Department of Pathophysiology and Transplantation, Università Degli Studi di Milano, 20100, Milan, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Via Capecelatro 66, 20148, Milan, Italy
| | - Davide Cattaneo
- Department of Pathophysiology and Transplantation, Università Degli Studi di Milano, 20100, Milan, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Via Capecelatro 66, 20148, Milan, Italy
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Ozen MS, Calik-Kutukcu E, Salci Y, Karanfil E, Tuncer A, Armutlu K. Is there a relationship between respiratory function and trunk control and functional mobility in patients with relapsing-remitting multiple sclerosis? Neurol Res 2023; 45:619-626. [PMID: 36780377 DOI: 10.1080/01616412.2023.2176628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2023]
Abstract
OBJECTIVE Multiple sclerosis (MS) causes impairment of respiratory function, trunk control, and functional mobility. The purpose of this study was to investigate the relationship between functional mobility and respiratory function and trunk control in MS patients and to compare the findings with those in healthy individuals. METHODS Thirty MS patients and 30 healthy subjects were included in this case-control study. All participants were evaluated with a pulmonary function test, maximal inspiratory and expiratory pressure (MIP, MEP), core stability tests, a lumbopelvic stability test (LST), a 2-minute walk test (2MWT), and the Timed Up and Go test (TUG). The disability level of the MS patients was assessed with the Expanded Disability Status Scale (EDSS). RESULTS Respiratory function, respiratory muscle strength, trunk control, and functional mobility were lower in the MS patients than in the controls (p < 0.05). TUG values had a significant negative correlation and the 2MWT values had a significant positive correlation with MEP, core stability tests, and the LST (p < 0.05). Of the variance in the 2MWT distance, 69% was explained by the LST, EDSS, and MEP; of the variance in TUG time, 40% was explained by the EDSS and MEP (p < 0.05). CONCLUSIONS To preserve and develop functional mobility in MS patients, approaches to increase respiratory function and trunk control should be included in rehabilitation programs. CLINICALTRIALS.GOV REGISTRATION NUMBER NCT03826095.
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Affiliation(s)
- Melike Sumeyye Ozen
- Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation, Bandirma Onyedi Eylul University, Bandirma, Turkey
| | - Ebru Calik-Kutukcu
- Faculty of Physical Therapy and Rehabilitation, Hacettepe University, Ankara, Turkey
| | - Yeliz Salci
- Faculty of Physical Therapy and Rehabilitation, Hacettepe University, Ankara, Turkey
| | - Ecem Karanfil
- Faculty of Physical Therapy and Rehabilitation, Hacettepe University, Ankara, Turkey
| | - Asli Tuncer
- Faculty of Medicine, Department of Neurology, Hacettepe University, Ankara, Turkey
| | - Kadriye Armutlu
- Faculty of Physical Therapy and Rehabilitation, Hacettepe University, Ankara, Turkey
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6
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Palmerini L, Reggi L, Bonci T, Del Din S, Micó-Amigo ME, Salis F, Bertuletti S, Caruso M, Cereatti A, Gazit E, Paraschiv-Ionescu A, Soltani A, Kluge F, Küderle A, Ullrich M, Kirk C, Hiden H, D’Ascanio I, Hansen C, Rochester L, Mazzà C, Chiari L. Mobility recorded by wearable devices and gold standards: the Mobilise-D procedure for data standardization. Sci Data 2023; 10:38. [PMID: 36658136 PMCID: PMC9852581 DOI: 10.1038/s41597-023-01930-9] [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: 04/12/2022] [Accepted: 01/03/2023] [Indexed: 01/21/2023] Open
Abstract
Wearable devices are used in movement analysis and physical activity research to extract clinically relevant information about an individual's mobility. Still, heterogeneity in protocols, sensor characteristics, data formats, and gold standards represent a barrier for data sharing, reproducibility, and external validation. In this study, we aim at providing an example of how movement data (from the real-world and the laboratory) recorded from different wearables and gold standard technologies can be organized, integrated, and stored. We leveraged on our experience from a large multi-centric study (Mobilise-D) to provide guidelines that can prove useful to access, understand, and re-use the data that will be made available from the study. These guidelines highlight the encountered challenges and the adopted solutions with the final aim of supporting standardization and integration of data in other studies and, in turn, to increase and facilitate comparison of data recorded in the scientific community. We also provide samples of standardized data, so that both the structure of the data and the procedure can be easily understood and reproduced.
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Affiliation(s)
- Luca Palmerini
- grid.6292.f0000 0004 1757 1758University of Bologna, Department of Electrical, Electronic and Information Engineering ‘Guglielmo Marconi’, Bologna, Italy ,grid.6292.f0000 0004 1757 1758University of Bologna, Health Sciences and Technologies—Interdepartmental Center for Industrial Research (CIRI-SDV), Bologna, Italy
| | - Luca Reggi
- grid.6292.f0000 0004 1757 1758University of Bologna, Health Sciences and Technologies—Interdepartmental Center for Industrial Research (CIRI-SDV), Bologna, Italy
| | - Tecla Bonci
- grid.11835.3e0000 0004 1936 9262The University of Sheffield, INSIGNEO Institute for in silico Medicine, Sheffield, UK ,grid.11835.3e0000 0004 1936 9262The University of Sheffield, Department of Mechanical Engineering, Sheffield, UK
| | - Silvia Del Din
- grid.1006.70000 0001 0462 7212Newcastle University, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle, UK
| | - M. Encarna Micó-Amigo
- grid.1006.70000 0001 0462 7212Newcastle University, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle, UK
| | - Francesca Salis
- grid.11450.310000 0001 2097 9138University of Sassari, Department of Biomedical Sciences, Sassari, Italy
| | - Stefano Bertuletti
- grid.11450.310000 0001 2097 9138University of Sassari, Department of Biomedical Sciences, Sassari, Italy
| | - Marco Caruso
- grid.4800.c0000 0004 1937 0343Politecnico di Torino, Department of Electronics and Telecommunications, Torino, Italy ,grid.4800.c0000 0004 1937 0343Politecnico di Torino, PolitoBIOMed Lab – Biomedical Engineering Lab, Torino, Italy
| | - Andrea Cereatti
- grid.4800.c0000 0004 1937 0343Politecnico di Torino, Department of Electronics and Telecommunications, Torino, Italy
| | - Eran Gazit
- grid.413449.f0000 0001 0518 6922Tel Aviv Sourasky Medical Center, Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv-Yafo, Israel
| | - Anisoara Paraschiv-Ionescu
- grid.5333.60000000121839049Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Abolfazl Soltani
- grid.5333.60000000121839049Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Felix Kluge
- grid.5330.50000 0001 2107 3311Machine Learning and Data Analytics Lab, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Arne Küderle
- grid.5330.50000 0001 2107 3311Machine Learning and Data Analytics Lab, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Martin Ullrich
- grid.5330.50000 0001 2107 3311Machine Learning and Data Analytics Lab, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Cameron Kirk
- grid.1006.70000 0001 0462 7212Newcastle University, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle, UK
| | - Hugo Hiden
- grid.1006.70000 0001 0462 7212Newcastle University, School of Computing, Newcastle, UK
| | - Ilaria D’Ascanio
- grid.6292.f0000 0004 1757 1758University of Bologna, Department of Electrical, Electronic and Information Engineering ‘Guglielmo Marconi’, Bologna, Italy
| | - Clint Hansen
- grid.412468.d0000 0004 0646 2097Neurogeriatrics Kiel, Department of Neurology, University Hospital Schleswig-Holstein, Kiel, Germany
| | - Lynn Rochester
- grid.1006.70000 0001 0462 7212Newcastle University, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle, UK ,The Newcastle upon Tyne NHS Foundation Trust, Newcastle, UK
| | - Claudia Mazzà
- grid.11835.3e0000 0004 1936 9262The University of Sheffield, INSIGNEO Institute for in silico Medicine, Sheffield, UK ,grid.11835.3e0000 0004 1936 9262The University of Sheffield, Department of Mechanical Engineering, Sheffield, UK
| | - Lorenzo Chiari
- grid.6292.f0000 0004 1757 1758University of Bologna, Department of Electrical, Electronic and Information Engineering ‘Guglielmo Marconi’, Bologna, Italy ,grid.6292.f0000 0004 1757 1758University of Bologna, Health Sciences and Technologies—Interdepartmental Center for Industrial Research (CIRI-SDV), Bologna, Italy
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Carpinella I, Anastasi D, Gervasoni E, Di Giovanni R, Tacchino A, Brichetto G, Confalonieri P, Rovaris M, Solaro C, Ferrarin M, Cattaneo D. Balance Impairments in People with Early-Stage Multiple Sclerosis: Boosting the Integration of Instrumented Assessment in Clinical Practice. SENSORS (BASEL, SWITZERLAND) 2022; 22:9558. [PMID: 36502265 PMCID: PMC9736931 DOI: 10.3390/s22239558] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 11/15/2022] [Accepted: 12/03/2022] [Indexed: 06/17/2023]
Abstract
The balance of people with multiple sclerosis (PwMS) is commonly assessed during neurological examinations through clinical Romberg and tandem gait tests that are often not sensitive enough to unravel subtle deficits in early-stage PwMS. Inertial sensors (IMUs) could overcome this drawback. Nevertheless, IMUs are not yet fully integrated into clinical practice due to issues including the difficulty to understand/interpret the big number of parameters provided and the lack of cut-off values to identify possible abnormalities. In an attempt to overcome these limitations, an instrumented modified Romberg test (ImRomberg: standing on foam with eyes closed while wearing an IMU on the trunk) was administered to 81 early-stage PwMS and 38 healthy subjects (HS). To facilitate clinical interpretation, 21 IMU-based parameters were computed and reduced through principal component analysis into two components, sway complexity and sway intensity, descriptive of independent aspects of balance, presenting a clear clinical meaning and significant correlations with at least one clinical scale. Compared to HS, early-stage PwMS showed a 228% reduction in sway complexity and a 63% increase in sway intensity, indicating, respectively, a less automatic (more conscious) balance control and larger and faster trunk movements during upright posture. Cut-off values were derived to identify the presence of balance abnormalities and if these abnormalities are clinically meaningful. By applying these thresholds and integrating the ImRomberg test with the clinical tandem gait test, balance impairments were identified in 58% of PwMS versus the 17% detected by traditional Romberg and tandem gait tests. The higher sensitivity of the proposed approach would allow for the direct identification of early-stage PwMS who could benefit from preventive rehabilitation interventions aimed at slowing MS-related functional decline during neurological examinations and with minimal modifications to the tests commonly performed.
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Affiliation(s)
| | - Denise Anastasi
- IRCCS Fondazione Don Carlo Gnocchi Onlus, 20148 Milan, Italy
| | - Elisa Gervasoni
- IRCCS Fondazione Don Carlo Gnocchi Onlus, 20148 Milan, Italy
| | - Rachele Di Giovanni
- Department of Rehabilitation, Centro di Recupero e Rieducazione Funzionale (CRRF) “Mons. Luigi Novarese”, 13040 Moncrivello, Italy
| | - Andrea Tacchino
- Italian Multiple Sclerosis Foundation, Scientific Research Area, 16126 Genoa, Italy
| | - Giampaolo Brichetto
- Italian Multiple Sclerosis Foundation, Scientific Research Area, 16126 Genoa, Italy
| | - Paolo Confalonieri
- IRCCS Foundation “Carlo Besta” Neurological Institute, 20133 Milan, Italy
| | - Marco Rovaris
- IRCCS Fondazione Don Carlo Gnocchi Onlus, 20148 Milan, Italy
| | - Claudio Solaro
- Department of Rehabilitation, Centro di Recupero e Rieducazione Funzionale (CRRF) “Mons. Luigi Novarese”, 13040 Moncrivello, Italy
| | | | - Davide Cattaneo
- IRCCS Fondazione Don Carlo Gnocchi Onlus, 20148 Milan, Italy
- Department of Physiopathology and Transplants, University of Milan, 20122 Milan, Italy
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8
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Berg-Hansen P, Moen SM, Austeng A, Gonzales V, Klyve TD, Negård H, Seeberg TM, Celius EG, Meyer F. Sensor-based gait analyses of the six-minute walk test identify qualitative improvement in gait parameters of people with multiple sclerosis after rehabilitation. J Neurol 2022; 269:3723-3734. [PMID: 35166925 PMCID: PMC8853386 DOI: 10.1007/s00415-022-10998-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 01/23/2022] [Accepted: 01/24/2022] [Indexed: 02/06/2023]
Abstract
The aim of this work was to determine whether wearable inertial measurement units (IMUs) could detect gait improvements across different disability groups of people with Multiple Sclerosis (pwMS) by the six-minute walk test (6MWT) during a rehabilitation stay in a specialized rehabilitation center. Forty-six pwMS and 20 healthy controls (HC) were included in the study. They performed the 6MWT with two inertial measurement units (IMUs) placed on the feet. Thirty-two of the pwMS were retested at the end of the stay. PwMS were divided in a mild-disability and a moderate-disability group. The 6MWT was divided in six sections of 1 min each for technical analysis, and linear mixed models were used for statistical analyses. The comparison between the two disability groups and HC highlighted significant differences for each gait parameter (all p < 0.001). The crossing effect between the test–retest and the two disability groups showed greater improvement for the moderate-disability group. Finally, the gait parameter with the higher effect size, allowing the best differentiation between the disability groups, was the foot flat ratio (R2 = 0.53). Gait analyses from wearable sensors identified different evolutions of gait patterns during the 6MWT in pwMS with different physical disability. The measured effect of a short-time rehabilitation on gait with 6MWT was higher for pwMS with higher degree of disability. Using IMUs in a clinical setting allowed to identify significant changes in inter-stride gait patterns. Wearable sensors and key parameters have the potential as useful clinical tools for focusing on gait in pwMS.
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Affiliation(s)
- Pål Berg-Hansen
- Department of Neurology, Oslo University Hospital, Ullevål, Sognsvannsveien 20, 0372, Oslo, Norway.
| | | | | | | | | | | | | | - Elisabeth Gulowsen Celius
- Department of Neurology, Oslo University Hospital, Ullevål, Sognsvannsveien 20, 0372, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Frédéric Meyer
- Department of Informatics, University of Oslo, Oslo, Norway
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Abstract
Pathological gait is often associated with a lack of symmetry. A possible way to quantify this feature is to use acceleration data measured by a sensor located on the lower trunk. The most common approach calculates a symmetry index starting from the autocorrelation function, aiming to measure the divergence in motion of the left and right sides of the body. The various methods proposed to implement this approach are based on nonlinear and discontinuous functions, and the interpretation of their output is far from straightforward. The aim of this study was to propose a linear and easier to interpret quantification measure for gait asymmetry. The proposed measure was tested on data from healthy controls and from patients with Multiple Sclerosis and Parkinson’s Disease, and it was shown to negate the flaws present in previous methods and to provide more directly interpretable results.
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