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Tinggaard AB, Sørensen L, Vissing K, Jessen N, Nørrelund H, Wiggers H. Daily physical activity and prognostic implications in patients with heart failure: an accelerometer study. Clin Res Cardiol 2024:10.1007/s00392-024-02508-0. [PMID: 39222281 DOI: 10.1007/s00392-024-02508-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Accepted: 07/26/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND Physical activity (PA) measured by accelerometry is proposed as a novel trial endpoint for heart failure (HF). However, standardised methods and associations with established markers are lacking. This study aimed to examine PA measurements and accelerometer repeatability in patients with HF and age- and sex-matched controls, and study correlations with established prognostic HF markers, body composition, and quality of life (QoL). METHODS Accelerometry was performed in 105 patients with HF with left ventricular ejection fraction (LVEF) ≤ 40% and in 46 controls. Participants also underwent dual X-ray absorptiometry, cardiopulmonary exercise testing, a six-minute walking test (6MWT), echocardiography, and NT-proBNP measurement, and completed a QoL questionnaire. RESULTS Average acceleration was markedly reduced in patients with HF compared with healthy controls (16.1 ± 4.8 mg vs 27.2 ± 8.5 mg, p < 0.001). Healthy controls spent a median daily 56 min (IQR 41-96 min) in moderate-to-vigorous PA (MVPA), whereas HF patients spent only 12 min (IQR 6-24) in MVPA. In HF patients, average acceleration correlated moderately with 6MWT (R = 0.41, p < 0.001) and maximal oxygen uptake (peak VO2) (R = 0.36, p < 0.001) but not with NT-proBNP, LVEF, or QoL. Patients in NYHA class II showed a higher average acceleration than patients in NYHA III (16.6 ± 4.9 mg vs 14.0 ± 3.6 mg, p = 0.01). CONCLUSIONS Daily PA was severely reduced in patients with HF compared with healthy controls. In HF patients, we found moderate correlations of accelerometer measurements with markers of physical capacity but not with LVEF or NT-proBNP. TRIAL REGISTRATION NCT05063955. Registered 01 June 2021-retrospectively registered.
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Affiliation(s)
- Andreas Bugge Tinggaard
- Department of Cardiology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark.
- Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark.
| | - Lotte Sørensen
- Department of Physiotherapy and Occupational Therapy, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark
| | - Kristian Vissing
- Section for Sport Science, Department of Public Health, Aarhus University, Bartholins Allé 2, 8000, Aarhus C, Denmark
| | - Niels Jessen
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Palle Juul-Jensens Boulevard 11, 8200, Aarhus N, Denmark
- Department of Biomedicine, Aarhus University, Hoegh-Guldbergsgade 10, 8000, Aarhus C, Denmark
- Department of Clinical Pharmacology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark
| | - Helene Nørrelund
- Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark
| | - Henrik Wiggers
- Department of Cardiology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark
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Pîrșcoveanu CI, Oliveira AS, Franch J, Madeleine P. Absolute and Relative Reliability of Spatiotemporal Gait Characteristics Extracted from an Inertial Measurement Unit among Senior Adults Using a Passive Hip Exoskeleton: A Test-Retest Study. SENSORS (BASEL, SWITZERLAND) 2024; 24:5213. [PMID: 39204911 PMCID: PMC11360760 DOI: 10.3390/s24165213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Revised: 08/07/2024] [Accepted: 08/07/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND Seniors wearing a passive hip exoskeleton (Exo) show increased walking speed and step length but reduced cadence. We assessed the test-retest reliability of seniors' gait characteristics with Exo. METHODS Twenty seniors walked with and without Exo (noExo) on a 10 m indoor track over two sessions separated by one week. Speed, step length, cadence and step time variability were extracted from one inertial measurement unit (IMU) placed over the L5 vertebra. Relative and absolute reliability were assessed using the intraclass correlation coefficient (ICC), standard error of measurement (SEM) and minimal detectable change (MDC). RESULTS The relative reliability of speed, step length, cadence and step time variability ranged from "almost perfect to substantial" for Exo and noExo with ICC values between 0.75 and 0.87 and 0.60 and 0.92, respectively. The SEM and MDC values for speed, step length cadence and step time variability during Exo and noExo were <0.002 and <0.006 m/s, <0.002 and <0.005 m, <0.30 and <0.83 steps/min and <0.38 s and <1.06 s, respectively. CONCLUSIONS The high test-retest reliability of speed, step length and cadence estimated from IMU suggest a robust extraction of spatiotemporal gait characteristics during exoskeleton use. These findings indicate that IMUs can be used to assess the effects of wearing an exoskeleton on seniors, thus offering the possibility of conducting longitudinal studies.
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Affiliation(s)
- Cristina-Ioana Pîrșcoveanu
- Department of Health Science and Technology, ExerciseTech, Aalborg University, 9260 Gistrup, Denmark; (J.F.); (P.M.)
| | | | - Jesper Franch
- Department of Health Science and Technology, ExerciseTech, Aalborg University, 9260 Gistrup, Denmark; (J.F.); (P.M.)
| | - Pascal Madeleine
- Department of Health Science and Technology, ExerciseTech, Aalborg University, 9260 Gistrup, Denmark; (J.F.); (P.M.)
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Silva RSD, Silva STD, Cardoso DCR, Quirino MAF, Silva MHA, Gomes LA, Fernandes JD, Oliveira RANDS, Fernandes ABGS, Ribeiro TS. Psychometric properties of wearable technologies to assess post-stroke gait parameters: A systematic review. Gait Posture 2024; 113:543-552. [PMID: 39178597 DOI: 10.1016/j.gaitpost.2024.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 07/16/2024] [Accepted: 08/07/2024] [Indexed: 08/26/2024]
Abstract
BACKGROUND Wearable technologies using inertial sensors are an alternative for gait assessment. However, their psychometric properties in evaluating post-stroke patients are still being determined. This systematic review aimed to evaluate the psychometric properties of wearable technologies used to assess post-stroke gait and analyze their reliability and measurement error. The review also investigated which wearable technologies have been used to assess angular changes in post-stroke gait. METHODS The present review included studies in English with no publication date restrictions that evaluated the psychometric properties (e.g., validity, reliability, responsiveness, and measurement error) of wearable technologies used to assess post-stroke gait. Searches were conducted from February to March 2023 in the following databases: Cochrane Central Registry of Controlled Trials (CENTRAL), Medline/PubMed, EMBASE Ovid, CINAHL EBSCO, PsycINFO Ovid, IEEE Xplore Digital Library (IEEE), and Physiotherapy Evidence Database (PEDro); the gray literature was also verified. The Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) risk-of-bias tool was used to assess the quality of the studies that analyzed reliability and measurement error. RESULTS Forty-two studies investigating validity (37 studies), reliability (16 studies), and measurement error (6 studies) of wearable technologies were included. Devices presented good reliability in measuring gait speed and step count; however, the quality of the evidence supporting this was low. The evidence of measurement error in step counts was indeterminate. Moreover, only two studies obtained angular results using wearable technology. SIGNIFICANCE Wearable technologies have demonstrated reliability in analyzing gait parameters (gait speed and step count) among post-stroke patients. However, higher-quality studies should be conducted to improve the quality of evidence and to address the measurement error assessment. Also, few studies used wearable technology to analyze angular changes during post-stroke gait.
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Affiliation(s)
- Raiff Simplicio da Silva
- Postgraduate Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil.
| | - Stephano Tomaz da Silva
- Postgraduate Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil.
| | - Daiane Carla Rodrigues Cardoso
- Postgraduate Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil.
| | - Maria Amanda Ferreira Quirino
- Graduation Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil.
| | - Maria Heloiza Araújo Silva
- Postgraduate Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil.
| | - Larissa Araujo Gomes
- Graduation Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil.
| | - Jefferson Doolan Fernandes
- Federal Institute of Science and Technology of Rio Grande do Norte, Natal, Rio Grande do Norte 59015-000, Brazil.
| | | | - Aline Braga Galvão Silveira Fernandes
- Postgraduate Program in Physical Therapy, Faculty of Health Sciences of Trairi, Federal University of Rio Grande do Norte, Rua Vila Trairi, Santa Cruz, RN 59200-000, Brazil.
| | - Tatiana Souza Ribeiro
- Postgraduate Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil.
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Garcia Oliveira S, Nogueira SL, Uliam NR, Girardi PM, Russo TL. Measurement properties of activity monitoring for a rehabilitation (AMoR) platform in post-stroke individuals in a simulated home environment. Top Stroke Rehabil 2024:1-11. [PMID: 39003747 DOI: 10.1080/10749357.2024.2377520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 07/02/2024] [Indexed: 07/16/2024]
Abstract
AIM The aim of this study was to evaluate the measurement properties of activity monitoring for a rehabilitation (AMoR) platform for step counting, time spent in sedentary behavior, and postural changes during activities of daily living (ADLs) in a simulated home environment. METHODS Twenty-one individuals in the post-stroke chronic phase used the AMoR platform during an ADL protocol and were monitored by a video camera. Spearman's correlation coefficient, mean absolute percent error (MAPE), intraclass correlation coefficient (ICC), and Bland-Altman plot analyses were used to estimate the validity and reliability between the AMoR platform and the video for step counting, time spent sitting/lying, and postural changes from sit-to-stand (SI-ST) and sit-to-stand (ST-SI). RESULTS Validity of the platform was observed with very high correlation values for step counting (rs = 0.998) and time spent sitting/lying (rs = 0.992) and high correlation for postural change of SI-ST (rs = 0.850) and ST-SI (rs = 0.851) when compared to the video. An error percentage above 5% was observed only for the SI-ST postural change (7.13%). The ICC values show excellent agreement for step counting (ICC3, k = 0.999) and time spent sitting/lying (ICC3, k = 0.992), and good agreement for SI-ST (ICC3, k = 0.859) and ST-SI (ICC3, k = 0.936) postural change. Values of the differences for step counting, sitting/lying time, and postural change were within the limits of agreement according to the analysis of the Bland-Altman graph. CONCLUSION The AMoR platform presented validity and reliability for step counting, time spent sitting/lying, and identification of SI-ST and ST-SI postural changes during tests in a simulated environment in post-stroke individuals.
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Affiliation(s)
| | | | - Nicoly Ribeiro Uliam
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, Brazil
| | - Paulo Matheus Girardi
- Department of Electrical Engineering, Federal University of São Carlos, São Carlos, Brazil
| | - Thiago Luiz Russo
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, Brazil
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Hinchliffe C, Rehman RZU, Pinaud C, Branco D, Jackson D, Ahmaniemi T, Guerreiro T, Chatterjee M, Manyakov NV, Pandis I, Davies K, Macrae V, Aufenberg S, Paulides E, Hildesheim H, Kudelka J, Emmert K, Van Gassen G, Rochester L, van der Woude CJ, Reilmann R, Maetzler W, Ng WF, Del Din S. Evaluation of walking activity and gait to identify physical and mental fatigue in neurodegenerative and immune disorders: preliminary insights from the IDEA-FAST feasibility study. J Neuroeng Rehabil 2024; 21:94. [PMID: 38840208 PMCID: PMC11151484 DOI: 10.1186/s12984-024-01390-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 05/21/2024] [Indexed: 06/07/2024] Open
Abstract
BACKGROUND Many individuals with neurodegenerative (NDD) and immune-mediated inflammatory disorders (IMID) experience debilitating fatigue. Currently, assessments of fatigue rely on patient reported outcomes (PROs), which are subjective and prone to recall biases. Wearable devices, however, provide objective and reliable estimates of gait, an essential component of health, and may present objective evidence of fatigue. This study explored the relationships between gait characteristics derived from an inertial measurement unit (IMU) and patient-reported fatigue in the IDEA-FAST feasibility study. METHODS Participants with IMIDs and NDDs (Parkinson's disease (PD), Huntington's disease (HD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), primary Sjogren's syndrome (PSS), and inflammatory bowel disease (IBD)) wore a lower-back IMU continuously for up to 10 days at home. Concurrently, participants completed PROs (physical fatigue (PF) and mental fatigue (MF)) up to four times a day. Macro (volume, variability, pattern, and acceleration vector magnitude) and micro (pace, rhythm, variability, asymmetry, and postural control) gait characteristics were extracted from the accelerometer data. The associations of these measures with the PROs were evaluated using a generalised linear mixed-effects model (GLMM) and binary classification with machine learning. RESULTS Data were recorded from 72 participants: PD = 13, HD = 9, RA = 12, SLE = 9, PSS = 14, IBD = 15. For the GLMM, the variability of the non-walking bouts length (in seconds) with PF returned the highest conditional R2, 0.165, and with MF the highest marginal R2, 0.0018. For the machine learning classifiers, the highest accuracy of the current analysis was returned by the micro gait characteristics with an intrasubject cross validation method and MF as 56.90% (precision = 43.9%, recall = 51.4%). Overall, the acceleration vector magnitude, bout length variation, postural control, and gait rhythm were the most interesting characteristics for future analysis. CONCLUSIONS Counterintuitively, the outcomes indicate that there is a weak relationship between typical gait measures and abnormal fatigue. However, factors such as the COVID-19 pandemic may have impacted gait behaviours. Therefore, further investigations with a larger cohort are required to fully understand the relationship between gait and abnormal fatigue.
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Affiliation(s)
- Chloe Hinchliffe
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, The Catalyst, 3 Science Square, Room 3.27, Newcastle Upon Tyne, NE4 5TG, UK
| | | | | | - Diogo Branco
- LASIGE, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal
| | - Dan Jackson
- Open Lab, School of Computing, Newcastle University, Newcastle Upon Tyne, UK
| | | | - Tiago Guerreiro
- LASIGE, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal
| | | | | | | | - Kristen Davies
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, The Catalyst, 3 Science Square, Room 3.27, Newcastle Upon Tyne, NE4 5TG, UK
| | - Victoria Macrae
- NIHR Newcastle Clinical Research Facility, Newcastle Upon Tyne, UK
- National Institute for Health and Care Research (NIHR) Newcastle Biomedical Research Centre (BRC), Newcastle University and The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK
- The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK
| | | | - Emma Paulides
- Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Hanna Hildesheim
- Department of Neurology, University Medical Center Schleswig-Holstein Campus, Kiel, Germany
| | - Jennifer Kudelka
- Department of Neurology, University Medical Center Schleswig-Holstein Campus, Kiel, Germany
| | - Kirsten Emmert
- Department of Neurology, University Medical Center Schleswig-Holstein Campus, Kiel, Germany
| | | | - Lynn Rochester
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, The Catalyst, 3 Science Square, Room 3.27, Newcastle Upon Tyne, NE4 5TG, UK
- National Institute for Health and Care Research (NIHR) Newcastle Biomedical Research Centre (BRC), Newcastle University and The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK
- The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK
| | - C Janneke van der Woude
- Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | | | - Walter Maetzler
- Department of Neurology, University Medical Center Schleswig-Holstein Campus, Kiel, Germany
| | - Wan-Fai Ng
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, The Catalyst, 3 Science Square, Room 3.27, Newcastle Upon Tyne, NE4 5TG, UK
- NIHR Newcastle Clinical Research Facility, Newcastle Upon Tyne, UK
- National Institute for Health and Care Research (NIHR) Newcastle Biomedical Research Centre (BRC), Newcastle University and The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK
- The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK
| | - Silvia Del Din
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, The Catalyst, 3 Science Square, Room 3.27, Newcastle Upon Tyne, NE4 5TG, UK.
- National Institute for Health and Care Research (NIHR) Newcastle Biomedical Research Centre (BRC), Newcastle University and The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK.
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Mc Ardle R, Taylor L, Cavadino A, Rochester L, Del Din S, Kerse N. Characterizing Walking Behaviors in Aged Residential Care Using Accelerometry, With Comparison Across Care Levels, Cognitive Status, and Physical Function: Cross-Sectional Study. JMIR Aging 2024; 7:e53020. [PMID: 38842168 PMCID: PMC11185191 DOI: 10.2196/53020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 03/05/2024] [Accepted: 03/06/2024] [Indexed: 06/07/2024] Open
Abstract
Background Walking is important for maintaining physical and mental well-being in aged residential care (ARC). Walking behaviors are not well characterized in ARC due to inconsistencies in assessment methods and metrics as well as limited research regarding the impact of care environment, cognition, or physical function on these behaviors. It is recommended that walking behaviors in ARC are assessed using validated digital methods that can capture low volumes of walking activity. Objective This study aims to characterize and compare accelerometry-derived walking behaviors in ARC residents across different care levels, cognitive abilities, and physical capacities. Methods A total of 306 ARC residents were recruited from the Staying UpRight randomized controlled trial from 3 care levels: rest home (n=164), hospital (n=117), and dementia care (n=25). Participants' cognitive status was classified as mild (n=87), moderate (n=128), or severe impairment (n=61); physical function was classified as high-moderate (n=74) and low-very low (n=222) using the Montreal Cognitive Assessment and the Short Physical Performance Battery cutoff scores, respectively. To assess walking, participants wore an accelerometer (Axivity AX3; dimensions: 23×32.5×7.6 mm; weight: 11 g; sampling rate: 100 Hz; range: ±8 g; and memory: 512 MB) on their lower back for 7 days. Outcomes included volume (ie, daily time spent walking, steps, and bouts), pattern (ie, mean walking bout duration and alpha), and variability (of bout length) of walking. Analysis of covariance was used to assess differences in walking behaviors between groups categorized by level of care, cognition, or physical function while controlling for age and sex. Tukey honest significant difference tests for multiple comparisons were used to determine where significant differences occurred. The effect sizes of group differences were calculated using Hedges g (0.2-0.4: small, 0.5-0.7: medium, and 0.8: large). Results Dementia care residents showed greater volumes of walking (P<.001; Hedges g=1.0-2.0), with longer (P<.001; Hedges g=0.7-0.8), more variable (P=.008 vs hospital; P<.001 vs rest home; Hedges g=0.6-0.9) bouts compared to other care levels with a lower alpha score (vs hospital: P<.001; Hedges g=0.9, vs rest home: P=.004; Hedges g=0.8). Residents with severe cognitive impairment took longer (P<.001; Hedges g=0.5-0.6), more variable (P<.001; Hedges g=0.4-0.6) bouts, compared to those with mild and moderate cognitive impairment. Residents with low-very low physical function had lower walking volumes (total walk time and bouts per day: P<.001; steps per day: P=.005; Hedges g=0.4-0.5) and higher variability (P=.04; Hedges g=0.2) compared to those with high-moderate capacity. Conclusions ARC residents across different levels of care, cognition, and physical function demonstrate different walking behaviors. However, ARC residents often present with varying levels of both cognitive and physical abilities, reflecting their complex multimorbid nature, which should be considered in further work. This work has demonstrated the importance of considering a nuanced framework of digital outcomes relating to volume, pattern, and variability of walking behaviors among ARC residents.
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Affiliation(s)
- Ríona Mc Ardle
- Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, United Kingdom
- National Institute for Health and Care Research Biomedical Research Centre, Newcastle University and the Newcastle Upon Tyne Hospitals National Health Service Foundation Trust, Newcastle Upon Tyne, United Kingdom
| | - Lynne Taylor
- School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Alana Cavadino
- School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Lynn Rochester
- Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, United Kingdom
- National Institute for Health and Care Research Biomedical Research Centre, Newcastle University and the Newcastle Upon Tyne Hospitals National Health Service Foundation Trust, Newcastle Upon Tyne, United Kingdom
- The Newcastle Upon Tyne Hospitals National Health Institute Foundation Trust, Newcastle Upon Tyne, United Kingdom
| | - Silvia Del Din
- Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, United Kingdom
- National Institute for Health and Care Research Biomedical Research Centre, Newcastle University and the Newcastle Upon Tyne Hospitals National Health Service Foundation Trust, Newcastle Upon Tyne, United Kingdom
| | - Ngaire Kerse
- School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
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Mitchell CJ, Cronin J. Methodological Critique of Concussive and Non-Concussive Dual Task Walking Assessments: A Scoping Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:5227. [PMID: 36982135 PMCID: PMC10048786 DOI: 10.3390/ijerph20065227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 03/12/2023] [Accepted: 03/14/2023] [Indexed: 06/18/2023]
Abstract
OBJECTIVE To understand the methodological approaches taken by various research groups and determine the kinematic variables that could consistently and reliably differentiate between concussed and non-concussed individuals. METHODS MEDLINE via PubMed, CINAHL Complete via EBSCO, EBSCOhost, SPORTDiscus, and Scopus were searched from inception until 31 December 2021, using key terms related to concussion, mild traumatic brain injury, gait, cognition and dual task. Studies that reported spatiotemporal kinematic outcomes were included. Data were extracted using a customised spreadsheet, including detailed information on participant characteristics, assessment protocols, equipment used, and outcomes. RESULTS Twenty-three studies involving 1030 participants met the inclusion criteria. Ten outcome measures were reported across these articles. Some metrics such as gait velocity and stride length may be promising but are limited by the status of the current research; the majority of the reported variables were not sensitive enough across technologies to consistently differentiate between concussed and non-concussed individuals. Understanding variable sensitivity was made more difficult given the absence of any reporting of reliability of the protocols and variables in the respective studies. CONCLUSION Given the current status of the literature and the methodologies reviewed, there would seem little consensus on which gait parameters are best to determine return to play readiness after concussion. There is potential in this area for such technologies and protocols to be utilised as a tool for identifying and monitoring concussion; however, improving understanding of the variability and validity of technologies and protocols underpins the suggested directions of future research. Inertial measurement units appear to be the most promising technology in this aspect and should guide the focus of future research. IMPACT Results of this study may have an impact on what technology is chosen and may be utilised to assist with concussion diagnosis and return to play protocols.
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Affiliation(s)
- Courtney Jade Mitchell
- Sport Performance Research in New Zealand (SPRINZ), AUT Millennium Institute, AUT University, Auckland 1010, New Zealand
- Department of Sport and Recreation, Toi Ohomai Institute of Technology, Tauranga 3112, New Zealand
| | - John Cronin
- Sport Performance Research in New Zealand (SPRINZ), AUT Millennium Institute, AUT University, Auckland 1010, New Zealand
- Athlete Training and Health, 23910 Katy Freeway, Suite 101, Katy, TX 77494, USA
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Mathunny JJ, Karthik V, Devaraj A, Jacob J. A scoping review on recent trends in wearable sensors to analyze gait in people with stroke: From sensor placement to validation against gold-standard equipment. Proc Inst Mech Eng H 2023; 237:309-326. [PMID: 36704959 DOI: 10.1177/09544119221142327] [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: 01/28/2023]
Abstract
The purpose of the review is to evaluate wearable sensor placement, their impact and validation of wearable sensors on analyzing gait, primarily the postural instability in people with stroke. Databases, namely PubMed, Cochrane, SpringerLink, and IEEE Xplore were searched to identify related articles published since January 2005. The authors have selected the articles by considering patient characteristics, intervention details, and outcome measurements by following the priorly set inclusion and exclusion criteria. From a total of 1077 articles, 142 were included in this study and classified into functional fields, namely postural stability (PS) assessments, physical activity monitoring (PA), gait pattern classification (GPC), and foot drop correction (FDC). The review covers the types of wearable sensors, their placement, and their performance in terms of reliability and validity. When employing a single wearable sensor, the pelvis and foot were the most used locations for detecting gait asymmetry and kinetic parameters, respectively. Multiple Inertial Measurement Units placed at different body parts were effectively used to estimate postural stability and gait pattern. This review article has compared results of placement of sensors at different locations helping researchers and clinicians to identify the best possible placement for sensors to measure specific kinematic and kinetic parameters in persons with stroke.
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Affiliation(s)
- Jaison Jacob Mathunny
- Department of Biomedical Engineering, SRM Institute of Science and Technology, Chennai, India
| | - Varshini Karthik
- Department of Biomedical Engineering, SRM Institute of Science and Technology, Chennai, India
| | - Ashokkumar Devaraj
- Department of Biomedical Engineering, SRM Institute of Science and Technology, Chennai, India
| | - James Jacob
- Department of Physical Therapy, Kindred Healthcare, Munster, IN, USA
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Moore SA, Boyne P, Fulk G, Verheyden G, Fini NA. Walk the Talk: Current Evidence for Walking Recovery After Stroke, Future Pathways and a Mission for Research and Clinical Practice. Stroke 2022; 53:3494-3505. [PMID: 36069185 PMCID: PMC9613533 DOI: 10.1161/strokeaha.122.038956] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Achieving safe, independent, and efficient walking is a top priority for stroke survivors to enable quality of life and future health. This narrative review explores the state of the science in walking recovery after stroke and potential for development. The importance of targeting walking capacity and performance is explored in relation to individual stroke survivor gait recovery, applying a common language, measurement, classification, prediction, current and future intervention development, and health care delivery. Findings are summarized in a model of current and future stroke walking recovery research and a mission statement is set for researchers and clinicians to drive the field forward to improve the lives of stroke survivors and their carers.
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Affiliation(s)
- Sarah A Moore
- Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK, and Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom (S.A.M.)
| | - Pierce Boyne
- Department of Rehabilitation Exercise and Nutritional Science, University of Cincinnati, OH (P.B.)
| | - George Fulk
- Department of Rehabilitation Medicine, Emory University, Atlanta, GA (G.F.)
| | - Geert Verheyden
- Department of Rehabilitation Sciences, KU Leuven, University of Leuven, Belgium (G.V.)
| | - Natalie A Fini
- Medicine Dentistry and Health Sciences, The University of Melbourne, Australia (N.A.F.)
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10
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Shin H. Deep Convolutional Neural Network-Based Hemiplegic Gait Detection Using an Inertial Sensor Located Freely in a Pocket. SENSORS 2022; 22:s22051920. [PMID: 35271066 PMCID: PMC8914729 DOI: 10.3390/s22051920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 01/27/2022] [Accepted: 02/09/2022] [Indexed: 02/01/2023]
Abstract
In most previous studies, the acceleration sensor is attached to a fixed position for gait analysis. However, if it is aimed at daily use, wearing it in a fixed position may cause discomfort. In addition, since an acceleration sensor can be built into the smartphones that people always carry, it is more efficient to use such a sensor rather than wear a separate acceleration sensor. We aimed to distinguish between hemiplegic and normal walking by using the inertial signal measured by means of an acceleration sensor and a gyroscope. We used a machine learning model based on a convolutional neural network to classify hemiplegic gaits and used the acceleration and angular velocity signals obtained from a system freely located in the pocket as inputs without any pre-processing. The classification model structure and hyperparameters were optimized using Bayesian optimization method. We evaluated the performance of the developed model through a clinical trial, which included a walking test of 42 subjects (57.8 ± 13.8 years old, 165.1 ± 9.3 cm tall, weighing 66.3 ± 12.3 kg) including 21 hemiplegic patients. The optimized convolutional neural network model has a convolutional layer, with number of fully connected nodes of 1033, batch size of 77, learning rate of 0.001, and dropout rate of 0.48. The developed model showed an accuracy of 0.78, a precision of 0.80, a recall of 0.80, an area under the receiver operating characteristic curve of 0.80, and an area under the precision–recall curve of 0.84. We confirmed the possibility of distinguishing a hemiplegic gait by applying the convolutional neural network to the signal measured by a six-axis inertial sensor freely located in the pocket without additional pre-processing or feature extraction.
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Affiliation(s)
- Hangsik Shin
- Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Korea
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11
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Felius RAW, Geerars M, Bruijn SM, van Dieën JH, Wouda NC, Punt M. Reliability of IMU-Based Gait Assessment in Clinical Stroke Rehabilitation. SENSORS 2022; 22:s22030908. [PMID: 35161654 PMCID: PMC8839370 DOI: 10.3390/s22030908] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 01/16/2022] [Accepted: 01/19/2022] [Indexed: 02/06/2023]
Abstract
Background: Gait is often impaired in people after stroke, restricting personal independence and affecting quality of life. During stroke rehabilitation, walking capacity is conventionally assessed by measuring walking distance and speed. Gait features, such as asymmetry and variability, are not routinely determined, but may provide more specific insights into the patient’s walking capacity. Inertial measurement units offer a feasible and promising tool to determine these gait features. Objective: We examined the test–retest reliability of inertial measurement units-based gait features measured in a two-minute walking assessment in people after stroke and while in clinical rehabilitation. Method: Thirty-one people after stroke performed two assessments with a test–retest interval of 24 h. Each assessment consisted of a two-minute walking test on a 14-m walking path. Participants were equipped with three inertial measurement units, placed at both feet and at the low back. In total, 166 gait features were calculated for each assessment, consisting of spatio-temporal (56), frequency (26), complexity (63), and asymmetry (14) features. The reliability was determined using the intraclass correlation coefficient. Additionally, the minimal detectable change and the relative minimal detectable change were computed. Results: Overall, 107 gait features had good–excellent reliability, consisting of 50 spatio-temporal, 8 frequency, 36 complexity, and 13 symmetry features. The relative minimal detectable change of these features ranged between 0.5 and 1.5 standard deviations. Conclusion: Gait can reliably be assessed in people after stroke in clinical stroke rehabilitation using three inertial measurement units.
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Affiliation(s)
- Richard A. W. Felius
- Research Group Lifestyle and Health, Utrecht University of Applied Sciences, 3584 CS Utrecht, The Netherlands; (M.G.); (N.C.W.); (M.P.)
- Faculty of Human Movement Sciences, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; (S.M.B.); (J.H.v.D.)
- Correspondence:
| | - Marieke Geerars
- Research Group Lifestyle and Health, Utrecht University of Applied Sciences, 3584 CS Utrecht, The Netherlands; (M.G.); (N.C.W.); (M.P.)
- Physiotherapy Department Neurology, Rehabilitation Center de Parkgraaf, 3526 KJ Utrecht, The Netherlands
| | - Sjoerd M. Bruijn
- Faculty of Human Movement Sciences, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; (S.M.B.); (J.H.v.D.)
| | - Jaap H. van Dieën
- Faculty of Human Movement Sciences, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; (S.M.B.); (J.H.v.D.)
| | - Natasja C. Wouda
- Research Group Lifestyle and Health, Utrecht University of Applied Sciences, 3584 CS Utrecht, The Netherlands; (M.G.); (N.C.W.); (M.P.)
- Physiotherapy Department Neurology, De Hoogstraat Revalidatie, 3583 TM Utrecht, The Netherlands
| | - Michiel Punt
- Research Group Lifestyle and Health, Utrecht University of Applied Sciences, 3584 CS Utrecht, The Netherlands; (M.G.); (N.C.W.); (M.P.)
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12
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Celik Y, Powell D, Woo WL, Stuart S, Godfrey A. Developing and exploring a methodology for multi-modal indoor and outdoor gait assessment. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:6759-6762. [PMID: 34892659 DOI: 10.1109/embc46164.2021.9629502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Gait assessment is emerging as a prominent way to understand impaired mobility and underlying neurological deficits. Various technologies have been used to assess gait inside and outside of laboratory settings, but wearables are the preferred option due to their cost-effective and practical use in both. There are robust conceptual gait models developed to ease the interpretation of gait parameters during indoor and outdoor environments. However, these models examine uni-modal gait characteristics (e.g., spatio-temporal parameters) only. Previous studies reported that understanding the underlying reason for impaired gait requires multi-modal gait assessment. Therefore, this study aims to develop a multi-modal approach using a synchronized inertial and electromyography (EMG) signals. Firstly, initial contact (IC), final contact (FC) moments and corresponding time stamps were identified from inertial data, producing temporal outcomes e.g., step time. Secondly, IC/FC time stamps were used to segment EMG data and define onset and offset times of muscle activities within the gait cycle and its subphases. For investigation purposes, we observed notable differences in temporal characteristics as well as muscle onset/offset timings and amplitudes between indoor and outdoor walking of three stroke survivors. Our preliminary analysis suggests a multi-modal approach may be important to augment and improve current inertial conceptual gait models by providing additional quantitative EMG data.
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Estimation of Walking Speed and Its Spatiotemporal Determinants Using a Single Inertial Sensor Worn on the Thigh: From Healthy to Hemiparetic Walking. SENSORS 2021; 21:s21216976. [PMID: 34770283 PMCID: PMC8587282 DOI: 10.3390/s21216976] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Revised: 09/24/2021] [Accepted: 09/24/2021] [Indexed: 11/16/2022]
Abstract
We present the use of a single inertial measurement unit (IMU) worn on the thigh to produce stride-by-stride estimates of walking speed and its spatiotemporal determinants (i.e., stride time and stride length). Ten healthy and eight post-stroke individuals completed a 6-min walk test with an 18-camera motion capture system used for ground truth measurements. Subject-specific estimation models were trained to estimate walking speed using the polar radius extracted from phase portraits produced from the IMU-measured thigh angular position and velocity. Consecutive flexion peaks in the thigh angular position data were used to define each stride and compute stride times. Stride-by-stride estimates of walking speed and stride time were then used to compute stride length. In both the healthy and post-stroke cohorts, low error and high consistency were observed for the IMU estimates of walking speed (MAE < 0.035 m/s; ICC > 0.98), stride time (MAE < 30 ms; ICC > 0.97), and stride length (MAE < 0.037 m; ICC > 0.96). This study advances the use of a single wearable sensor to accurately estimate walking speed and its spatiotemporal determinants during both healthy and hemiparetic walking.
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14
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Celik Y, Stuart S, Woo WL, Godfrey A. Wearable Inertial Gait Algorithms: Impact of Wear Location and Environment in Healthy and Parkinson's Populations. SENSORS 2021; 21:s21196476. [PMID: 34640799 PMCID: PMC8512498 DOI: 10.3390/s21196476] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 09/22/2021] [Accepted: 09/23/2021] [Indexed: 11/16/2022]
Abstract
Wearable inertial measurement units (IMUs) are used in gait analysis due to their discrete wearable attachment and long data recording possibilities within indoor and outdoor environments. Previously, lower back and shin/shank-based IMU algorithms detecting initial and final contact events (ICs-FCs) were developed and validated on a limited number of healthy young adults (YA), reporting that both IMU wear locations are suitable to use during indoor and outdoor gait analysis. However, the impact of age (e.g., older adults, OA), pathology (e.g., Parkinson's Disease, PD) and/or environment (e.g., indoor vs. outdoor) on algorithm accuracy have not been fully investigated. Here, we examined IMU gait data from 128 participants (72-YA, 20-OA, and 36-PD) to thoroughly investigate the suitability of ICs-FCs detection algorithms (1 × lower back and 1 × shin/shank-based) for quantifying temporal gait characteristics depending on IMU wear location and walking environment. The level of agreement between algorithms was investigated for different cohorts and walking environments. Although mean temporal characteristics from both algorithms were significantly correlated for all groups and environments, subtle but characteristically nuanced differences were observed between cohorts and environments. The lowest absolute agreement level was observed in PD (ICC2,1 = 0.979, 0.806, 0.730, 0.980) whereas highest in YA (ICC2,1 = 0.987, 0.936, 0.909, 0.989) for mean stride, stance, swing, and step times, respectively. Absolute agreement during treadmill walking (ICC2,1 = 0.975, 0.914, 0.684, 0.945), indoor walking (ICC2,1 = 0.987, 0.936, 0.909, 0.989) and outdoor walking (ICC2,1 = 0.998, 0.940, 0.856, 0.998) was found for mean stride, stance, swing, and step times, respectively. Findings of this study suggest that agreements between algorithms are sensitive to the target cohort and environment. Therefore, researchers/clinicians should be cautious while interpreting temporal parameters that are extracted from inertial sensors-based algorithms especially for those with a neurological condition.
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Affiliation(s)
- Yunus Celik
- Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK;
| | - Sam Stuart
- Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle upon Tyne NE1 8ST, UK;
| | - Wai Lok Woo
- Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK;
- Correspondence: (W.L.W.); (A.G.); Tel.: +44-0-191-227-3642 (A.G.)
| | - Alan Godfrey
- Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK;
- Correspondence: (W.L.W.); (A.G.); Tel.: +44-0-191-227-3642 (A.G.)
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15
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Real-time gait metric estimation for everyday gait training with wearable devices in people poststroke. ACTA ACUST UNITED AC 2021; 2. [PMID: 34396094 PMCID: PMC8360352 DOI: 10.1017/wtc.2020.11] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Hemiparetic walking after stroke is typically slow, asymmetric, and inefficient, significantly impacting activities of daily living. Extensive research shows that functional, intensive, and task-specific gait training is instrumental for effective gait rehabilitation, characteristics that our group aims to encourage with soft robotic exosuits. However, standard clinical assessments may lack the precision and frequency to detect subtle changes in intervention efficacy during both conventional and exosuit-assisted gait training, potentially impeding targeted therapy regimes. In this paper, we use exosuit-integrated inertial sensors to reconstruct three clinically meaningful gait metrics related to circumduction, foot clearance, and stride length. Our method corrects sensor drift using instantaneous information from both sides of the body. This approach makes our method robust to irregular walking conditions poststroke as well as usable in real-time applications, such as real-time movement monitoring, exosuit assistance control, and biofeedback. We validate our algorithm in eight people poststroke in comparison to lab-based optical motion capture. Mean errors were below 0.2 cm (9.9%) for circumduction, −0.6 cm (−3.5%) for foot clearance, and 3.8 cm (3.6%) for stride length. A single-participant case study shows our technique’s promise in daily-living environments by detecting exosuit-induced changes in gait while walking in a busy outdoor plaza.
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16
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Garcia Oliveira S, Lourenço Nogueira S, Alex Matos Ribeiro J, Carnaz L, Regina Rocha Urruchia V, Alcantara CC, L Russo T. Concurrent validity and reliability of an activity monitoring for rehabilitation (AMoR) platform for step counting and sitting/lying time in post-stroke individuals. Top Stroke Rehabil 2021; 29:103-113. [PMID: 33605190 DOI: 10.1080/10749357.2021.1886639] [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: 10/22/2022]
Abstract
BACKGROUND Objective and reliable measurements to investigate daily behavior patterns in people with stroke could help therapeutic interventions after a stroke. OBJECTIVE To evaluate whether the Activity Monitoring for Rehabilitation (AMoR) platform has adequate concurrent validity and reliability for step counting and time spent sitting/lying in people post-stroke and to investigate its percentage accuracy for step counting at different walking speeds. METHODS Cross-sectional observational study. Fifty chronic post-stroke subjects used the AMoR platform and SAM simultaneously while a Video camera recorded the same activities during clinical trials. Spearman's correlation coefficient, the mean absolute percentage error, the intraclass correlation coefficient and Bland-Altman plot analyses were used to estimate the validity and reliability of the AMoR platform and StepWatchTM Activity Monitor (SAM). The accuracy percentage was calculated for each device and plotted as a function of the walking speed during the 10-meter walk test (10MWT). RESULTS There was a very high correlation for step counting in all tests and a high correlation for time spent sitting/lying. The mean absolute percentage error values remained below 4% for step counting and time sitting/lying. The AMoR platform also showed excellent reliability for step counting and sitting/lying time, with values within the limit of agreement in the Bland-Altman plots. A high percentage of accuracy for step counting in the AMoR platform was observed during the 10MWT. CONCLUSION The AMoR platform is valid and reliable for step counting and time spent sitting/lying, with a high percentage of accuracy at different walking speeds in the post-stroke population.
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Affiliation(s)
| | | | | | - Letícia Carnaz
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, Brazil
| | | | | | - Thiago L Russo
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, Brazil
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17
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Mc Ardle R, Del Din S, Donaghy P, Galna B, Thomas AJ, Rochester L. The Impact of Environment on Gait Assessment: Considerations from Real-World Gait Analysis in Dementia Subtypes. SENSORS 2021; 21:s21030813. [PMID: 33530508 PMCID: PMC7865394 DOI: 10.3390/s21030813] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 01/19/2021] [Accepted: 01/21/2021] [Indexed: 01/05/2023]
Abstract
Laboratory-based gait assessments are indicative of clinical outcomes (e.g., disease identification). Real-world gait may be more sensitive to clinical outcomes, as impairments may be exaggerated in complex environments. This study aims to investigate how different environments (e.g., lab, real world) impact gait. Different walking bout lengths in the real world will be considered proxy measures of context. Data collected in different dementia disease subtypes will be analysed as disease-specific gait impairments are reported between these groups. Thirty-two people with cognitive impairment due to Alzheimer’s disease (AD), 28 due to dementia with Lewy bodies (DLB) and 25 controls were recruited. Participants wore a tri-axial accelerometer for six 10 m walks in lab settings, and continuously for seven days in the real world. Fourteen gait characteristics across five domains were measured (i.e., pace, variability, rhythm, asymmetry, postural control). In the lab, the DLB group showed greater step length variability (p = 0.008) compared to AD. Both subtypes demonstrated significant gait impairments (p < 0.01) compared to controls. In the real world, only very short walking bouts (<10 s) demonstrated different gait impairments between subtypes. The context where walking occurs impacts signatures of gait impairment in dementia subtypes. To develop real-world gait assessment as a clinical tool, algorithms and metrics must accommodate for changes in context.
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Affiliation(s)
- Ríona Mc Ardle
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK; (S.D.D.); (P.D.); (B.G.); (A.J.T.); (L.R.)
- Correspondence:
| | - Silvia Del Din
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK; (S.D.D.); (P.D.); (B.G.); (A.J.T.); (L.R.)
| | - Paul Donaghy
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK; (S.D.D.); (P.D.); (B.G.); (A.J.T.); (L.R.)
| | - Brook Galna
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK; (S.D.D.); (P.D.); (B.G.); (A.J.T.); (L.R.)
- School of Biomedical, Nutritional and Sport Sciences, Newcastle University, Newcastle Upon Tyne NE1 7RU, UK
| | - Alan J Thomas
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK; (S.D.D.); (P.D.); (B.G.); (A.J.T.); (L.R.)
| | - Lynn Rochester
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK; (S.D.D.); (P.D.); (B.G.); (A.J.T.); (L.R.)
- Newcastle Upon Tyne Hospital NHS Foundation Trust, Newcastle Upon Tyne NE7 7DN, UK
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18
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Powell D, Celik Y, Trojaniello D, Young F, Moore J, Stuart S, Godfrey A. Instrumenting traditional approaches to physical assessment. Digit Health 2021. [DOI: 10.1016/b978-0-12-818914-6.00005-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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19
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Morris R, Mancin M. Lab-on-a-chip: wearables as a one stop shop for free-living assessments. Digit Health 2021. [DOI: 10.1016/b978-0-12-818914-6.00017-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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20
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Klompstra L, Kyriakou M, Lambrinou E, Piepoli MF, Coats AJS, Cohen-Solal A, Cornelis J, Gellen B, Marques-Sule E, Niederseer D, Orso F, Piotrowicz E, Van Craenenbroeck EM, Simonenko M, Witte KK, Wozniak A, Volterrani M, Jaarsma T. Measuring physical activity with activity monitors in patients with heart failure: from literature to practice. A position paper from the Committee on Exercise Physiology and Training of the Heart Failure Association of the European Society of Cardiology. Eur J Heart Fail 2020; 23:83-91. [PMID: 33111464 PMCID: PMC8048426 DOI: 10.1002/ejhf.2035] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 10/16/2020] [Accepted: 10/26/2020] [Indexed: 12/14/2022] Open
Abstract
The aims of this paper were to provide an overview of available activity monitors used in research in patients with heart failure and to identify the key criteria in the selection of the most appropriate activity monitor for collecting, reporting, and analysing physical activity in heart failure research. This study was conducted in three parts. First, the literature was systematically reviewed to identify physical activity concepts and activity monitors used in heart failure research. Second, an additional scoping literature search for validation of these activity monitors was conducted. Third, the most appropriate criteria in the selection of activity monitors were identified. Nine activity monitors were evaluated in terms of size, weight, placement, costs, data storage, water resistance, outcomes and validation, and cut‐off points for physical activity intensity levels were discussed. The choice of a monitor should depend on the research aims, study population and design regarding physical activity. If the aim is to motivate patients to be active or set goals, a less rigorously tested tool can be considered. On the other hand, if the aim is to measure physical activity and its changes over time or following treatment adjustment, it is important to choose a valid activity monitor with a storage and battery longevity of at least one week. The device should provide raw data and valid cut‐off points should be chosen for analysing physical activity intensity levels. Other considerations in choosing an activity monitor should include data storage location and ownership and the upfront costs of the device.
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Affiliation(s)
- Leonie Klompstra
- Department of Health, Medicine and Caring Sciences, Linkoping University, Linkoping, Sweden
| | - Martha Kyriakou
- Department of Nursing, School of Health Sciences, Cyprus University of Technology, Limassol, Cyprus.,Intensive Care Unit, Nicosia General Hospital, Nicosia, Cyprus
| | - Ekaterini Lambrinou
- Department of Nursing, School of Health Sciences, Cyprus University of Technology, Limassol, Cyprus
| | - Massimo F Piepoli
- Heart Failure Unit, Cardiology, G. da Saliceto Hospital, Piacenza, Italy
| | - Andrew J S Coats
- Monash University Australia and University of Warwick, Warwick, UK
| | - Alain Cohen-Solal
- Paris University, Cardiology Department, Lariboisière Hospital, Paris, France
| | - Justien Cornelis
- Faculty of Medicine and Health Sciences, Translational Pathophysiological Research, University of Antwerp, Antwerp, Belgium.,Belgian Health Care Knowledge Centre (KCE), Brussels, Belgium
| | | | | | - David Niederseer
- Department of Cardiology, University Heart Center Zurich, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Francesco Orso
- Section of Geriatric Medicine and Cardiology, Department of Geriatrics, Careggi University Hospital, Florence, Italy
| | - Ewa Piotrowicz
- Telecardiology Center, National Institute of Cardiology, Warsaw, Poland
| | - Emeline M Van Craenenbroeck
- Department of Cardiology, Antwerp University Hospital and Research Group Cardiovascular Diseases, University of Antwerp, Antwerp, Belgium
| | - Maria Simonenko
- Physiology Research and Blood Circulation Department, Cardiopulmonary Exercise Test SRL, Heart Transplantation Outpatient Department, Federal State Budgetary Institution, 'V.A. Almazov National Medical Research Centre' of the Ministry of Health of the Russian Federation, Saint Petersburg, Russian Federation
| | - Klaus K Witte
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Anna Wozniak
- Cardio-Respiratory Department, Doncaster and Bassetlaw Teaching Hospitals NHS Foundation Trust, Doncaster, UK
| | - Maurizio Volterrani
- Department of Cardiovascular and Respiratory Sciences, IRCCS San Raffaele Pisana, Rome, Italy
| | - Tiny Jaarsma
- Department of Health, Medicine and Caring Sciences, Linkoping University, Linkoping, Sweden.,Julius Center, University Medical Center Utrecht, Utrecht, The Netherlands
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21
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Amitrano F, Coccia A, Ricciardi C, Donisi L, Cesarelli G, Capodaglio EM, D’Addio G. Design and Validation of an E-Textile-Based Wearable Sock for Remote Gait and Postural Assessment. SENSORS (BASEL, SWITZERLAND) 2020; 20:E6691. [PMID: 33238448 PMCID: PMC7700449 DOI: 10.3390/s20226691] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 11/14/2020] [Accepted: 11/19/2020] [Indexed: 11/16/2022]
Abstract
This paper presents a new wearable e-textile based system, named SWEET Sock, for biomedical signals remote monitoring. The system includes a textile sensing sock, an electronic unit for data transmission, a custom-made Android application for real-time signal visualization, and a software desktop for advanced digital signal processing. The device allows the acquisition of angular velocities of the lower limbs and plantar pressure signals, which are postprocessed to have a complete and schematic overview of patient's clinical status, regarding gait and postural assessment. In this work, device performances are validated by evaluating the agreement between the prototype and an optoelectronic system for gait analysis on a set of free walk acquisitions. Results show good agreement between the systems in the assessment of gait cycle time and cadence, while the presence of systematic and proportional errors are pointed out for swing and stance time parameters. Worse results were obtained in the comparison of spatial metrics. The "wearability" of the system and its comfortable use make it suitable to be used in domestic environment for the continuous remote health monitoring of de-hospitalized patients but also in the ergonomic assessment of health workers, thanks to its low invasiveness.
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Affiliation(s)
- Federica Amitrano
- Department of Information Technologies and Electrical Engineering, University of Naples ‘Federico II’, 80125 Naples, Italy; (F.A.); (A.C.)
- Scientific Clinical Institutes ICS Maugeri SPA SB, 27100 Pavia (PV), Italy; (C.R.); (L.D.); (G.C.); (E.M.C.)
| | - Armando Coccia
- Department of Information Technologies and Electrical Engineering, University of Naples ‘Federico II’, 80125 Naples, Italy; (F.A.); (A.C.)
- Scientific Clinical Institutes ICS Maugeri SPA SB, 27100 Pavia (PV), Italy; (C.R.); (L.D.); (G.C.); (E.M.C.)
| | - Carlo Ricciardi
- Scientific Clinical Institutes ICS Maugeri SPA SB, 27100 Pavia (PV), Italy; (C.R.); (L.D.); (G.C.); (E.M.C.)
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy
| | - Leandro Donisi
- Scientific Clinical Institutes ICS Maugeri SPA SB, 27100 Pavia (PV), Italy; (C.R.); (L.D.); (G.C.); (E.M.C.)
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy
| | - Giuseppe Cesarelli
- Scientific Clinical Institutes ICS Maugeri SPA SB, 27100 Pavia (PV), Italy; (C.R.); (L.D.); (G.C.); (E.M.C.)
- Department of Chemical, Materials and Production Engineering, University of Naples Federico II, 80125 Naples, Italy
| | - Edda Maria Capodaglio
- Scientific Clinical Institutes ICS Maugeri SPA SB, 27100 Pavia (PV), Italy; (C.R.); (L.D.); (G.C.); (E.M.C.)
| | - Giovanni D’Addio
- Scientific Clinical Institutes ICS Maugeri SPA SB, 27100 Pavia (PV), Italy; (C.R.); (L.D.); (G.C.); (E.M.C.)
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Celik Y, Stuart S, Woo WL, Godfrey A. Gait analysis in neurological populations: Progression in the use of wearables. Med Eng Phys 2020; 87:9-29. [PMID: 33461679 DOI: 10.1016/j.medengphy.2020.11.005] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 11/02/2020] [Accepted: 11/11/2020] [Indexed: 12/19/2022]
Abstract
Gait assessment is an essential tool for clinical applications not only to diagnose different neurological conditions but also to monitor disease progression as it contributes to the understanding of underlying deficits. There are established methods and models for data collection and interpretation of gait assessment within different pathologies. This narrative review aims to depict the evolution of gait assessment from observation and rating scales to wearable sensors and laboratory technologies and provide limitations and possible future directions in the field of gait assessment. In this context, we first present an extensive review of current clinical outcomes and gait models. Then, we demonstrate commercially available wearable technologies with their technical capabilities along with their use in gait assessment studies for various neurological conditions. In the next sections, a descriptive knowledge for existing inertial and EMG based algorithms and a sign based guide that shows the outcomes of previous neurological gait assessment studies are presented. Finally, we state a discussion for the use of wearables in gait assessment and speculate the possible research directions by revealing the limitations and knowledge gaps in the literature.
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Affiliation(s)
- Y Celik
- Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
| | - S Stuart
- Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
| | - W L Woo
- Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
| | - A Godfrey
- Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK.
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23
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Rast FM, Labruyère R. Systematic review on the application of wearable inertial sensors to quantify everyday life motor activity in people with mobility impairments. J Neuroeng Rehabil 2020; 17:148. [PMID: 33148315 PMCID: PMC7640711 DOI: 10.1186/s12984-020-00779-y] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 10/22/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Recent advances in wearable sensor technologies enable objective and long-term monitoring of motor activities in a patient's habitual environment. People with mobility impairments require appropriate data processing algorithms that deal with their altered movement patterns and determine clinically meaningful outcome measures. Over the years, a large variety of algorithms have been published and this review provides an overview of their outcome measures, the concepts of the algorithms, the type and placement of required sensors as well as the investigated patient populations and measurement properties. METHODS A systematic search was conducted in MEDLINE, EMBASE, and SCOPUS in October 2019. The search strategy was designed to identify studies that (1) involved people with mobility impairments, (2) used wearable inertial sensors, (3) provided a description of the underlying algorithm, and (4) quantified an aspect of everyday life motor activity. The two review authors independently screened the search hits for eligibility and conducted the data extraction for the narrative review. RESULTS Ninety-five studies were included in this review. They covered a large variety of outcome measures and algorithms which can be grouped into four categories: (1) maintaining and changing a body position, (2) walking and moving, (3) moving around using a wheelchair, and (4) activities that involve the upper extremity. The validity or reproducibility of these outcomes measures was investigated in fourteen different patient populations. Most of the studies evaluated the algorithm's accuracy to detect certain activities in unlabeled raw data. The type and placement of required sensor technologies depends on the activity and outcome measure and are thoroughly described in this review. The usability of the applied sensor setups was rarely reported. CONCLUSION This systematic review provides a comprehensive overview of applications of wearable inertial sensors to quantify everyday life motor activity in people with mobility impairments. It summarizes the state-of-the-art, it provides quick access to the relevant literature, and it enables the identification of gaps for the evaluation of existing and the development of new algorithms.
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Affiliation(s)
- Fabian Marcel Rast
- Swiss Children’s Rehab, University Children’s Hospital Zurich, Mühlebergstrasse 104, 8910 Affoltern am Albis, Switzerland
- Children’s Research Center, University Children’s Hospital of Zurich, University of Zurich, Zurich, Switzerland
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Rob Labruyère
- Swiss Children’s Rehab, University Children’s Hospital Zurich, Mühlebergstrasse 104, 8910 Affoltern am Albis, Switzerland
- Children’s Research Center, University Children’s Hospital of Zurich, University of Zurich, Zurich, Switzerland
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24
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Coulby G, Clear A, Jones O, Young F, Stuart S, Godfrey A. Towards remote healthcare monitoring using accessible IoT technology: state-of-the-art, insights and experimental design. Biomed Eng Online 2020; 19:80. [PMID: 33126878 PMCID: PMC7602322 DOI: 10.1186/s12938-020-00825-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 10/21/2020] [Indexed: 11/30/2022] Open
Abstract
Healthcare studies are moving toward individualised measurement. There is need to move beyond supervised assessments in the laboratory/clinic. Longitudinal free-living assessment can provide a wealth of information on patient pathology and habitual behaviour, but cost and complexity of equipment have typically been a barrier. Lack of supervised conditions within free-living assessment means there is need to augment these studies with environmental analysis to provide context to individual measurements. This paper reviews low-cost and accessible Internet of Things (IoT) technologies with the aim of informing biomedical engineers of possibilities, workflows and limitations they present. In doing so, we evidence their use within healthcare research through literature and experimentation. As hardware becomes more affordable and feature rich, the cost of data magnifies. This can be limiting for biomedical engineers exploring low-cost solutions as data costs can make IoT approaches unscalable. IoT technologies can be exploited by biomedical engineers, but more research is needed before these technologies can become commonplace for clinicians and healthcare practitioners. It is hoped that the insights provided by this paper will better equip biomedical engineers to lead and monitor multi-disciplinary research investigations.
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Affiliation(s)
- G. Coulby
- Department of Computer and Information Sciences, Faculty of Engineering and Environment, Northumbria University, Newcastle Upon Tyne, NE1 8ST UK
| | - A. Clear
- Department of Computer and Information Sciences, Faculty of Engineering and Environment, Northumbria University, Newcastle Upon Tyne, NE1 8ST UK
| | - O. Jones
- Director of Research, Ryder Architecture, Newcastle Upon Tyne, NE1 3NN UK
| | - F. Young
- Department of Computer and Information Sciences, Faculty of Engineering and Environment, Northumbria University, Newcastle Upon Tyne, NE1 8ST UK
| | - S. Stuart
- Department of Sport, Exercise and Rehabilitation, Faculty of Health and Life Sciences, Northumbria University, Newcastle Upon Tyne, NE1 8ST UK
| | - A. Godfrey
- Department of Computer and Information Sciences, Faculty of Engineering and Environment, Northumbria University, Newcastle Upon Tyne, NE1 8ST UK
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25
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Lee SH, Lee HJ, Shim Y, Chang WH, Choi BO, Ryu GH, Kim YH. Wearable hip-assist robot modulates cortical activation during gait in stroke patients: a functional near-infrared spectroscopy study. J Neuroeng Rehabil 2020; 17:145. [PMID: 33121535 PMCID: PMC7596937 DOI: 10.1186/s12984-020-00777-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 10/21/2020] [Indexed: 12/21/2022] Open
Abstract
Background Gait dysfunction is common in post-stroke patients as a result of impairment in cerebral gait mechanism. Powered robotic exoskeletons are promising tools to maximize neural recovery by delivering repetitive walking practice. Objectives The purpose of this study was to investigate the modulating effect of the Gait Enhancing and Motivating System-Hip (GEMS-H) on cortical activation during gait in patients with chronic stroke. Methods. Twenty chronic stroke patients performed treadmill walking at a self-selected speed either with assistance of GEMS-H (GEMS-H) or without assistance of GEMS-H (NoGEMS-H). Changes in oxygenated hemoglobin (oxyHb) concentration in the bilateral primary sensorimotor cortex (SMC), premotor cortices (PMC), supplemental motor areas (SMA), and prefrontal cortices (PFC) were recorded using functional near infrared spectroscopy. Results Walking with the GEMS-H promoted symmetrical SMC activation, with more activation in the affected hemisphere than in NoGEMS-H conditions. GEMS-H also decreased oxyHb concentration in the late phase over the ipsilesional SMC and bilateral SMA (P < 0.05). Conclusions The results of the present study reveal that the GEMS-H promoted more SMC activation and a balanced activation pattern that helped to restore gait function. Less activation in the late phase over SMC and SMA during gait with GEMS-H indicates that GEMS-H reduces the cortical participation of stroke gait by producing rhythmic hip flexion and extension movement and allows a more coordinate and efficient gait patterns. Trial registration NCT03048968. Registered 06 Feb 2017
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Affiliation(s)
- Su-Hyun Lee
- Department of Physical and Rehabilitation Medicine, Center for Prevention and Rehabilitation, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Irwon-ro 115, Gangnam-gu, Seoul, 06355, Republic of Korea
| | - Hwang-Jae Lee
- Department of Physical and Rehabilitation Medicine, Center for Prevention and Rehabilitation, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Irwon-ro 115, Gangnam-gu, Seoul, 06355, Republic of Korea.,Department of Health Sciences and Technology, Department of Medical Device Management and Research, Department of Digital Health, SAIHST, Sungkyunkwan University, Irwon-ro 81, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Youngbo Shim
- Samsung Research, Samsung Electronics, 56, Seongchon-gil, Seocho-gu, Seoul, 06756, Republic of Korea
| | - Won Hyuk Chang
- Department of Physical and Rehabilitation Medicine, Center for Prevention and Rehabilitation, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Irwon-ro 115, Gangnam-gu, Seoul, 06355, Republic of Korea
| | - Byung-Ok Choi
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Irwon-ro 81, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Gyu-Ha Ryu
- Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University School of Medicine, Irwon-ro 81, Gangnam-gu, Seoul, 06351, Republic of Korea.,The Office of R&D Strategy & Planning, Samsung Medical Center, Irwon-ro 81, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Yun-Hee Kim
- Department of Physical and Rehabilitation Medicine, Center for Prevention and Rehabilitation, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Irwon-ro 115, Gangnam-gu, Seoul, 06355, Republic of Korea. .,Department of Health Sciences and Technology, Department of Medical Device Management and Research, Department of Digital Health, SAIHST, Sungkyunkwan University, Irwon-ro 81, Gangnam-gu, Seoul, 06351, Republic of Korea.
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26
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Martini DN, Parrington L, Stuart S, Fino PC, King LA. Gait Performance in People with Symptomatic, Chronic Mild Traumatic Brain Injury. J Neurotrauma 2020; 38:218-224. [PMID: 32495691 DOI: 10.1089/neu.2020.6986] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
There is a dearth of knowledge about how symptom severity affects gait in the chronic (>3 months) mild traumatic brain injury (mTBI) population despite up to 53% of people reporting persisting symptoms after mTBI. The aim of this investigation was to determine whether gait is affected in a symptomatic, chronic mTBI group and to assess the relationship between gait performance and symptom severity on the Neurobehavioral Symptom Inventory (NSI). Gait was assessed under single- and dual-task conditions using five inertial sensors in 57 control subjects and 65 persons with chronic mTBI (1.0 year from mTBI). The single- and dual-task gait domains of Pace, Rhythm, Variability, and Turning were calculated from individual gait characteristics. Dual-task cost (DTC) was calculated for each domain. The mTBI group walked (domain z-score mean difference, single-task = 0.70; dual-task = 0.71) and turned (z-score mean difference, single-task = 0.69; dual-task = 0.70) slower (p < 0.001) under both gait conditions, with less rhythm under dual-task gait (z-score difference = 0.21; p = 0.001). DTC was not different between groups. Higher NSI somatic subscore was related to higher single- and dual-task gait variability as well as slower dual-task pace and turning (p < 0.01). Persons with chronic mTBI and persistent symptoms exhibited altered gait, particularly under dual-task, and worse gait performance related to greater symptom severity. Future gait research in chronic mTBI should assess the possible underlying physiological mechanisms for persistent symptoms and gait deficits.
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Affiliation(s)
- Douglas N Martini
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA.,Veterans Affairs Portland Healthcare System, Portland, Oregon, USA
| | - Lucy Parrington
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA.,Veterans Affairs Portland Healthcare System, Portland, Oregon, USA
| | - Samuel Stuart
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA.,Veterans Affairs Portland Healthcare System, Portland, Oregon, USA.,Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle upon Tyne, United Kingdom
| | - Peter C Fino
- Department of Health, Kinesiology, and Recreation, University of Utah, Salt Lake City, Utah, USA
| | - Laurie A King
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA.,Veterans Affairs Portland Healthcare System, Portland, Oregon, USA
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27
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Del Din S, Lewis EG, Gray WK, Collin H, Kissima J, Rochester L, Dotchin C, Urasa S, Walker R. Monitoring Walking Activity with Wearable Technology in Rural-dwelling Older Adults in Tanzania: A Feasibility Study Nested within a Frailty Prevalence Study. Exp Aging Res 2020; 46:367-381. [PMID: 32643558 PMCID: PMC7497586 DOI: 10.1080/0361073x.2020.1787752] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Background Older adults with lower levels of activity can be at risk of poor health outcomes.
Wearable technology has improved the acceptability and objectivity of measuring activity
for older adults in high-income countries. Nevertheless, the technology is
under-utilized in low-to-middle income countries. The aim was to explore feasibility,
acceptability and utility of wearable technology to measure walking activity in
rural-dwelling, older Tanzanians. Methods A total of 65 participants (73.9 ± 11.2 years), 36 non-frail and 29 frail, were
assessed. Free-living data were recorded for 7 days with an accelerometer on the lower
back. Data were analyzed via an automatic cloud-based pipeline: volume, pattern and
variability of walking were extracted. Acceptability questionnaires were completed.
T-tests were used for comparison between the groups. Results 59/65 datasets were analyzed. Questionnaires indicated that 15/65 (23.0%) experienced
some therapeutic benefit from the accelerometer, 15/65 (23.0%) expected diagnostic
benefit; 16/65 (24.6%) experienced symptoms while wearing the accelerometer (e.g.
itching). Frail adults walked significantly less, had less variable walking patterns,
and had a greater proportion of shorter walking bouts compared to the non-frail. Conclusion This study suggests that important contextual and practical limitations withstanding
wearable technology may be feasible for measuring walking activity in older
rural-dwelling adults in low-income settings, identifying those with frailty.
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Affiliation(s)
- Silvia Del Din
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Clinical Ageing Research Unit, Newcastle University , Newcastle upon Tyne, UK
| | - Emma Grace Lewis
- Northumbria Healthcare NHS Foundation Trust, North Tyneside General Hospital , North Shields, UK.,Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University , Newcastle upon Tyne, UK
| | - William K Gray
- Northumbria Healthcare NHS Foundation Trust, North Tyneside General Hospital , North Shields, UK
| | - Harry Collin
- The Medical School, Newcastle University , Newcastle upon Tyne, UK
| | - John Kissima
- Hai District Hospital , Boma Ng'ombe, Hai, Kilimanjaro, Tanzania
| | - Lynn Rochester
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Clinical Ageing Research Unit, Newcastle University , Newcastle upon Tyne, UK.,Newcastle upon Tyne Hospitals, NHS Foundation Trust , Newcastle upon Tyne, UK
| | - Catherine Dotchin
- Northumbria Healthcare NHS Foundation Trust, North Tyneside General Hospital , North Shields, UK.,Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University , Newcastle upon Tyne, UK
| | - Sarah Urasa
- Kilimanjaro Christian Medical Centre , Moshi, Tanzania
| | - Richard Walker
- Northumbria Healthcare NHS Foundation Trust, North Tyneside General Hospital , North Shields, UK.,Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University , Newcastle upon Tyne, UK
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28
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Ogihara H, Tsushima E, Kamo T, Sato T, Matsushima A, Niioka Y, Asahi R, Azami M. Kinematic gait asymmetry assessment using joint angle data in patients with chronic stroke-A normalized cross-correlation approach. Gait Posture 2020; 80:168-173. [PMID: 32521470 DOI: 10.1016/j.gaitpost.2020.05.042] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 04/22/2020] [Accepted: 05/26/2020] [Indexed: 02/02/2023]
Abstract
BACKGROUND Gait asymmetry is an important characteristic often studied in stroke patients. Several methods have been used to define gait asymmetry using joint angles. However, these methods may require normative data from healthy individuals as reference points. This study used normalized cross-correlation (CCnorm) to define kinematic gait asymmetry in individuals after stroke and investigated the usefulness of this assessment. RESEARCH QUESTION Is the analysis of kinematic gait asymmetry based on joint angle data using CCnorm useful for gait assessment in patients with chronic stroke? METHODS The study involved 12 patients with chronic stroke. A motion analysis system was used to record gait speed, hip joint angles, knee joint angles, ankle joint angles, stance time, and swing time. The CCnorm was calculated using the flexion-extension joint angles of hip, knee, and ankle in the sagittal plane to assess the degree of kinematic gait asymmetry. The symmetry ratio (SR) was calculated using stance and swing times to assess the degree of temporal gait asymmetry. Clinical outcomes were measured using the Fugl-Meyer Assessment for the lower extremity (FMA-LE), Berg Balance Scale (BBS), and Functional Independence Measure (FIM). RESULTS Hip CCnorm was correlated with SRswing (r=-0.612, p < 0.05). Knee CCnorm was correlated with SRstance (r = 0.807, p < 0.01), SRswing (r=-0.752, p < 0.05), gait speed (r = 0.654, p < 0.05), BBS (r = 0.717, p < 0.01), and FIM (r = 0.735, p < 0.01). SIGNIFICANCE Hip and knee joint CCnorm appear to be useful tools for the assessment of gait asymmetry in stroke patients. In addition, kinematic gait asymmetry of the knee joint could reflect physical function, balance, and activities of daily living. These findings underline the importance of using kinematic gait asymmetry assessment in chronic stroke patients.
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Affiliation(s)
- Hirofumi Ogihara
- Department of Physical Therapy, School of Health Sciences, Japan University of Health Sciences, 2-555, Hirasuka, Satte-city, Saitama, 340-0145 Japan; Graduate School of Health Sciences, Hirosaki University, 66-1, Honcho, Hirosaki-city, Aomori, 036-8564 Japan.
| | - Eiki Tsushima
- Graduate School of Health Sciences, Hirosaki University, 66-1, Honcho, Hirosaki-city, Aomori, 036-8564 Japan
| | - Tomohiko Kamo
- Department of Physical Therapy, School of Health Sciences, Japan University of Health Sciences, 2-555, Hirasuka, Satte-city, Saitama, 340-0145 Japan
| | - Takaaki Sato
- Graduate School of Health Sciences, Hirosaki University, 66-1, Honcho, Hirosaki-city, Aomori, 036-8564 Japan; Department of Physical Therapy, Kakeyu Hospital, 1308, Kakeyuonsen, Ueda-city, Nagano, 386-0396 Japan
| | - Akira Matsushima
- Department of Neurology, Kakeyu Hospital, 1308, Kakeyuonsen, Ueda-city, Nagano, 386-0396 Japan
| | - Yamato Niioka
- Department of Physical Therapy, School of Health Sciences, Aomori University of Health and Welfare, Mase 58-1, Hamadate, Aomori-city, Aomori, 030-8505 Japan
| | - Ryoma Asahi
- Department of Physical Therapy, School of Health Sciences, Japan University of Health Sciences, 2-555, Hirasuka, Satte-city, Saitama, 340-0145 Japan
| | - Masato Azami
- Department of Physical Therapy, School of Health Sciences, Japan University of Health Sciences, 2-555, Hirasuka, Satte-city, Saitama, 340-0145 Japan
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Using an Accelerometer-Based Step Counter in Post-Stroke Patients: Validation of a Low-Cost Tool. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17093177. [PMID: 32370210 PMCID: PMC7246942 DOI: 10.3390/ijerph17093177] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 04/29/2020] [Accepted: 04/29/2020] [Indexed: 11/29/2022]
Abstract
Monitoring the real-life mobility of stroke patients could be extremely useful for clinicians. Step counters are a widely accessible, portable, and cheap technology that can be used to monitor patients in different environments. The aim of this study was to validate a low-cost commercial tri-axial accelerometer-based step counter for stroke patients and to determine the best positioning of the step counter (wrists, ankles, and waist). Ten healthy subjects and 43 post-stroke patients were enrolled and performed four validated clinical tests (10 m, 50 m, and 6 min walking tests and timed up and go tests) while wearing five step counters in different positions while a trained operator counted the number of steps executed in each test manually. Data from step counters and those collected manually were compared using the intraclass coefficient correlation and mean average percentage error. The Bland–Altman plot was also used to describe agreement between the two quantitative measurements (step counter vs. manual counting). During walking tests in healthy subjects, the best reliability was found for lower limbs and waist placement (intraclass coefficient correlations (ICCs) from 0.46 to 0.99), and weak reliability was observed for upper limb placement in every test (ICCs from 0.06 to 0.38). On the contrary, in post-stroke patients, moderate reliability was found only for the lower limbs in the 6 min walking test (healthy ankle ICC: 0.69; pathological ankle ICC: 0.70). Furthermore, the Bland–Altman plot highlighted large average discrepancies between methods for the pathological group. However, while the step counter was not able to reliably determine steps for slow patients, when applied to the healthy ankle of patients who walked faster than 0.8 m/s, it counted steps with excellent precision, similar to that seen in the healthy subjects (ICCs from 0.36 to 0.99). These findings show that a low-cost accelerometer-based step counter could be useful for measuring mobility in select high-performance patients and could be used in clinical and real-world settings.
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Are Accelerometer-based Functional Outcome Assessments Feasible and Valid After Treatment for Lower Extremity Sarcomas? Clin Orthop Relat Res 2020; 478:482-503. [PMID: 31390339 PMCID: PMC7145056 DOI: 10.1097/corr.0000000000000883] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
BACKGROUND Aspects of physical functioning, including balance and gait, are affected after surgery for lower limb musculoskeletal tumors. These are not routinely measured but likely are related to how well patients function after resection or amputation for a bone or soft tissue sarcoma. Small, inexpensive portable accelerometers are available that might be clinically useful to assess balance and gait in these patients, but they have not been well studied. QUESTIONS/PURPOSES In patients treated for lower extremity musculoskeletal tumors, we asked: (1) Are accelerometer-based body-worn monitor assessments of balance, gait, and timed up-and-go tests (TUG) feasible and acceptable? (2) Do these accelerometer-based body-worn monitor assessments produce clinically useful data (face validity), distinguish between patients and controls (discriminant validity), reflect findings obtained using existing clinical measures (convergent validity) and standard manual techniques in clinic (concurrent validity)? METHODS This was a prospective cross-sectional study. Out of 97 patients approached, 34 adult patients treated for tumors in the femur/thigh (19), pelvis/hip (3), tibia/leg (9), or ankle/foot (3) were included in this study. Twenty-seven had limb-sparing surgery and seven underwent amputation. Patients performed standard activities while wearing a body-worn monitor on the lower back, including standing, walking, and TUG tests. Summary measures of balance (area [ellipsis], magnitude [root mean square {RMS}], jerkiness [jerk], frequency of postural sway below which 95% of power of acceleration power spectrum is observed [f95 of postural sway]), gait [temporal outcomes, step length and velocity], and TUG time were derived. Body-worn monitor assessments were evaluated for feasibility by investigating data loss and patient-reported acceptability and comfort. In addition, outcomes in patients were compared with datasets of healthy participants collected in parallel studies using identical methods as in this study to assess discriminant validity. Body-worn monitor assessments were also investigated for their relationships with routine clinical scales (the Musculoskeletal Tumour Society Scoring system [MSTS], the Toronto Extremity Salvage Score [TESS], and the Quality of life-Cancer survivors [QoL-CS)] to assess convergent validity and their agreement with standard manual techniques (video and stopwatch) to assess concurrent validity. RESULTS Although this was a small patient group, there were initial indications that body-worn monitor assessments were well-tolerated, feasible to perform, acceptable to patients who responded (95% [19 of 20] of patients found the body-worn monitor acceptable and comfortable and 85% [17 of 20] found it user-friendly), and produced clinically useful data comparable with the evidence. Balance and gait measures distinguished patients and controls (discriminant validity), for instance balance outcome (ellipsis) in patients (0.0475 m/s [95% confidence interval 0.0251 to 0.0810]) was affected compared with controls (0.0007 m/s [95% CI 0.0003 to 0.0502]; p = 0.001). Similarly gait outcome (step time) was affected in patients (0.483 seconds [95% CI 0.451 to 0.512]) compared with controls (0.541 seconds [95% CI 0.496 to 0.573]; p < 0.001). Moreover, body-worn monitor assessments showed relationships with existing clinical scales (convergent validity), for instance ellipsis with MSTS (r = -0.393; p = 0.024). Similarly, manual techniques showed excellent agreement with body-worn monitor assessments (concurrent validity), for instance stopwatch time 22.28 +/- 6.93 seconds with iTUG time 21.18 +/- 6.23 seconds (intraclass correlation coefficient agreement = 0.933; p < 0.001). P < 0.05 was considered statistically significant. CONCLUSIONS Although we had a small, heterogeneous patient population, this pilot study suggests that body-worn monitors might be useful clinically to quantify physical functioning in patients treated for lower extremity tumors. Balance and gait relate to disability and quality of life. These measurements could provide clinicians with useful novel information on balance and gait, which in turn could guide rehabilitation strategies. LEVEL OF EVIDENCE Level III, diagnostic study.
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31
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Differentiating dementia disease subtypes with gait analysis: feasibility of wearable sensors? Gait Posture 2020; 76:372-376. [PMID: 31901765 DOI: 10.1016/j.gaitpost.2019.12.028] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 12/17/2019] [Accepted: 12/19/2019] [Indexed: 02/06/2023]
Abstract
BACKGROUND There are unique signatures of gait impairments in different dementia disease subtypes, such as Alzheimer's disease (AD), dementia with Lewy bodies (DLB) and Parkinson's disease (PDD). This suggests gait analysis is a useful differential marker for dementia disease subtypes, but this has yet to be assessed using inexpensive wearable technology. RESEARCH QUESTION This study aimed to assess whether a single accelerometer-based wearable could differentiate dementia disease subtypes through gait analysis. METHODS 80 people with mild cognitive impairment or dementia due to AD, DLB or PD performed six ten-metre walks. An accelerometer-based wearable (Axivity) assessed gait. Data was processed using algorithms validated in other neurological disorders and older adults. Fourteen spatiotemporal characteristic were computed, that broadly represent pace, variability, rhythm, asymmetry and postural control features of gait. One way analysis of variance and Kruskall Wallis tests identified significant between-group differences, and post-hoc independent t-tests and Mann Whitney U's established where differences lay. Receiver Operating Characteristics and Area Under the Curve (AUC) demonstrated overall accuracy for single gait characteristics. RESULTS The wearable was able to differentiate dementia disease subtypes (p ≤ .05) and demonstrated significant differences between the groups in 7 gait characteristics with modest accuracy. For reference the instrumented walkway showed 2 between-group differences in gait characteristics. SIGNIFICANCE This study found that a wearable device can be used to differentiate dementia disease subtypes. This provides a foundation for future research to investigate the application of wearable technology as a clinical tool to aid diagnostic accuracy, allowing the correct treatment and care to be applied. Wearable technology may be particularly useful as its use is less restricted to context, making it easier to implement.
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Buckley C, Micó-Amigo ME, Dunne-Willows M, Godfrey A, Hickey A, Lord S, Rochester L, Del Din S, Moore SA. Gait Asymmetry Post-Stroke: Determining Valid and Reliable Methods Using a Single Accelerometer Located on the Trunk. SENSORS (BASEL, SWITZERLAND) 2019; 20:E37. [PMID: 31861630 PMCID: PMC6983246 DOI: 10.3390/s20010037] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2019] [Revised: 12/13/2019] [Accepted: 12/17/2019] [Indexed: 01/30/2023]
Abstract
Asymmetry is a cardinal symptom of gait post-stroke that is targeted during rehabilitation. Technological developments have allowed accelerometers to be a feasible tool to provide digital gait variables. Many acceleration-derived variables are proposed to measure gait asymmetry. Despite a need for accurate calculation, no consensus exists for what is the most valid and reliable variable. Using an instrumented walkway (GaitRite) as the reference standard, this study compared the validity and reliability of multiple acceleration-derived asymmetry variables. Twenty-five post-stroke participants performed repeated walks over GaitRite whilst wearing a tri-axial accelerometer (Axivity AX3) on their lower back, on two occasions, one week apart. Harmonic ratio, autocorrelation, gait symmetry index, phase plots, acceleration, and jerk root mean square were calculated from the acceleration signals. Test-retest reliability was calculated, and concurrent validity was estimated by comparison with GaitRite. The strongest concurrent validity was obtained from step regularity from the vertical signal, which also recorded excellent test-retest reliability (Spearman's rank correlation coefficients (rho) = 0.87 and Intraclass correlation coefficient (ICC21) = 0.98, respectively). Future research should test the responsiveness of this and other step asymmetry variables to quantify change during recovery and the effect of rehabilitative interventions for consideration as digital biomarkers to quantify gait asymmetry.
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Affiliation(s)
- Christopher Buckley
- Institute of Neuroscience/Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK; (C.B.); (M.E.M.-A.); (S.L.); (L.R.); (S.D.D.)
| | - M. Encarna Micó-Amigo
- Institute of Neuroscience/Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK; (C.B.); (M.E.M.-A.); (S.L.); (L.R.); (S.D.D.)
| | - Michael Dunne-Willows
- EPSRC Centre for Doctoral Training in Cloud Computing for Big Data, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK;
| | - Alan Godfrey
- Department of Computer and Information Science, Northumbria University, Newcastle upon Tyne NE1 8ST, UK;
| | - Aodhán Hickey
- Department of Health Intelligence, HSC Public Health Agency, Belfast BT2 7ES, Northern Ireland;
| | - Sue Lord
- Institute of Neuroscience/Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK; (C.B.); (M.E.M.-A.); (S.L.); (L.R.); (S.D.D.)
- Auckland University of Technology, 55 Wellesley St E, Auckland 1010, New Zealand
| | - Lynn Rochester
- Institute of Neuroscience/Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK; (C.B.); (M.E.M.-A.); (S.L.); (L.R.); (S.D.D.)
- The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne NE7 7DN, UK
| | - Silvia Del Din
- Institute of Neuroscience/Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK; (C.B.); (M.E.M.-A.); (S.L.); (L.R.); (S.D.D.)
| | - Sarah A. Moore
- Institute of Neuroscience/Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK; (C.B.); (M.E.M.-A.); (S.L.); (L.R.); (S.D.D.)
- Institute of Neuroscience (Stroke Research Group), Newcastle University, 3-4 Claremont Terrace, Newcastle upon Tyne NE2 4AE, UK
- Stroke Northumbria, Northumbria Healthcare NHS Foundation Trust, Rake Lane, North Shields, Tyne and Wear NE29 8NH, UK
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Next Steps in Wearable Technology and Community Ambulation in Multiple Sclerosis. Curr Neurol Neurosci Rep 2019; 19:80. [DOI: 10.1007/s11910-019-0997-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Aung N, Bovonsunthonchai S, Hiengkaew V, Tretriluxana J, Rojasavastera R, Pheung-Phrarattanatrai A. Concurrent validity and intratester reliability of the video-based system for measuring gait poststroke. PHYSIOTHERAPY RESEARCH INTERNATIONAL 2019; 25:e1803. [PMID: 31418511 DOI: 10.1002/pri.1803] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2018] [Revised: 05/20/2019] [Accepted: 07/04/2019] [Indexed: 11/10/2022]
Abstract
BACKGROUND AND PURPOSE Spatio-temporal parameters are commonly used in gait assessment. Advanced tools provide valid and reliable data, considered very effective for physiotherapy intervention. However, these tools may be limited in clinical usage caused by complicated applicability, inaccessibility, and high cost. Therefore, a video-based system is an alternative choice that is easy and affordable for the clinical setting. The purpose of the study was to evaluate the concurrent validity of the video-based system against the validated instrumented gait system (Force Distribution Measurement [FDM]) on the spatio-temporal gait parameters in individuals with stroke. In addition, the intratester reliability of a novice tester was determined. METHODS Twenty individuals with stroke participated in the study. Gait was captured by the video-based and FDM systems simultaneously to measure the degree of concurrent validity. Parameters composed of the affected and unaffected step lengths (cm) and step time (s), stride length (cm), gait velocity (m/s), and cadence (steps/min). Pearson correlation coefficient, paired t test, and intraclass correlation coefficient (ICC) were used to determine the concurrent validity, the difference of the data, and intratester reliability. RESULTS All spatio-temporal gait parameters showed excellent degrees of correlation (rp = .94 to.99, p <.001) between the video-based and FDM systems. No significant difference in all parameters was found between the two systems. Excellent intratester reliability (ICC3,1 = 0.91 to 0.99, p < .001) of all gait parameters were found in a novice tester. CONCLUSION The video-based system was valid and reliable for a novice tester to measure the spatio-temporal gait parameters in individuals with stroke.
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Affiliation(s)
- Nilar Aung
- Faculty of Physical Therapy, Mahidol University, Nakhon Pathom, Thailand.,Department of Physiotherapy, University of Medical Technology, Yangon, Myanmar
| | | | - Vimonwan Hiengkaew
- Faculty of Physical Therapy, Mahidol University, Nakhon Pathom, Thailand
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Petraglia F, Scarcella L, Pedrazzi G, Brancato L, Puers R, Costantino C. Inertial sensors versus standard systems in gait analysis: a systematic review and meta-analysis. Eur J Phys Rehabil Med 2018; 55:265-280. [PMID: 30311493 DOI: 10.23736/s1973-9087.18.05306-6] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
INTRODUCTION The increasing popularity of inertial sensors in clinical practice is not supported by precise information on their reliability or guidelines for their use in rehabilitation. The authors investigated the state of the literature concerning the use of inertial sensors for gait analysis in both healthy and pathological adults comparing traditional systems. Furthermore, trying to define directions for clinicians. EVIDENCE ACQUISITION In accordance with the PRISMA statement, authors searched in PubMed, Web of Science and Scopus all paper published from January 1st, 2005 until December 31st, 2017. They included both healthy and pathological adults' subjects as population, wearable or inertial sensors used for gait analysis and compared with classical gait analysis performed in a Motion Lab as intervention and comparison, gait parameters as outcomes. Considering the methodological quality, authors focused on: sample; description of the study; type of gait analysis used for comparison; type of sensor; sensor placement on the body; gait task requested. EVIDENCE SYNTHESIS From a total of 888 articles, 16 manuscripts were selected and 7 of them were considered for meta-analysis for different gait parameters. Demographic data, tested devices, reference systems, test procedures and outcomes were analyzed. CONCLUSIONS Our results show a good agreement between inertial sensors and classical gait analysis for some gait parameters, supporting their use as a solution for capturing kinematic information over an extended space and time and even outside a laboratory in real-life conditions. Authors can support the use of portable inertial sensors for a practical gait analysis in clinical setting with good reliability. It will then be the experience of the clinician to direct the decision-making process.
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Affiliation(s)
| | - Luca Scarcella
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Giuseppe Pedrazzi
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | | | | | - Cosimo Costantino
- Department of Medicine and Surgery, University of Parma, Parma, Italy -
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