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Herbers C, Zhang R, Erdman A, Johnson MD. Distinguishing features of Parkinson's disease fallers based on wireless insole plantar pressure monitoring. NPJ Parkinsons Dis 2024; 10:67. [PMID: 38503777 PMCID: PMC10951221 DOI: 10.1038/s41531-024-00678-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 03/07/2024] [Indexed: 03/21/2024] Open
Abstract
Postural instability is one of the most disabling motor signs of Parkinson's disease (PD) and often underlies an increased likelihood of falling and loss of independence. Current clinical assessments of PD-related postural instability are based on a retropulsion test, which introduces human error and only evaluates reactive balance. There is an unmet need for objective, multi-dimensional assessments of postural instability that directly reflect activities of daily living in which individuals may experience postural instability. In this study, we trained machine-learning models on insole plantar pressure data from 111 participants (44 with PD and 67 controls) as they performed simulated static and active postural tasks of activities that often occur during daily living. Models accurately classified PD from young controls (area under the curve (AUC) 0.99+/- 0.00), PD from age-matched controls (AUC 0.99+/- 0.01), and PD fallers from PD non-fallers (AUC 0.91+/- 0.08). Utilizing features from both static and active postural tasks significantly improved classification performances, and all tasks were useful for separating PD from controls; however, tasks with higher postural threats were preferred for separating PD fallers from PD non-fallers.
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Affiliation(s)
- Cara Herbers
- Department of Mechanical Engineering, University of Minnesota, 111 Church Street SE, Minneapolis, 55455, MN, USA
| | - Raymond Zhang
- Department of Biomedical Engineering, University of Minnesota, 312 Church Street SE, Minneapolis, 55455, MN, USA
| | - Arthur Erdman
- Department of Mechanical Engineering, University of Minnesota, 111 Church Street SE, Minneapolis, 55455, MN, USA
| | - Matthew D Johnson
- Department of Biomedical Engineering, University of Minnesota, 312 Church Street SE, Minneapolis, 55455, MN, USA.
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2
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Bohlke K, Redfern MS, Rosso AL, Sejdic E. Accelerometry applications and methods to assess standing balance in older adults and mobility-limited patient populations: a narrative review. Aging Clin Exp Res 2023; 35:1991-2007. [PMID: 37526887 PMCID: PMC10881067 DOI: 10.1007/s40520-023-02503-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 07/11/2023] [Indexed: 08/02/2023]
Abstract
Accelerometers provide an opportunity to expand standing balance assessments outside of the laboratory. The purpose of this narrative review is to show that accelerometers are accurate, objective, and accessible tools for balance assessment. Accelerometry has been validated against current gold standard technology, such as optical motion capture systems and force plates. Many studies have been conducted to show how accelerometers can be useful for clinical examinations. Recent studies have begun to apply classification algorithms to accelerometry balance measures to discriminate populations at risk for falls. In addition to healthy older adults, accelerometry can monitor balance in patient populations such as Parkinson's disease, multiple sclerosis, and traumatic brain injury. The lack of software packages or easy-to-use applications have hindered the shift into the clinical space. Lack of consensus on outcome metrics has also slowed the clinical adoption of accelerometer-based balance assessments. Future studies should focus on metrics that are most helpful to evaluate balance in specific populations and protocols that are clinically efficacious.
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Affiliation(s)
- Kayla Bohlke
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
| | - Mark S Redfern
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
| | - Andrea L Rosso
- Department of Epidemiology, School of Public Health, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
| | - Ervin Sejdic
- The Edward S. Rogers Department of Electrical and Computer Engineering, Faculty of Applied Science and Engineering, University of Toronto, 27 King's College Cir, Toronto, ON, M5S, Canada.
- North York General Hospital, 4001 Leslie St., Toronto, ON, M2K, Canada.
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3
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Lantis K, Schnell P, Bland CR, Wilder J, Hock K, Vargo C, Glover NA, Hackney ME, Lustberg MB, Worthen-Chaudhari L. Biomechanical effect of neurologic dance training (NDT) for breast cancer survivors with chemotherapy-induced neuropathy: study protocol for a randomized controlled trial and preliminary baseline data. Trials 2023; 24:564. [PMID: 37658464 PMCID: PMC10472642 DOI: 10.1186/s13063-023-07554-z] [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: 05/27/2023] [Accepted: 07/28/2023] [Indexed: 09/03/2023] Open
Abstract
BACKGROUND Breast cancer (BC) is among the most common forms of cancer experienced by women. Up to 80% of BC survivors treated with chemotherapy experience chemotherapy-induced neuropathy (CIN), which degrades motor control, sensory function, and quality of life. CIN symptoms include numbness, tingling, and/or burning sensations in the extremities; deficits in neuromotor control; and increased fall risk. Physical activity (PA) and music-based medicine (MBM) are promising avenues to address sensorimotor symptoms. Therefore, we propose that we can combine the effects of music- and PA-based medicine through neurologic dance training (NDT) through partnered Adapted Tango (NDT-Tango). We will assess the intervention effect of NDT-Tango v. home exercise (HEX) intervention on biomechanically-measured variables. We hypothesize that 8 weeks of NDT-Tango practice will improve the dynamics of posture and gait more than 8 weeks of HEX. METHODS In a single-center, prospective, two-arm randomized controlled clinical trial, participants are randomly assigned (1:1 ratio) to the NDT-Tango experimental or the HEX active control intervention group. Primary endpoints are change from baseline to after intervention in posture and gait. Outcomes are collected at baseline, midpoint, post, 1-month follow-up, and 6-month follow-up. Secondary and tertiary outcomes include clinical and biomechanical tests of function and questionnaires used to compliment primary outcome measures. Linear mixed models will be used to model changes in postural, biomechanical, and PROs. The primary estimand will be the contrast representing the difference in mean change in outcome measure from baseline to week 8 between treatment groups. DISCUSSION The scientific premise of this study is that NDT-Tango stands to achieve more gains than PA practice alone through combining PA with MBM and social engagement. Our findings may lead to a safe non-pharmacologic intervention that improves CIN-related deficits. TRIAL REGISTRATION This trial was first posted on 11/09/21 at ClinicalTrials.gov under the identifier NCT05114005.
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Affiliation(s)
- Kristen Lantis
- College of Medicine, Department of Physical Medicine and Rehabilitation, The Ohio State University, Columbus, OH, USA.
| | - Patrick Schnell
- College of Public Health, Division of Biostatistics, The Ohio State University, Columbus, OH, USA
| | - Courtney R Bland
- College of Medicine, Department of Physical Medicine and Rehabilitation, The Ohio State University, Columbus, OH, USA
| | - Jacqueline Wilder
- College of Medicine, Department of Physical Medicine and Rehabilitation, The Ohio State University, Columbus, OH, USA
| | - Karen Hock
- Comprehensive Cancer Center, The Ohio State University, 281 W Lane Ave, Columbus, OH, 43210, USA
| | - Craig Vargo
- Comprehensive Cancer Center, The Ohio State University, 281 W Lane Ave, Columbus, OH, 43210, USA
| | - Nelson A Glover
- George Mason University, 4400 University Dr, Fairfax, VA, 22030, USA
| | - Madeleine E Hackney
- Department of Medicine, Division of Geriatrics and Gerontology, Emory University School of Medicine, Atlanta, GA, USA
- Atlanta VA Center for Visual and Neurocognitive Rehabilitation, 2015 Uppergate Dr, Atlanta, GA, 30307, USA
| | | | - Lise Worthen-Chaudhari
- College of Medicine, Department of Physical Medicine and Rehabilitation, The Ohio State University, Columbus, OH, USA
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Tam W, Alajlani M, Abd-Alrazaq A. An Exploration of Wearable Device Features Used in UK Hospital Parkinson Disease Care: Scoping Review. J Med Internet Res 2023; 25:e42950. [PMID: 37594791 PMCID: PMC10474516 DOI: 10.2196/42950] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 03/13/2023] [Accepted: 04/14/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND The prevalence of Parkinson disease (PD) is becoming an increasing concern owing to the aging population in the United Kingdom. Wearable devices have the potential to improve the clinical care of patients with PD while reducing health care costs. Consequently, exploring the features of these wearable devices is important to identify the limitations and further areas of investigation of how wearable devices are currently used in clinical care in the United Kingdom. OBJECTIVE In this scoping review, we aimed to explore the features of wearable devices used for PD in hospitals in the United Kingdom. METHODS A scoping review of the current research was undertaken and reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The literature search was undertaken on June 6, 2022, and publications were obtained from MEDLINE or PubMed, Embase, and the Cochrane Library. Eligible publications were initially screened by their titles and abstracts. Publications that passed the initial screening underwent a full review. The study characteristics were extracted from the final publications, and the evidence was synthesized using a narrative approach. Any queries were reviewed by the first and second authors. RESULTS Of the 4543 publications identified, 39 (0.86%) publications underwent a full review, and 20 (0.44%) publications were included in the scoping review. Most studies (11/20, 55%) were conducted at the Newcastle upon Tyne Hospitals NHS Foundation Trust, with sample sizes ranging from 10 to 418. Most study participants were male individuals with a mean age ranging from 57.7 to 78.0 years. The AX3 was the most popular device brand used, and it was commercially manufactured by Axivity. Common wearable device types included body-worn sensors, inertial measurement units, and smartwatches that used accelerometers and gyroscopes to measure the clinical features of PD. Most wearable device primary measures involved the measured gait, bradykinesia, and dyskinesia. The most common wearable device placements were the lumbar region, head, and wrist. Furthermore, 65% (13/20) of the studies used artificial intelligence or machine learning to support PD data analysis. CONCLUSIONS This study demonstrated that wearable devices could help provide a more detailed analysis of PD symptoms during the assessment phase and personalize treatment. Using machine learning, wearable devices could differentiate PD from other neurodegenerative diseases. The identified evidence gaps include the lack of analysis of wearable device cybersecurity and data management. The lack of cost-effectiveness analysis and large-scale participation in studies resulted in uncertainty regarding the feasibility of the widespread use of wearable devices. The uncertainty around the identified research gaps was further exacerbated by the lack of medical regulation of wearable devices for PD, particularly in the United Kingdom where regulations were changing due to the political landscape.
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Affiliation(s)
- William Tam
- Insitute of Digital Healthcare, Warwick Manufacturing Group, University of Warwick, Coventry, United Kingdom
| | - Mohannad Alajlani
- Insitute of Digital Healthcare, Warwick Manufacturing Group, University of Warwick, Coventry, United Kingdom
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Castiglia SF, Trabassi D, Conte C, Ranavolo A, Coppola G, Sebastianelli G, Abagnale C, Barone F, Bighiani F, De Icco R, Tassorelli C, Serrao M. Multiscale Entropy Algorithms to Analyze Complexity and Variability of Trunk Accelerations Time Series in Subjects with Parkinson's Disease. SENSORS (BASEL, SWITZERLAND) 2023; 23:4983. [PMID: 37430896 DOI: 10.3390/s23104983] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 04/14/2023] [Accepted: 05/16/2023] [Indexed: 07/12/2023]
Abstract
The aim of this study was to assess the ability of multiscale sample entropy (MSE), refined composite multiscale entropy (RCMSE), and complexity index (CI) to characterize gait complexity through trunk acceleration patterns in subjects with Parkinson's disease (swPD) and healthy subjects, regardless of age or gait speed. The trunk acceleration patterns of 51 swPD and 50 healthy subjects (HS) were acquired using a lumbar-mounted magneto-inertial measurement unit during their walking. MSE, RCMSE, and CI were calculated on 2000 data points, using scale factors (τ) 1-6. Differences between swPD and HS were calculated at each τ, and the area under the receiver operating characteristics, optimal cutoff points, post-test probabilities, and diagnostic odds ratios were calculated. MSE, RCMSE, and CIs showed to differentiate swPD from HS. MSE in the anteroposterior direction at τ4 and τ5, and MSE in the ML direction at τ4 showed to characterize the gait disorders of swPD with the best trade-off between positive and negative posttest probabilities and correlated with the motor disability, pelvic kinematics, and stance phase. Using a time series of 2000 data points, a scale factor of 4 or 5 in the MSE procedure can yield the best trade-off in terms of post-test probabilities when compared to other scale factors for detecting gait variability and complexity in swPD.
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Affiliation(s)
- Stefano Filippo Castiglia
- Department of Medical and Surgical Sciences and Biotechnologies, "Sapienza" University of Rome, Polo Pontino, 04100 Latina, Italy
- Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, INAIL, 00078 Monte Porzio Catone, Italy
| | - Dante Trabassi
- Department of Medical and Surgical Sciences and Biotechnologies, "Sapienza" University of Rome, Polo Pontino, 04100 Latina, Italy
| | - Carmela Conte
- Department of Medical and Surgical Sciences and Biotechnologies, "Sapienza" University of Rome, Polo Pontino, 04100 Latina, Italy
| | - Alberto Ranavolo
- Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy
| | - Gianluca Coppola
- Department of Medical and Surgical Sciences and Biotechnologies, "Sapienza" University of Rome, Polo Pontino, 04100 Latina, Italy
| | - Gabriele Sebastianelli
- Department of Medical and Surgical Sciences and Biotechnologies, "Sapienza" University of Rome, Polo Pontino, 04100 Latina, Italy
| | - Chiara Abagnale
- Department of Medical and Surgical Sciences and Biotechnologies, "Sapienza" University of Rome, Polo Pontino, 04100 Latina, Italy
| | - Francesca Barone
- Department of Medical and Surgical Sciences and Biotechnologies, "Sapienza" University of Rome, Polo Pontino, 04100 Latina, Italy
| | - Federico Bighiani
- Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy
- Movement Analysis Research Unit, IRCSS Mondino Foundation, 27100 Pavia, Italy
| | - Roberto De Icco
- Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy
- Movement Analysis Research Unit, IRCSS Mondino Foundation, 27100 Pavia, Italy
| | - Cristina Tassorelli
- Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy
- Movement Analysis Research Unit, IRCSS Mondino Foundation, 27100 Pavia, Italy
| | - Mariano Serrao
- Department of Medical and Surgical Sciences and Biotechnologies, "Sapienza" University of Rome, Polo Pontino, 04100 Latina, Italy
- Movement Analysis Laboratory, Policlinico Italia, 00162 Rome, Italy
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Promsri A, Bangkomdet K, Jindatham I, Jenchang T. Leg Dominance—Surface Stability Interaction: Effects on Postural Control Assessed by Smartphone-Based Accelerometry. Sports (Basel) 2023; 11:sports11040075. [PMID: 37104149 PMCID: PMC10145104 DOI: 10.3390/sports11040075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 03/19/2023] [Accepted: 03/28/2023] [Indexed: 04/03/2023] Open
Abstract
The preferential use of one leg over another in performing lower-limb motor tasks (i.e., leg dominance) is considered to be one of the internal risk factors for sports-related lower-limb injuries. The current study aimed to investigate the effects of leg dominance on postural control during unipedal balancing on three different support surfaces with increasing levels of instability: a firm surface, a foam pad, and a multiaxial balance board. In addition, the interaction effect between leg dominance and surface stability was also tested. To this end, a tri-axial accelerometer-based smartphone sensor was placed over the lumbar spine (L5) of 22 young adults (21.5 ± 0.6 years) to record postural accelerations. Sample entropy (SampEn) was applied to acceleration data as a measure of postural sway regularity (i.e., postural control complexity). The results show that leg dominance (p < 0.001) and interaction (p < 0.001) effects emerge in all acceleration directions. Specifically, balancing on the dominant (kicking) leg shows more irregular postural acceleration fluctuations (high SampEn), reflecting a higher postural control efficiency or automaticity than balancing on the non-dominant leg. However, the interaction effects suggest that unipedal balancing training on unstable surfaces is recommended to reduce interlimb differences in neuromuscular control for injury prevention and rehabilitation.
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Affiliation(s)
- Arunee Promsri
- Department of Physical Therapy, School of Allied Health Sciences, University of Phayao, Phayao 56000, Thailand
- Unit of Excellence in Neuromechanics, School of Allied Health Sciences, University of Phayao, Phayao 56000, Thailand
- Correspondence: ; Tel.: +66-54-466-666 (ext. 3817)
| | - Kotchakorn Bangkomdet
- Department of Physical Therapy, School of Allied Health Sciences, University of Phayao, Phayao 56000, Thailand
| | - Issariya Jindatham
- Department of Physical Therapy, School of Allied Health Sciences, University of Phayao, Phayao 56000, Thailand
| | - Thananya Jenchang
- Department of Physical Therapy, School of Allied Health Sciences, University of Phayao, Phayao 56000, Thailand
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Liddy J, Busa M. Considerations for Applying Entropy Methods to Temporally Correlated Stochastic Datasets. ENTROPY (BASEL, SWITZERLAND) 2023; 25:306. [PMID: 36832672 PMCID: PMC9955719 DOI: 10.3390/e25020306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 01/18/2023] [Accepted: 01/29/2023] [Indexed: 06/18/2023]
Abstract
The goal of this paper is to highlight considerations and provide recommendations for analytical issues that arise when applying entropy methods, specifically Sample Entropy (SampEn), to temporally correlated stochastic datasets, which are representative of a broad range of biomechanical and physiological variables. To simulate a variety of processes encountered in biomechanical applications, autoregressive fractionally integrated moving averaged (ARFIMA) models were used to produce temporally correlated data spanning the fractional Gaussian noise/fractional Brownian motion model. We then applied ARFIMA modeling and SampEn to the datasets to quantify the temporal correlations and regularity of the simulated datasets. We demonstrate the use of ARFIMA modeling for estimating temporal correlation properties and classifying stochastic datasets as stationary or nonstationary. We then leverage ARFIMA modeling to improve the effectiveness of data cleaning procedures and mitigate the influence of outliers on SampEn estimates. We also emphasize the limitations of SampEn to distinguish among stochastic datasets and suggest the use of complementary measures to better characterize the dynamics of biomechanical variables. Finally, we demonstrate that parameter normalization is not an effective procedure for increasing the interoperability of SampEn estimates, at least not for entirely stochastic datasets.
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Affiliation(s)
- Joshua Liddy
- Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA 01003, USA
| | - Michael Busa
- Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA 01003, USA
- Institute for Applied Life Sciences, University of Massachusetts Amherst, Amherst, MA 01003, USA
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Guo CC, Chiesa PA, de Moor C, Fazeli MS, Schofield T, Hofer K, Belachew S, Scotland A. Digital Devices for Assessing Motor Functions in Mobility-Impaired and Healthy Populations: Systematic Literature Review. J Med Internet Res 2022; 24:e37683. [DOI: 10.2196/37683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 07/18/2022] [Accepted: 10/11/2022] [Indexed: 11/22/2022] Open
Abstract
Background
With the advent of smart sensing technology, mobile and wearable devices can provide continuous and objective monitoring and assessment of motor function outcomes.
Objective
We aimed to describe the existing scientific literature on wearable and mobile technologies that are being used or tested for assessing motor functions in mobility-impaired and healthy adults and to evaluate the degree to which these devices provide clinically valid measures of motor function in these populations.
Methods
A systematic literature review was conducted by searching Embase, MEDLINE, CENTRAL (January 1, 2015, to June 24, 2020), the United States and European Union clinical trial registries, and the United States Food and Drug Administration website using predefined study selection criteria. Study selection, data extraction, and quality assessment were performed by 2 independent reviewers.
Results
A total of 91 publications representing 87 unique studies were included. The most represented clinical conditions were Parkinson disease (n=51 studies), followed by stroke (n=5), Huntington disease (n=5), and multiple sclerosis (n=2). A total of 42 motion-detecting devices were identified, and the majority (n=27, 64%) were created for the purpose of health care–related data collection, although approximately 25% were personal electronic devices (eg, smartphones and watches) and 11% were entertainment consoles (eg, Microsoft Kinect or Xbox and Nintendo Wii). The primary motion outcomes were related to gait (n=30), gross motor movements (n=25), and fine motor movements (n=23). As a group, sensor-derived motion data showed a mean sensitivity of 0.83 (SD 7.27), a mean specificity of 0.84 (SD 15.40), a mean accuracy of 0.90 (SD 5.87) in discriminating between diseased individuals and healthy controls, and a mean Pearson r validity coefficient of 0.52 (SD 0.22) relative to clinical measures. We did not find significant differences in the degree of validity between in-laboratory and at-home sensor-based assessments nor between device class (ie, health care–related device, personal electronic devices, and entertainment consoles).
Conclusions
Sensor-derived motion data can be leveraged to classify and quantify disease status for a variety of neurological conditions. However, most of the recent research on digital clinical measures is derived from proof-of-concept studies with considerable variation in methodological approaches, and much of the reviewed literature has focused on clinical validation, with less than one-quarter of the studies performing analytical validation. Overall, future research is crucially needed to further consolidate that sensor-derived motion data may lead to the development of robust and transformative digital measurements intended to predict, diagnose, and quantify neurological disease state and its longitudinal change.
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Tam W, Alajlani M, Abd-alrazaq A. An Exploration of Wearable Device Features Used in UK Hospital Parkinson Disease Care: Scoping Review (Preprint).. [DOI: 10.2196/preprints.42950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
BACKGROUND
The prevalence of Parkinson disease (PD) is becoming an increasing concern owing to the aging population in the United Kingdom. Wearable devices have the potential to improve the clinical care of patients with PD while reducing health care costs. Consequently, exploring the features of these wearable devices is important to identify the limitations and further areas of investigation of how wearable devices are currently used in clinical care in the United Kingdom.
OBJECTIVE
In this scoping review, we aimed to explore the features of wearable devices used for PD in hospitals in the United Kingdom.
METHODS
A scoping review of the current research was undertaken and reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The literature search was undertaken on June 6, 2022, and publications were obtained from MEDLINE or PubMed, Embase, and the Cochrane Library. Eligible publications were initially screened by their titles and abstracts. Publications that passed the initial screening underwent a full review. The study characteristics were extracted from the final publications, and the evidence was synthesized using a narrative approach. Any queries were reviewed by the first and second authors.
RESULTS
Of the 4543 publications identified, 39 (0.86%) publications underwent a full review, and 20 (0.44%) publications were included in the scoping review. Most studies (11/20, 55%) were conducted at the Newcastle upon Tyne Hospitals NHS Foundation Trust, with sample sizes ranging from 10 to 418. Most study participants were male individuals with a mean age ranging from 57.7 to 78.0 years. The AX3 was the most popular device brand used, and it was commercially manufactured by Axivity. Common wearable device types included body-worn sensors, inertial measurement units, and smartwatches that used accelerometers and gyroscopes to measure the clinical features of PD. Most wearable device primary measures involved the measured gait, bradykinesia, and dyskinesia. The most common wearable device placements were the lumbar region, head, and wrist. Furthermore, 65% (13/20) of the studies used artificial intelligence or machine learning to support PD data analysis.
CONCLUSIONS
This study demonstrated that wearable devices could help provide a more detailed analysis of PD symptoms during the assessment phase and personalize treatment. Using machine learning, wearable devices could differentiate PD from other neurodegenerative diseases. The identified evidence gaps include the lack of analysis of wearable device cybersecurity and data management. The lack of cost-effectiveness analysis and large-scale participation in studies resulted in uncertainty regarding the feasibility of the widespread use of wearable devices. The uncertainty around the identified research gaps was further exacerbated by the lack of medical regulation of wearable devices for PD, particularly in the United Kingdom where regulations were changing due to the political landscape.
CLINICALTRIAL
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Costa EDC, Santinelli FB, Moretto GF, Figueiredo C, von Ah Morano AE, Barela JA, Barbieri FA. A multiple domain postural control assessment in people with Parkinson's disease: traditional, non-linear, and rambling and trembling trajectories analysis. Gait Posture 2022; 97:130-136. [PMID: 35932689 DOI: 10.1016/j.gaitpost.2022.07.250] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 05/06/2022] [Accepted: 07/24/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Postural impairment is one of the most debilitating symptoms in people with Parkinson's disease (PD), which show faster and more variable oscillation during quiet stance than neurologically healthy individuals. Despite the center of pressure parameters can characterize PD's body sway, they are limited to uncover underlying mechanisms of postural stability and instability. RESEARCH QUESTION Do a multiple domain analysis, including postural adaptability and rambling and trembling components, explain underlying postural stability and instability mechanisms in people with PD? METHOD Twenty-four individuals (12 people with PD and 12 neurologically healthy peers) performed three 60-s trials of upright quiet standing on a force platform. Traditional and non-linear parameters (Detrended Fluctuation Analysis- DFA and Multiscale Entropy- MSE) and rambling and trembling trajectories were calculated for anterior-posterior (AP) and medial-lateral (ML) directions. RESULTS PDG's postural control was worse compared to CG, displaying longer displacement, higher velocity, and RMS. Univariate analyses revealed largely longer displacement and RMS only for the AP direction and largely higher velocity for both AP and ML directions. Also, PD individuals showed lower AP complexity, higher AP and ML DFA, and increased AP and ML displacement, velocity, and RMS of rambling and trembling components compared to neurologically healthy individuals. SIGNIFICANCE Based upon these results, people with PD have a lower capacity to adapt posture and impaired both rambling and trembling components compared to neurologically healthy individuals. These findings provide new insights to explain the larger, faster, and more variable sway in people with PD.
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Affiliation(s)
- Elisa de Carvalho Costa
- São Paulo State University (Unesp), School of Sciences, Department of Physical Education, Human Movement Research Laboratory (MOVI-LAB), Bauru, SP, Brazil
| | - Felipe Balistieri Santinelli
- São Paulo State University (Unesp), School of Sciences, Department of Physical Education, Human Movement Research Laboratory (MOVI-LAB), Bauru, SP, Brazil; REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium
| | - Gabriel Felipe Moretto
- São Paulo State University (Unesp), School of Sciences, Department of Physical Education, Human Movement Research Laboratory (MOVI-LAB), Bauru, SP, Brazil
| | - Caique Figueiredo
- São Paulo State University (Unesp), School of Technology and Sciences, Department of Physical Education, Physical Education, Exercise and Immunometabolism Research Group, Presidente Prudente, SP, Brazil
| | - Ana Elisa von Ah Morano
- São Paulo State University (Unesp), School of Technology and Sciences, Department of Physical Education, Physical Education, Exercise and Immunometabolism Research Group, Presidente Prudente, SP, Brazil
| | - José Angelo Barela
- São Paulo State University (Unesp) - Institute of Biosciences, Department of Physical Education, Campus Rio Claro, SP, Brazil
| | - Fabio Augusto Barbieri
- São Paulo State University (Unesp), School of Sciences, Department of Physical Education, Human Movement Research Laboratory (MOVI-LAB), Bauru, SP, Brazil.
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Workman CD, Sosnoff JJ, Rudroff T. Sample entropy discriminates balance performance of older cannabis users from non-users. Clin Biomech (Bristol, Avon) 2022; 93:105593. [PMID: 35151108 PMCID: PMC8960352 DOI: 10.1016/j.clinbiomech.2022.105593] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 12/16/2021] [Accepted: 02/01/2022] [Indexed: 02/07/2023]
Abstract
BACKGROUND Maintaining an upright stance involves a complex interaction of sensory processing and motor outputs to adequately perform this fundamental motor skill. Aging and cannabis use independently disrupt balance performance, but our recent data did not find differences in static balance performance between older cannabis Users and older Non-Users using traditional linear measures (i.e., characteristics of the center of pressure sway). The purpose of this analysis was to determine whether an unbiased entropy measure (sample entropy) can differentiate postural control (standing posture) strategies between older cannabis Users and Non-Users when typical linear measures could not. METHODS Eight medical cannabis Users and eight age- and sex-matched controls completed static posturography testing in an eyes-open condition for 60 s. Linear measures included pathlength of the anterior-posterior and medio-lateral directions and an ellipse that encapsulates 95% of the 2D area explored. The nonlinear measure was the sample entropy of the center of pressure time-series in anterior-posterior and medio-lateral directions. Group comparisons were accomplished via pairwise testing and effect size calculations. FINDINGS The statistical testing revealed that sample entropy in the anterior-posterior direction was significantly larger in the Users (mean ± SD = 0.29 ± 0.08) compared to the Non-Users (0.19 ± 0.05; P = 0.01, d = 1.55). INTERPRETATION This finding indicates that the Users had a decreased regularity of their center of pressure signal in the anterior-posterior direction, which might reflect reduced balance adaptability and accompanies the increased fall risk observed in our recent report on these same subjects.
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Affiliation(s)
- Craig D. Workman
- Department of Health and Human Physiology, University of Iowa, Iowa City, IA 52242 USA,Corresponding author: Craig D. Workman, Department of Health and Human Physiology, N418 Field House, University of Iowa, Iowa City, IA 52242 USA,
| | - Jacob J. Sosnoff
- Department of Physical Therapy, Rehabilitation Science and Athletic Training, University of Kansas Medical Center, Kansas City, KS 66160 USA
| | - Thorsten Rudroff
- Department of Health and Human Physiology, University of Iowa, Iowa City, IA 52242 USA,Department of Neurology, University of Iowa Health Clinics, Iowa City, IA 52242 USA
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12
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Wilkins KB, Petrucci MN, Kehnemouyi Y, Velisar A, Han K, Orthlieb G, Trager MH, O’Day JJ, Aditham S, Bronte-Stewart H. Quantitative Digitography Measures Motor Symptoms and Disease Progression in Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2022; 12:1979-1990. [PMID: 35694934 PMCID: PMC9535590 DOI: 10.3233/jpd-223264] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 05/22/2022] [Indexed: 11/21/2022]
Abstract
BACKGROUND Assessment of motor signs in Parkinson's disease (PD) requires an in-person examination. However, 50% of people with PD do not have access to a neurologist. Wearable sensors can provide remote measures of some motor signs but require continuous monitoring for several days. A major unmet need is reliable metrics of all cardinal motor signs, including rigidity, from a simple short active task that can be performed remotely or in the clinic. OBJECTIVE Investigate whether thirty seconds of repetitive alternating finger tapping (RAFT) on a portable quantitative digitography (QDG) device, which measures amplitude and timing, produces reliable metrics of all cardinal motor signs in PD. METHODS Ninety-six individuals with PD and forty-two healthy controls performed a thirty-second QDG-RAFT task and clinical motor assessment. Eighteen individuals were followed longitudinally with repeated assessments for an average of three years and up to six years. RESULTS QDG-RAFT metrics showed differences between PD and controls and provided correlated metrics for total motor disability (MDS-UPDRS III) and for rigidity, bradykinesia, tremor, gait impairment, and freezing of gait (FOG). Additionally, QDG-RAFT tracked disease progression over several years off therapy and showed differences between akinetic-rigid and tremor-dominant phenotypes, as well as people with and without FOG. CONCLUSIONS QDG is a reliable technology, which could be used in the clinic or remotely. This could improve access to care, allow complex remote disease management based on data received in real time, and accurate monitoring of disease progression over time in PD. QDG-RAFT also provides the comprehensive motor metrics needed for therapeutic trials.
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Affiliation(s)
- Kevin B. Wilkins
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Matthew N. Petrucci
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Yasmine Kehnemouyi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Anca Velisar
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- The Smith-Kettlewell Eye Research Institute, San Francisco, CA, USA
| | - Katie Han
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Gerrit Orthlieb
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Megan H. Trager
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Columbia University College of Physicians and Surgeons, New York City, NY, USA
| | - Johanna J. O’Day
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Sudeep Aditham
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Helen Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA
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13
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Kempster PA, Perju-Dumbrava L. The Thermodynamic Consequences of Parkinson's Disease. Front Neurol 2021; 12:685314. [PMID: 34512508 PMCID: PMC8427692 DOI: 10.3389/fneur.2021.685314] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 08/04/2021] [Indexed: 12/31/2022] Open
Abstract
Several lines of evidence point to a pervasive disturbance of energy balance in Parkinson's disease (PD). Weight loss, common and multifactorial, is the most observable sign of this. Bradykinesia may be best understood as an underinvestment of energy in voluntary movement. This accords with rodent experiments that emphasise the importance of dopamine in allocating motor energy expenditure. Oxygen consumption studies in PD suggest that, when activities are standardised for work performed, these inappropriate energy thrift settings are actually wasteful. That the dopaminergic deficit of PD creates a problem with energy efficiency highlights the role played by the basal ganglia, and by dopamine, in thermodynamic governance. This involves more than balancing energy, since living things maintain their internal order by controlling transformations of energy, resisting probabilistic trends to more random states. This review will also look at recent research in PD on the analysis of entropy-an information theory metric of predictability in a message-in recordings from the basal ganglia. Close relationships between energy and information converge around the concept of entropy. This is especially relevant to the motor system, which regulates energy exchange with the outside world through its flow of information. The malignant syndrome in PD, a counterpart of neuroleptic malignant syndrome, demonstrates how much thermodynamic disruption can result from breakdown of motor signalling in an extreme hypodopaminergic state. The macroenergetic disturbances of PD are consistent with a unifying hypothesis of dopamine's neurotransmitter actions-to adapt energy expenditure to prevailing economic circumstances.
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Affiliation(s)
- Peter A. Kempster
- Neurosciences Department, Monash Medical Centre, Clayton, VIC, Australia
- Department of Medicine, School of Clinical Sciences, Monash University, Clayton, VIC, Australia
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14
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Liu Y, Lawton MA, Lo C, Bowring F, Klein JC, Querejeta-Coma A, Scotton S, Welch J, Razzaque J, Barber T, Ben-Shlomo Y, Hu MT. Longitudinal Changes in Parkinson's Disease Symptoms with and Without Rapid Eye Movement Sleep Behavior Disorder: The Oxford Discovery Cohort Study. Mov Disord 2021; 36:2821-2832. [PMID: 34448251 DOI: 10.1002/mds.28763] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 07/27/2021] [Accepted: 08/02/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Parkinson's disease (PD) comorbid with rapid eye movement sleep behavior disorder (RBD) may show more severe motor and nonmotor symptoms, suggesting a distinct PD subtype. OBJECTIVE The aim of this study was to investigate the impact of RBD on the longitudinal change of motor and nonmotor symptoms in patients with PD. METHODS Patients with early PD (diagnosed within 3.5 years) recruited from 2010 to 2019 were followed every 18 months in the Oxford Parkinson's Disease Centre Discovery cohort. At each visit, we used standard questionnaires and measurements to assess demographic features and motor and nonmotor symptoms (including RBD, daytime sleepiness, mood, autonomic symptoms, cognition, and olfaction). Data were analyzed with linear mixed effects and Cox regression models. Possible RBD (pRBD) was longitudinally determined according to RBD Screening Questionnaire scores. RESULTS A total of 923 patients were recruited (mean age: 67.1 ± 9.59 years; 35.9% female), and 788 had follow-up assessment(s) (mean: 4.8 ± 1.98 years, range: 1.3-8.3). Among them, 33.3% were identified as pRBD (PD + pRBD). Patients with PD + pRBD had more severe baseline symptoms and showed faster progression on Movement Disorder Society-Unified Parkinson's Disease Rating Scale parts I and III, Purdue Pegboard test, and Beck Depression Inventory scores. Moreover, PD + pRBD was associated with an increased level of risk for mild cognitive impairment (hazard ratio [HR] = 1.36, 95% confidence interval [CI]: 1.01-1.83), freezing of gait (HR = 1.42, 95% CI: 1.10-1.86), and frequent falling (HR = 1.62, 95% CI: 1.02-2.60). CONCLUSIONS Patients with PD + pRBD progress faster on motor, mood, and cognitive symptoms, confirming a more aggressive PD subtype that can be identified at baseline and has major clinical implications. © 2021 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Yaping Liu
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Michael A Lawton
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Christine Lo
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Department of Neurology, Royal Hallamshire Hospital, Sheffield, United Kingdom
| | - Francesca Bowring
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom
| | - Johannes C Klein
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Department of Neurology, John Radcliffe Hospital, Oxford, United Kingdom
| | - Agustin Querejeta-Coma
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Department of Neurology, John Radcliffe Hospital, Oxford, United Kingdom.,Department of Neurology, Infanta Elena University Hospital, Valdemoro, Spain.,Department of Neurology, Rey Juan Carlos University Hospital, Móstoles, Spain
| | - Sangeeta Scotton
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom
| | - Jessica Welch
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom
| | - Jamil Razzaque
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom
| | - Thomas Barber
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Department of Neurology, John Radcliffe Hospital, Oxford, United Kingdom
| | - Yoav Ben-Shlomo
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Michele T Hu
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Department of Neurology, John Radcliffe Hospital, Oxford, United Kingdom
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15
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Hansen C, Beckbauer M, Romijnders R, Warmerdam E, Welzel J, Geritz J, Emmert K, Maetzler W. Reliability of IMU-Derived Static Balance Parameters in Neurological Diseases. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18073644. [PMID: 33807432 PMCID: PMC8037984 DOI: 10.3390/ijerph18073644] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 03/25/2021] [Accepted: 03/26/2021] [Indexed: 01/03/2023]
Abstract
Static balance is a commonly used health measure in clinical practice. Usually, static balance parameters are assessed via force plates or, more recently, with inertial measurement units (IMUs). Multiple parameters have been developed over the years to compare patient groups and understand changes over time. However, the day-to-day variability of these parameters using IMUs has not yet been tested in a neurogeriatric cohort. The aim of the study was to examine day-to-day variability of static balance parameters of five experimental conditions in a cohort of neurogeriatric patients using data extracted from a lower back-worn IMU. A group of 41 neurogeriatric participants (age: 78 ± 5 years) underwent static balance assessment on two occasions 12-24 h apart. Participants performed a side-by-side stance, a semi-tandem stance, a tandem stance on hard ground with eyes open, and a semi-tandem assessment on a soft surface with eyes open and closed for 30 s each. The intra-class correlation coefficient (two-way random, average of the k raters' measurements, ICC2, k) and minimal detectable change at a 95% confidence level (MDC95%) were calculated for the sway area, velocity, acceleration, jerk, and frequency. Velocity, acceleration, and jerk were calculated in both anterior-posterior (AP) and medio-lateral (ML) directions. Nine to 41 participants could successfully perform the respective balance tasks. Considering all conditions, acceleration-related parameters in the AP and ML directions gave the highest ICC results. The MDC95% values for all parameters ranged from 39% to 220%, with frequency being the most consistent with values of 39-57%, followed by acceleration in the ML (43-55%) and AP direction (54-77%). The present results show moderate to poor ICC and MDC values for IMU-based static balance assessment in neurogeriatric patients. This suggests a limited reliability of these tasks and parameters, which should induce a careful selection of potential clinically relevant parameters.
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Affiliation(s)
- Clint Hansen
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
- Correspondence:
| | - Maximilian Beckbauer
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
| | - Robbin Romijnders
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
- Digital Signal Processing and System Theory, Institute of Electrical and Information Engineering, Kiel University, Kaiserstrasse 2, 24143 Kiel, Germany
| | - Elke Warmerdam
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
- Digital Signal Processing and System Theory, Institute of Electrical and Information Engineering, Kiel University, Kaiserstrasse 2, 24143 Kiel, Germany
| | - Julius Welzel
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
| | - Johanna Geritz
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
| | - Kirsten Emmert
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
| | - Walter Maetzler
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
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16
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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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17
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Nonlinear Measures to Evaluate Upright Postural Stability: A Systematic Review. ENTROPY 2020; 22:e22121357. [PMID: 33266239 PMCID: PMC7760950 DOI: 10.3390/e22121357] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 11/25/2020] [Accepted: 11/28/2020] [Indexed: 11/30/2022]
Abstract
Conventional biomechanical analyses of human movement have been generally derived from linear mathematics. While these methods can be useful in many situations, they fail to describe the behavior of the human body systems that are predominately nonlinear. For this reason, nonlinear analyses have become more prevalent in recent literature. These analytical techniques are typically investigated using concepts related to variability, stability, complexity, and adaptability. This review aims to investigate the application of nonlinear metrics to assess postural stability. A systematic review was conducted of papers published from 2009 to 2019. Databases searched were PubMed, Google Scholar, Science-Direct and EBSCO. The main inclusion consisted of: Sample entropy, fractal dimension, Lyapunov exponent used as nonlinear measures, and assessment of the variability of the center of pressure during standing using force plate. Following screening, 43 articles out of the initial 1100 were reviewed including 33 articles on sample entropy, 10 articles on fractal dimension, and 4 papers on the Lyapunov exponent. This systematic study shows the reductions in postural regularity related to aging and the disease or injures in the adaptive capabilities of the movement system and how the predictability changes with different task constraints.
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18
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Flood MW, O'Callaghan BPF, Diamond P, Liegey J, Hughes G, Lowery MM. Quantitative clinical assessment of motor function during and following LSVT-BIG® therapy. J Neuroeng Rehabil 2020; 17:92. [PMID: 32660495 PMCID: PMC7359464 DOI: 10.1186/s12984-020-00729-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 07/08/2020] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND LSVT-BIG® is an intensively delivered, amplitude-oriented exercise therapy reported to improve mobility in individuals with Parkinson's disease (PD). However, questions remain surrounding the efficacy of LSVT-BIG® when compared with similar exercise therapies. Instrumented clinical tests using body-worn sensors can provide a means to objectively monitor patient progression with therapy by quantifying features of motor function, yet research exploring the feasibility of this approach has been limited to date. The aim of this study was to use accelerometer-instrumented clinical tests to quantify features of gait, balance and fine motor control in individuals with PD, in order to examine motor function during and following LSVT-BIG® therapy. METHODS Twelve individuals with PD undergoing LSVT-BIG® therapy, eight non-exercising PD controls and 14 healthy controls were recruited to participate in the study. Functional mobility was examined using features derived from accelerometry recorded during five instrumented clinical tests: 10 m walk, Timed-Up-and-Go, Sit-to-Stand, quiet stance, and finger tapping. PD subjects undergoing therapy were assessed before, each week during, and up to 13 weeks following LSVT-BIG®. RESULTS Accelerometry data captured significant improvements in 10 m walk and Timed-Up-and-Go times with LSVT-BIG® (p < 0.001), accompanied by increased stride length. Temporal features of the gait cycle were significantly lower following therapy, though no change was observed with measures of asymmetry or stride variance. The total number of Sit-to-Stand transitions significantly increased with LSVT-BIG® (p < 0.001), corresponding to a significant reduction of time spent in each phase of the Sit-to-Stand cycle. No change in measures related to postural or fine motor control was observed with LSVT-BIG®. PD subjects undergoing LSVT-BIG® showed significant improvements in 10 m walk (p < 0.001) and Timed-Up-and-Go times (p = 0.004) over a four-week period when compared to non-exercising PD controls, who showed no week-to-week improvement in any task examined. CONCLUSIONS This study demonstrates the potential for wearable sensors to objectively quantify changes in motor function in response to therapeutic exercise interventions in PD. The observed improvements in accelerometer-derived features provide support for instrumenting gait and sit-to-stand tasks, and demonstrate a rescaling of the speed-amplitude relationship during gait in PD following LSVT-BIG®.
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Affiliation(s)
- Matthew W Flood
- Neuromuscular Systems Lab, School of Electrical & Electronic Engineering, University College Dublin, Belfield, Dublin 4, Ireland.
- Insight Centre for Data Analytics, O'Brien Centre for Science, University College Dublin, Belfield, Dublin 4, Ireland.
| | - Ben P F O'Callaghan
- Neuromuscular Systems Lab, School of Electrical & Electronic Engineering, University College Dublin, Belfield, Dublin 4, Ireland
| | - Paul Diamond
- Neuromuscular Systems Lab, School of Electrical & Electronic Engineering, University College Dublin, Belfield, Dublin 4, Ireland
- Occupational Therapy, Day Hospital, Royal Hospital Donnybrook, Bloomfield Avenue, Dublin 4, Ireland
| | - Jérémy Liegey
- Neuromuscular Systems Lab, School of Electrical & Electronic Engineering, University College Dublin, Belfield, Dublin 4, Ireland
| | - Graham Hughes
- Department of Geriatric Medicine, St. Vincent's University Hospital, Elm Park, Dublin 4, Ireland
| | - Madeleine M Lowery
- Neuromuscular Systems Lab, School of Electrical & Electronic Engineering, University College Dublin, Belfield, Dublin 4, Ireland
- Insight Centre for Data Analytics, O'Brien Centre for Science, University College Dublin, Belfield, Dublin 4, Ireland
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Coates L, Shi J, Rochester L, Del Din S, Pantall A. Entropy of Real-World Gait in Parkinson's Disease Determined from Wearable Sensors as a Digital Marker of Altered Ambulatory Behavior. SENSORS 2020; 20:s20092631. [PMID: 32380692 PMCID: PMC7249239 DOI: 10.3390/s20092631] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 04/29/2020] [Accepted: 05/02/2020] [Indexed: 02/07/2023]
Abstract
Parkinson’s disease (PD) is a common age-related neurodegenerative disease. Gait impairment is frequent in the later stages of PD contributing to reduced mobility and quality of life. Digital biomarkers such as gait velocity and step length are predictors of motor and cognitive decline in PD. Additional gait parameters may describe different aspects of gait and motor control in PD. Sample entropy (SampEnt), a measure of signal predictability, is a nonlinear approach that quantifies regularity of a signal. This study investigated SampEnt as a potential biomarker for PD and disease duration. Real-world gait data over a seven-day period were collected using an accelerometer (Axivity AX3, York, UK) placed on the low back and gait metrics extracted. SampEnt was determined for the stride time, with vector length and threshold parameters optimized. People with PD had higher stride time SampEnt compared to older adults, indicating reduced gait regularity. The range of SampEnt increased over 36 months for the PD group, although the mean value did not change. SampEnt was associated with dopaminergic medication dose but not with clinical motor scores. In conclusion, this pilot study indicates that SampEnt from real-world data may be a useful parameter reflecting clinical status although further research is needed involving larger populations.
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Affiliation(s)
- Lucy Coates
- School of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne NE1 7RU, UK; (L.C.); (J.S.)
| | - Jian Shi
- School of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne NE1 7RU, UK; (L.C.); (J.S.)
| | - Lynn Rochester
- Translational and Clinical Research Unit, Clinical Ageing Research Unit, Newcastle University, Newcastle upon Tyne NE4 5PL, UK; (L.R.); (S.D.D.)
- Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE7 7DN, UK
| | - Silvia Del Din
- Translational and Clinical Research Unit, Clinical Ageing Research Unit, Newcastle University, Newcastle upon Tyne NE4 5PL, UK; (L.R.); (S.D.D.)
| | - Annette Pantall
- Translational and Clinical Research Unit, Clinical Ageing Research Unit, Newcastle University, Newcastle upon Tyne NE4 5PL, UK; (L.R.); (S.D.D.)
- Correspondence:
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20
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Morris ME, Dreher T. Gait and Posture Virtual Special Issue "Gait Complexity in Parkinson's Disease". Gait Posture 2020; 78:89-90. [PMID: 30639119 DOI: 10.1016/j.gaitpost.2018.11.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Affiliation(s)
| | - Thomas Dreher
- Pediatric Orthopaedics and Traumatology, University Children's Hospital Zurich, Steinwiesstrasse 75, 8032 Zurich, Switzerland.
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21
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Reliability, Validity and Utility of Inertial Sensor Systems for Postural Control Assessment in Sport Science and Medicine Applications: A Systematic Review. Sports Med 2020; 49:783-818. [PMID: 30903440 DOI: 10.1007/s40279-019-01095-9] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
BACKGROUND Recent advances in mobile sensing and computing technology have provided a means to objectively and unobtrusively quantify postural control. This has resulted in the rapid development and evaluation of a series of wearable inertial sensor-based assessments. However, the validity, reliability and clinical utility of such systems is not fully understood. OBJECTIVES This systematic review aims to synthesise and evaluate studies that have investigated the ability of wearable inertial sensor systems to validly and reliably quantify postural control performance in sports science and medicine applications. METHODS A systematic search strategy utilising the PRISMA guidelines was employed to identify eligible articles through ScienceDirect, Embase and PubMed databases. In total, 47 articles met the inclusion criteria and were evaluated and qualitatively synthesised under two main headings: measurement validity and measurement reliability. Furthermore, studies that investigated the utility of these systems in clinical populations were summarised and discussed. RESULTS After duplicate removal, 4374 articles were identified with the search strategy, with 47 papers included in the final review. In total, 28 studies investigated validity in healthy populations, and 15 studies investigated validity in clinical populations; 13 investigated the measurement reliability of these sensor-based systems. CONCLUSIONS The application of wearable inertial sensors for sports science and medicine postural control applications is an evolving field. To date, research has primarily focused on evaluating the validity and reliability of a heterogeneous set of assessment protocols, in a laboratory environment. While researchers have begun to investigate their utility in clinical use cases such as concussion and musculoskeletal injury, most studies have leveraged small sample sizes, are of low quality and use a variety of descriptive variables, assessment protocols and sensor-mounting locations. Future research should evaluate the clinical utility of these systems in large high-quality prospective cohort studies to establish the role they may play in injury risk identification, diagnosis and management. This systematic review was registered with the International Prospective Register of Systematic Reviews on 10 August 2018 (PROSPERO registration: CRD42018106363): https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=106363 .
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Buckley C, Alcock L, McArdle R, Rehman RZU, Del Din S, Mazzà C, Yarnall AJ, Rochester L. The Role of Movement Analysis in Diagnosing and Monitoring Neurodegenerative Conditions: Insights from Gait and Postural Control. Brain Sci 2019; 9:E34. [PMID: 30736374 PMCID: PMC6406749 DOI: 10.3390/brainsci9020034] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Accepted: 01/31/2019] [Indexed: 12/22/2022] Open
Abstract
Quantifying gait and postural control adds valuable information that aids in understanding neurological conditions where motor symptoms predominate and cause considerable functional impairment. Disease-specific clinical scales exist; however, they are often susceptible to subjectivity, and can lack sensitivity when identifying subtle gait and postural impairments in prodromal cohorts and longitudinally to document disease progression. Numerous devices are available to objectively quantify a range of measurement outcomes pertaining to gait and postural control; however, efforts are required to standardise and harmonise approaches that are specific to the neurological condition and clinical assessment. Tools are urgently needed that address a number of unmet needs in neurological practice. Namely, these include timely and accurate diagnosis; disease stratification; risk prediction; tracking disease progression; and decision making for intervention optimisation and maximising therapeutic response (such as medication selection, disease staging, and targeted support). Using some recent examples of research across a range of relevant neurological conditions-including Parkinson's disease, ataxia, and dementia-we will illustrate evidence that supports progress against these unmet clinical needs. We summarise the novel 'big data' approaches that utilise data mining and machine learning techniques to improve disease classification and risk prediction, and conclude with recommendations for future direction.
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Affiliation(s)
- Christopher Buckley
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
| | - Lisa Alcock
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
| | - Ríona McArdle
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
| | - Rana Zia Ur Rehman
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
| | - Silvia Del Din
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
| | - Claudia Mazzà
- Department of Mechanical Engineering, Sheffield University, Sheffield S1 3JD, UK.
| | - Alison J Yarnall
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
- The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne NE7 7DN, UK.
| | - Lynn Rochester
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
- The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne NE7 7DN, UK.
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Pantall A, Suresparan P, Kapa L, Morris R, Yarnall A, Del Din S, Rochester L. Postural Dynamics Are Associated With Cognitive Decline in Parkinson's Disease. Front Neurol 2018; 9:1044. [PMID: 30568629 PMCID: PMC6290334 DOI: 10.3389/fneur.2018.01044] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2018] [Accepted: 11/19/2018] [Indexed: 11/25/2022] Open
Abstract
Early features of Parkinson's disease (PD) include both motor and cognitive changes, suggesting shared common pathways. A common motor dysfunction is postural instability, a known predictor of falls, which have a major impact on quality of life. Understanding mechanisms of postural dynamics in PD and specifically how they relate to cognitive changes is essential for developing effective interventions. The aims of this study were to examine the changes that occur in postural metrics over time and explore the relationship between postural and cognitive dysfunction. The study group consisted of 35 people (66 ± 8years, 12 female, UPDRS III: 22.5 ± 9.6) diagnosed with PD who were recruited as part of the Incidence of Cognitive Impairment in Cohorts with Longitudinal Evaluation—PD Gait (ICICLE-GAIT) study. Postural and cognitive assessments were performed at 18, 36, and 54 months after enrolment. Participants stood still for 120 s, eyes open and arms by their side. Postural dynamics were measured using metrics derived from a single tri-axial accelerometer (Axivity AX3, York, UK) on the lower back. Accelerometry metrics included jerk (derivative of acceleration), root mean square, frequency, and ellipsis (acceleration area). Cognition was evaluated by neuropsychological tests including the Montreal Cognitive Assessment (MoCA) and digit span. There was a significant decrease in accelerometry parameters, greater in the anteroposterior direction, and a decline in cognitive function over time. Accelerometry metrics were positively correlated with lower cognitive function and increased geriatric depression score and negatively associated with a qualitative measure of balance confidence. In conclusion, people with PD showed reduced postural dynamics that may represent a postural safety strategy. Associations with cognitive function and depression, both symptoms that may pre-empt motor symptoms, suggest shared neural pathways. Further studies, involving neuroimaging, may determine how these postural parameters relate to underlying neural and clinical correlates.
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Affiliation(s)
- Annette Pantall
- Clinical Ageing Research Unit, Institute of Neuroscience, Newcastle University Institute of Ageing, Newcastle upon Tyne, United Kingdom
| | - Piriya Suresparan
- Clinical Ageing Research Unit, Institute of Neuroscience, Newcastle University Institute of Ageing, Newcastle upon Tyne, United Kingdom
| | - Leanne Kapa
- Clinical Ageing Research Unit, Institute of Neuroscience, Newcastle University Institute of Ageing, Newcastle upon Tyne, United Kingdom
| | - Rosie Morris
- Clinical Ageing Research Unit, Institute of Neuroscience, Newcastle University Institute of Ageing, Newcastle upon Tyne, United Kingdom.,Department of Neurology, Oregon Health and Science University, Portland, OR, United States
| | - Alison Yarnall
- The Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, United Kingdom
| | - Silvia Del Din
- Clinical Ageing Research Unit, Institute of Neuroscience, Newcastle University Institute of Ageing, Newcastle upon Tyne, United Kingdom
| | - Lynn Rochester
- Clinical Ageing Research Unit, Institute of Neuroscience, Newcastle University Institute of Ageing, Newcastle upon Tyne, United Kingdom.,The Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, United Kingdom
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