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Burtscher J, Moraud EM, Malatesta D, Millet GP, Bally JF, Patoz A. Exercise and gait/movement analyses in treatment and diagnosis of Parkinson's Disease. Ageing Res Rev 2024; 93:102147. [PMID: 38036102 DOI: 10.1016/j.arr.2023.102147] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 11/23/2023] [Accepted: 11/23/2023] [Indexed: 12/02/2023]
Abstract
Cardinal motor symptoms in Parkinson's disease (PD) include bradykinesia, rest tremor and/or rigidity. This symptomatology can additionally encompass abnormal gait, balance and postural patterns at advanced stages of the disease. Besides pharmacological and surgical therapies, physical exercise represents an important strategy for the management of these advanced impairments. Traditionally, diagnosis and classification of such abnormalities have relied on partially subjective evaluations performed by neurologists during short and temporally scattered hospital appointments. Emerging sports medical methods, including wearable sensor-based movement assessment and computational-statistical analysis, are paving the way for more objective and systematic diagnoses in everyday life conditions. These approaches hold promise to facilitate customizing clinical trials to specific PD groups, as well as personalizing neuromodulation therapies and exercise prescriptions for each individual, remotely and regularly, according to disease progression or specific motor symptoms. We aim to summarize exercise benefits for PD with a specific emphasis on gait and balance deficits, and to provide an overview of recent advances in movement analysis approaches, notably from the sports science community, with value for diagnosis and prognosis. Although such techniques are becoming increasingly available, their standardization and optimization for clinical purposes is critically missing, especially in their translation to complex neurodegenerative disorders such as PD. We highlight the importance of integrating state-of-the-art gait and movement analysis approaches, in combination with other motor, electrophysiological or neural biomarkers, to improve the understanding of the diversity of PD phenotypes, their response to therapies and the dynamics of their disease progression.
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Affiliation(s)
- Johannes Burtscher
- Institute of Sport Sciences, University of Lausanne, Lausanne, Switzerland.
| | - Eduardo Martin Moraud
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Defitech Centre for Interventional Neurotherapies (NeuroRestore), UNIL-CHUV and Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Davide Malatesta
- Institute of Sport Sciences, University of Lausanne, Lausanne, Switzerland
| | - Grégoire P Millet
- Institute of Sport Sciences, University of Lausanne, Lausanne, Switzerland
| | - Julien F Bally
- Service of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Aurélien Patoz
- Institute of Sport Sciences, University of Lausanne, Lausanne, Switzerland; Research and Development Department, Volodalen Swiss Sport Lab, Aigle, Switzerland
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Weber KS, Godkin FE, Cornish BF, McIlroy WE, Van Ooteghem K. Wrist Accelerometer Estimates of Physical Activity Intensity During Walking in Older Adults and People Living With Complex Health Conditions: Retrospective Observational Data Analysis Study. JMIR Form Res 2023; 7:e41685. [PMID: 36920452 PMCID: PMC10131658 DOI: 10.2196/41685] [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: 08/04/2022] [Revised: 01/10/2023] [Accepted: 01/10/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND Accurate measurement of daily physical activity (PA) is important as PA is linked to health outcomes in older adults and people living with complex health conditions. Wrist-worn accelerometers are widely used to estimate PA intensity, including walking, which composes much of daily PA. However, there is concern that wrist-derived PA data in these cohorts is unreliable due to slow gait speed, mobility aid use, disease-related symptoms that impact arm movement, and transient activities of daily living. Despite the potential for error in wrist-derived PA intensity estimates, their use has become ubiquitous in research and clinical application. OBJECTIVE The goals of this work were to (1) determine the accuracy of wrist-based estimates of PA intensity during known walking periods in older adults and people living with cerebrovascular disease (CVD) or neurodegenerative disease (NDD) and (2) explore factors that influence wrist-derived intensity estimates. METHODS A total of 35 older adults (n=23 with CVD or NDD) wore an accelerometer on the dominant wrist and ankle for 7 to 10 days of continuous monitoring. Stepping was detected using the ankle accelerometer. Analyses were restricted to gait bouts ≥60 seconds long with a cadence ≥80 steps per minute (LONG walks) to identify periods of purposeful, continuous walking likely to reflect moderate-intensity activity. Wrist accelerometer data were analyzed within LONG walks using 15-second epochs, and published intensity thresholds were applied to classify epochs as sedentary, light, or moderate-to-vigorous physical activity (MVPA). Participants were stratified into quartiles based on the percent of walking epochs classified as sedentary, and the data were examined for differences in behavioral or demographic traits between the top and bottom quartiles. A case series was performed to illustrate factors and behaviors that can affect wrist-derived intensity estimates during walking. RESULTS Participants averaged 107.7 (SD 55.8) LONG walks with a median cadence of 107.3 (SD 10.8) steps per minute. Across participants, wrist-derived intensity classification was 22.9% (SD 15.8) sedentary, 27.7% (SD 14.6) light, and 49.3% (SD 25.5) MVPA during LONG walks. All participants measured a statistically lower proportion of wrist-derived activity during LONG walks than expected (all P<.001), and 80% (n=28) of participants had at least 20 minutes of LONG walking time misclassified as sedentary based on wrist-derived intensity estimates. Participants in the highest quartile of wrist-derived sedentary classification during LONG walks were significantly older (t16=4.24, P<.001) and had more variable wrist movement (t16=2.13, P=.049) compared to those in the lowest quartile. CONCLUSIONS The current best practice wrist accelerometer method is prone to misclassifying activity intensity during walking in older adults and people living with complex health conditions. A multidevice approach may be warranted to advance methods for accurately assessing PA in these groups.
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Affiliation(s)
- Kyle S Weber
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - F Elizabeth Godkin
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Benjamin F Cornish
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - William E McIlroy
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Karen Van Ooteghem
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
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Van Ooteghem K, Godkin FE, Thai V, Beyer KB, Cornish BF, Weber KS, Bernstein H, Kheiri SO, Swartz RH, Tan B, McIlroy WE, Roberts AC. User-centered design of feedback regarding health-related behaviors derived from wearables: An approach targeting older adults and persons living with neurodegenerative disease. Digit Health 2023; 9:20552076231179031. [PMID: 37312943 PMCID: PMC10259132 DOI: 10.1177/20552076231179031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 05/12/2023] [Indexed: 06/15/2023] Open
Abstract
Objective There has been tremendous growth in wearable technologies for health monitoring but limited efforts to optimize methods for sharing wearables-derived information with older adults and clinical cohorts. This study aimed to co-develop, design and evaluate a personalized approach for information-sharing regarding daily health-related behaviors captured with wearables. Methods A participatory research approach was adopted with: (a) iterative stakeholder, and evidence-led development of feedback reporting; and (b) evaluation in a sample of older adults (n = 15) and persons living with neurodegenerative disease (NDD) (n = 25). Stakeholders included persons with lived experience, healthcare providers, health charity representatives and individuals involved in aging/NDD research. Feedback report information was custom-derived from two limb-mounted inertial measurement units and a mobile electrocardiography device worn by participants for 7-10 days. Mixed methods were used to evaluate reporting 2 weeks following delivery. Data were summarized using descriptive statistics for the group and stratified by cohort and cognitive status. Results Participants (n = 40) were 60% female (median 72 (60-87) years). A total of 82.5% found the report easy to read or understand, 80% reported the right amount of information was shared, 90% found the information helpful, 92% shared the information with a family member or friend and 57.5% made a behavior change. Differences emerged in sub-group comparisons. A range of participant profiles existed in terms of interest, uptake and utility. Conclusions The reporting approach was generally well-received with perceived value that translated into enhanced self-awareness and self-management of daily health-related behaviors. Future work should examine potential for scale, and the capacity for wearables-derived feedback to influence longer-term behavior change.
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Affiliation(s)
- Karen Van Ooteghem
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - F Elizabeth Godkin
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Vanessa Thai
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Kit B Beyer
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Benjamin F Cornish
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Kyle S Weber
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Hannah Bernstein
- Department of Nanotechnology Engineering, University of Waterloo, Waterloo, ON, Canada
| | - Soha O Kheiri
- Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada
| | - Richard H Swartz
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Brian Tan
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - William E McIlroy
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Angela C Roberts
- School of Communication Sciences and Disorders, Western University, London, ON, Canada
- Department of Computer Science, Western University, London, ON, Canada
- Canadian Centre for Activity and Aging, Western University, London, ON, Canada
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Handlery R, Stewart JC, Pellegrini C, Monroe C, Hainline G, Flach A, Handlery K, Fritz S. Physical Activity in De Novo Parkinson Disease: Daily Step Recommendation and Effects of Treadmill Exercise on Physical Activity. Phys Ther 2021; 101:6317708. [PMID: 34244805 DOI: 10.1093/ptj/pzab174] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 02/19/2021] [Accepted: 05/11/2021] [Indexed: 11/14/2022]
Abstract
OBJECTIVE People with Parkinson disease (PD) have low physical activity (PA) levels and are at risk for cardiovascular events. The 3 purposes of this study were to determine a step threshold that corresponds to meeting aerobic PA guidelines, determine effects of treadmill exercise on PA, and quantify the relationship between changes in daily steps and fitness. METHODS This was a secondary analysis of the Study in Parkinson's Disease of Exercise trial, which randomized participants to high-intensity treadmill exercise, moderate-intensity treadmill exercise, or usual care for 6 months. Daily steps and moderate- to vigorous-intensity PA (MVPA) were assessed at baseline and once each month using an activity monitor. Fitness was assessed via graded exercise test at baseline and at 6 months. A step threshold that corresponds to meeting PA guidelines was determined by receiver operating characteristic curves. The effect of treadmill exercise on PA was examined in those below the step threshold (ie, the least active participants). Pearson r correlations determined the relationship between daily steps and fitness. RESULTS Individuals with de novo PD (n = 110) were included. Those with ≥4200 steps were 23 times more likely (95% CI = 7.72 to 68) to meet PA guidelines than those with <4200 steps. For those with <4200 steps at baseline (n = 33), only those in the high-intensity exercise group increased daily steps (median of differences = 1250 steps, z = -2.35) and MVPA (median of differences = 12.5 minutes, z = -2.67) at 6 months. For those with <4200 steps, changes in daily steps were not associated with changes in fitness (r = .183). CONCLUSION In people with PD and <4200 daily steps at baseline, high-intensity treadmill exercise increased daily steps and MVPA, but these changes were not associated with changes in fitness. IMPACT People with PD should be encouraged to take ≥4200 daily steps to meet PA guidelines through walking.
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Affiliation(s)
- Reed Handlery
- School of Physical Therapy, Arkansas Colleges of Health Education, Fort Smith, Arkansas, USA
| | - Jill Campbell Stewart
- Department of Exercise Science, Physical Therapy Program, University of South Carolina, Columbia, South Carolina, USA
| | - Christine Pellegrini
- Department of Exercise Science, University of South Carolina, Columbia, South Carolina, USA
| | - Courtney Monroe
- Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, South Carolina, USA
| | - Garrett Hainline
- Department of Exercise Science, University of South Carolina, Columbia, South Carolina, USA
| | - Alicia Flach
- Department of Exercise Science, Physical Therapy Program, University of South Carolina, Columbia, South Carolina, USA
| | - Kaci Handlery
- Department of Exercise Science, Physical Therapy Program, University of South Carolina, Columbia, South Carolina, USA
| | - Stacy Fritz
- Department of Exercise Science, Physical Therapy Program, University of South Carolina, Columbia, South Carolina, USA
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