Quantifying physical activity in early Parkinson disease using a commercial activity monitor

Pradhan, Sarita; Kelly, Valerie E.

doi:10.1016/j.parkreldis.2019.08.001

Cited by 50 publications

(51 citation statements)

References 27 publications

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“…This is suggested by earlier PD studies using only sEMG and triaxial accelerometry worn on the affected limbs in unscripted, but closely monitored patient activity to assess tremor and dyskinesia [ 4 ]. Even in the form of a simple sports watch, a reduction in the activity and intensity of activity has been demonstrated in PD patients compared to healthy active subjects [ 5 ]. The Parkinson@ Home Study demonstrated long-term (6–12 weeks) compliance in the use of a smart watch coupled with a smartphone intended to record and monitor activity and disease-related events [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Detecting Parkinson’s Disease from Wrist-Worn Accelerometry in the U.K. Biobank

Williamson

Telfer

Mullany

et al. 2021

Sensors

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Parkinson’s disease (PD) is a chronic movement disorder that produces a variety of characteristic movement abnormalities. The ubiquity of wrist-worn accelerometry suggests a possible sensor modality for early detection of PD symptoms and subsequent tracking of PD symptom severity. As an initial proof of concept for this technological approach, we analyzed the U.K. Biobank data set, consisting of one week of wrist-worn accelerometry from a population with a PD primary diagnosis and an age-matched healthy control population. Measures of movement dispersion were extracted from automatically segmented gait data, and measures of movement dimensionality were extracted from automatically segmented low-movement data. Using machine learning classifiers applied to one week of data, PD was detected with an area under the curve (AUC) of 0.69 on gait data, AUC = 0.84 on low-movement data, and AUC = 0.85 on a fusion of both activities. It was also found that classification accuracy steadily improved across the one-week data collection, suggesting that higher accuracy could be achievable from a longer data collection. These results suggest the viability of using a low-cost and easy-to-use activity sensor for detecting movement abnormalities due to PD and motivate further research on early PD detection and tracking of PD symptom severity.

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Section: Introductionmentioning

confidence: 99%

Detecting Parkinson’s Disease from Wrist-Worn Accelerometry in the U.K. Biobank

Williamson

Telfer

Mullany

et al. 2021

Sensors

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“…r r e c t e d A u t h o r P r o o f S.D. Din et al / Real-World Monitoring of PD with Wearables 9Commercial devices are widely utilized in PD for quantifying physical activity[40][41][42]. Although people with PD have lower levels of physical activity compared to older adults (discriminant validity), con-FUTURE PERSPECTIVES: HOW CAN WE MOVE FORWARD?…”

mentioning

confidence: 99%

Body-Worn Sensors for Remote Monitoring of Parkinson’s Disease Motor Symptoms: Vision, State of the Art, and Challenges Ahead

Din

Kirk

Yarnall

et al. 2021

JPD

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The increasing prevalence of neurodegenerative conditions such as Parkinson’s disease (PD) and related mobility issues places a serious burden on healthcare systems. The COVID-19 pandemic has reinforced the urgent need for better tools to manage chronic conditions remotely, as regular access to clinics may be problematic. Digital health technology in the form of remote monitoring with body-worn sensors offers significant opportunities for transforming research and revolutionizing the clinical management of PD. Significant efforts are being invested in the development and validation of digital outcomes to support diagnosis and track motor and mobility impairments “off-line”. Imagine being able to remotely assess your patient, understand how well they are functioning, evaluate the impact of any recent medication/intervention, and identify the need for urgent follow-up because things are changing? This could offer new pragmatic solutions for personalized care and clinical research. So the question remains: how close are we to achieving this? Here, we describe the state-of-the-art based on representative papers published between 2017 and 2020. We focus on remote (i.e., real-world, daily-living) monitoring of PD using body-worn sensors (e.g., accelerometers, inertial measurement units) for assessing motor symptoms and their complications. Despite the tremendous potential, existing challenges exist (e.g., validity, regulatory) that are preventing the widespread clinical adoption of body-worn sensors as a digital outcome. We propose a roadmap with clear recommendations for addressing these challenges and future directions to bring us closer to the implementation and widespread adoption of this important way of improving the clinical care, evaluation, and monitoring of PD.

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“…PD patients are likely to experience nausea, dyspepsia, constipation, medication side effects, dysphagia, anorexia and depressive symptoms that cause reduced energy intake [14]. Thirdly, it has also been found that PD patients have lower levels of physical activity (in terms of amount and intensity) compared to healthy older adults [15–17].…”

Section: Discussionmentioning

confidence: 99%

Clinical correlates of sarcopenia and falls in Parkinson’s disease

Lima

Almeida

Bonfadini

et al. 2019

Preprint

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35 Background: Sarcopenia is a complex and multifactorial geriatric condition seen in 36 several chronic degenerative diseases. This study aimed to screen for sarcopenia and fall 37 risk in a sample of Parkinson's disease (PD) patients and to investigate demographic 38 and clinical factors associated.39 Methods: This is a cross-sectional study. We evaluated 218 PD patients at the 40 Movement Disorders Clinic in Fortaleza, Brazil, and collected clinical data including 41 experiencing falls in the six months prior to their medical visit. Probable sarcopenia 42 diagnosis was confirmed by using a sarcopenia screening tool (SARC-F questionnaire) 43 and the presence of low muscle strength.44 Results: One hundred and twenty-one patients (55.5%) were screened positive for 45 sarcopenia using the SARC-F and 103 (47.4%) met the criteria for probable sarcopenia.46 Disease duration, modified Hoehn and Yahr stage, Schwab and England Activities of 47 Daily Living Scale score, levodopa equivalent dose, probable sarcopenia and positive 48 SARC-F screening were all associated with experiencing falls in the prior six months.49 Disease duration, lower quality of life and female gender were independently associated 50 with sarcopenia. Experiencing falls in the prior six months was significantly more 51 frequent among patients screened positive in the SARC-F compared to those screened 52 negative. 53 Conclusions: Sarcopenia and PD share common pathways and may affect each other's 54 prognosis and patients' quality of life. Since sarcopenia is associated with lower quality 55 of life and increased risk of falls, active case finding, diagnosis and proper management 56 of sarcopenia in PD patients is essential. 57 58 Key words: Parkinson's disease; Sarcopenia; Falls 3 59 60 INTRODUCTION 61Sarcopenia is a complex and multifactorial geriatric condition seen in several 62 chronic degenerative diseases. It stems from abnormally reduced muscle mass quality 63 and quantity and is associated to several negative outcomes such as falls, disability, 64 poor quality of life, institutionalization, hospitalization, and death [1]. The prevalence of 65 sarcopenia has increased and it has become a serious global public health concern [2].66 Patients with Parkinson's disease (PD) show higher prevalence of sarcopenia and higher 67 frequency of falls compared to non-PD patients [3,4]. Despite its importance, few 68 studies have assessed the prevalence and characteristics of sarcopenia in this population. 69Falls are a serious concern in PD with an annual incidence of 60% among PD 70 patients. The risk of falls is greater in this population compared to healthy individuals 71 and those with other neurological diseases with high risk of falls such polyneuropathy, 72 spinal disorders and multiple sclerosis [5]. It is very important to early detect sarcopenia 73 and fall risk in PD patients because they can benefit from simple interventions such as 74 high-protein diet and resistance exercise training [6]. 75 To the best of our knowledge, there are no large st...

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Quantifying physical activity in early Parkinson disease using a commercial activity monitor

Cited by 50 publications

References 27 publications

Detecting Parkinson’s Disease from Wrist-Worn Accelerometry in the U.K. Biobank

Detecting Parkinson’s Disease from Wrist-Worn Accelerometry in the U.K. Biobank

Body-Worn Sensors for Remote Monitoring of Parkinson’s Disease Motor Symptoms: Vision, State of the Art, and Challenges Ahead

Clinical correlates of sarcopenia and falls in Parkinson’s disease

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