Motion sensors in multiple sclerosis: Narrative review and update of applications

Sasaki, Jeffer Eidi; Sandroff, Brian M.; Bamman, Marcas M.; Motl, Robert W.

doi:10.1080/17434440.2017.1386550

Cited by 40 publications

(32 citation statements)

References 83 publications

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“…6 Another study examined this relationship in persons with MS who had varying levels of ambulatory disability during over-ground walking at comfortable, slower, and faster speeds, and reported different step-rate thresholds for MVPA based on disability and height. 7 Overall, those step-rate thresholds have been quite valuable for quantifying and prescribing physical activity in multiple sclerosis, 8 and there might be similar value in PD.…”

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confidence: 99%

Step‐rate threshold for physical activity intensity in Parkinson’s disease

et al. 2020

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Objectives: To examine the relationship between step-rate and energy expenditure during treadmill walking in persons with PD and then further develop a step-rate cutpoint for moderate-to-vigorous physical activity (MVPA) for persons with PD. Materials and Methods: The sample consisted of 30 persons with mild-to-moderate PD and 30 controls matched by age and sex. Participants performed a 6-minute bout of over-ground walking at comfortable speed, and then completed three, 6-minute bouts of treadmill walking at 13.4 m/min slower, comfortable, and 13.4 m/min faster than comfortable speeds. The three treadmill speeds were based on the initial overground walking speed. The total number of steps per treadmill walking bout was recorded using a hand-tally counter, and energy expenditure was measured using a portable, indirect spirometry system. Results: The results indicated a strong association between step-rate and energy expenditure for persons with PD (R 2 = .92) and controls (R 2 = .92). The analyses further indicated a steeper slope of the association for persons with PD compared with controls (t(58) = −1.87, P < .05), resulting in a lower step-rate threshold (t(58) = 2.19, P < .05) for persons with PD (~80 steps•per minutes) than controls (~93 steps•per minutes). Conclusion: Collectively, these results support the application of this disease-specific step-rate threshold for MVPA among persons with PD. This has important implications for physical activity promotion, prescription, and monitoring using accelerometers and pedometers for persons with PD to manage health and symptoms of PD.

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confidence: 99%

Step‐rate threshold for physical activity intensity in Parkinson’s disease

et al. 2020

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“…It can be used to evaluate efficacy of treatment. Motion sensors and posture detection devices will probably be very important in monitoring patients with balance problems, Parkinson's disease, patients in rehabilitation processes and sleep disorders (2,3,11,12). The motor symptoms of Parkinson's disease have hypokinetic and hyperkinetic features.…”

Section: Potential Uses Of Wearable Technologies In Medicinementioning

confidence: 99%

“…Freezing of the gate is one of the most disabling symptoms in the late stages. Wearable devices delivering auditory commands or light may help to overcome immobility (11).…”

Section: Potential Uses Of Wearable Technologies In Medicinementioning

confidence: 99%

“…Commercially available equipment is used to record step numbers and temporal parameters of gait such as stride time, swing time, and step time (12). Sedentary behavior seems more common in MS patients with mobility disability than those without mobility disability (11). One study assessed sedentary behavior with actigraph.…”

Section: Potential Uses Of Wearable Technologies In Medicinementioning

confidence: 99%

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Monitoring physical activity with wearable technologies

Tokuçoğlu

2018

Archives of Neuropsychiatry

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Living a healthy and fulfilling life or at least carrying on the daily activities inevitably depends on some physical activity in different scales. Therefore, measuring the physical activity is necessary to evaluate both healthy people and patients in order to plan their needs for wellbeing. Objective and accurate measurements can be made with wearable sensors and related technologies. Evaluating health and wellness, efficacy of treatment, safety, physical ability and disability are in the scope of monitoring physical activity with wearable technologies.

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“…That same preparation for calibrating output from accelerometers has been applied in other populations such as persons with the neurological disease multiple sclerosis (MS) [15]; we note PLOS ONE doctoral fellowship from the National Multiple Sclerosis Society (MB 0011). https://www.…”

Section: Introductionmentioning

confidence: 99%

Accelerometer output and its association with energy expenditure in persons with mild-to-moderate Parkinson’s disease

Jeng¹,

Cederberg²,

Lai³

et al. 2020

PLoS ONE

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Objective This study examined the association between ActiGraph accelerometer output and energy expenditure across different speeds of walking in persons with Parkinson’s disease (PD), and further generated cut-points that represent a metric for quantifying time spent in moderate-to-vigorous physical activity (MVPA) among persons with PD. Methods The sample included 30 persons with mild-to-moderate PD (Hoehn and Yahr stages 2–3) and 30 adults without PD matched by sex and age. All participants completed 5 minutes of quiet, seated rest and then underwent three, 6-minute bouts of walking on a treadmill at three different speeds relative to the individual’s self-selected pace. Activity counts were measured using an ActiGraph accelerometer worn at the waist level on the least affected side for persons with PD and the dominant side for controls. The rate of oxygen consumption, or energy expenditure, was measured using a portable, open-circuit spirometry system. Results Our results indicated a strong association between activity counts and energy expenditure for persons with PD (R2 = 0.87) and controls (R2 = 0.89). However, the significant difference in slopes resulted in a lower cut-point of 1,354 counts·min-1 for persons with PD than the cut-point of 2,010 counts·min-1 for controls. Conclusion Our results support the application of the disease-specific cut-point for quantifying the amount of time spent in MVPA using ActiGraph accelerometers among persons with mild-to-moderate PD. Such an application may provide accurate estimates of MVPA in this population, and better inform future research examining the possible determinants and consequences of physical activity as well as testing of interventions for changing MVPA in PD.

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Motion sensors in multiple sclerosis: Narrative review and update of applications

Cited by 40 publications

References 83 publications

Step‐rate threshold for physical activity intensity in Parkinson’s disease

Step‐rate threshold for physical activity intensity in Parkinson’s disease

Monitoring physical activity with wearable technologies

Accelerometer output and its association with energy expenditure in persons with mild-to-moderate Parkinson’s disease

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