Understanding the impact of deep brain stimulation on ambulatory activity in advanced Parkinson’s disease

Rochester, Lynn; Chastin, Sébastien; Lord, Sue; Baker, Katherine; Burn, David J.

doi:10.1007/s00415-011-6301-9

Cited by 59 publications

(60 citation statements)

References 24 publications

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“…In our opinion, further studies are required to detect OFF periods when patients are at rest (one of the objectives of the ongoing REMPARK project) [14]. However, since patients, even in moderate or advanced phases of the disease, walk more than 40 times per day [15,16], a system like ours, could still produce enough frequent detections. Although not continuous, detection of the motor status with our system could provide very useful information for a better clinical monitoring, since the ON/OFF periods usually last for 1 to 3 hours [17].…”

Section: Discussionmentioning

confidence: 99%

Validation of a Portable Device for Mapping Motor and Gait Disturbances in Parkinson’s Disease

Rodríguez‐Molinero¹,

Samà²,

Pérez-Martínez³

et al. 2015

JMIR mHealth uHealth

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BackgroundPatients with severe idiopathic Parkinson’s disease experience motor fluctuations, which are often difficult to control. Accurate mapping of such motor fluctuations could help improve patients’ treatment.ObjectiveThe objective of the study was to focus on developing and validating an automatic detector of motor fluctuations. The device is small, wearable, and detects the motor phase while the patients walk in their daily activities.MethodsAlgorithms for detection of motor fluctuations were developed on the basis of experimental data from 20 patients who were asked to wear the detector while performing different daily life activities, both in controlled (laboratory) and noncontrolled environments. Patients with motor fluctuations completed the experimental protocol twice: (1) once in the ON, and (2) once in the OFF phase. The validity of the algorithms was tested on 15 different patients who were asked to wear the detector for several hours while performing daily activities in their habitual environments. In order to assess the validity of detector measurements, the results of the algorithms were compared with data collected by trained observers who were accompanying the patients all the time.ResultsThe motor fluctuation detector showed a mean sensitivity of 0.96 (median 1; interquartile range, IQR, 0.93-1) and specificity of 0.94 (median 0.96; IQR, 0.90-1).ConclusionsON/OFF motor fluctuations in Parkinson's patients can be detected with a single sensor, which can be worn in everyday life.

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Section: Discussionmentioning

confidence: 99%

Validation of a Portable Device for Mapping Motor and Gait Disturbances in Parkinson’s Disease

Rodríguez‐Molinero¹,

Samà²,

Pérez-Martínez³

et al. 2015

JMIR mHealth uHealth

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“…Activity monitors use accelerations to measure relative daily activity and/or the percent of the day a subject is standing, walking or sitting/lying (Ford et al, 2010; Skidmore et al, 2008; Zwartjes, Heida, van Vugt, Geelen, & Veltink, 2010). More informative measures include total activity duration, total number of steps taken, the time spent in each activity, and time spent engaging in different intensity levels of activity (Cavanaugh et al, 2012; Lord et al, 2013; Rochester, Chastin, Lord, Baker, & Burn, 2012). Whilst informative, these measures do not characterize specific gait impairments, features of postural control, or the patterns of daily activity.…”

Section: Introductionmentioning

confidence: 99%

Continuous monitoring of turning in Parkinson’s disease: Rehabilitation potential

Mancini

El‐Gohary²,

Pearson³

et al. 2015

NRE

141

136

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Background Difficulty turning during gait is a major contributor to mobility disability, falls and reduced quality of life in patients with Parkinson’s disease (PD). Unfortunately, the assessment of mobility in the clinic may not adequately reflect typical mobility function or its variability during daily life. We hypothesized that quality of turning mobility, rather than overall quantity of activity, would be impaired in people with PD over 7 days of continuous recording. Methods 13 subjects with PD and 8 healthy control subjects of similar age wore 3 Opal inertial sensors (on their belt and on each foot) throughout 7 consecutive days during normal daily activities. Turning metrics included average and coefficient of variation (CV) of: 1) number of turns per hour, 2) turn angle amplitude, 3) turn duration, 4) turn mean velocity, and 5) number of steps per turn. Turning characteristics during continuous monitoring were compared with turning 90 and 180 degrees in a observed gait task. Results No differences were found between PD and control groups for observed turns. In contrast, subjects with PD showed impaired quality of turning compared to healthy control subjects (Turn Mean Velocity: 43.3±4.8°/s versus 38±5.7°/s, mean number of steps 1.7±1.1 versus 3.2±0.8). In addition, PD patients showed higher variability within the day and across days compared to controls. However, no differences were seen between PD and control subjects in the overall activity (number of steps per day or percent of the day walking) during the 7 days. Conclusions We show that continuous monitoring of natural turning during daily activities inside or outside the home is feasible for patients with PD and the elderly. This is the first study showing that continuous monitoring of turning was more sensitive to PD than observed turns. In addition, the quality of turning characteristics was more sensitive to PD than quantity of turns. Characterizing functional turning during daily activities will address a critical barrier to rehabilitation practice and clinical trials: objective measures of mobility characteristics in real-life environments.

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“…Both average bout length and S 2 were calculated using a maximum likelihood technique because data were log-normally distributed [13]. We also calculated the proportion of participants who achieved the public health recommendations of at least 150 min of activity accumulated in bouts !10 min over 1 week.…”

Section: Ambulatory Outcomesmentioning

confidence: 99%

“…Ambulation was defined by established outcome measures analysing volume, pattern and variability [2,13]:…”

Section: Ambulatory Outcomesmentioning

confidence: 99%

Defining ambulatory bouts in free-living activity: Impact of brief stationary periods on bout metrics

et al. 2015

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The aim of this study was to assess the effect of varying the maximum resting period between consecutive ambulatory bouts in community-based outcomes. Ambulation was assessed in 97 community-dwelling older adults (mean (SD) age 69.2 (7.7) years) using an accelerometer (activPAL™) worn on the upper thigh for 7 consecutive days. The volume, pattern and variability of ambulation were calculated over a range of maximum resting periods (1-30s). Outcomes with a maximum resting period from 1 to 6s did not vary due to device functionality. Non-linear regression (power law, r(2) > 0.99) showed that increasing the maximum resting period from 6 to 30s resulted in changes in volume (increased duration spent walking, and decreased number of bouts), variability (S2 increased) and pattern (α decreased), and a linear relationship with an increase in average bout length. With a MRP of 6s, 6% of the cohort achieved the public health guidelines of 150 min of ambulation/week accumulated in bouts ≥ 10 min, which increased to 40% using a maximum resting period of 30s. Modifying the maximum resting period impacts on volume, pattern and variability measures of community based ambulation, and attainment of public health guidelines. This highlights the need for standardised algorithms to aid interpretation and explicit reporting of the maximum resting period to aid comparison between studies.

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Understanding the impact of deep brain stimulation on ambulatory activity in advanced Parkinson’s disease

Cited by 59 publications

References 24 publications

Validation of a Portable Device for Mapping Motor and Gait Disturbances in Parkinson’s Disease

Validation of a Portable Device for Mapping Motor and Gait Disturbances in Parkinson’s Disease

Continuous monitoring of turning in Parkinson’s disease: Rehabilitation potential

Defining ambulatory bouts in free-living activity: Impact of brief stationary periods on bout metrics

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