Physical activity levels measured by remote monitoring are consistently low in people with MS , stroke and dementia , and patterns of physical activity are altered in PD .
In MS , decreased ambulatory activity assessed via remote monitoring is associated with greater disability and lower quality of life .
In stroke , remote measures of upper limb function and ambulation are associated with functional recovery following rehabilitation and goal -directed interventions .
In PD , remote monitoring may help to predict falls .
In dementia , remote physical activity measures correlate with disease severity and can detect w and ering .
Conclusions These studies show that remote physical activity monitoring is feasible in neurological diseases , including in people with moderate to severe neurological disability .
Remote monitoring can be a psychometrically sound and responsive way to assess physical activity in neurological disease .
Objective To perform a systematic review of studies using remote physical activity monitoring in neurological diseases , highlighting advances and determining gaps .
Objective Assessment of Fall Risk in Parkinson's Disease Using a Body-Fixed Sensor Worn for 3 Days
Background Patients with Parkinson 's disease ( PD ) suffer from a high fall risk . Previous approaches for evaluating fall risk are based on self-report or testing at a given time point and may , therefore , be insufficient to optimally capture fall risk . We tested , for the first time , whether metrics derived from 3 day continuous recordings are associated with fall risk in PD . Methods and Material s 107 patients ( Hoehn & Yahr Stage : 2.6±0.7 ) wore a small , body-fixed sensor ( 3D accelerometer ) on lower back for 3 days .  Walking quantity ( e.g. , steps per 3-days ) and quality ( e.g. , frequency-derived measures of gait variability ) were determined . Subjects were classified as fallers or non-fallers based on fall history . Subjects were also followed for one year to evaluate predictors of the transition from non-faller to faller . Results The 3 day acceleration derived measures were significantly different in fallers and non-fallers and were significantly correlated with previously vali date d measures of fall risk . Walking quantity was similar in the two groups . In contrast , the fallers walked with higher step-to-step variability , e.g. , anterior-posterior width of the dominant frequency was larger ( p = 0.012 ) in the fallers ( 0.78±0.17 Hz ) compared to the non-fallers ( 0.71±0.07 Hz ) . Among subjects who reported no falls in the year prior to testing , sensor-derived measures predicted the time to first fall ( p = 0.0034 ) , whereas many traditional measures did not . Cox regression analysis showed that anterior-posterior width was significantly ( p = 0.0039 ) associated with time to fall during the follow-up period , even after adjusting for traditional measures . Conclusions / Significance These findings indicate that a body-fixed sensor worn continuously can evaluate fall risk in PD . This sensor-based approach was able to identify transition from non-faller to faller , whereas many traditional metrics were not successful . This approach may facilitate earlier detection of fall risk and may in the future , help reduce high costs associated with falls
Physical activity levels measured by remote monitoring are consistently low in people with MS , stroke and dementia , and patterns of physical activity are altered in PD .
In MS , decreased ambulatory activity assessed via remote monitoring is associated with greater disability and lower quality of life .
In stroke , remote measures of upper limb function and ambulation are associated with functional recovery following rehabilitation and goal -directed interventions .
In PD , remote monitoring may help to predict falls .
In dementia , remote physical activity measures correlate with disease severity and can detect w and ering .
Conclusions These studies show that remote physical activity monitoring is feasible in neurological diseases , including in people with moderate to severe neurological disability .
Remote monitoring can be a psychometrically sound and responsive way to assess physical activity in neurological disease .
Objective To perform a systematic review of studies using remote physical activity monitoring in neurological diseases , highlighting advances and determining gaps .