Accelerometer based free-living data: Does macro gait behaviour differ between fallers and non-fallers with and without Parkinson's disease?

[Poster] BACKGROUND AND AIM: Gait impairment and falls are frequent among older adults and people with Parkinson's disease (PD), and may lead to loss of functional independence and poor quality of life. Current approaches for evaluating falls risk are based on self-report or testing at a given time point and therefore may be suboptimal. Continuous monitoring of gait is emerging as a powerful tool to assess motor impairment and falls risk in real life using accelerometer-based technology, potentially providing an accurate and objective measure of risk [1]. Macro level gait behaviours (e.g., volume, pattern, and variability of walking bouts) are sensitive to PD pathology [2], however, there are conflicting reports about their association with falls risk. The aim of this study was to explore the association between physical activity (PA) and falls history by analysing whether macro level gait behaviour differs between fallers and non-fallers with and without PD using 7 day accelerometer-based free-living data. METHODS: 227 fallers (F: 106 elderly, 121 PD; age: 76±6 yrs, and 72±6 yrs, respectively) enrolled in the V-TIME study [3], who fell twice or more in the 6 months prior to assessment, together with 65 participants without a history of falls (NF: 50 elderly, 15 PD, age: 65±9 yrs, 70±7 yrs, respectively) enrolled into ICICLE-GAIT [2] were tested. Data were recorded continuously for 7 days with a tri-axial accelerometer (Axivity AX3, UK, 100Hz, ±8g) placed on the low back (L5). Macro level outcomes (MLO) representing the volume (% walking time, number of steps, mean bout length), pattern (alpha (α)), and variability (S2) of free-living activity were extracted in MATLAB® (R2012a) [2]. General linear modelling examined the effect of fall history (F vs NF) and pathology (PD vs elderly) on MLO, controlling for age, sex and BMI. RESULTS: Although the % walking time and number of steps was not related to fall history, F tended to walk in shorter bouts (p=.004) and had a less variable walking pattern (lower S2, p=.019) compared to NF. PD spent less time walking (p=.002), took fewer steps (p=.002), and accumulated proportionally more steps in shorter bouts (higher α) compared to the elderly (p=.006), regardless of falls history. There were no interactions between pathology and falls history for any of the outcomes. CONCLUSIONS: Our results showed that there is an association between falls history and PA. Volume-based MLO, pattern and variability of the walking bouts derived from free-living accelerometer-based data are independently associated with a history of falls and PD. These results support the use of a single accelerometer-based sensor to assess falls risk in free living settings, however, future work is needed to confirm if MLO can predict falls, potentially guiding clinical decision making. REFERENCES: [1] Lord S et al., Mov Disord, 2013; 28(11):1534-43 [2] Lord S et al., J Neurol, 2013; 260(12):2964-72 [3] Mirelman A et al., BMC Neurol, 2013;13:1

Everyday Stepping Quantity and Quality Among Older Adult Fallers With and Without Mild Cognitive Impairment: Initial Evidence for New Motor Markers of Cognitive Deficits?

Background: Recent work demonstrated that the gait of people with mild cognitive impairment (MCI) differs from that of age-matched controls and, in general, that walking ability, as measured in the clinic, does not necessarily reflect actual, daily performance. We evaluated if the quantity and quality of everyday walking (ie, community ambulation) differs in older adults with MCI, compared to age-matched controls.Methods: Inclusion criteria included: age 65-90 years, able to walk at least 5 minutes unassisted, and >= 2 falls in the past 6 months. Subjects with MCI were included if they scored 0.5 on the Clinical Dementia Rating Scale. To assess stepping quantity and quality, subjects wore a tri-axial accelerometer on the lower-back for 7 days.Results: Age and gender were similar (p > .10) in MCI (n = 36, 77.8 +/- 6.4 years; 27.8% men) and controls (n = 100, 76.0 +/- 6.2 years; 22.0% men). As expected, Montreal Cognitive Assessment scores were lower (p < .001) in MCI (21.31 +/- 4.05), compared to controls (25.81 +/- 2.64). Walking time was lower (p = .016) in MCI (0.74 +/- 0.48 hours/d), compared to controls (1.05 +/- 0.66 hours/d). Within-bout walking (eg, stride regularity) was less consistent (p = .024) in MCI (0.51 +/- 0.14), compared to controls (0.58 +/- 0.14). Changes in stride regularity across bouts were lower (p < .001) in MCI (0.13 +/- 0.04), compared to controls (0.17 +/- 0.01).Conclusions: Older adults with MCI walk less and with a more variable within-bout and less variable across-bout walking pattern, as compared to cognitively-intact subjects matched with respect to age and gender. These findings extend previous clinical work and suggest that MCI affects both the quantity and quality of community ambulation

Gait impairments in Parkinson's disease

Gait impairments are among the most common and disabling symptoms of Parkinson's disease. Nonetheless, gait is not routinely assessed quantitatively but is described in general terms that are not sensitive to changes ensuing with disease progression. Quantifying multiple gait features (eg, speed, variability, and asymmetry) under natural and more challenging conditions (eg, dual-tasking, turning, and daily living) enhanced sensitivity of gait quantification. Studies of neural connectivity and structural network topology have provided information on the mechanisms of gait impairment. Advances in the understanding of the multifactorial origins of gait changes in patients with Parkinson's disease promoted the development of new intervention strategies, such as neurostimulation and virtual reality, aimed at alleviating gait impairments and enhancing functional mobility. For clinical applicability, it is important to establish clear links between specific gait impairments, their underlying mechanisms, and disease progression to foster the acceptance and usability of quantitative gait measures as outcomes in future disease-modifying clinical trials

Do Patients With Parkinson\u2019s Disease With Freezing of Gait Respond Differently Than Those Without to Treadmill Training Augmented by Virtual Reality?

Background. People with Parkinson\u2019s disease and freezing of gait (FOG+) have more falls, postural instability and cognitive impairment compared with FOG 12. Objective. To conduct a secondary analysis of the V-TIME study, a randomized, controlled investigation showing a greater reduction of falls after virtual reality treadmill training (TT + VR) compared with usual treadmill walking (TT) in a mixed population of fallers. We addressed whether these treadmill interventions led to similar gains in FOG+ as in FOG 12. Methods. A total of 77 FOG+ and 44 FOG 12 were assigned randomly to TT + VR or TT. Participants were assessed pre- and posttraining and at 6 months\u2019 follow-up. Main outcome was postural stability assessed by the Mini Balance Evaluation System Test (Mini-BEST) test. Falls were documented using diaries. Other outcomes included the New Freezing of Gait Questionnaire (NFOG-Q) and the Trail Making Test (TMT-B). Results. Mini-BEST scores and the TMT-B improved in both groups after training (P =.001), irrespective of study arm and FOG subgroup. However, gains were not retained at 6 months. Both FOG+ and FOG 12 had a greater reduction of falls after TT + VR compared with TT (P =.008). NFOG-Q scores did not change after both training modes in the FOG+ group. Conclusions. Treadmill walking (with or without VR) improved postural instability in both FOG+ and FOG 12, while controlling for disease severity differences. As found previously, TT + VR reduced falls more than TT alone, even among those with FOG. Interestingly, FOG itself was not helped by training, suggesting that although postural instability, falls and FOG are related, they may be controlled by different mechanisms