Evidence of slow and variable choice-stepping reaction time in cancer survivors with chemotherapy-induced peripheral neuropathy.

BACKGROUND: Chemotherapy-induced peripheral neuropathy (CIPN) is reported to affect up to 70 % of cancer survivors. Despite evidence that CIPN-related impairments often translate into balance and mobility deficits, the effects on stepping and quality of gait, well-documented risk factors for falls, are unclear. AIMS: (i) Establish choice-stepping reaction time (CSRT) performance in survivors with CIPN compared to young and older healthy controls and people with Parkinson's disease; (ii) document walking stability; (iii) investigate relationships between stepping and gait data to objective and patient-reported outcomes. METHODS: 41 cancer survivors with CIPN (mean (SD) age: 60.8 (9.7) years) who were ≥3months post chemotherapy, performed tests of simple and inhibitory CSRT. Walking stability measures were derived from 3-D accelerometry data during the 6-minute walk test. CIPN was assessed using neurological grading and patient-reported outcome measures (European Organization for Research and Treatment of Cancer Quality of Life Questionnaire in CIPN Questionnaire scale EORTC CIPN20). RESULTS: In both stepping tests, CIPN participants performed at the level of adults aged 10 years older and people with mild to moderate Parkinson's disease. Mean (SD) total stepping response times in both CSRT (1160 (190) milliseconds) and inhibitory CSRT (1191 (164) milliseconds) tests were not associated with objective neurological grading but were correlated with increased difficulty feeling the ground. Participants with lower-limb vibration sensation deficit had slower and more variable CSRT times. There were no associations between walking stability and objective measures of CIPN, and limited correlations with the EORTC-CIPN20. CONCLUSIONS: Cancer survivors with CIPN showed deficits in voluntary stepping responses and seemed to compensate for their sensory and motor deficits by walking slower to maintain stability. Objective and patient-reported outcomes of CIPN were correlated with slower and more variable stepping response times. Future studies should aim to identify the causes of the apparent premature decline in cognitive-motor function and develop remediating interventions.

A taxonomy of cognitive tasks to evaluate cognitive-motor interference on spatiotemoporal gait parameters in older people: a systematic review and meta-analysis.

BACKGROUND: Walking in natural environments can be considered a dual-task (DT) scenario that requires increasing cognitive resources with advancing age. Previous reviews concluded that gait speed under DT conditions is equivalent to gait speed as a single task (ST) in the prediction of future falls in older people. However, without a clear taxonomy, these conclusions might be premature. The aim of this review is to use a taxonomy for classifying cognitive tasks of cognitive-motor interference (CMI) paradigms while walking to identify which task domains lead to more pronounced cognitive-motor decrements due to fall risk and concern about falling (CoF) in older people. METHODS: A systematic literature research following PRISMA guidelines was conducted using MEDLINE, Psych-Info and EMBASE. Inclusion criteria were: older people ≥60 years with a previous fall or CoF, use of a DT paradigm to discriminate fallers and non-fallers, straight overground walking, reported gait measurements during ST and DT conditions. A meta-analysis estimated the effect of DT costs for the cognitive task domain and spatiotemporal gait parameters. RESULTS: N = 3737 studies were found within the databases. Nineteen studies were included (n = 14 for meta-analysis). Fallers and people with CoF showed reduced walking speed for ST and DT conditions. Effects of DT were examined for mental tracking tasks. The combined odds ratio (OR [95% confidence interval]) for fallers vs. non-fallers for ST was 3.13 [0.47, 5.80] with moderate heterogeneity (I 2 = 48%). For DT, the OR was 5.17 [2.42, 7.93] with low heterogeneity (I 2 = 37%). Comparing participants with and without CoF, the OR for ST was 12.41 [9.97, 14.84] with high heterogeneity (I 2 = 85%) and OR for mental tracking DT was 10.49 [7.58, 13.40] with moderate heterogeneity (I 2 = 51%). CONCLUSION: CMI was not significantly different between fallers and non-fallers or people with and without CoF; however, our taxonomy revealed a large variety of cognitive conditions and a higher number of studies using mental tracking tasks, which make it impossible to draw firm conclusions. Future studies should use a more standardised and ecologically valid approach when evaluating the validity of DT gait performance in the prediction of falls, CoF or other age-related conditions. TRIAL REGISTRATION: This review was registered at Prospero with the ID: CRD42017068912.

Inertial wearables as pragmatic tools in dementia.

Dementia is a critically important issue due to its wide impact on health services as well as its personal and societal costs. Limitations exist for current dementia protocols, and there are calls to introduce modern technology that facilitates the addition of digital biomarkers to routine clinical practice. Wearable technology (wearables) are nearly ubiquitous in everyday life, gathering discrete and continuous digital data on habitual activities, but their utility in modern medicine remains low. Due to advances in data analytics, wearables are now commonly discussed as pragmatic tools to aid the diagnosis and treatment of a range of neurological disorders. Inertial sensor-based wearables are one such technology; they offer a low-cost approach to quantify routine movements that are fundamental to normal activities of daily living, most notably postural control and gait. Here, we provide a narrative review of how wearables are providing useful postural control and gait data to facilitate the capture of digital markers to aid dementia research. We outline the history of wearables, from their humble beginnings to their current use beyond the clinic, and explore their integration into modern systems, as well as the ongoing standardisation and regulatory efforts to integrate their use in clinical trials.

The effect of walking speed on quality of gait in older adults.

BACKGROUND: Gait quality characteristics can contribute to the identification of individuals at risk of falls. Since older adults with high fall risk tend to walk slower than older adults with a lower fall risk, walking speed may underlie differences in gait quality characteristics. RESEARCH QUESTION: How does walking speed affect gait quality characteristics in older people? METHODS: We investigated the effect of walking speed on gait characteristics in 11 older adults (aged 69.6 ±â€¯4.1 years). Trunk accelerations (Dynaport MoveMonitor) were recorded during 5 min of treadmill walking at four different speeds. From these trunk accelerations we calculated step frequency, root mean square, harmonic ratio, index of harmonicity, sample entropy and logarithmic divergence rate per stride. RESULTS: Our results showed that all gait characteristics were affected by walking speed, except for sample entropy in antero-posterior (AP) direction. An increase in walking speed resulted in a higher step frequency, higher standard deviation, more symmetric gait, more smooth vertical (VT) accelerations, less smooth accelerations in medio-lateral (ML) and AP directions, less regular dynamics in ML direction, more regular dynamics in VT direction, and a more stable gait pattern overall. SIGNIFICANCE: These findings suggest that, within a range of 0.5-1.4 m/s, a lower walking speed results in a lower gait quality, which may underlie differences in gait quality between older fallers and non-fallers.

A benchmark test of accuracy and precision in estimating dynamical systems characteristics from a time series.

Characteristics of dynamical systems are often estimated to describe physiological processes. For instance, Lyapunov exponents have been determined to assess the stability of the cardio-vascular system, respiration, and, more recently, human gait and posture. However, the systematic evaluation of the accuracy and precision of these estimates is problematic because the proper values of the characteristics are typically unknown. We fill this void with a set of standardized time series with well-defined dynamical characteristics that serve as a benchmark. Estimates ought to match these characteristics, at least to good approximation. We outline a procedure to employ this generic benchmark test and illustrate its capacity by examining methods for estimating the maximum Lyapunov exponent. In particular, we discuss algorithms by Wolf and co-workers and by Rosenstein and co-workers and evaluate their performances as a function of signal length and signal-to-noise ratio. In all scenarios, the precision of Rosenstein's algorithm was found to be equal to or greater than Wolf's algorithm. The latter, however, appeared more accurate if reasonably large signal lengths are available and noise levels are sufficiently low. Due to its modularity, the presented benchmark test can be used to evaluate and tune any estimation method to perform optimally for arbitrary experimental data.