Perspectives on Aging Vestibular Function

Locomotion results from intricate dynamic interactions between a central program and feedback mechanisms. The central program relies fundamentally on a genetically determined spinal circuitry (central pattern generator) capable of generating the basic locomotor pattern and on various descending pathways that can trigger, stop, and steer locomotion. The feedback originates from muscles and skin afferents as well as from special senses (vision, audition, vestibular) and dynamically adapts the locomotor pattern to the requirements of the environment. The dynamic interactions are ensured by modulating transmission in locomotor pathways in a state- and phase-dependent manner. For instance, proprioceptive inputs from extensors can, during stance, adjust the timing and amplitude of muscle activities of the limbs to the speed of locomotion but be silenced during the opposite phase of the cycle. Similarly, skin afferents participate predominantly in the correction of limb and foot placement during stance on uneven terrain, but skin stimuli can evoke different types of responses depending on when they occur within the step cycle. Similarly, stimulation of descending pathways may affect the locomotor pattern in only certain phases of the step cycle. Section ii reviews dynamic sensorimotor interactions mainly through spinal pathways. Section iii describes how similar sensory inputs from the spinal or supraspinal levels can modify locomotion through descending pathways. The sensorimotor interactions occur obviously at several levels of the nervous system. Section iv summarizes presynaptic, interneuronal, and motoneuronal mechanisms that are common at these various levels. Together these mechanisms contribute to the continuous dynamic adjustment of sensorimotor interactions, ensuring that the central program and feedback mechanisms are congruous during locomotion. Show more

Falls in elderly people are a major health burden, especially in the long-term care environment. Yet little objective evidence is available for how and why falls occur in this population. We aimed to provide such evidence by analysing real-life falls in long-term care captured on video. We did this observational study between April 20, 2007, and June 23, 2010, in two long-term care facilities in British Columbia, Canada. Digital video cameras were installed in common areas (dining rooms, lounges, hallways). When a fall occurred, facility staff completed an incident report and contacted our teams so that we could collect video footage. A team reviewed each fall video with a validated questionnaire that probed the cause of imbalance and activity at the time of falling. We then tested whether differences existed in the proportion of participants falling due to the various causes, and while engaging in various activities, with generalised linear models, repeated measures logistic regression, and log-linear Poisson regression. We captured 227 falls from 130 individuals (mean age 78 years, SD 10). The most frequent cause of falling was incorrect weight shifting, which accounted for 41% (93 of 227) of falls, followed by trip or stumble (48, 21%), hit or bump (25, 11%), loss of support (25, 11%), and collapse (24, 11%). Slipping accounted for only 3% (six) of falls. The three activities associated with the highest proportion of falls were forward walking (54 of 227 falls, 24%), standing quietly (29 falls, 13%), and sitting down (28 falls, 12%). Compared with previous reports from the long-term care setting, we identified a higher occurrence of falls during standing and transferring, a lower occurrence during walking, and a larger proportion due to centre-of-mass perturbations than base-of-support perturbations. By providing insight into the sequences of events that most commonly lead to falls, our results should lead to more valid and effective approaches for balance assessment and fall prevention in long-term care. Canadian Institutes for Health Research. Copyright © 2013 Elsevier Ltd. All rights reserved. Show more

Timed Up and Go (TUG) test is a widely used clinical paradigm to evaluate balance and mobility. Although TUG includes several complex subcomponents, namely: sit-to-stand, gait, 180 degree turn, and turn-to-sit; the only outcome is the total time to perform the task. We have proposed an instrumented TUG, called iTUG, using portable inertial sensors to improve TUG in several ways: automatic detection and separation of subcomponents, detailed analysis of each one of them and a higher sensitivity than TUG. Twelve subjects in early stages of Parkinson's disease (PD) and 12 age matched control subjects were enrolled. Stopwatch measurements did not show a significant difference between the two groups. The iTUG, however, showed a significant difference in cadence between early PD and control subjects (111.1 +/- 6.2 versus 120.4 +/- 7.6 step/min, p < 0.006) as well as in angular velocity of arm-swing (123 +/- 32.0 versus 174.0+/-50.4 degrees/s, p < 0.005), turning duration (2.18 +/- 0.43 versus 1.79 +/- 0.27 s, p < 0.023), and time to perform turn-to-sits (2.96 +/- 0.68 versus 2.40 +/- 0.33 s, p < 0.023). By repeating the tests for a second time, the test-retest reliability of iTUG was also evaluated. Among the subcomponents of iTUG, gait, turning, and turn-to-sit were the most reliable and sit-to-stand was the least reliable. Show more