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BackgroundFatigue and ageing contribute to impaired control of walking and are linked to falls. In this project, fatigue was induced by maximum speed walking to examine fatigue effects on lower limb trajectory control and associated tripping risk and overall gait functions of older adults.MethodsEleven young (18–35 years) and eleven older adults (>65 years) conducted 5-minute preferred speed treadmill walking prior to and following 6-minute maximum fast walking. Spatio-temporal gait parameters and minimum foot clearance (MFC) were obtained. Maximal muscle strength (hamstrings and quadriceps) was measured on an isokinetic dynamometer. Heart rate (HR) and rating of perceived exertion (RPE) assessed physiological effort and subjective fatigue. Physiological Cost Index computed walking efficiency.ResultsFatigue due to fast walking increased step length, double support time and variability of step width. Only older adults reduced MFC due to fatigue. A trend of longer double support with greater MFC was found in the non-dominant limb. Lower walking efficiency was characterised as the ageing effect. Older adults did not increase HR during fast walking but higher RPE scores were observed.ConclusionsOlder adults can increase tripping risk by 6 minutes of fast walking possibly by both impaired walking efficiency based on cardiac capacity and higher perceived fatigue due to elevated caution level. Regardless of age, increased step width variability due to fatigue was observed, a sign of impaired balance. Longer double support and greater MFC observed in the older adults’ non-dominant limb could be an asymmetrical gait adaptation for safety.Electronic supplementary materialThe online version of this article (doi:10.1186/1743-0003-11-155) contains supplementary material, which is available to authorized users.

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Impaired walking increases injury risk during locomotion, including falls-related acute injuries and overuse damage to lower limb joints. Gait impairments seriously restrict voluntary, habitual engagement in injury prevention activities, such as recreational walking and exercise. There is, therefore, an urgent need for technology-based interventions for gait disorders that are cost effective, willingly taken-up, and provide immediate positive effects on walking. Gait control using shoe-insoles has potential as an effective population-based intervention, and new sensor technologies will enhance the effectiveness of these devices. Shoe-insole modifications include: (i) ankle joint support for falls prevention; (ii) shock absorption by utilising lower-resilience materials at the heel; (iii) improving reaction speed by stimulating cutaneous receptors; and (iv) preserving dynamic balance via foot centre of pressure control. Using sensor technology, such as in-shoe pressure measurement and motion capture systems, gait can be precisely monitored, allowing us to visualise how shoe-insoles change walking patterns. In addition, in-shoe systems, such as pressure monitoring and inertial sensors, can be incorporated into the insole to monitor gait in real-time. Inertial sensors coupled with in-shoe foot pressure sensors and global positioning systems (GPS) could be used to monitor spatiotemporal parameters in real-time. Real-time, online data management will enable ‘big-data’ applications to everyday gait control characteristics.

Slipping is hazardous in everyday locomotion and occupational settings. This study investigated foot control kinematics and kinetics across various gait tasks on both a non-contaminated and an oil-contaminated walking surface. Turning, gait termination and gait initiation were associated with a greater risk of slip-related falls than unconstrained walking.

Hemiplegic stroke often impairs gait and increases falls risk during rehabilitation. Tripping is the leading cause of falls, but the risk can be reduced by increasing vertical swing foot clearance, particularly at the mid-swing phase event, minimum foot clearance (MFC). Based on previous reports, real-time biofeedback training may increase MFC. Six post-stroke individuals undertook eight biofeedback training sessions over a month, in which an infrared marker attached to the front part of the shoe was tracked in real-time, showing vertical swing foot motion on a monitor installed in front of the subject during treadmill walking. A target increased MFC range was determined, and participants were instructed to control their MFC within the safe range. Gait assessment was conducted three times: Baseline, Post-training and one month from the final biofeedback training session. In addition to MFC, step length, step width, double support time and foot contact angle were measured. After biofeedback training, increased MFC with a trend of reduced step-to-step variability was observed. Correlation analysis revealed that MFC height of the unaffected limb had interlinks with step length and ankle angle. In contrast, for the affected limb, step width variability and MFC height were positively correlated. The current pilot-study suggested that biofeedback gait training may reduce tripping falls for post-stroke individuals.

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