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Despite extensive preventive efforts, falls continue to be a major source of morbidity and mortality among elderly. Real-time detection of falls and their urgent communication to a telecare center may enable rapid medical assistance, thus increasing the sense of security of the elderly and reducing some of the negative consequences of falls. Many different approaches have been explored to automatically detect a fall using inertial sensors. Although previously published algorithms report high sensitivity (SE) and high specificity (SP), they have usually been tested on simulated falls performed by healthy volunteers. We recently collected acceleration data during a number of real-world falls among a patient population with a high-fall-risk as part of the SensAction-AAL European project. The aim of the present study is to benchmark the performance of thirteen published fall-detection algorithms when they are applied to the database of 29 real-world falls. To the best of our knowledge, this is the first systematic comparison of fall detection algorithms tested on real-world falls. We found that the SP average of the thirteen algorithms, was (mean±std) 83.0%±30.3% (maximum value = 98%). The SE was considerably lower (SE = 57.0%±27.3%, maximum value = 82.8%), much lower than the values obtained on simulated falls. The number of false alarms generated by the algorithms during 1-day monitoring of three representative fallers ranged from 3 to 85. The factors that affect the performance of the published algorithms, when they are applied to the real-world falls, are also discussed. These findings indicate the importance of testing fall-detection algorithms in real-life conditions in order to produce more effective automated alarm systems with higher acceptance. Further, the present results support the idea that a large, shared real-world fall database could, potentially, provide an enhanced understanding of the fall process and the information needed to design and evaluate a high-performance fall detector.

This paper presents an analysis of spatio-temporal gait parameters during overground walking based upon a method that needs only lower trunk accelerations. Twenty-six healthy young subjects and 15 healthy elderly subjects participated in an experiment where overground walking was studied at different speeds. Accelerations of the lower trunk were measured by a tri-axial accelerometer connected to a portable data logger carried on the body. An analysis of trunk acceleration data produced temporal gait parameters (duration of subsequent stride cycles and left/right steps) and convincing estimations of spatial parameters (step length and walking speed). Typical differences in spatio-temporal gait parameters between young and elderly subjects could be demonstrated, i.e. a limited range of walking speeds, smaller step lengths, and a somewhat higher variability of temporal parameters in elderly subjects. It is concluded from these results that essential spatio-temporal gait parameters can be determined during overground walking using only one tri-axial accelerometer. The method is easy-to-use and does not interfere with regular walking patterns. Both the accelerometer and the data logger can be miniaturised to one small instrument that can be carried on the trunk during hours of walking. Thus, the method can easily be incorporated in current activity monitors so that 24-h monitoring of postures and activities can be combined with assessment of gait characteristics during these monitoring periods. In addition, the presented method can be a basis for more sophisticated gait analyses during overground walking, e.g. an analysis of kinematic signals or muscle activity within subsequent stride cycles.

BackgroundFalls are a leading cause of injury among older adults and most often occur during walking. While strength and balance training moderately improve falls risk, training reactive recovery responses following sudden perturbations during walking may be more task-specific for falls prevention. The aim of this review was to determine the variety, characteristics and effectiveness of gait perturbation paradigms that have been used for improving reactive recovery responses during walking and reducing falls among healthy older adults.MethodsA systematic search was conducted in PubMed, Web of Science, MEDLINE and CINAHL databases in December 2015, repeated in May 2016, using sets of terms relating to gait, perturbations, adaptation and training, and ageing. Inclusion criteria: studies were conducted with healthy participants of 60 years or older; repeated, unpredictable, mechanical perturbations were applied during walking; and reactive recovery responses to gait perturbations or the incidence of laboratory or daily life falls were recorded. Results were narratively synthesised. The risk of bias for each study (PEDro Scale) and the levels of evidence for each perturbation type were determined.ResultsIn the nine studies that met the inclusion criteria, moveable floor platforms, ground surface compliance changes, or treadmill belt accelerations or decelerations were used to perturb the gait of older adults. Eight studies used a single session of perturbations, with two studies using multiple sessions. Eight of the studies reported improvement in the reactive recovery response to the perturbations. Four studies reported a reduction in the percentage of laboratory falls from the pre- to post-perturbation experience measurement and two studies reported a reduction in daily life falls. As well as the range of perturbation types, the magnitude and frequency of the perturbations varied between the studies.ConclusionsTo date, a range of perturbation paradigms have been used successfully to perturb older adults’ gait and stimulate reactive response adaptations. Variation also exists in the number and magnitudes of applied perturbations. Future research should examine the effects of perturbation type, magnitude and number on the extent and retention of the reactive recovery response adaptations, as well as on falls, over longer time periods among older adults.Electronic supplementary materialThe online version of this article (doi:10.1186/s11556-017-0173-7) contains supplementary material, which is available to authorized users.

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