The analysis of human gait is of fundamental importance for the monitoring and enhancement of athletes’ performances. The kinematics and kinetics of human gait are mostly investigated with optical motion capture systems and force plates that require specialised laboratories and limit the possible test conditions. On the contrary, body-attached sensor networks provide an opportunity for long-term acquisitions in unsupervised, naturalistic scenarios. In this study, a wearable sensor network consisting of two wireless dataloggers and two instrumented insoles with eight pressure sensors each is used. Custom algorithms for the automatic detection of hike events and the estimation of the related temporal parameters based on sensors data are presented. The proposed algorithms were tested against laboratory measurements performed on an instrumented treadmill and showed relative errors of less than 2.5% in the estimation of stride time, step time and cadence. Higher relative errors were found in the estimation of stance and swing phases. The developed algorithms were also applied in a field study. In this paper data from one subject are considered. The aim of this research work is to provide an effective sensor-based methodology for the evaluation of gait parameters in naturalistic settings.

The aim of this research was to study the effects of cycling gloves on hand-arm vibrations in realistic load scenarios. A test has been performed in the laboratory, a road bicycle handlebar was mounted to the hydraulic cylinder of a universal testing machine, and the bicycle was fixed on an indoor trainer. Tests were executed for three different hand sizes (small, medium, large), three different frequency ranges (15–25, 35–45, 85–95 Hz), with two different types of gloves (gel-padded; non-padded) and without gloves. The amplitudes and each frequency bands were obtained from a previous field test. Hand-arm vibrations were quantified by means of root mean square values of the frequency-weighted accelerations measured at the subject’s wrist joint. Analysis of variance (ANOVA) showed no significant effect of gloves in reducing vibration transmissibility.

This research activity aims to develop new cycling gloves. A first step was focused on the definition of the functional requirements through user centred design methods. Since vibrations coming to the hand-arm system of a cyclist have a considerable effect a second step was concentrated on the analysis of hand-arm vibrations in road cycling. The paper shows results of laboratory tests executed for three different hand sizes, three different frequency ranges, with two different type of gloves and without gloves. Load conditions used for the test were determined with a former field test. Results obtained were analysed using Analysis of Variance (ANOVA), that showed no significant effect of existing gloves in reducing vibration transmissibility. This led to the need of new kind of cycling gloves that could reduce those vibrations and increase the cyclist’s comfort.