The effective force applied on the crank, the index of pedalling effectiveness, and the economy of movement at 60, 75, 90, and 105 rev/min cadences were examined in nine cyclists and eight triathletes. Tests were performed on two days. Maximal oxygen uptake was measured and the second ventilatory threshold was estimated on day 1 using a stationary bicycle. On day 2, the four different cadences were tested at about 5% below the second ventilatory threshold. A strain gauge instrumented clip-less pedal mounted on the bicycle enabled us to measure the normal and tangential forces exerted on the pedal, while the pedal and crank angles were monitored with the aid of a video system. Based on this information, the effective force and the index of pedalling effectiveness were calculated. Cyclists produced significantly more effective force and a higher index of pedalling effectiveness at 60 and 75 rev/min and were significantly more economic at all cadences than triathletes. The significant and positive correlation between effective force and economy at all cadences suggests that improvement of the effective force would reflect on economy.

WalkinSense is a new device designed to monitor walking. The aim of this study was to measure the accuracy and repeatability of the gait analysis performed by the WalkinSense system. Descriptions of values recorded by WalkinSense depicting typical gait in adults are also presented. A bench experiment using the Trublu calibration device was conducted to statically test the WalkinSense. Following this, a dynamic test was carried out overlapping the WalkinSense and the Pedar insoles in 40 healthy participants during walking. Pressure peak, pressure peak time, pressure-time integral, and mean pressure at eight-foot regions were calculated. In the bench experiments, the repeatability (i) among the WalkinSense sensors (within), (ii) between two WalkinSense devices, and (iii) between the WalkinSense and the Trublu devices was excellent. In the dynamic tests, the repeatability of the WalkinSense (i) between stances in the same trial (within-trial) and (ii) between trials was also excellent (ICC > 0.90). When the eight-foot regions were analyzed separately, the within-trial and between-trials repeatability was good-to-excellent in 88% (ICC > 0.80) of the data and fair in 11%. In short, the data suggest that the WalkinSense has good-to-excellent levels of accuracy and repeatability for plantar pressure variables.

The alterations in gait pattern of people with transfemoral amputation leave them more susceptible to musculoskeletal injury. Principal component analysis is a method that reduces the amount of gait data and allows analyzing the entire waveform. To use the principal component analysis to compare the ground reaction force and center of pressure displacement waveforms obtained during gait between able-bodied subjects and both limbs of individuals with transfemoral amputation. This is a transversal study with a convenience sample. We used a force plate and pressure plate to record the anterior–posterior, medial–lateral and vertical ground reaction force, and anterior–posterior and medial–lateral center of pressure positions of 12 participants with transfemoral amputation and 20 able-bodied subjects during gait. The principal component analysis was performed to compare the gait waveforms between the participants with transfemoral amputation and the able-bodied individuals. The principal component analysis model explained between 74% and 93% of the data variance. In all ground reaction force and center of pressure waveforms relevant portions were identified; and always at least one principal component presented scores statistically different (p < 0.05) between the groups of participants in these relevant portions. Principal component analysis was able to discriminate many portions of the stance phase between both lower limbs of people with transfemoral amputation compared to the able-bodied participants. Principal component analysis reduced the amount of data, allowed analyzing the whole waveform, and identified specific sub-phases of gait that were different between the groups. Therefore, this approach seems to be a powerful tool to be used in gait evaluation and following the rehabilitation status of people with transfemoral amputation.

This study’s aim was two-fold: (i) to test the intra-session reliability of the one-leg balance activity test; and (ii) to assess the influence of age on reaction time (RT) and the differences between dominant and non-dominant feet. Fifty young soccer players with an average age of 12.4 ± 1.8 years were divided into two groups: younger soccer players (n = 26; 11.6 ± 0.9 years) and older soccer players (n = 24; 14.2 ± 0.8 years). Each group then completed four trials (two with each leg) of the one-leg balance activity (OLBA) to evaluate RT under a single-leg stance. Mean RT and the number of hits were calculated, and the best trial was also selected. T-tests and Pearson correlations were performed for statistical analysis. Values for RT were lower, and the number of hits was higher while standing on the non-dominant foot (p = 0.01). MANOVA revealed that the “Dominant Leg” factor did not affect the multivariate composite (Pillai Trace = 0.05; F(4, 43) = 0.565; p = 0.689; Partial ETA Squared = 0.050; Observed Power = 0.174). The “Age” factor did not present an effect on the multivariate composite (Pillai Trace = 0.104; F(4, 43) = 1.243; p = 0.307; Partial ETA Squared = 0.104; Observed Power = 0.355). The results of the present investigation demonstrate that RT may be lower while standing on the non-dominant foot.