**2.5. Signals analysis**

The EMG signals and those from the pressure sensors were recorded digitally at a frequency of 3000 samples per second using an analog-to-digital card CODAS (DataQ Instruments, OH, USA). The records were afterwards selected for further processing based on the signal obtained with the pressure sensors.

Comparison by EMG of Running Barefoot and Running Shod 77

featuring different geometry and damping characteristics. The barefoot condition was interpreted as the one in which the external protection and shock reduction at the beginning of the stance phase were minimal. The standard shoe was harder than the athletic one,

For the realization of this goal we propose more specific objectives: to determine the profile of the muscle electrical activity and the order of muscle participation, to detect changes in the amplitude of the electrical signal muscles, and to measure the level of coactivation of antagonistic muscles. The different phases of the gait cycle were measured based on the records obtained by the pressure sensors (see **Figure 1**) located under the foot or shoe

**Figure 1.** Bilateral support and non-support patterns from each foot obtained with pressure sensors.

The speed was higher when jogging with the own athletic shoes, and of a similar magnitude when jogging barefoot than when using standard sneakers. **Figure 2** shows the mean values of the speed and, for both legs, the mean values of the phases of: support, non support, and double flight. When running shod, the duration of the phases of the stride was different with respect the barefoot condition. The stance phase was shorter and the non-support phase, longer. The time length of the double flight increased. Between the two types of footwear used (standard and athletic) there were differences in speed but not

**Figure 3** shows the EMG signal, processed and expressed as GEAV for the three conditions. To assess the influence of footwear, we have divided the stride into two phases: (1) support phase and (2) non-support phase, each of which exhibited its own characteristics in muscle

In order to check whether there are differences in the muscular effort depending on the locomotion condition, we calculated the area under each muscle's GEAV for each condition and used it as an estimation of that effort. The ANOVA found that there is no statistically significant difference between the three conditions with respect to the general effort

cushioning less the impact.

sole.

in phases.

activity.

**3.1. Muscular activity: EMG** 

required for the locomotion.

In order to determine the intensity of the signal, peak amplitude (peak activity), and time of its appearance, it is necessary to use quantitative methods on the EMG signal such as the LE. The steps to obtain it are: (1) complete (full-wave) rectification of the raw EMG, and (2) obtaining the linear envelop window (LE window) by calculating the average amplitude values contained in a moving window of 50 points.

Further processing was carried out with the signals of six subjects (the records of four subjects were excluded because their signals were not fully valid). From each record, the activity corresponding to 2 (out of 5) cycles were used (5x2 = 10), for 6 subjects (10 x 6 = 60), so 60 cycles were used in each condition. Since there are 3 different conditions, we analyzed a total of 180 (60 x 3) cycles. Therefore, the database consisted of 180 files; each file containing the 51 values of the LE corresponding to each of the 12 muscles and the time length of the phases of the cycle for both feet.

Each file has been then processes in a spreadsheet to obtain time-space parameters and the 51 values of each of the 12 muscles' EMG signals expressed in mV and corresponding to each 2% of the normalized length of jogging cycle.

For each subject, the LE corresponding to the 2% for each consecutive cycle locomotion were averaged across the 10 selected strides resulting in a pattern "ensemble average" of EMG (EAV), which represents an average pattern of the intra-subject LE. Using the EAV of all subjects, the Great Ensemble Average (GEAV) was obtained.

Muscle activity, represented by its LE, was expressed between the 0% and the 100% of the duration of the cycle. The maximum amplitude and time of peak onset were obtained from the GEAV.
