## 3 Results
The accelerometer data show changes in the shoe's speed along two axes (X, Y), as is shown in Figure 7. Based on these data, one can assume that at the beginning of the movement, the shoe's speed along the \(X\)-axis (forward-backward) increases, which corresponds to the forward movement of the foot when climbing stairs. Then, the speed along the \(X\)-axis decreases, corresponding to a pause on the stairs. The accelerometer data provide foot orientation as well. Spatial orientation and orbit require further signal processing in the form of double integration with respect to time and proper phase angle definition from initial conditions. Actual latencies of the data-transmission process during experimental research are provided in Figure 8. As is seen from the graph, the latencies of the data transmission are not equal for each measurement. However, data-transmission latencies generally do not exceed 2 ms; therefore, such a system can run easily at a much higher operational speed. Fluctuations in latencies can be explained by adjustment of the internal slave  
Figure 6: Gyroscope sensor data around Cartesian axes. Figure 7: Acceleration of the insole during the process of climbing the stairs. microprocessor to the data-reading cycle and occupation of the CPU. The transmission of data distance was small, and its influence was neglected. In case of significant distances, they can affect the data-transmission rate. The transmission rate could also be affected by signal disturbance from other electromagnetic sources; therefore, data-transmission latency can be multiplied by several times. The transmission rate is evaluated in an intended practical experiment environment to determine whether the system retains the required transmission rate in its practical application. In case of an insufficient transmission rate, the required conditions of the experiment's environment are revised (for example, the allowed distance between the human-body interface and the data-reception unit is lowered), or the network configuration and hardware are reassessed (for example, a router can be implemented as an intermediary device for communication). The data-acquisition cycle consists of a transmission process, as shown in Figure 9, and of an idle delay, used to meet the requirement of the maximum input speed allowed by the cloud storage. It can be observed that Tx\({}_{2}\) messages are read once the sensors' reading is over. The measurements of intervals Tx\({}_{\mathrm{IL}}\) (command-message latency) and Rx\({}_{\mathrm{IL}}\) (data-message latency) were displayed in Figure 9, as these messages are sent immediately after being queued for sending. The overall cycle takes approximately 26 ms and matches the allowed input rate of the implemented cloud storage. As shown in the graph, data transmission has a longer duration, and there is a reserve to shorten the latency period. A faster network connection (5 GHz) can ensure faster data transmission. The command for ready state and the request for data hardly depend on the network; these issues are related to the microcontroller. Another possibility of minimizing latency duration is data packing. On the one hand, it will squeeze data and save network facilities. But, on the other hand, it can overload the microcontroller CPU, and time-saving can be flawed. The resulting data-transmission process shows great possibilities for the IoT, when simple devices can be managed using internal network control features. Further network development recently let us implement the hierarchical connection of devices when fast and slow devices can be synchronized into the data flow using smart network facilities. In an additional experiment determining the delay and stability of communication depending on distance and obstacles, several results were obtained that make it possible to understand how applicable this solution is in real gait analysis. Latency was measured in a long corridor at a distance of up to 90 m (Figure 10).