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Figure 4 shows the flow of data in the estimation system. We use the sensor module in the insole of the shoe for the right foot and require walkers to wear this shoe to collect data during the walking period. The collected data are sent to a smartphone in the pocket of the walkers for storage Oxygenase and processing through the Bluetooth connection. We remove noise in the data received from the foot-worn sensors using a band-pass Butterworth filter with fc1 = 5 Hz, fc2 = 10 Hz. Finally, we apply our calculation method on these data to estimate the walking distance. Figure 4 Diagram of data processing in the estimation system. 2.3. Stride Determination It is clear that the number of walking strides equals the number of swing phases, which is the period immediately after a user pushes off his foot, releasing it from the ground until the foot again contacts the ground. Therefore, to detect swing phases, and thus possibly count the number of walking strides, we analyze the pressure under the walker��s shoes. We basically utilize the data received from pressure sensors to determine the time interval of the swing phase. When a walker releases his foot from the ground, the pressure value of the sensor under his foot will be virtually zero, whereas when the foot contacts the ground, the pressure value is not zero. Based on this fact, we create an on/off filter to detect swing phases of walking. If all pressure sensors point to ��not press�� state, the foot is defined as being in swing phase. However, we experimentally observed that Sensor 8 sometimes provides a level of ��slightly pressed��, corresponding to the 012 value selleck compound in the binary system, when users transit from late swing phase to heel strike phase and are still in the late swing phase. Therefore, to remove this effect, we set a threshold corresponding to the wrong case of Sensor 8, i.e., threshold = 1. This threshold-based method works because the swing phase is only identified when all sensors are in ��off�� state. This means that all sensors should point to the ��no press�� state. Applying these analyses, we create a simple filter to detect the period of the swing phase in human walking: F(k)=0if?p(k)Selleck Gefitinib 5 illustrates the scenario of a pressure value received from walking in a 16 s walking period. The blue part represents the pressure data measured by the pressure sensor integrated under the users�� shoes. The red part shows the result F(k) of the on/off filter presented in Equation (1). In other words, F(k)=1 means the insole is in swing phase at the k moment. Based on this pressure-based swing phase filter, we can determine the starting and stopping moments of swing phases as well as movement. Figure 5 Swing phase determination based on pressure information. 2.4.
