The stride data re divided into 4 different stride types: • Normal • Abnormal: Slow, Fast, • Irregular: Right Antalgic, Left Antalgic Each type of stride file has 4 different subjects, labeled subjects 1 through 4. The data reflect trails/experiments from 4 subjects, 5 stride types, and 2 gait parameters (stride width/leg gap). Each experiment/trial contains six segments (of walking). Normal gait is defined as walking at a normal pace, one that requires no conscious attention or focus on the nature or speed of gait. Fast gait is defined as walking at a brisk pace, as if in a hurry. Slow gait is defined as walking slowly, as if enjoying a sunny day. Right antalgic is defined as walking in such a way that the stance/swing ration on the right side of the body is shortened compared to normal gait. This is achieved by walking with the left shoe off and simulates a right limp. Left antalgic is defined as walking in such a way that the stance/swing ratio on the left side of the body is shortened compared to normal gait. This is achieved by walking with the right shoe off and simulates a left limp. The data for each subject and each type of gait are divided into 6 segments of continuous walking. Each segment measured approximately 34 feet or 10 meters. Therefore, each trial covered approximately 60 total meters. Each segment represents a sequence of continuous steps without stop, pause, or turn. The stride width (or leg gap) data provided represent value (cm) at the peak sensor output associated with each step involving only the swing of the left leg (i.e., mid-stance peak). This is identified as the midstance peak, when the legs are closest together. The leg gap width is the minimum width between the legs during a particular stride. The cadence data represent the steps/minute that the individual took during adjacent steps or strides. To determine these mid-stance peaks, noise in the raw sensor data was first reduced by identifying local maxima in the sensor output that were at least 0.8 s apart. Once these local maxima were identified, the sensor output was filtered by replacing all data that did not correspond to one of these local maxima with value corresponding to the sensor baseline. Then, the local maxima were filtered by their prominence in order to eliminate spurious, low-signal maxima that did not represent mid-stance peaks. Leg Gap width is provided in units of cm. Cadence provided in units of steps per minute.