Twenty-six healthy young adult (25.9±3.0 years; 175.7±8.8 cm; 72.9±11.9kg; 12 male) and 24 healthy older adult (70.9±4.1 years; 173.2±11.2 cm; 76.2±13.2 kg; 13 male) subjects were recruited and provided informed consent for this study. All subjects were independently residing in the community, were able to ambulate independently for a distance of 60 meters without an assistive device and were not diagnosed with a progressive neurologic condition. All subjects were free of any pathological condition that directly affects the musculoskeletal system, leading to an abnormal walking pattern. The University’s Institutional Review Board approved all study procedures.
Prior to data collection, subjects were asked to walk on a treadmill for a maximum of eight minutes. This eight-minute warm-up has been considered sufficient for individuals to achieve a proficient treadmill movement pattern 12 (link) . During the eight-minute warm-up a self-selected speed was found. If a subject indicated that a speed was comfortable, they continued to walk at that speed for one minute and then asked again if the speed was too fast or too slow. If they indicated it was too fast, the treadmill was slowed or vice versa. This continued until a comfortable speed was found. After the warm-up period, subjects were asked to walk on the treadmill at their selected speed for a total of three minutes while three-dimensional marker trajectories were recorded. Active rigid body markers were placed on the lateral sides of the foot and six position sensors recorded at 100 Hz (Optotrak Certus system; Northern Digital Inc., Waterloo, Canada). In addition, virtual markers were identified prior to data collection through the use of wand marking. These markers included the location of the toe, heel and the first and fifth metatarsal heads. The position data of the virtual markers was tracked in real-time (First Principles software; Northern Digital Inc., Waterloo, Canada) with reference to the corresponding rigid bodies. The unfiltered position data for the x, y, and z coordinates of each virtual marker were exported and processed using custom computer code (MatLab; Mathworks Inc., Natick, Massachusetts). This software calculated step length, step width and step time for each subject. Step length was defined as the distance between heel contact and subsequent heel contact of the contralateral foot. Step width was defined as the mediolateral distance between heel markers at successive heel strikes. Step time was defined as the amount of time from heel strike of one foot to the subsequent heel strike of the contralateral foot. All subjects walked a minimum of 200 steps during the data collection period. Therefore, the time series of step length, step width and step time were cut to 200 data points.
Prior to data collection, subjects were asked to walk on a treadmill for a maximum of eight minutes. This eight-minute warm-up has been considered sufficient for individuals to achieve a proficient treadmill movement pattern 12 (link) . During the eight-minute warm-up a self-selected speed was found. If a subject indicated that a speed was comfortable, they continued to walk at that speed for one minute and then asked again if the speed was too fast or too slow. If they indicated it was too fast, the treadmill was slowed or vice versa. This continued until a comfortable speed was found. After the warm-up period, subjects were asked to walk on the treadmill at their selected speed for a total of three minutes while three-dimensional marker trajectories were recorded. Active rigid body markers were placed on the lateral sides of the foot and six position sensors recorded at 100 Hz (Optotrak Certus system; Northern Digital Inc., Waterloo, Canada). In addition, virtual markers were identified prior to data collection through the use of wand marking. These markers included the location of the toe, heel and the first and fifth metatarsal heads. The position data of the virtual markers was tracked in real-time (First Principles software; Northern Digital Inc., Waterloo, Canada) with reference to the corresponding rigid bodies. The unfiltered position data for the x, y, and z coordinates of each virtual marker were exported and processed using custom computer code (MatLab; Mathworks Inc., Natick, Massachusetts). This software calculated step length, step width and step time for each subject. Step length was defined as the distance between heel contact and subsequent heel contact of the contralateral foot. Step width was defined as the mediolateral distance between heel markers at successive heel strikes. Step time was defined as the amount of time from heel strike of one foot to the subsequent heel strike of the contralateral foot. All subjects walked a minimum of 200 steps during the data collection period. Therefore, the time series of step length, step width and step time were cut to 200 data points.
