Uncovering Human Natural Walking Patterns at Home
Abstract
The way we walk at home, that is, in a restricted and obstacle-ridden environment filled
with furniture, reveals crucial information about locomotor efficiency. Trajectories, walking
metrics, and space occupancy are for instance personalized variables that allow studying
indoor human locomotor behavior. Links between psychological states and human loco-
motion(1) have been preliminary addressed, and it would be helpful to identify a walking
signature of psychological states including wellness. The objective of this research was to
study the evolution of human locomotor behavior through (i) space occupancy(2), (ii) loco-
motor trajectories(3) and (iii) indoor walking metrics(4). Activations related to participants’
movements were continuously captured and recorded by a smart floor, the SensFloor(5).
This capacitive proximity capture device was installed in the HUman at home projecT(6)
apartment in Montpellier, South of France. Trajectories were detected, identified and recon-
structed by the Walk@Home algorithm(7) which allowed to quantify walking metrics such as
distance, time, walking velocity and space occupancy. Analyses were conducted on a dyad
of participants, during four years of real occupancy of the apartment. Locomotor behavior
from the first dyad (222 days, 660 000 steps, 423 km) already revealed an average of 190
trajectories per day, with (i) an average walking speed =0,59 m/s (=0,03 m/s), (ii) an av-
erage daily walking distance = 1000m, and (iii) an average walking time of = 1 683,89s.
The longitudinal study of walking parameters over the four years of recording now allows us
to focus on a motor signature of home walking and, in perspectives, on its correspondence
with well-being.