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Communication Dans Un Congrès Année : 2022

Uncovering Human Natural Walking Patterns at Home

Mélodie Sannier
Stefan Janaqi
Gérard Dray
Benoit G. Bardy


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.
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Dates et versions

hal-03858175 , version 1 (17-11-2022)


  • HAL Id : hal-03858175 , version 1


Mélodie Sannier, Stefan Janaqi, Gérard Dray, Benoit G. Bardy. Uncovering Human Natural Walking Patterns at Home. HUT LaConf 2022 - L'interdisciplinarité au service des environnements intelligents, Nov 2022, Montpellier, France. ⟨hal-03858175⟩
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