Publications

A Phase-Invariant Linear Torque-Angle-Velocity Relation Hidden in Human Walking Data

E. S. Altinkaynak and D. J. Braun
IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 27, no. 4, pp. 702–711, 2019
DOI
@article{Altinkaynak2019,
  author  = {E. S. Altinkaynak and D. J. Braun},
  title   = {A Phase-Invariant Linear Torque-Angle-Velocity Relation Hidden in Human Walking Data},
  journal = IEEEtnsre,
  volume  = {27},
  number  = {4},
  pages   = {702--711},
  year    = {2019},
  doi     = {10.1109/TNSRE.2019.2899970}
}

This paper shows that the complex dynamics of human walking can be captured with a single linear controller. Analyzing data from seven subjects, the study demonstrates that one sparse, phase-invariant linear relation between joint torques, angles, and velocities explains over 96% of the variance in walking data. This simple controller performs nearly as well as much more complex multi-phase controllers traditionally assumed necessary for locomotion.

Why it matters: Conventional wisdom suggests that walking requires multiple distinct controllers for different gait phases. This work challenges that view, showing that a single compact control structure can explain human walking dynamics. Such simplicity could lead to more efficient and robust control strategies for prostheses and exoskeletons that assist or augment human mobility.