Controlling a Robotic Hip Exoskeleton with Noncontact Capacitive Sensors

Simona Crea, Silvia Manca, Andrea Parri, Enhao Zheng, Jingeng Mai, Raffaele Molino Lova, Nicola Vitiello, Qining Wang

Research output: Contribution to journalArticlepeer-review


For partial lower-limb exoskeletons, an accurate real-time estimation of the gait phase is paramount to provide timely and well-tailored assistance during gait. To this end, dedicated wearable sensors separated from the exoskeletons mechanical structure may be preferable because they are typically isolated from movement artifacts that often result from the transient dynamics of the physical human-robot interaction. Moreover, wearable sensors that do not require time-consuming calibration procedures are more easily acceptable by users. In this paper, a robotic hip orthosis was controlled using capacitive sensors placed in orthopedic cuffs on the shanks. The capacitive signals are zeroed after donning the cuffs and do not require any further calibration. The capacitive-sensing-based controller was designed to perform online estimation of the gait cycle phase via adaptive oscillators, and to provide a phase-locked assistive torque. Two experimental activities were carried out to validate the effectiveness of the proposed control strategy. Experiments conducted with seven healthy subjects walking on a treadmill at different speeds demonstrated that the controller can estimate the gait phase with an average error of 4%, while also providing hip flexion assistance. Moreover, experiments carried out with four healthy subjects showed that the capacitive-sensing-based controller could reduce the metabolic expenditure of subjects compared to the unassisted condition (mean SEM,-3.2% 1.1).

Original languageEnglish
Article number8766856
Pages (from-to)2227-2235
Number of pages9
JournalIEEE/ASME Transactions on Mechatronics
Issue number5
Publication statusPublished - Oct 2019


  • Capacitive sensing
  • gait phase estimation
  • hip exoskeleton
  • wearable robotics

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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