Computer Interface for Real-Time Gait Biofeedback Using a Wearable Integrated Sensor System for Data Acquisition

Inigo Sanz-Pena, Julio Blanco, Joo H. Kim

Research output: Contribution to journalArticlepeer-review

Abstract

Computer interfaces with visual biofeedback (BF) capabilities in robot-assisted gait training applications can help design subject-specific therapies, define tasks based on the patient's condition, and increase the training outcomes. This study presents the use of an open-source real-time computer interface as a subject-specific visual BF and monitoring tool during gait. The interface is used in combination with a low-cost Wearable integrated Sensor System for Data Acquisition (WiSSDA), which consists of a 3-D printed lower extremity exoskeleton equipped with rotary encoders and pressure-sensitive insoles that measure biometric data during the gait cycle. The system obtains the lower extremities' joint kinematics in the sagittal plane and estimates the vertical component of the foot contact forces and the foot center of pressure. Experimental tests were performed to evaluate different gait parameters using the computer interface as visual BF to guide the subject with reference boundaries of kinematic and kinetic parameters as target trajectories. The results were used to evaluate the interface's performance for specific gait tasks. The results demonstrated the capabilities of the computer interface combined with WiSSDA for robot-assisted gait training applications using BF; providing an open-source, portable, and ambulatory device that can be used in outdoor environments. The proposed system can help bring gait rehabilitation outside the laboratory environment, eliminating the need for stationary equipment.

Original languageEnglish (US)
Pages (from-to)484-493
Number of pages10
JournalIEEE Transactions on Human-Machine Systems
Volume51
Issue number5
DOIs
StatePublished - Oct 2021

Keywords

  • Biofeedback (BF) computer interface
  • data acquisition
  • lower extremity exoskeleton
  • robot-assisted gait training (RAGT)
  • wearable sensors

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Control and Systems Engineering
  • Signal Processing
  • Human-Computer Interaction
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

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