IEEE Transactions on Neural Systems and Rehabilitation Engineering (Jan 2023)

Modulation of Arm Swing Frequency and Gait Using Rhythmic Tactile Feedback

  • Mohsen Alizadeh Noghani,
  • Md. Tanzid Hossain,
  • Babak Hejrati

DOI
https://doi.org/10.1109/TNSRE.2023.3249628
Journal volume & issue
Vol. 31
pp. 1542 – 1553

Abstract

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Due to the neural coupling between upper and lower limbs and the importance of interlimb coordination in human gait, focusing on appropriate arm swing should be a part of gait rehabilitation in individuals with walking impairments. Despite its vital importance, there is a lack of effective methods to exploit the potential of arm swing inclusion for gait rehabilitation. In this work, we present a lightweight and wireless haptic feedback system that provides highly synchronized vibrotactile cues to the arms to manipulate arm swing and investigate the effects of this manipulation on the subjects’ gait in a study with 12 participants (20-44 years). We found the developed system effectively adjusted the subjects’ arm swing and stride cycle times by significantly reducing and increasing those parameters by up to 20% and 35%, respectively, compared to their baseline values during normal walking with no feedback. Particularly, the reduction of arms’ and legs’ cycle times translated into a substantial increase of up to 19.3% (on average) in walking speed. The response of the subjects to the feedback was also quantified in both transient and steady-state walking. The analysis of settling times from the transient responses revealed a fast and similar adaptation of both arms’ and legs’ movements to the feedback for reducing cycle times (i.e., increasing speed). Conversely, larger settling times and time differences between arms’ and legs’ responses were observed during feedback for increasing cycle times (i.e., reducing speed). The results clearly demonstrate the potential of the developed system to induce different arm-swing patterns as well as the ability of the proposed method to modulate key gait parameters through leveraging the interlimb neural coupling, with implications for gait training.

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