An underactuated wearable arm-swing rehabilitator for gait training

Barnes, Owen R.; Hejrati, Babak; Abbott, Jake J.

doi:10.1109/icra.2015.7139894

Cited by 6 publications

(4 citation statements)

References 18 publications

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“…The data-driven models simply require five independent variables-height, mass, gender, walking speed, and surface slope-to describe the shoulder-angle parameters such as frequency, amplitude, offset value, and phase, as well as the elbow-angle amplitude and offset value. The trajectories generated by Equation 10 may be useful for robotic [20,21] or other rehabilitation devices [6,12] that integrate arm swing in gait rehabilitation. Equation 10 can use a patient's physical information as primary inputs, and walking speed and surface slope can be measured during walking or be provided as predetermined values to generate desired shoulder-angle trajectories.…”

Section: Discussionmentioning

confidence: 99%

“…Equation 10 can use a patient's physical information as primary inputs, and walking speed and surface slope can be measured during walking or be provided as predetermined values to generate desired shoulder-angle trajectories. These trajectories can be applied to the patient by means of devices similar to what is proposed in [20,21] to correct the patient's arm swing for more effective gait rehabilitation.…”

Section: Discussionmentioning

confidence: 99%

“…Although the integration of arm swing in gait rehabilitation has been attempted by previous studies [6,20,21], a fundamental question still needs to be answered: What are the correct and normal arm-swing trajectories that should be utilized for gait rehabilitation and assessment under various conditions? Most studies that propose models for describing arm swing during walking have been motivated to answer the question of whether arm swing is passive or active.…”

Section: Introductionmentioning

confidence: 99%

“…The data-driven models can be used to generate arm-swing trajectories in rehabilitative devices aiming to integrate arm swing in gait rehabilitation of patients with walking disabilities [12,20,21]. Furthermore, the elbow joint range of motion and its relative phase with respect to the ipsilateral shoulder joint angle during walking may be useful in the design and control of poweredelbow prostheses [41,42].…”

Section: Introductionmentioning

confidence: 99%

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Comprehensive quantitative investigation of arm swing during walking at various speed and surface slope conditions

Hejrati

Chesebrough

Foreman

et al. 2016

Human Movement Science

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Previous studies have shown that inclusion of arm swing in gait rehabilitation leads to more effective walking recovery in patients with walking impairments. However, little is known about the correct arm-swing trajectories to be used in gait rehabilitation given the fact that changes in walking conditions affect arm-swing patterns. In this paper we present a comprehensive look at the effects of a variety of conditions on arm-swing patterns during walking. The results describe the effects of surface slope, walking speed, and physical characteristics on arm-swing patterns in healthy individuals. We propose data-driven mathematical models to describe arm-swing trajectories. Thirty individuals (fifteen females and fifteen males) with a wide range of height (1.58-1.91m) and body mass (49-98kg), participated in our study. Based on their self-selected walking speed, each participant performed walking trials with four speeds on five surface slopes while their whole-body kinematics were recorded. Statistical analysis showed that walking speed, surface slope, and height were the major factors influencing arm swing during locomotion. The results demonstrate that data-driven models can successfully describe arm-swing trajectories for normal gait under varying walking conditions. The findings also provide insight into the behavior of the elbow during walking.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%