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Published on: January 15, 2016
Phase-specific analysis of 180° turning gait in post-stroke hemiplegia
Haochen Tian1, Jiaxin Wang2, Shijie Guo3
1Academy for Engineering & Technology, Fudan University, Shanghai, China.
Background:
The 180° turning movement can be divided into the approach phase, turning phase, and departure phase. Compared with integral turning research, phase‑specific analysis is capable of revealing more detailed and comprehensive turning characteristics. To date, few studies have focused on the phase‑specific characteristics of turning movements in patients with post‑stroke hemiplegia.
Research Question:
What are the phase‑specific characteristics and differences in 180° turning movements between patients with post‑stroke hemiplegia and healthy older adults?
Methods:
A motion capture system (VICON) with 14 cameras was used to record the 180° turning movements of 12 post‑stroke hemiplegic patients and 12 healthy participants. Seven spatiotemporal gait parameters, seven pelvic movement parameters, and eight gait asymmetry indices were calculated. A three‑factor mixed repeated‑measures ANOVA was employed to determine the effects of group, turning direction, limb side, and phase.
Results:
Compared with healthy controls, post‑stroke hemiplegic patients exhibited slower walking speed, shorter step length and stride length, wider step width, longer turning time, higher proportions of stance phase and double‑support phase, poorer pelvic stability, and greater gait asymmetry. Most of these differences (e.g., walking speed, step width, double‑support phase percentage) showed significant phase‑specific characteristics, especially in the turning phase, and were dependent on turning direction and limb side. The phase‑specific analysis indicated that patients adopted a "Static Uniformity Mode" rather than the "Robust Efficient Mode" used by healthy participants to complete the turning task.
Significance:
This study confirms the value of phase‑specific analysis in revealing post‑stroke hemiplegic patients' turning gait characteristics, filling a gap in this field. It provides a theoretical basis for clinical rehabilitation assessment and for optimizing turning‑assist exoskeletons' sensing, control, and safety.
