Early Intelligent Active Assistance in Walking for Hemiplegic Patients under Suspension Protection: A Randomized Controlled Trial

Abstract

BACKGROUND: Hemiplegia, a prevalent stroke-related condition, is often studied for motor dysfunction; however, spasticity remains under-researched. Abnormal muscle tone significantly hinders hemiplegic patients' walking recovery. OBJECTIVE: To determine whether early suspension-protected training with a personal assistant machine for stroke patients enhances walking ability and prevents muscle spasms. METHODS: Thirty-two early-stage stroke patients from Shenzhen University General Hospital and the China Rehabilitation Research Center were randomly assigned to the experimental group (n=16) and the control group (n=16). Both groups underwent 4 weeks of gait training under the suspension protection system for 30 minutes daily, 5 days a week. The experimental group used the personal assistant machine during training. Three-dimensional gait analysis (using the Cortex motion capture system), Brunnstrom staging, Fugl-Meyer Assessment for lower limb motor function, Fugl-Meyer balance function, and the modified Ashworth Scale were evaluated within 1 week before the intervention and after 4 weeks of intervention. RESULTS AND CONCLUSION: After the 4-week intervention, all outcome measures showed significant changes in each group. The experimental group had a small but significant increase in the modified Ashworth Scale score (P < 0.05, d=|0.15|), while the control group had a large significant increase (P < 0.05, d=|1.48|). The experimental group demonstrated greater improvements in walking speed (16.5 to 38.44 cm/s, P < 0.05, d=|4.01|), step frequency (46.44 to 64.94 steps/min, P < 0.05, d=|2.32|), stride length (15.50 to 29.81 cm, P < 0.05, d=|3.44|), and peak hip and knee flexion (d=|1.82| to |2.17|). After treatment, the experimental group showed significantly greater improvements than the control group in walking speed (38.44 vs. 26.63 cm/s, P < 0.05, d=|2.75|), stride length, peak hip and knee flexion (d=|1.31| to |1.45|), step frequency (64.94 vs. 59.38 steps/min, P < 0.05, d=|0.85|), and a reduced support phase (bilateral: 24.31% vs. 28.38%, P < 0.05, d=|0.88|; non-paretic: 66.19% vs. 70.13%, P < 0.05, d=|0.94|). For early hemiplegia, personal assistant machine-assisted gait training under the suspension protection system helps establish a correct gait pattern, prevents muscle spasms, and improves motor function.

1. Introduction

Stroke is the second leading cause of death globally and the primary cause of adult disability [1], significantly impacting patients' quality of life and healthcare systems. Approximately 80% of stroke survivors experience motor dysfunction, particularly in lower limb ambulation [2]. Restoring walking function is crucial for daily life reintegration and preventing secondary complications [3]. However, traditional gait rehabilitation faces limitations: early-stage patients often require therapist-assisted, body weight-supported training due to muscle weakness, balance deficits, and spasticity risks, leading to insufficient intensity and standardization challenges [4]. Passive training models lacking real-time biomechanical feedback may reinforce compensatory movements and abnormal motor patterns [5]. Addressing these gaps through technological innovation remains a critical challenge in neurorehabilitation.

In recent years, the integration of body weight support systems with smart assistive devices has introduced innovative approaches to stroke rehabilitation. The body weight support system mitigates fall risks by providing dynamic body weight support, enabling multiplanar gait training in a safe environment [6]. Intelligent walking aids, such as exoskeletons and wearable gait-assist devices, utilize sensors to monitor joint kinematics in real time and guide standardized movements through mechanical feedback [7]. For example, the hybrid assistive limb employs surface electromyography to drive hip and knee torque assistance, significantly enhancing gait symmetry in stroke patients [8], while the Ekso GT utilizes inertial measurement units to deliver real-time gait-phase cues, thereby reducing compensatory trunk tilt [9]. However, current devices predominantly focus on mid-to-late rehabilitation phases, with limited evidence supporting their efficacy in preventing early-stage spasticity and establishing correct motor patterns.