Researchers use a soft, wearable robot to help a person living with Parkinson’s walk without freezing

By Vijay Kumar MalesuJan 9 2024Reviewed by Danielle Ellis, B.Sc.

In a recent study published in Nature Medicine, a group of researchers demonstrated the effectiveness of soft robotic apparel in averting Freezing of Gait (FoG) in Parkinson's disease (PD) patients, showcasing significant improvements in mobility and gait quality.

Background 

PD, impacting over 9.4 million people worldwide, with numbers expected to double by 2040, is a leading cause of disability. It is characterized by a loss of dopamine-producing neurons, resulting in impaired movement and gait issues, including FoG in up to 80% of patients. FoG severely restricts physical movement and quality of life, while existing treatments only provide short-term and temporary relief.

The complexity of FoG, involving biomechanical disruptions in walking mechanics, necessitates innovative solutions like wearable robotic devices. However, no specific robotic intervention for FoG in PD exists yet. Consequently, further research is needed to develop effective treatments for this challenging aspect of PD.

About the study

The present study involved a participant who provided written consent, including for blurred photo/video recording. The participant was recruited through convenience sampling and received remuneration for expenses. Cognitive, mobility, and medical screenings, followed by baseline data on PD symptoms and motor function, were acquired at the start of this study.

The main protocol involved five study visits, focusing on the 2-Minute Walk Test (2MWT) during medication 'on-phase' under single-task conditions. The participant walked a marked indoor walkway, alternating between wearing robotic apparel (ASSIST ON) and not (ASSIST OFF/NO SUIT). Additional protocols included dual-tasking during 2MWT to increase cognitive challenge, a medication 'off-phase' 2MWT, and a 6MWT in outdoor settings.

The team assessed the immediacy of the robotic apparel's effects and its biomechanical impact through various walking tests, including a 10-meter walk test using motion capture systems.

The robotic apparel, designed to assist hip flexion, consisted of thigh wraps, waist belts, and shoulder straps, with actuators and sensors mounted on the belt. The actuator generated hip flexion moment using a miniature rope winch design. The controller delivered consistent hip flexion force, using an Inertial Measurement Unit (IMU)-based algorithm to detect stride patterns and apply force during the swing phase of the gait cycle.

Biomechanical data were post-processed to analyze cadence, step length, walking speed, and hip range of motion. FoG episodes were identified through video review and sensor data analysis, focusing on limb movement patterns. The study used various statistical analyses, including Wilcoxon signed-rank tests, descriptive statistics, linear regression, and randomization tests, to evaluate the robotic apparel's impact on gait and FoG. 

Study results 

In the single-subject study, the effectiveness of robotic apparel was evaluated to address FoG in a 73-year-old male with PD. Despite deep brain stimulation and pharmacological management, he experienced frequent, incapacitating FoG episodes. This functional apparel, encompassing the waist and thighs, was integrated with flexible cable-driven actuators and sensors.

The study, spanning six months, involved repeated measurements in both laboratory and real-world outdoor settings. It encompassed a series of tests, 2MWT and 6MWT, under medication 'on-phase' and single-task conditions. Additional testing conditions were designed to provoke FoG, including dual-tasking and walking during medication 'off-phase.' The immediacy of the robotic apparel's effects was also assessed by intermittently toggling its power during continuous walking.

Remarkably, the robotic apparel consistently eliminated FoG across various conditions. In the lab, FoG was entirely averted with the apparel, contrasting with substantial freezing episodes without it. The apparel significantly increased walking distance and reduced stride length variability, demonstrating both gait-enhancing and gait-preserving effects. Outdoor testing revealed substantial FoG mitigation, although not complete elimination, possibly due to the complexity of outdoor walking and environmental triggers.

Biomechanical analysis showed that the apparel significantly increased hip range of motion, step length, and regulated cadence. It improved foot trajectory, contributing to enhanced gait quality and function. These results indicate that correcting fundamental walking mechanics and rhythmicity can effectively avert FoG.

Throughout the study, the participant reported positive experiences with the robotic apparel, noting improved stride length, reduced effort in walking, and prevention of FoG. He expressed interest in using the apparel for broader walking activities outside his home, highlighting its potential impact on the quality of life for individuals with PD.

These findings underscore the potential of biomechanical interventions in managing PD symptoms, offering a promising alternative to current pharmacological, surgical, and behavioral treatments. The participant's positive feedback further suggests its feasibility and acceptability for real-world application.

Conclusions

In this study, a single participant with PD underwent rigorous testing with wearable sensors to assess the effectiveness of robotic apparel in managing FoG. This trial highlighted the apparel's immediate, repeatable, and clinically meaningful impact on improving gait quality and function, effectively averting FoG across various conditions.

The findings suggest that moderate hip flexion assistance during the swing phase of walking can significantly enhance walking ability in PD patients. This work, an early proof of concept, represents a significant step in developing innovative, technology-based interventions for FoG, addressing a critical need in PD management.