A wearable, soft, robotic device could help patients with Parkinson’s disease (PD) walk without experiencing freezing of gait (FoG), early research suggested.
The robotic apparel, worn around the hips and thighs, gently pushes the hips as the leg swings, facilitating a longer stride and preventing FoG, a common disorder in PD that affects nearly all patients over the disease course.
The small, proof-of-concept study included one person with PD. But investigators noted the reduction in freezing and falls and improvement in walking distance and speed was dramatic. Incidence of FoG decreased from 63% to just 6% when the patient wore the robotic garment outdoors. Wearing the device indoors eliminated freezing altogether.
“We demonstrate proof-of-concept that FoG can be averted using a soft robotic device — a machine that aims to apply physical assistance to movement with minimal restriction, a fundamentally different approach to rigid exoskeletons,” lead investigators Conor Walsh, PhD, and Terry Ellis, PhD, PT, told this news organization.
Walsh is a professor at Harvard John A. Paulson School of Engineering and Applied Sciences in Boston, and Ellis is a professor and chair of the physical therapy department and director of the Center for Neurorehabilitation, Boston University, Boston, Massachusetts.
The study was published online on January 5, 2024, in Nature Medicine.
Disabling Disturbance
From a biomechanical perspective, FoG is manifested by an overt breakdown in spatial and temporal mechanics of walking. The impaired limb coordination occurs during the “swing phase” of the gait cycle.
There are currently no interventions that prevent FoG. Available treatment interventions include pharmacotherapy, such as dopamine replacement; deep brain stimulation (DBS) of the subthalamic nucleus; and behavioral interventions, such as cueing strategies. All have shown only modest effects in reducing FoG and, in some cases, might even worsen it, the investigators noted.
“This challenge led us to become interested in leveraging soft wearable robots to deliver mechanical cues to disrupt aberrant gait mechanics and prevent FOG in people with PD,” Dr. Walsh and Dr. Ellis said.
“Wearable robots” have been used to augment kinematics in neurologic conditions, such as stroke, cerebral palsy, and spinal cord injury. Harnessing this technology to address FoG required “a collaboration between engineers, rehabilitation scientists, physical therapists, biomechanists, and apparel designers,” the researchers said.
The wearable robotic device uses cable-driven actuators, which enable physical movement by converting electrical energy into mechanical force, and sensors worn around the waist and thighs. Using motion data collected by the sensors, algorithms estimate the phase of the walking cycle and generate assistive forces in concert with biological muscles.
Real-World Testing
The researchers tested the robotic garment on a 73-year-old man with idiopathic PD of 10-year duration. The man’s ongoing pharmacologic treatment included 1.5 tablets of 25- to 100-mg carbidopa/levodopa taken four times per day, one tablet of 100-mg amantadine twice per day, and one tablet of 200-mg entacapone taken four times per day.
He had also undergone DBS to the globus pallidus internus and utilized behavioral strategies. Despite these interventions, he continued to endure more than 10 episodes of FoG per day and numerous falls.
The patient tended to use walls to stabilize himself when walking. Freezing episodes were observed mostly when he walked in open hallways, turned, walked outdoors, and when he tried to walk and talk simultaneously.
The research was conducted over a 6-month period, with a total of five study sessions that consisted of walking trials. Four were administered in the laboratory. The fifth was conducted in a real-world outdoor community setting.
During the first visit, a biomechanical analysis of walking was performed under single-task conditions during the medication-on phase.
Testing was usually conducted during medication-on phase and under single-task conditions. But testing conditions also included attention-demanding dual tasks and single-task walking during the medication-off phase.
The researchers compared the effects of the assistance of the robotic apparel to no apparel and with the apparel turned off. They measured the percentage of time spent freezing and the total distance walked.