Project Summary
Progressive gait dysfunction is one of the main motor symptoms in people with Parkinson's disease (PD). It
is generally expressed as reduced step length and gait speed, and as increased variability in step time and
length. People with PD also exhibit stooped posture, which besides apparent disfigurement, also disrupts gait.
The gait and posture impairments are usually resistant to the pharmacological treatment, worsen as the
disease progresses, increase the likelihood of falls, and result in higher rates of hospitalization and mortality.
These impairments may be caused by perceptual (spatial awareness) difficulties due to deficiency in
processing information related to movement initiation and execution, which can result in misperceptions of the
actual effort required to perform a desired movement and posture. Due to this, people with PD often depend on
external cues during motor tasks.
Although numerous studies have shown that cues can improve gait in PD, they did not provide feedback of
the performance in real-time which is crucial to perceive, modulate, and achieve the desired movements.
There are a few studies that provided real-time feedback using treadmill-based systems and observed
improvements in gait in PD, however, they are not suitable for practicing target movements conveniently during
free-living conditions, which can strongly reinforce movement patterns and improve clinical outcomes. There
has been very little investigations of wearable real-time feedback (WRTF) systems to improve gait and posture
in PD. To the best of our knowledge, we are aware of only one study that tried to improve gait using a
wearable system with real-time feedback capabilities, but the study did not provide any feedback on posture.
Also, some of the parameters used for feedback were not easy to perceive and modulate in real-time.
Based on our recent success with a treadmill-based real-time feedback system which improved gait and
posture in people with PD, the proposed study will develop a WRTF system, validate its performance with gold
standard measures from a motion capture system, and test its feasibility in a group of people with mild to
moderate PD. The most novel aspects of the proposed system are that it will provide feedback on parameters
such as step length, arm swing, step time, and upright posture which have been greatly affected in PD and
shown to increase the risk factors for balance disorders and falls. In addition, the system will consists of two
types of feedback: a Continuous Feedback (CF) mode and an On-Demand Feedback (ODF) mode. The CF
mode will help users learn and practice desired gait and posture movements and the ODF mode will help to
maintain them during activities of daily living. The gait and posture performances during feedback and non-
feedback conditions will be compared and, if the expected benefits are observed, a follow-up randomized
clinical trial will be performed to test the effectiveness of this novel technology during daily activities.