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.
Nearly 1% of people older than 65 years of age have been diagnosed with Parkinson's disease (PD) and as the disease worsens almost all people with PD develop impairments in walking (gait) and postural capabilities that severely impact independence, health, and quality of life. This project is directed at developing a novel wearable system with real-time feedback capability and testing its feasibility in PD to improve gait and posture parameters (step length, step time, arm swing, and upright posture) that are greatly impaired and shown to increase the risk of falling in people with PD. The proposed system will feature two modes of feedback, one to facilitate learning and practicing desired gait and posture movements and the other to maintain the desired movement patterns during daily activities, which in turn may significantly enhance independence and quality of life in people with PD.
