Wearable Real-Time Feedback System to Improve Gait and Posture in Parkinson's Disease

NCT03953222 | Unknown

• 1 other identifier: STUDY00007993
• Study Type: interventional
• Target: 26
• Locations: 0 countries
• Sites: N/A

Brief 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. The investigators 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 the investigators' 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.

Conditions

Parkinson Disease

Keywords

Parkinson's disease; Real-time feedback; Gait; Posture; Rehabilitation

Outcome Measures

Primary Outcomes (5)

• Intra-class correlation coefficient Reliability coefficient

  These measures will be utilized to test the validity of the wearable real-time feedback system.

  Year 1

• Step length

  Any increases in step length during feedback compared to no feedback will indicate that gait amplitude can be improved by the proposed real-time feedback system.

  Year 2

• Back Angle

  Any increases in back angle during feedback compared to no feedback will indicate improvements in upright posture due to the wearable real-time feedback system.

  Year 2

• Step-length coefficient of variation

  Any decreases in the coefficient of variation in step length during feedback compared to no feedback will indicate that the wearable real-time feedback system can improve consistency in gait amplitude.

  Year 2

• Step-time coefficient of variation

  Any decreases in the coefficient of variation in step time during feedback compared to no feedback will indicate that the wearable real-time feedback system can improve gait rhythmicity.

  Year 2

Study Arms (1)

Experimental

EXPERIMENTAL

A single group of people with Parkinson's disease will undergo real-time feedback intervention.

Device: Wearable real-time feedback device

Interventions

Wearable real-time feedback device DEVICE

The proposed wearable device can provide real-time feedback of primary gait and posture measures through auditory feedback. The feasibility of people with Parkinson's disease (PD) to utilize to feedback to modulate and improve their gait and posture will be investigated. Two types of feedback will be studied: (a) continuous feedback involving sonification of movements to facilitate learning proper movements (such as to take big steps, swing arms, rhythmic walking, maintain upright posture, etc.) and (b) on-demand feedback where the feedback is provided only if necessary to reduce overload of information and prevent developing dependency on the system.

Experimental

Eligibility Criteria

• Age: 50 Years - 80 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Age range must be between 50-80 years for males and females
• Diagnosis of idiopathic Parkinson's disease (PD) according to United Kingdom Brain Bank Criteria
• Unified Parkinson's Disease Rating Scale (UPDRS) walking score \>= 1 during on-medication state
• Stable dose of PD medication for 4 weeks prior to screening
• Ability to perform long (100-meter) walking trials

You may not qualify if:

• Presence of dementia according to Emre criteria
• Regular use of assistive gait device, such as a walker or cane
• Presence of significant ON/OFF motor fluctuations (\>25% throughout the day), frequent falls (UPDRS fall score \> 1), or freezing leading to falls or balance impairment, that in the opinion of the medical monitor (Dr. Shill or a St. Joseph's Hospital and Medical Center sub-investigator) can affect the subject's safety or compliance with the study protocols
• Recent history of unstable heart or lung disease, evidence of pregnancy (self-reported by patient), major neurological (e.g., stroke, except PD) or metabolic problems (e.g., diabetes).
• Postural hypotension (symptomatic or any prior history of postural hypertension), cardiovascular disorders, musculoskeletal disorders, or vestibular dysfunction limiting locomotion or balance
• Lack of approval from subject's cardiologist or primary care physician (PCP) to participation in the study
• A medication schedule that results in having to take a dose of PD medication during the data collection sessions ( to avoid confounding factors of medication dosage due to necessity to take medication during data collection sessions
• Untreated chemical addiction or abuse or uncontrolled psychiatric illness
• Failure to sign informed consent

Sponsors & Collaborators

• Arizona State University: lead
• St. Joseph's Hospital and Medical Center, Phoenix: collaborator

MeSH Terms

Conditions

Parkinson Disease

Condition Hierarchy (Ancestors)

Parkinsonian Disorders; Basal Ganglia Diseases; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Movement Disorders; Synucleinopathies; Neurodegenerative Diseases

Central Study Contacts

Narayanan Krishnamurthi

CONTACT

16024960912; Narayanan.Krishnamurthi@asu.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: TREATMENT
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Assistant Professor

Study Record Dates

• First Submitted: May 10, 2019
• First Posted: May 16, 2019
• Study Start: October 1, 2020
• Primary Completion: March 30, 2021
• Study Completion: June 30, 2021
• Last Updated: June 5, 2020

Record last verified: 2020-06

Data Sharing

• IPD Sharing: Will not share