The Efficacy of Online Exergaming-Integrated Physiotherapy for Parkinson's Disease

NCT ID: NCT06317792

Last Updated: 2024-03-19

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Clinical Phase: NA
• Total Enrollment: 50 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2024-04-01
• Study Completion Date: 2026-06-30

Brief Summary

To validate the efficiency of online exergaming-based physiotherapy. We will enroll patients with Parkinson's disease in postural instability and gait disturbance motor phenotype in the study and divide them into two groups in a randomized controlled study.

Detailed Description

The investigators will enroll patients in PIGD and divide them into two groups in a randomized controlled study. Participants received an exergaming intervention using the Kinect sensor (Microsoft Corporation, Redmond, WA, USA) from a commercially available exercise system (HappyGoGo, LONGGOOD MEDITECH LTD., Taipei, Taiwan). The Kinect sensor incorporates infrared light and a video camera, which creates a 3D map of the area in front of it. This device provides full-body 3D motion capture.

The online exergaming-based physiotherapy programs focus on training in shoulder, hip, and knee ROM balance, weight-bearing, strength, weight shifting, and walking based on RF in machine learning to the features selection in patients with PIGD. The training tasks consist of 10 pieces of training (20 minutes per session, five sessions every week, for 8 weeks). Five exergaming programs were used for training, designed to incorporate an appropriate level of challenge to match the ability and fitness of patients with PD.

To confirm the status of individual training at home, the data will be sent back to the computer output report of the medical side after each training is completed. These data include the quantitative data of a joint ROM, the movement cycle change diagram, and the upper and low limb movements decomposed by each movement plane. The investigators also obtain the trajectory path mapping to understand whether the quality of individual actions is accurate, in place, and line with expected benchmarks.

Safety and Tolerability: If the patient can not complete half of the rehabilitation program, this/her data will be excluded from the analysis.

Exergame rehabilitation outcome assessments To evaluate the efficiency and the durability of the training effect. Outcomes were measured at five different periods including Month 0 (pretest) (clinical score, gait cycle, cognitive function, and fMRI), Month 2 (posttest) (clinical score, gait cycle, and fMRI), and Month 8 (follow-up) (clinical score, gait cycle, and cognitive function) and Year 2 and year 3 (follow-up) (clinical score, gait cycle, and cognitive function).

1. Functional Outcome Measure: Clinical scores and parameters of walking gait cycle The Functional Outcome measure includes the (1) UPDRS score, (2) Tinetti balance and gait score, (3) Berg Balance Scale, (4) Time-up to go test, and (5) parameters in the gait cycle including plantar pressure measurement, static and dynamic balance measures, COP trajectory measurements during gait initiation, and spatiotemporal and kinematic gait analysis in straightforward walking and turning through study completion, an average of three years.

2. Secondary outcome measures include Severity, frequency, and situations of falling and Physical (balance, mobility, freezing of gait, habitual physical activity) and psychological (fear of falling, affect) measures during the intervention and through study completion, an average of three years.

Conditions

Parkinsonism in Diseases Classified Elsewhere

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: TREATMENT
• Blinding Strategy: DOUBLE

Study Groups

Online exergaming-based physiotherapy intervention group

The training tasks consist of a set of 10 pieces of training (20 min per session, five sessions every week, for 8 weeks)

Group Type: EXPERIMENTAL

online exergaming-based physiotherapy programs

Intervention Type: OTHER

The online exergaming-based physiotherapy programs focus on training in shoulder, hip, and knee ROM balance, weight-bearing, strength, weight shifting, and walking based on RF in machine learning to the features selection in patients with PIGD. The training tasks consist of a set of 10 pieces of training (20 min per session, five sessions every week, for 8 weeks). Five exergaming programs were used for training, designed to incorporate an appropriate level of challenge to match the ability and fitness of patients with PD.

Online exergaming-based physiotherapy observation group

Observation only

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

online exergaming-based physiotherapy programs

The online exergaming-based physiotherapy programs focus on training in shoulder, hip, and knee ROM balance, weight-bearing, strength, weight shifting, and walking based on RF in machine learning to the features selection in patients with PIGD. The training tasks consist of a set of 10 pieces of training (20 min per session, five sessions every week, for 8 weeks). Five exergaming programs were used for training, designed to incorporate an appropriate level of challenge to match the ability and fitness of patients with PD.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

1． Clinical diagnosis of Parkinson's disease

Exclusion Criteria

1. Moderate and severe dementia (Clinical Dementia Rating more than or equal to 2)

2. Advanced PD stage (Hoehn and Yahr staging equal or more than four)

• Minimum Eligible Age: 20 Years
• Maximum Eligible Age: 90 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

National Science and Technology Council

FED

Sponsor Role: collaborator

Chang Gung Memorial Hospital

OTHER

Sponsor Role: lead

Responsible Party

Cheng-Hsien Lu, MD, MSc

Professor of neurology

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine

Kaohsiung City, , Taiwan

Countries

Taiwan

Central Contacts

Cheng-Hsien Lu, MD

Role: CONTACT

chlu99@adm.cgmh.org.tw

+886975056603

Other Identifiers

202201719B0

Identifier Type: -

Identifier Source: org_study_id