Parkinson Disease Clinical Trial
Official title:
Development and Research of an Individualized Intelligent Platform for Rehabilitaion in Patients With Parkinson's Disease
The present study aims to compare the clinical efficacy of intelligent POWER therapy, intelligent LSVT-BIG therapy, and the three exercise models currently in clinical use. DCM_IR analysis will also be incorporated into the analysis to develop a personalized and intelligent Parkinson's rehabilitative therapy platform.
Background:
Parkinson's disease is a progressively degenerative disorder. Patients need early screening,
therapeutic intervention, and personalized interaction with outpatient rehabilitative
treatment. In the past, it had been difficult to meet these goals. Recent advances in
bio-sensors technology has enabled collection of bio-metric data. Models of brainwave
analysis have also matured. In addition, our ability to analyze vibrational spectrogram had
also greatly improved. How to combine these enabling technologies to meet the needs of
Parkinson's patients is an urgent topic of research.
Objective:
The present study aims to compare the clinical efficacy of intelligent POWER therapy,
intelligent LSVT-BIG therapy, and the three exercise models currently in clinical use. DCM_IR
analysis will also be incorporated into the analysis to develop a personalized and
intelligent Parkinson's rehabilitative therapy platform.
Method:
Patients will be randomly assigned into three groups, i.e. intelligent POWER, intelligent
LSVT-BIG, and current protocol group. Single blind data collection will be used. Patients
will be evaluated immediately before treatment, immediately after treatment, and 4 weeks
after treatment. Evaluated criteria will include mini-BESTest, Unified Parkinson's disease
rating scale, muscle power of lower extremity, time up and go, walk velocity, step length,
cadence, and Parkinson's disease questionnaire PDQ-39.
Expected Outcome:
An intelligent rehabilitative therapy platform may be built on the sensor data and
neural-network analysis of the data. The platform will enable patients to interact with
medical personnel on out-patient basis. If further combined with DCM_IR analysis,
personalized therapeutic efficacy indicator may be uncovered, thereby, realizing intelligent
personalized rehabilitative therapy.
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