Quantitative Evaluation of Spasticity in Upper Limb based on Muscle Model of Hemiparesis
Objectives
Objective 1: To model the stroke patient's upper extremity physical recovery characteristics using appropriate classification method
Objective 2: To define the dynamic mapping between patient's recovery parameters and control parameters using intelligent model free technique
Objective 3: To evaluate the performance of the adaptive impedance control framework on the robot-assisted neuro-rehabilitation platform
Paper published
Classifier SVM: 76% accuracy; Features selection 1) Catch Position 2) 3)4); related paper publish-1
simulation: adaptive control with switching event (Hybrid Automata)
Apply controller on hardware and test the performance 
Thesis outline
3 conference
1 scopus journal
PhD requirement:
1 Q1/Q2 journal
1 Q3/Q4 journal + 1 scopus journal
4 scopus journal
Chapter 1:Introduction
Chapter 2: Literature Review
Chapter 3: Methodology
Chapter 4: Clinical Database
Chapter 6: Controller Framework
Chapter 7: Prototype Development
Chapter 5: Classification
Chapter 8: Conclusion and Recommendation
Problem statement
Research Objectives
New Finding Knowledge
Scope and limitation
Significance of research
Outline of thesis
Introduction
Neurological Assessment Tools
Spasticity
Articulation of upper limb
Robotic Assessment rehabilitation
Control strategies
Summary
Classification
Research Framework
Research Method
Clinical Data Measurement
Clinical Data Analysis
Feature Extraction
Features Selection
Classifier
System Design
Software Design