Ye Ma
gait researcher
Facts
10 properties- Instance of
- human
- Occupation
- researcher
- Employer
- Ningbo University[2]
- Educated at
- University of Auckland
- Doctoral advisor
- Shane Sheng Quan Xie, Yanxin Zhang[3][4]
- Academic degree
- Doctor of Philosophy[5]
- Academic thesis
- Patient-Specific Neuromusculoskeletal Models for Improving the Effectiveness of Human-Inspired Gait Rehabilitation Robots[8]
- On focus list of Wikimedia project
- NZThesisProject[9]
🏷️ Also known as
en Ye Ma
🔖 Identifiers · 2
- ORCID iD
- 0000-0002-1964-045X
- OpenAlex ID
- A5026397109
🔗 Connections
Author of 7
A patient-specific EMG-driven neuromuscular model for the potential use of human-inspired gait rehabilitation robots,
Application of supervised machine learning algorithms in the classification of sagittal gait patterns of cerebral palsy children with spastic diplegia,
Deep Learning-Based Upper Limb Functional Assessment Using a Single Kinect v2 Sensor,
Image based beef and lamb slice authentication using convolutional neural networks,
Placement Recommendations for Single Kinect-Based Motion Capture System in Unilateral Dynamic Motion Analysis,
The Validity and Reliability of a Kinect v2-Based Gait Analysis System for Children with Cerebral Palsy,
Validity and Reliability of Upper Limb Functional Assessment Using the Microsoft Kinect V2 Sensor
← Authored by 7
A patient-specific EMG-driven neuromuscular model for the potential use of human-inspired gait rehabilitation robots,
Application of supervised machine learning algorithms in the classification of sagittal gait patterns of cerebral palsy children with spastic diplegia,
Deep Learning-Based Upper Limb Functional Assessment Using a Single Kinect v2 Sensor,
Image based beef and lamb slice authentication using convolutional neural networks,
Placement Recommendations for Single Kinect-Based Motion Capture System in Unilateral Dynamic Motion Analysis,
The Validity and Reliability of a Kinect v2-Based Gait Analysis System for Children with Cerebral Palsy,
Validity and Reliability of Upper Limb Functional Assessment Using the Microsoft Kinect V2 Sensor
Affiliated with 3
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