Towards Wearable-Inertial-Sensor-Based Gait Posture Evaluation for Subjects with Unbalanced Gaits
SEN QIU,
Huihui Wang,
Jie Li,
Hongyu Zhao,
Zhelong Wang,
Jiaxin Wang,
Qiong Wang,
Dirk Plettemeier,
Michael Bärhold,
Tony Bauer,
Bo Ru
Affiliations
SEN QIU
Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education,
Dalian University of Technology, Dalian 116024, China
Huihui Wang
School of Fundamental Education, Dalian Neusoft University of Information, Dalian 116023, China
Jie Li
Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education,
Dalian University of Technology, Dalian 116024, China
Hongyu Zhao
Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education,
Dalian University of Technology, Dalian 116024, China
Zhelong Wang
Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education,
Dalian University of Technology, Dalian 116024, China
Jiaxin Wang
Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education,
Dalian University of Technology, Dalian 116024, China
Qiong Wang
Chair for Radio Frequency and Photonics Engineering, Communication Laboratory,
Technische Universität Dresden, 01062 Dresden, Germany
Dirk Plettemeier
Chair for Radio Frequency and Photonics Engineering, Communication Laboratory,
Technische Universität Dresden, 01062 Dresden, Germany
Michael Bärhold
Chair for Radio Frequency and Photonics Engineering, Communication Laboratory,
Technische Universität Dresden, 01062 Dresden, Germany
Tony Bauer
Chair for Radio Frequency and Photonics Engineering, Communication Laboratory,
Technische Universität Dresden, 01062 Dresden, Germany
Bo Ru
School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China
Human gait reflects health condition and is widely adopted as a diagnostic basisin clinical practice. This research adopts compact inertial sensor nodes to monitor the functionof human lower limbs, which implies the most fundamental locomotion ability. The proposedwearable gait analysis system captures limb motion and reconstructs 3D models with high accuracy.It can output the kinematic parameters of joint flexion and extension, as well as the displacementdata of human limbs. The experimental results provide strong support for quick access to accuratehuman gait data. This paper aims to provide a clue for how to learn more about gait postureand how wearable gait analysis can enhance clinical outcomes. With an ever-expanding gait database,it is possible to help physiotherapists to quickly discover the causes of abnormal gaits, sports injuryrisks, and chronic pain, and provides guidance for arranging personalized rehabilitation programsfor patients. The proposed framework may eventually become a useful tool for continually monitoringspatio-temporal gait parameters and decision-making in an ambulatory environment.
