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Article citations


Frenkel-Toledo, S., Giladi, N., Peretz, C., Herman, T., Gruendlinger, L. and Hausdorff, J.M. (2005) Treadmill Walking as an External Pacemaker to Improve Gait Rhythm and Stability in Parkinson’s Disease. Movement Disorders, 20, 1109-1114.

has been cited by the following article:

  • TITLE: Application of Multiple Sensor Data Fusion for the Analysis of Human Dynamic Behavior in Space: Assessment and Evaluation of Mobility-Related Functional Impairments

    AUTHORS: Thompson Sarkodie-Gyan, Huiying Yu, Melaku Bogale, Noe Vargas Hernandez, Miguel Pirela-Cruz

    KEYWORDS: Superimposed Body Segments, Transfer Functions, Multiple Sensor Data Fusion, Musculoskeletal System

    JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.10 No.4, April 30, 2017

    ABSTRACT: The authors have applied a systems analysis approach to describe the musculoskeletal system as consisting of a stack of superimposed kinematic hier-archical segments in which each lower segment tends to transfer its motion to the other superimposed segments. This segmental chain enables the derivation of both conscious perception and sensory control of action in space. This applied systems analysis approach involves the measurements of the complex motor behavior in order to elucidate the fusion of multiple sensor data for the reliable and efficient acquisition of the kinetic, kinematics and electromyographic data of the human spatial behavior. The acquired kinematic and related kinetic signals represent attributive features of the internal recon-struction of the physical links between the superimposed body segments. In-deed, this reconstruction of the physical links was established as a result of the fusion of the multiple sensor data. Furthermore, this acquired kinematics, kinetics and electromyographic data provided detailed means to record, annotate, process, transmit, and display pertinent information derived from the musculoskeletal system to quantify and differentiate between subjects with mobility-related disabilities and able-bodied subjects, and enabled an inference into the active neural processes underlying balance reactions. To gain insight into the basis for this long-term dependence, the authors have applied the fusion of multiple sensor data to investigate the effects of Cerebral Palsy, Multiple Sclerosis and Diabetic Neuropathy conditions, on biomechanical/neurophysiological changes that may alter the ability of the human loco-motor system to generate ambulation, balance and posture.