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生物医学工程评论综述™
SJR: 0.207 SNIP: 0.376 CiteScore™: 0.79

ISSN 打印: 0278-940X
ISSN 在线: 1943-619X

生物医学工程评论综述™

DOI: 10.1615/CritRevBiomedEng.v28.i12.410
pages 237-245

On Automatic Determination of Movement Phases in Manual Transport During the Precision Grip

Nasser Hosseini
Department of Neurology, Goteborg University, S-413 45 Goteborg; and Department of Signals and Systems, Chalmers University of Technology, Goteborg, Sweden
Blanka Hejdukova
Departmeпt of Neurology, First Faculty of Medicine, Charles University, Prague, Czech Republic
Pall E. Ingvarsson
Department of Neurology, Goteborg University, S-413 45 Goteborg, Sweden
Bo Johnels
Department of Neurology, Goteborg University, S-413 45 Goteborg, Sweden
Torsten Olsson
Department of Signals and Systems, Chalmers University of Technology, Goteborg, Sweden

ABSTRACT

Integrated movement and force analysis of the precision grip-lift sequence (grasping an object between index finger and thumb) is a useful tool in studies on manipulative hand functions. The everyday Manual Transport tasks, moving objects from one place to another, exhibits powerful test possibilities because it includes the precision grip. In this study, as a step towards the exploitation of these possibilities, we created an algorithm that extracts sequence of phases in this task.
The mathematical and dynamical properties of the movement and force signals were used to determine the start and the end of each phase. The grip-lift synergy was quantified by the con-elation coefficient during each phase.
Eight patients with Parkinson's Disease (PD) and 10 healthy persons were studied. The PD patients were tested both in the medicated (ON) and the unmedicated (OFF) state. The object was lifted with the index finger and the thumb, moved a short distance, and put down on a shelf. The preliminary results of these experiments displayed significantly higher coordination between the grip and load forces in the initial phases, before the lift was completely established, than during the transport phases. This was evident both in PD patients and healthy subjects.
This method provides an automatic analysis of the motor performance during an arm-hand movement that is important in daily life to aid in clinical diagnosis.


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