Literature DB >> 15531051

Force tracking system for the assessment of grip force control in patients with neuromuscular diseases.

Gregorij Kurillo1, Anton Zupan, Tadej Bajd.   

Abstract

BACKGROUND: The majority of hand functionality assessment methods consist of the maximal voluntary grip force measurement. Additional knowledge on sensory-motor control can be obtained by capturing functional grip force in a time frame. Tracking methods have been successfully used for the assessment of grip force control in stroke patients and patients with Parkinson's disease.
METHODS: A novel tracking system for the evaluation of grip force control is presented. The system consists of a grip-measuring device with the end-objects of different shapes which was used as input to a tracking task where the patient applied the grip force according to the visual feedback. The grip force control was assessed in 20 patients with neuromuscular diseases and 9 healthy subjects. The performance of two tracking tasks was analysed in five grips. The ramp-tracking task was designed to assess the grip strength and muscle fatigue. The sinus-tracking task was used to evaluate grip force control during periodic muscle activation.
FINDINGS: The results suggest that in some patients the disease did not affect their grip force control despite evident muscular weakness. Most patients produced larger tracking errors in precision grip while the healthy subjects showed less significant differences in performance among the grips tested.
INTERPRETATION: The current study investigated force control in patients with neuromuscular diseases where detection of small changes in motor performance is important when following the progress of disease. The presented evaluation method can provide additional information on muscle activation and fatigue as compared to traditional grip strength testing.

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Year:  2004        PMID: 15531051     DOI: 10.1016/j.clinbiomech.2004.07.003

Source DB:  PubMed          Journal:  Clin Biomech (Bristol, Avon)        ISSN: 0268-0033            Impact factor:   2.063


  16 in total

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8.  Reversing cognitive-motor impairments in Parkinson's disease patients using a computational modelling approach to deep brain stimulation programming.

Authors:  Anneke M M Frankemolle; Jennifer Wu; Angela M Noecker; Claudia Voelcker-Rehage; Jason C Ho; Jerrold L Vitek; Cameron C McIntyre; Jay L Alberts
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9.  Deficits in motor abilities for multi-finger force control in hemiparetic stroke survivors.

Authors:  Yushin Kim; Woo-Sub Kim; Kyung Koh; BumChul Yoon; Diane L Damiano; Jae Kun Shim
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10.  Brain Activation in Primary Motor and Somatosensory Cortices during Motor Imagery Correlates with Motor Imagery Ability in Stroke Patients.

Authors:  Linda Confalonieri; Giuseppe Pagnoni; Lawrence W Barsalou; Justin Rajendra; Simon B Eickhoff; Andrew J Butler
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