Regularity of force tremor in Parkinson's disease

Vaillancourt, David E.; Slifkin, Andrew B.; Newell, Karl M.

doi:10.1016/s1388-2457(01)00593-4

Cited by 107 publications

(82 citation statements)

References 22 publications

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“…However, these methods ignore the temporal structure of the variability, limiting inferences that can be made regarding underlying control system dynamics (42). Indeed with pathology and aging there may be no change in the amplitude or modal frequency profile of fluctuations but significant differences in the underlying time-dependent structure (57)(58)(59). Nonlinear means of assessing force fluctuations yields information on the deterministic and stochastic organization of motor system output, which cannot be inferred from conventional linear methods alone (42).…”

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confidence: 99%

Complexity of force output during static exercise in individuals with Down syndrome

Heffernan¹,

Sosnoff²,

Ofori³

et al. 2009

Journal of Applied Physiology

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Force variability is greater in individuals with Down syndrome (DS) compared with persons without DS and is similar to that seen with normal aging. The purpose of this study was to examine the structure (in both time and frequency domains) of force output variability in persons with DS to determine whether deficits in force control are similar between individuals with DS and older adults. An isometric handgrip task at a constant force (30% of maximal voluntary contraction) was completed by individuals with DS (n ϭ 29, age 26 yr), and healthy young (n ϭ 26, age 27 yr) and older (n ϭ 33, age 70 yr) individuals. Mean, standard deviation (SD), and coefficient of variation (CV) were used to analyze the magnitude of force output variability. Spectral analysis and approximate entropy (ApEn) were used to analyze the structure of force output variability. Mean force output for DS was lower than in young controls (P Ͻ 0.05) but no different from old controls. Individuals with DS had greater SD and CV than young and old controls (P Ͻ 0.05). The DS group had a significantly greater proportion of spectral power within the 0-to 4-Hz bandwidth than the young and older controls (P Ͻ 0.05). The DS group had significantly lower ApEn values than the young controls (P Ͻ 0.05), but there were no differences in ApEn between the DS group and the old controls (P Ͼ 0.05). In conclusion, young persons with DS demonstrate enhanced temporal structure and greater amplitude of low-frequency oscillations in the force output signal than age-matched non-DS peers. Interestingly, young persons with DS and older persons without DS have similar time-dependent structure of force output variability. This would suggest a possible link between premature aging and less complex force output in persons with DS. motor control; approximate entropy DOWN SYNDROME (DS) is the most commonly inherited form of developmental disability in North America (7). It is estimated that 1 out of every 700 -1,000 newborns in the United States will be diagnosed with DS, and there are currently over 350,000 persons living with DS in the United States (7). In more than 90% of cases, DS results from an excess of genetic material from chromosome 21 (i.e., trisomy 21). Trisomy 21 results in a constellation of dysfunctions, spanning several physiological systems. Individuals with DS have poor balance, poor coordination, slow reaction time, reduced visual-motor control and sensory acuity, gross and fine motor skill dysfunction, and overall greater movement variability (1,2,11,29,30,60). Motor dysfunction in persons with DS prevents successful completion of many activities of daily living, attenuates vocational productivity, and contributes to low physical work capacity (20,36). This ultimately results in increased dependence on others and assisted living (36). Most striking, lack of mobility has been shown a predictor of mortality in this population (19,52). As such it is imperative to increase the understanding of the factors underlying neuromotor function in DS.The origin of moto...

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confidence: 99%

Complexity of force output during static exercise in individuals with Down syndrome

Heffernan¹,

Sosnoff²,

Ofori³

et al. 2009

Journal of Applied Physiology

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“…In order to eliminate the possibility that changes in the dependent measure of complexity (ApEn, Cross-ApEn) were not merely a reflection of a random stochastic process, the phase-randomised shuffle technique was used to generate surrogate data (Theiler et al 1992;Schreiber and Schmitz 2000;Vaillancourt et al 2001;. This technique maintains the same amplitude and frequency distribution of the original biological signal, but alters the temporal order.…”

Section: Discussionmentioning

confidence: 99%

Removing visual feedback for a single limb alters between-limb force tremor relationships during isometric bilateral contractions

2014

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This study examined how force tremor and muscle activity are altered between limbs when a visual target is removed for one limb during bilateral index finger abduction. Isometric index finger abduction force was examined in healthy adults (23 ± 4 years) when both index fingers abducted simultaneously. Abduction forces ranged from 5 to 20% maximum voluntary contraction, and these target forces were displayed on a PC monitor in front of the subject. Force tremor and first dorsal interosseous (FDI) activity were first collected while subjects viewed visual targets for both index fingers and then when the visual target was removed for the non-dominant index finger. Subjects successfully matched the force amplitudes generated for both limbs regardless of visual condition. When the visual target was removed for one limb, force tremor increased in this limb (p < 0.01). Different power spectral profiles were evident for each FDI EMG when targets were available for both limbs (p < 0.05); however, when one target was removed, the pattern of FDI EMG for the limb without a visual target closely reflected FDI EMG for the limb which had the visual target. The CNS actively modulates muscle activity in each limb to perform visually guided isometric contractions. Given that the goal was to match force output with both limbs, the requirements of the task must be established from the limb that had a visual target, and a copy of those motor commands appears to have been sent to the FDI of the limb without a visual target.

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“…These include slight changes in the timing of motion and the forces applied to objects, minor changes to handwriting and changes in underlying motor control mechanisms. Some of the early changes caused by this neurodegeneration can be measured using specialist techniques such as electromyography [6][7][8][9][10][11][12]. However, such assessments can be time consuming and the equipment and skilled operators are not always readily available.…”

Section: Assessment Using the Manus Platformmentioning

confidence: 99%