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A novel method for the quantification of key components of manual dexterity after stroke.

Térémetz M, Colle F, Hamdoun S, Maier MA, Lindberg PG - J Neuroeng Rehabil (2015)

Bottom Line: Four FFM tasks were used: (1) Finger Force Tracking to measure force control, (2) Sequential Finger Tapping to measure the ability to perform motor sequences, (3) Single Finger Tapping to measure timing effects, and (4) Multi-Finger Tapping to measure the ability to selectively move fingers in specified combinations (independence of finger movements).Patients showed less accurate force control, reduced tapping rate, and reduced independence of finger movements compared to controls.Quantifying some of the key components of manual dexterity with the FFM is feasible in moderately affected hemiparetic patients.

View Article: PubMed Central - PubMed

Affiliation: FR3636 CNRS, Université Paris Descartes, Sorbonne Paris Cité, 75006, Paris, France. mteremetz@gmail.com.

ABSTRACT

Background: A high degree of manual dexterity is a central feature of the human upper limb. A rich interplay of sensory and motor components in the hand and fingers allows for independent control of fingers in terms of timing, kinematics and force. Stroke often leads to impaired hand function and decreased manual dexterity, limiting activities of daily living and impacting quality of life. Clinically, there is a lack of quantitative multi-dimensional measures of manual dexterity. We therefore developed the Finger Force Manipulandum (FFM), which allows quantification of key components of manual dexterity. The purpose of this study was (i) to test the feasibility of using the FFM to measure key components of manual dexterity in hemiparetic stroke patients, (ii) to compare differences in dexterity components between stroke patients and controls, and (iii) to describe individual profiles of dexterity components in stroke patients.

Methods: 10 stroke patients with mild-to-moderate hemiparesis and 10 healthy subjects were recruited. Clinical measures of hand function included the Action Research Arm Test and the Moberg Pick-Up Test. Four FFM tasks were used: (1) Finger Force Tracking to measure force control, (2) Sequential Finger Tapping to measure the ability to perform motor sequences, (3) Single Finger Tapping to measure timing effects, and (4) Multi-Finger Tapping to measure the ability to selectively move fingers in specified combinations (independence of finger movements).

Results: Most stroke patients could perform the tracking task, as well as the single and multi-finger tapping tasks. However, only four patients performed the sequence task. Patients showed less accurate force control, reduced tapping rate, and reduced independence of finger movements compared to controls. Unwanted (erroneous) finger taps and overflow to non-tapping fingers were increased in patients. Dexterity components were not systematically related among each other, resulting in individually different profiles of deficient dexterity. Some of the FFM measures correlated with clinical scores.

Conclusions: Quantifying some of the key components of manual dexterity with the FFM is feasible in moderately affected hemiparetic patients. The FFM can detect group differences and individual profiles of deficient dexterity. The FFM is a promising tool for the measurement of key components of manual dexterity after stroke and could allow improved targeting of motor rehabilitation.

No MeSH data available.


Related in: MedlinePlus

Finger force tracking. Group comparison between control subjects (square) and stroke patients (circle). a) Mean RMSE for index finger tracking (±95 % confidence interval) for ramp and hold phase combined. b) Mean release duration for trials at 1N and 2N with the index finger. c) Mean baseline force between trials. Asterisks indicate (here and in the following Figures) significant differences between the two groups, with * p < 0.05 and ** p < 0.01
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Fig3: Finger force tracking. Group comparison between control subjects (square) and stroke patients (circle). a) Mean RMSE for index finger tracking (±95 % confidence interval) for ramp and hold phase combined. b) Mean release duration for trials at 1N and 2N with the index finger. c) Mean baseline force between trials. Asterisks indicate (here and in the following Figures) significant differences between the two groups, with * p < 0.05 and ** p < 0.01

Mentions: Patients and controls applied the same amount of force during the hold phase in 1N (controls: 0.98N ± 0.2; patients: 1.1N ± 0.2; P = 0.24) and 2N conditions (controls: 1.9N ± 0.4; patients: 2.0N ± 0.2; P = 0.36). This task revealed dramatic differences in the precision of force control: stroke patients showed increased tracking error (0.31N ± 0.1) compared to controls (0.13N ± 0.06). This difference was highly significant (GROUP effect: F = 21.18; P = 0.0002; Fig. 3a) and was apparent during both the ramp and hold phases, and at both force levels (P = 0.01). Performance was equally impaired when using the index or the middle finger. Furthermore, time taken to release force at the end of the hold period (Fig. 3b) was significantly prolonged (about six times longer) in stroke patients (702 ms ± 557) compared to controls (123 ms ± 84) (GROUP effect: F = 5.03; P = 0.014). Patients also showed difficulty in not applying force (relaxing) with the lead-finger during the baseline (i.e. between trials, see Fig. 2a). The mean baseline force (Fig. 3c) was significantly different and about four times higher in patients (0.28N ± 0.21) compared to controls (0.07N ± 0.09; GROUP effect: F = 4.10; P = 0.028).Fig. 3


A novel method for the quantification of key components of manual dexterity after stroke.

Térémetz M, Colle F, Hamdoun S, Maier MA, Lindberg PG - J Neuroeng Rehabil (2015)

Finger force tracking. Group comparison between control subjects (square) and stroke patients (circle). a) Mean RMSE for index finger tracking (±95 % confidence interval) for ramp and hold phase combined. b) Mean release duration for trials at 1N and 2N with the index finger. c) Mean baseline force between trials. Asterisks indicate (here and in the following Figures) significant differences between the two groups, with * p < 0.05 and ** p < 0.01
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4522286&req=5

Fig3: Finger force tracking. Group comparison between control subjects (square) and stroke patients (circle). a) Mean RMSE for index finger tracking (±95 % confidence interval) for ramp and hold phase combined. b) Mean release duration for trials at 1N and 2N with the index finger. c) Mean baseline force between trials. Asterisks indicate (here and in the following Figures) significant differences between the two groups, with * p < 0.05 and ** p < 0.01
Mentions: Patients and controls applied the same amount of force during the hold phase in 1N (controls: 0.98N ± 0.2; patients: 1.1N ± 0.2; P = 0.24) and 2N conditions (controls: 1.9N ± 0.4; patients: 2.0N ± 0.2; P = 0.36). This task revealed dramatic differences in the precision of force control: stroke patients showed increased tracking error (0.31N ± 0.1) compared to controls (0.13N ± 0.06). This difference was highly significant (GROUP effect: F = 21.18; P = 0.0002; Fig. 3a) and was apparent during both the ramp and hold phases, and at both force levels (P = 0.01). Performance was equally impaired when using the index or the middle finger. Furthermore, time taken to release force at the end of the hold period (Fig. 3b) was significantly prolonged (about six times longer) in stroke patients (702 ms ± 557) compared to controls (123 ms ± 84) (GROUP effect: F = 5.03; P = 0.014). Patients also showed difficulty in not applying force (relaxing) with the lead-finger during the baseline (i.e. between trials, see Fig. 2a). The mean baseline force (Fig. 3c) was significantly different and about four times higher in patients (0.28N ± 0.21) compared to controls (0.07N ± 0.09; GROUP effect: F = 4.10; P = 0.028).Fig. 3

Bottom Line: Four FFM tasks were used: (1) Finger Force Tracking to measure force control, (2) Sequential Finger Tapping to measure the ability to perform motor sequences, (3) Single Finger Tapping to measure timing effects, and (4) Multi-Finger Tapping to measure the ability to selectively move fingers in specified combinations (independence of finger movements).Patients showed less accurate force control, reduced tapping rate, and reduced independence of finger movements compared to controls.Quantifying some of the key components of manual dexterity with the FFM is feasible in moderately affected hemiparetic patients.

View Article: PubMed Central - PubMed

Affiliation: FR3636 CNRS, Université Paris Descartes, Sorbonne Paris Cité, 75006, Paris, France. mteremetz@gmail.com.

ABSTRACT

Background: A high degree of manual dexterity is a central feature of the human upper limb. A rich interplay of sensory and motor components in the hand and fingers allows for independent control of fingers in terms of timing, kinematics and force. Stroke often leads to impaired hand function and decreased manual dexterity, limiting activities of daily living and impacting quality of life. Clinically, there is a lack of quantitative multi-dimensional measures of manual dexterity. We therefore developed the Finger Force Manipulandum (FFM), which allows quantification of key components of manual dexterity. The purpose of this study was (i) to test the feasibility of using the FFM to measure key components of manual dexterity in hemiparetic stroke patients, (ii) to compare differences in dexterity components between stroke patients and controls, and (iii) to describe individual profiles of dexterity components in stroke patients.

Methods: 10 stroke patients with mild-to-moderate hemiparesis and 10 healthy subjects were recruited. Clinical measures of hand function included the Action Research Arm Test and the Moberg Pick-Up Test. Four FFM tasks were used: (1) Finger Force Tracking to measure force control, (2) Sequential Finger Tapping to measure the ability to perform motor sequences, (3) Single Finger Tapping to measure timing effects, and (4) Multi-Finger Tapping to measure the ability to selectively move fingers in specified combinations (independence of finger movements).

Results: Most stroke patients could perform the tracking task, as well as the single and multi-finger tapping tasks. However, only four patients performed the sequence task. Patients showed less accurate force control, reduced tapping rate, and reduced independence of finger movements compared to controls. Unwanted (erroneous) finger taps and overflow to non-tapping fingers were increased in patients. Dexterity components were not systematically related among each other, resulting in individually different profiles of deficient dexterity. Some of the FFM measures correlated with clinical scores.

Conclusions: Quantifying some of the key components of manual dexterity with the FFM is feasible in moderately affected hemiparetic patients. The FFM can detect group differences and individual profiles of deficient dexterity. The FFM is a promising tool for the measurement of key components of manual dexterity after stroke and could allow improved targeting of motor rehabilitation.

No MeSH data available.


Related in: MedlinePlus