Twelve young adults (27.4
4.44 years) and 12 older adults (74.5
8.95 years) volunteered to participate in the study. All subjects reported being healthy without any known neurological problems and were right-handed according to a standardized survey (Oldfield 1971
). Subjects provided written informed consent prior to participating in the study and the Human Research Committee at the University of Colorado in Boulder approved the protocol.
Each subject was seated and faced a 17-in. monitor that was located 1 m away at eye level. All subjects affirmed that they could clearly see the information displayed on the monitor. The left arm was abducted by 45° and the left elbow was flexed to 90°. The left forearm and hand were kept in a prone position with a custom-made device that only allowed movement of the index finger about the metacarpophalangeal joint in the abduction–adduction plane. The forearm and wrist were immobilized by metal plates and velcro straps that minimized the influence of the arm muscles on abduction of the index finger. The thumb, middle, ring, and fifth fingers of the left hand were restrained with metal plates, and there was approximately an 80° angle between the index finger and thumb. Only the left index finger was free to move, but it was placed in an adjustable finger orthosis to maintain the middle and distal interphalangeal joints in an extended position. The left hand was used so the results could be compared with previous studies (Burnett et al. 2000
; Christou et al. 2003
; Laidlaw et al. 2000
Measurement of index finger displacement
Loads were lifted (abduction) and lowered (adduction) over a 10° range of motion about the metacarpophalangeal joint. The lifting and lowering actions involved the first dorsal interosseus (FDI) and second palmar interosseus (SPI) muscles. The abduction–adduction displacement of the index finger was measured with a low-friction potentiometer (Helipot 7239-44-0) that was located directly under the metacarpophalangeal joint. The coefficient of sliding friction for the device was estimated as less than 9.8 mN. The index finger position was digitized at 1,000 samples/s with a Power 1401 data acquisition system (Cambridge Electronic Design, Cambridge, UK) and stored on a computer.
Abduction of the index finger is produced almost exclusively by FDI (Chao et al. 1989
; Li et al. 2003
; Zijdewind and Kernell 1994
), and the primary antagonist muscle is SPI. Activation of the two muscles was measured with intramuscular bipolar electrodes to ensure that the recordings were obtained from these muscles. Each electrode comprised two stainless steel wires (50 μm diameter) that were insulated with Formvar (California Fine Wire Company, Grover Beach, CA, USA). The electrodes were inserted into the belly of each muscle with a 30-gauge hypodermic needle; the needle was removed after the wires were inserted. Reference electrodes were placed on the styloid process of the ulna for FDI and on the dorsal surface of the fifth metacarpophalangeal joint for SPI. The EMG signals were amplified (×5,000) and band-pass filtered (13–5,000 Hz; Coulbourn Instruments, Allentown, PA, USA). The EMG signals were sampled at 10,000 samples/s with a Power 1401 data acquisition system (Cambridge Electronic Design, Cambridge, UK) and stored on a personal computer.
Subjects participated in one experimental session that lasted approximately 2 h. Each subject began the session by completing several questionnaires and then was familiarized with the experimental procedures. The familiarization included a demonstration of the lifting and lowering movements and an explanation of the feedback provided on the monitor. After the familiarization, each subject performed the following procedures: (1) maximal voluntary contractions (MVC) with the FDI (abduction of the index finger) and SPI (adduction of the index finger) muscles and (2) in a counterbalanced order, 30 lifting movements and 30 lowering movements (three blocks of ten contractions) to the target position.
Subjects were instructed to exert maximal abduction (FDI) and adduction (SPI) forces with the index finger in the shortest time possible. Index finger force was measured with a compression transducer (Model 41, Sensotec). The maximal force achieved in 600 ms was used to determine the load to be lifted and lowered. Prior to each MVC, subjects were required to maintain a constant abduction (or adduction) force of 0.05 N (~1.5% of the MVC force) for 3–5 s to minimize the electromechanical delay and to use procedures that were similar to the experimental task. The start of the MVC was denoted as the time when force was 0.1 N (~3% of the MVC). Three to five trials were recorded for each muscle, with a 60-s rest between consecutive trials. The EMGs for FDI and SPI were normalized to the peak EMG recorded during the MVC task.
The task was to match the displacement of the index finger to a target that comprised a thick black line on a white background. The target line was displayed on the bottom half (15
30 cm) of the monitor (Fig. , bottom row). The endpoint of the line had the target coordinates of 600 ms (time target) and 10° (displacement target). The size of the target was 0.1 cm2
. The load was 10% of the force achieved at 600 ms during the MVC task. A light load (10%) was selected because older adults are least steady when exerting low forces (Christou and Tracy 2005
) and the 600-ms target represents a moderate movement speed similar to many activities of daily living. Subjects were instructed to match the endpoint of the movement trajectory (finger position endpoint) to the end of the target line (displacement and time targets).
Fig. 1 The lifting and lowering tasks and the methods used to assess endpoint accuracy and to quantify EMG activity of the antagonistic muscles. Representative data from one young subject when lifting (left column) and lowering (right column) the light load. (more ...)
Subjects were required to begin the trial by holding the index finger at either 5° (abduction movement) or 15° (adduction movement) of abduction from the neutral position for 3–5 s. The target for the initial condition was presented to the subject in the top-half of the monitor as a thin black line and the position of the index finger was shown as a green line. Subjects were instructed to perform the accuracy task when ready (no reaction was required) after a “GO” cue from one of the investigators. The accuracy task was performed 30 times in each direction with a 5-s rest between trials. Subjects received visual feedback of the performance 0.1 s after each trial by displaying the displacement of the index finger as a red line superimposed on the target line (black line on white background) on the bottom half of the monitor. In addition, one of the investigators provided verbal feedback about the performance by describing it as (1) short movement, short time; (2) large movement, short time; (3) large movement, long time; or (4) short movement, long time. The knowledge of results provided by this feedback was intended to improve performance in subsequent trials.
Data were acquired with the Spike2 software (Version 5.07; Cambridge Electronic Design, Cambridge, UK) and analyzed off-line using programs written in Matlab (Mathworks Inc., Natick, MA, USA). The force was digitized at 1,000 samples/s and the EMG signals were acquired at 10,000 samples/s.
Finger displacement and movement performance
Displacement of the finger was characterized with the following measurements: (1) peak displacement, (2) time-to-peak displacement, (3) range of motion, and (4) average finger velocity. The accuracy of goal-directed movements was quantified in the spatial (degrees) and temporal (milliseconds) domains. The spatial error was the absolute difference between the target position and peak displacement achieved during the trial (Fig. , bottom row). The temporal error was the absolute difference between the target time and the time-to-peak displacement. The variability in performance was quantified for each set of 30 trials as the average standard deviation of acceleration (trajectory variability) and the standard deviations for peak displacement (degrees) and time-to-peak displacement (milliseconds).
Antagonistic EMG activity
The EMG and acceleration signals were quantified for the five phases shown in the left column of Fig. . The five phases were intended to indicate (Berardelli et al. 1996
; Corcos et al. 1989
) (1) postural control before the movement, (2) feedforward control at the beginning of the movement, (3) approximate time of peak velocity, (4) approach to the target, and (5) target acquisition. The EMG was quantified as the average EMG and the trial-to-trial variability of the EMG. The average activity was represented by the root mean square of the interference signal (Merletti et al. 2001
). The trial-to-trial variability was expressed as the standard deviation (SD) and coefficient of variation (CV
100) of each parameter for all 30 trials.
In addition, coactivation of FDI and SPI during each movement was quantified with the index developed by Olney and Winter (1985
The rate of improvement in performance of the two tasks was similar for young and older adults; thus, the data analysis focused on the average performance across 30 trials. Three ANOVA models (SPSS version 14.0) were used to compare young and older adults. A mixed, two-way ANOVA (2 age groups×2 movements) with repeated measures on movement type was used to compare the accuracy (displacement and time accuracy) of the two groups of subjects. A mixed, three-way ANOVA (2 age groups×2 movements×5 movement phases) with repeated measures on movement type and phases was used to compare trajectory variability (SD of acceleration) and coactivation index. A mixed, four-way ANOVA (2 age groups×2 movements×5 movement phases×2 muscles) with repeated measures on movement type, phases, and muscles was used to compare the muscle activity (average EMG and variability of EMG). Significant main effects and interactions from the ANOVAs were examined with post hoc analyses. Differences between the five phases of each trial were examined with one-way ANOVA and Tukey’s honestly significant difference test. The differences between the two age groups were identified with independent t tests, whereas differences between muscles and between movement types were identified with a dependent t test. Pearson correlations (r) were used to determine significant associations between endpoint error, motor output variability, and EMG variables.
Multiple linear regression models were used to establish statistical models that could predict the spatial and temporal errors (criterion variables) from the variability in peak displacement, variability in time-to-peak displacement, SD of acceleration, and FDI and SPI muscle activity (predictor variables). Predictor variables were included in the multiple regression models only when they were significantly associated (bivariate regressions; Pearson correlations) with the spatial or temporal error (criterion variable). Separate multiple linear regression models were used to predict spatial and temporal errors from the coactivation index.
The goodness-of-fit of the model, which indicates how well the linear combination of the variables predicted the spatial and temporal endpoint error, was given by the squared multiple correlation (R2
) and the adjusted squared multiple correlation (adjusted R2
). The adjusted R2
is reported because the R2
can overestimate the percentage of the variance in the criterion variable that can be accounted for by the linear combination of the predictor variables, especially when the sample size is small and the number of predictors is large (Green and Salkind 2002
). The relative importance of the predictors was estimated with part correlations (part r
), which provide the correlation between a predictor and the criterion after removing the effects of all other predictors in the regression equation from the predictor but not the criterion (Green and Salkind 2002
). A positive sign of the part correlation indicates that the predictor and the criterion are directly related, whereas a negative sign denotes an inverse relation.
The alpha level for all statistical tests was 0.05. Data are reported as means
SD within the text and tables and as means ± SEM in the figures. Only the significant main effects and interactions are presented, unless otherwise noted.