Exp Brain Res DOI 10.1007/s00221-015-4277-x

RESEARCH ARTICLE

A novel approach to enhancing limb control in older adults Jason B. Boyle1 · Deanna M. Kennedy2 · Charles H. Shea2 

Received: 30 October 2014 / Accepted: 3 April 2015 © Springer-Verlag Berlin Heidelberg 2015

Abstract  Two recent experiments have demonstrated that young adult participants were able to make faster and more harmonic movements in a typical reciprocal Fitts task (ID  = 6) following a practice session of sine wave tracking (Boyle et al. in Exp Brain Res 223:377–387, 2012; J Mot Behav 46:277–285, 2014). The purpose of the present experiment was to replicate these findings with a young adult population (age 18–25) and determine whether sine wave tracking also enhances goal-directed limb movements in an older adult population (age 65–90). To establish a performance baseline, all participants were first pretested on a typical ID = 6 Fitts task. Participants in each age group were then randomly assigned to one of the two training conditions where they practiced (45 trials) on a typical Fitts task (ID = 6) or they were asked to track a sine wave template (45 trials). Following practice, all participants were then posttested under the ID = 6 Fitts conditions. The results demonstrated that both young and older adult participants that practiced under the sine wave conditions enhanced their Fitts task performance compared to participants in their respective age groups who practiced under the Fitts conditions. These enhancements included faster movement times, smaller dwell times, and more harmonic movements, all without decreases in movement accuracy. These results replicate our previous findings with young adults and extend the finding to older adult participants. Interestingly, the performances of the older adults

* Charles H. Shea [email protected] 1

The University of Texas at El Paso, El Paso, TX, USA

2

Department of Health and Kinesiology, Texas A&M University, College Station, TX 77843‑4243, USA



following sine wave practice were as fast and as accurate as the young adults following Fitts task practice. Keywords  Aging · Fitts law · Aiming movements · Speed–accuracy trade-off · Optimizing difficult movements · Movement templates

Introduction Goal-directed limb movements to targets have repeatedly been shown to follow a linear speed–accuracy trade-off as the difficulty of the task increases (e.g., Fitts 1954; Woodworth 1899). This relationship has been shown in experiments involving reciprocal (e.g., Adam and Paas 1996; Boyle and Shea 2011; Boyle et al. 2012; Guiard 1997; Kovacs et al. 2008; Mottet and Bootsma 1999) and discrete movements of the limbs (e.g., Fitts and Peterson 1964; Meyer et al. 1988). In terms of the kinematic variables and control processes associated with this relationship, research has consistently demonstrated that as the index of difficulty (ID) increases, movement time also increases, and the proportion of movement time utilized in the deceleration phase of the limb (time from peak velocity to movement offset) motion also increases. This increase in the percent of time utilized in the deceleration phase of the movement indicates that as the task becomes more difficult, movement control shifts from preplanned cyclical control to more online or discrete visual control (e.g., Buchanan et al. 2006), resulting in additional time to manage the deceleration and correction processes required to achieve the smaller targets. Recently, studies have investigated potential ways to minimize the cost (in terms of movement time) of shifting to more online control. One technique involves providing augmented visual displays that facilitate online control (for

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review, see Casiez et al. 2008). For example, augmented and/or enlarged visual displays are used to enhance the performer’s ability to detect and correct movement errors. This typically involves increasing the size of the display (e.g., Boyle and Shea 2013; Casiez et al. 2008; Kovacs et al. 2008) or enhancing the display information as the participant nears the target area (e.g., Boyle et al. 2013; Fernandez and Bootsma 2008; Guiard et al. 1999). Augmented visual displays have proven beneficial in a number of experiments (e.g., Fernandez and Bootsma 2008; Guiard et al. 1999; Kovacs et al. 2008). It is important to note, however, the benefits associated with the enhancements of visual displays have been localized to more difficult tasks (i.e., high ID conditions) where the movement control involves feedback-based online corrections (Buchanan et al. 2003, 2004, 2006) with little or no effect on less difficult tasks (i.e., lower ID conditions) (Kovacs et al. 2008). Kovacs et al. (2008) suggested that when salient visual information is provided in the display, especially for high ID movements, the participants are able to more efficiently manage the deceleration/corrective phase of the movement. Another technique used to enhance aiming performance is to provide participants’ practice tracing optimized movement paths designed to promote the maintenance of cyclical control for difficult (e.g., ID = 6) movements (e.g., Boyle et al. 2012, 2014). In these experiments, participants were asked to follow a sine wave template provided in the display. This template, if followed, results in harmonic motion while achieving the task goals of speed and accuracy. As previously mentioned, lower difficulty movements are typically guided by cyclical control processes although high difficulty movements are regulated by more discrete visual error detection and correction processes (Buchanan et al. 2004, 2006). Display information that allows performers to successfully produce high ID movements using more cyclical control should result in more efficient and effective movements. Indeed, in recent experiments, Boyle et al. (2012, 2014) have provided evidence that high ID reciprocal aiming performance could be enhanced by providing practice following a template created from a sine wave with the same amplitude as required in the Fitts task. Practice following the template promoted a smooth movement trajectory to and through the targets area. Boyle et al. (2012, 2014) argued that the template simply promoted a more cyclical control strategy that allowed participants to “tune in” the task requirements (amplitude and target size). This result is consistent with research investigating augmented visual displays during bimanual coordination tasks (e.g., Kovacs et al. 2010a, b). This line of bimanual research has indicated that a wide variety of coordination patterns that were once thought difficult or even impossible to perform without extensive practice could be quickly and effectively “tuned-in” following a few minutes of practice when a goal

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Exp Brain Res

template with online integrated visual information was provided (e.g., Boyle et al. 2012; Kennedy et al. 2014, 2015; Kovacs et al. 2010a, b; Kovacs and Shea 2011; Wang et al. 2013). Although these display characteristics have been shown to enhance performance of young adults, the benefits of such manipulations have not been determined for older adults. Numerous studies have indicated that increasing the ID has a larger “slowing-down” effect on movement time for older adults than on that of young adults (e.g., Haaland et al. 1993; Ketcham et al. 2002; Rey-Robert et al. 2012; Sleimen-Malkoun et al. 2013; Temprado et al. 2013; Voelcker-Rehage 2008; York and Biederman 1990; Welford et al. 1969). In fact, older adults typically produce up to 70 % slower movements than younger adults, and this effect is even more pronounced as task difficulty is increased (Seidler-Dobrin and Stelmach 1998; Ketcham et al. 2002). Although increased movement time has been reported with both the acceleration and deceleration phases of aiming movements for older adults, older adults tend to show a greater increase in the deceleration phase of the movement (e.g., Cooke et al. 1989; Goggin and Meeuwsen 1992; Warabi et al. 1986). During the deceleration phase, feedback information is typically used to make adjustments in the movement trajectory to ensure that the target is obtained. For older adults, the increased amount of time spent in the deceleration phase of the movement has been linked to an increase in secondary, corrective sub-movement as they approach the target (Ketcham et al. 2002). In other words, older adults tend to make more afferent-based corrections around the target compared to young adults. An increase in the time utilized in the deceleration phase of the movement coupled with an increase in corrective submovements indicates that older adults may be relying to a greater extent on online or discrete visual control to obtain the target than young adults (Seidler-Dobrin and Stelmach 1998; Yan et al. 1998). Interestingly, however, older adults typically do not differ statistically with younger participants on accuracy scores (Goggin and Meeuwsen 1992). This is consistent with the notion that older adults tend to employ a strategy that emphasizes accuracy over speed (Goggin and Meeuwsen 1992; Ketcham et al. 2002; Rabbitt 1979; Welford 1984). When placing emphasis on accuracy, older adults likely slow down the movement to allow more time to process the feedback information and to make corrective adjustments in their movement trajectory. As such, providing augmented visual templates that facilitate online control, providing an optimized movement path to promote the maintenance of cyclical control, and/or promoting a strategy that emphasizes a compromise between speed and accuracy may be especially useful for older adults to

Exp Brain Res

optimize task performance. If older adults can effectively use augmented visual templates and optimal movement paths to promote more cyclical, preplanned control it may be possible to overcome some of the motor performance deficits associated with the aging process. Furthermore, enhanced movement control can have a positive impact on the ability of older adult to perform functional activities of daily living. Therefore, the purpose of this experiment is to replicate the earlier results using young adults and determine whether older adults can also effectively use augmented visual information to enhance movement control similar to young adults. Note the sine wave template was specifically designed to the same amplitude as the Fitts task, and the frequency was set to induce movement that was faster than that typically observed in the Fitts task.

Methods Participants Young adult participants (N  = 14) between the ages of 18–25 (mean age = 19.8) received class credit for participating in the experiment (7 participants per condition). Older adult participants (N  = 14) between the ages of 65–90 (mean age = 74.6) received a gift card valued at $10.00 for their participation (7 participants per condition). The experimental protocol was approved by the IRB for human subjects’ research at Texas A&M University. All participants in the 65–90 age range were screened for any neurological impairment that might hinder their performance (mini-mental state exam and health questionnaire). Participants were not aware of the specific purpose of the study and had no prior experience with the experimental task. Apparatus The apparatus consisted of a 16 in lever. The lever was attached to the right side of the table and pivoted on a near frictionless rotating axis. The lever freely moved in the horizontal plane. An adjustable handle was affixed to the distal end of the lever. The position of the handle could be adjusted to ensure that the elbow (arm flexion/extension) was positioned directly over the axis of rotation (Fig. 1). A potentiometer was attached to the bottom of the lever and was sampled at 200 Hz. A board was placed over the limb to occlude vision of the limb. A video projector was mounted above and behind the participant and was used to display the task requirements (targets, sine wave template, and cursor) on the wall in front of the participant. A height adjustable chair allowed the participants to comfortably rest their arm on the lever. The cursor and targets

were generated with custom software. The image of the task and cursor was displayed on a wall 2 m in front of the participants. The dimensions of the display were 1.64 × 1.23 m. Procedure Before entering the testing area, the participants (Young adults: 18–25 years, Older adults: 65–90 years) were randomly assigned to a practice condition (Fitts, Sine Wave). In the Fitts pretest (Fig. 1a, d), Fitts practice (Fig. 1b), and Fitts posttest (Fig. 1c, f), the movement amplitude was fixed at 16° and target width was set at .5° (ID = 6). The participants were asked to move the horizontal lever back and forth as quickly and accurately as possible so that the cursor projected on the wall in front of them moved between the two target areas. The two targets were each defined by a shaded area near the bottom and top of the display. In the sine wave practice condition (Fig. 1e), a sine wave template was presented in the visual display. Movements that matched the sine wave resulted in an amplitude of 16°, with the time from one reversal to the next being 1000 ms. The times for each movement half-cycle in the sine wave condition were set at 1000 ms because this resulted in movement times that were slightly faster than we had observed for young adults in our previous experiments using the Fitts condition at ID = 6. Note that the while the participant’s movements determined the up and down movement of the cursor, the left-to-right horizontal movement of the cursor at a constant velocity was controlled by the program. Participants were asked to move the cursor in the pattern indicated by this waveform. Participants were told that they did not have to trace the waveform but rather should adopt the cyclical movement pattern indicated by the waveform. In the sine wave condition, no mention was made of speed or accuracy. All participants were first pretested on a nine trial (15 s per trial) Fitts task (Fig. 1a, d). The final trial was analyzed and used as pretest performance data. Following the pretest, participants were trained in their respective conditions (Sine Wave, Fitts) for 45 trials of 15 s each (Fig. 1b, e). Following training, all participants were posttested on a nine trial Fitts task (Fig. 1c, f). The last trial of the posttest was recorded and analyzed. Thus, the pretest and posttest were conducted and analyzed in the same manner for all groups. Measures and data analysis Limb displacement time series were dual-passed filtered (Butterworth, 10 Hz) with data reduction performed using MATLAB (MathWorks, Natick, MA). A three-point central difference algorithm was used to calculate velocity. All

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Exp Brain Res

Fig. 1  Apparatus and displays for the Fitts (a–c) and sine wave (d– f) conditions. Note that the pretest (a, d) and posttest (c, e) conditions are identical for the two groups with only the practice condition

manipulated. The position and time measures were not provided in the display for the participant

dependent measures were analyzed on a half-cycle basis. First peak velocity (PV) and time of peak velocity (TPV) were determined for each half-cycle. Movement onset was determined by tracing backward from the TPV to a value of 2.5 % of that half-cycle PV. Movement offset was calculated by tracing forward from TPV to a value 2.5 % PV. For each half-cycle, there would be a single movement onset, peak velocity, and movement offset. Total time (TT) was calculated as, TT = movement onseti+1 − movement onseti. Movement time (MT) was calculated as, MT = movement offseti  − movement onseti. Dwell time (DT) was calculated by the equation, DT = movement onseti+1 − movement offseti. Percent time-to-peak velocity (%TPV) was determined by the equation, %TPV = ((TPVi  − onseti)/ (offseti  − onseti)  × 100). Movement endpoint variability (EPV) was calculated as the standard deviation of movement endpoints about their own mean. To examine the discrete-continuous nature of the limb movement, windows between a pair of zero crossings in

the displacement trace were defined in order to compute an index of harmonicity (HM) (Guiard 1993; also see Buchanan et al. 2003, 2004, 2006). Each nonoverlapping time window comprised a single displacement trace reversal. Within each time window, all deflections of the normalized displacement acceleration trace were identified. When the acceleration trace reversals were all positive or negative within this window, HM was computed as the ratio of minimum to maximum absolute acceleration reversals. When only one acceleration reversal was detected within this window, the value of HM was set to 1, indicating a harmonic movement. If the acceleration trace crossed from positive to negative (or vice versa) within this window, the value of HM was set to 0, indicating inharmonic movement. Finally, the individual harmonicity values of each time window for a trial were averaged, yielding a global estimate of motion HM. A value of HM = 0.5 has been described as the demarcation point between a shift from discrete to cyclical motion (Guiard 1997).

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The dependent variables of TT, MT, DT, PVEL, %TPV, HM, and EPV were analyzed in separate Condition (Sine Wave, Fitts) × Age (Young adults, Older adults) × Test (Pretest, Posttest) analyses of variance (ANOVAs) with repeated measure on Test. Simple main effects analyses were utilized when appropriate as post hoc procedures to follow-up on significant interactions. An α = .05 was used for all tests.

Results Examples of performance on the last trial of the pretest, training, and posttest for one participant in each age group and condition are provided in Fig. 2. Note that the participants in the Fitts condition performed the same Fitts task during training as used in the pretest and posttest. Participants in the sine wave condition practiced tracking a sine wave template during training and then transferred to the Fitts task. Thus, participants in the sine wave condition only experienced the Fitts task conditions on the pretest and posttest. Movement onset (square), time of peak velocity (circle), and movement offset (diamond) are depicted on the time series traces. Mean TT, MT, DT, PVEL, %TPV, HM, and EPV are provided in Fig. 3. Total time (TT) The analysis indicated a main effect for Age, F(1,25) = 40.58, p 

A novel approach to enhancing limb control in older adults.

Two recent experiments have demonstrated that young adult participants were able to make faster and more harmonic movements in a typical reciprocal Fi...
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