Motor Output Variability Impairs Driving Ability in Older Adults

Background: The functional declines with aging relate to deficits in motor control and strength. In this study, we determine whether older adults exhibit impaired driving as a consequence of declines in motor control or strength. Methods: Young and older adults performed the following tasks: (i) maximum voluntary contractions of ankle dorsiflexion and plantarflexion; (ii) sinusoidal tracking with isolated ankle dorsiflexion; and (iii) a reactive driving task that required responding to unexpected brake lights of the car ahead. We quantified motor control with ankle force variability, gas position variability, and brake force variability. We quantified reactive driving performance with a combination of gas pedal error, premotor and motor response times, and brake pedal error. Results: Reactive driving performance was ~30% more impaired (t = 3.38; p \u3c .01) in older adults compared with young adults. Older adults exhibited greater motor output variability during both isolated ankle dorsiflexion contractions (t = 2.76; p \u3c .05) and reactive driving (gas pedal variability: t = 1.87; p \u3c .03; brake pedal variability: t = 4.55; p \u3c .01). Deficits in reactive driving were strongly correlated to greater motor output variability (R 2 = .48; p \u3c .01) but not strength (p \u3e .05). Conclusions: This study provides novel evidence that age-related declines in motor control but not strength impair reactive driving. These findings have implications on rehabilitation and suggest that interventions should focus on improving motor control to enhance driving-related function in older adults

Motor Output Variability Impairs Driving Ability in Older Adults: Reply to Stinchcombe, Dickerson, Weaver, and Bedard

Driving is a complex skill, as indicated by Stinchcombe and colleagues in their letter. It requires the integration of sensory inputs, cognitive processing, and motor execution. Although our title is broad, we clearly indicate that our findings only address a single component of driving, namely reactive driving. We also indicate that these findings are based on a simulated task and recommend that future studies should examine the contribution of motor output variability to on-road driving performance (see Considerations in the Discussion section). Thus, we share the consideration of Stinchcombe and colleagues that the current results only address a small portion of the driving complexity

Force Control Is Related to Low-Frequency Oscillations in Force and Surface EMG

<div><p>Force variability during constant force tasks is directly related to oscillations below 0.5 Hz in force. However, it is unknown whether such oscillations exist in muscle activity. The purpose of this paper, therefore, was to determine whether oscillations below 0.5 Hz in force are evident in the activation of muscle. Fourteen young adults (21.07±2.76 years, 7 women) performed constant isometric force tasks at 5% and 30% MVC by abducting the left index finger. We recorded the force output from the index finger and surface EMG from the first dorsal interosseous (FDI) muscle and quantified the following outcomes: 1) variability of force using the SD of force; 2) power spectrum of force below 2 Hz; 3) EMG bursts; 4) power spectrum of EMG bursts below 2 Hz; and 5) power spectrum of the interference EMG from 10–300 Hz. The SD of force increased significantly from 5 to 30% MVC and this increase was significantly related to the increase in force oscillations below 0.5 Hz (<i>R</i>² = 0.82). For both force levels, the power spectrum for force and EMG burst was similar and contained most of the power from 0–0.5 Hz. Force and EMG burst oscillations below 0.5 Hz were highly coherent (coherence = 0.68). The increase in force oscillations below 0.5 Hz from 5 to 30% MVC was related to an increase in EMG burst oscillations below 0.5 Hz (<i>R</i>² = 0.51). Finally, there was a strong association between the increase in EMG burst oscillations below 0.5 Hz and the interference EMG from 35–60 Hz (<i>R</i>² = 0.95). In conclusion, this finding demonstrates that bursting of the EMG signal contains low-frequency oscillations below 0.5 Hz, which are associated with oscillations in force below 0.5 Hz.</p></div

Force variability and oscillations in force.

<p>A) The SD of force for 5 and 30% MVC. As expected, the variability of force was greater with higher force. B) Normalized power spectrum density of force from 0–2 Hz. In this figure we present the average normalized power spectrum density because it was similar for the two force levels. The greatest power (∼75%) occurred below 0.5 Hz. C) The association between low-frequency oscillations of force and SD of force was strong (<i>R²</i> = 0.82). This indicates that ∼80% of force variability is due to the oscillations in force below 0.5 Hz.</p

Normalized power spectrum density of low-pass rectified EMG power from 0–2 Hz.

<p>In this figure we present the average normalized power spectrum density because it was similar for the two force levels. The greatest power (∼40%) occurred below 0.5 Hz.</p

The associations between changes in force and muscle activity.

<p>We explain these associations starting at the bottom of the diagram. The change in variability of force (SD of force) from 5 to 30% MVC was strongly related to the change in force oscillations below 0.5 Hz (<i>R²</i> = 0.82). The change in force oscillations below 0.5 Hz was related to the change in EMG burst oscillations from 0–0.5 Hz (<i>R²</i> = 0.51). Interestingly, the change in EMG burst oscillations from 0–0.5 Hz was related to the change in power from 35–60 Hz in the interference EMG.</p

Changes (from 5 to 30% MVC) in EMG burst oscillations below 0.5 Hz and interference EMG.

<p>Based on the multiple regression model, the change in power from 35–60 Hz in the interference EMG strongly predicted the EMG burst oscillations below 0.5 Hz (<i>R²</i> = 0.95). This finding indicates that modulation of interference EMG from 35–60 Hz is strongly associated with EMG bursts below 0.5 Hz.</p

Quantification of low-frequency oscillations in force and muscle activity.

<p>A) The force task (left column) and its corresponding interference EMG (right column). B) The force signal (10–20 s; left column) and the corresponding rectified EMG signal used for analysis (right column). C) Both the force (left column) and the rectified EMG (right column) were low-pass filtered at 2 Hz. This low-pass filtering demonstrates the important frequencies in force and EMG bursting. D) The power spectrum density of the low-pass filtered force (left column) and low-pass rectified EMG (right column). Most power occurred below 0.5 Hz.</p

Coherence between the force and EMG burst oscillations.

<p>A) Representative example of a force and an EMG burst oscillations signal for 20 s. It is obvious that both signals exhibit common low-frequency oscillations. The dotted line represents low-pass filtered force and EMG burst at 2 Hz, whereas the solid line represents low-pass filtered force and EMG at 0.5 Hz. B) The overall coherence between the force and EMG burst oscillations when low-pass filtering the signals at 0.5 Hz and 2 Hz. The coherence for the two filtering procedures was similar, which indicates that low-pass filtering the force and EMG signals at 0.5 Hz captures well the synchrony between the two signals.</p