Effects of aging on eye movements in the real world

Abstract

The effects of aging on eye movements are well studied in the laboratory. Increased saccade latencies or decreased smooth-pursuit gain are well established findings. The question remains whether these findings are influenced by the rather untypical environment of a laboratory; that is, whether or not they transfer to the real world. We measured 34 healthy participants between the age of 25 and 85 during two everyday tasks in the real world: (I) walking down a hallway with free gaze, (II) visual tracking of an earth-fixed object while walking straight-ahead. Eye movements were recorded with a mobile light-weight eye tracker, the EyeSeeCam (ESC). We find that age significantly influences saccade parameters. With increasing age, saccade frequency, amplitude, peak velocity, and mean velocity are reduced and the velocity/amplitude distribution as well as the velocity profile become less skewed. In contrast to laboratory results on smooth pursuit, we did not find a significant effect of age on tracking eye-movements in the real world. Taken together, age-related eye-movement changes as measured in the laboratory only partly resemble those in the real world. It is well-conceivable that in the real world additional sensory cues, such as head-movement or vestibular signals, may partially compensate for age-related effects, which, according to this view, would be specific to early motion processing. In any case, our results highlight the importance of validity for natural situations when studying the impact of aging on real-life performance.

Keywords: aging; eye movements; natural environment; real-world gaze; saccades; self-motion; tracking eye-movements.

Figure 1

Illustration of a typical scene during calibration and the two tasks. Images were taken from the head mounted camera of the ESC. The red square indicates the current gaze position of a participant. (A) Calibration: Fixating stationary targets with a fixed distance of 7° as projected by a head-fixed laserpointer of the ESC (enhanced in this figure for visualization). (B) Task I: Walking down the hallway with free gaze and (C) Task II: visually tracking two stationary targets on the floor while walking straight-ahead.

Figure 2

Pearson correlation of different eye movement parameters with participants’ age. There is a significant decline with age of saccade frequency (A), saccade amplitude (C), saccade peak- (D) and mean-velocity (E) and q-value (F). Blink rate trended to be larger in older participants (B).

Figure 3

Standard deviations and variation coefficient of saccade amplitude (A,B), peak- (C,D) and mean-velocities (E,F) and q-value (G,H) in relation to the age of the participants. There is a clearly negative correlation for these parameters indicating a decreased variability of saccadic performance in older participants.

Figure 4

Illustration of Main-sequence power-function fits for different K-values, while the exponent (“L”) remains unchanged (A), each K-value relates to a different age cohort, as extracted from the linear regression of K-value over age (B). L-values were constant at 0.35 for all fits (C). With increasing age, smaller K-values (B) lead to decreasing slopes of the power functions and therefore smaller saccade peak-velocities for the same amplitudes when L-values are constant (C).

Figure 5

Pearson correlation of tracking-performance parameters with participants’ age. Neither tracking gain during free exploration (A), nor gain (B) or RMSE (C) of the tracking eye-movement of a specific target showed a significant correlation with age.