Biomechanical adaptation to post-stroke visual field loss: a systematic review

Stroke affects approximately 100,000 persons per annum in the UK [1]. As stroke is more common with older age, and the UK population is one of many countries with an ageing population, stroke is likely to be an ongoing health concern. A common problem post-stoke is visual impairment, with an estimated 65% of stroke survivors having visual impairment in the immediate aftermath of stroke [2]. The large prevalence of sight loss post-stroke imposes significant costs on public funds, private expenditure and health: an estimated £28.1 billion in 2013 in the UK [3].

Stroke-associated visual impairment can include impairment to central vision and peripheral vision (visual field), eye movement disorders, reading difficulties and visual perception disorders including visual neglect [2, 4]. Visual field defect (VFD) encompasses hemianopia, quadrantanopia, temporal crescent defect and scotoma, among others, with the most common defect being homonymous hemianopia (HH). HH involves vision loss on the same side of the visual field in both eyes and is associated with a worse prognosis for successful rehabilitation [5, 6], especially when combined with visual neglect [7]. Approximately 30% of stroke survivors have this visual field loss acutely while approximately 8–10% of stroke survivors have a permanent HH [8].

HH seriously impacts functional ability and quality of life following stroke [9]. For example, it causes an increased risk of falling, impaired ability to read, poor mood and higher levels of institutionalisation [10, 11]. Moreover, HH impacts participation in post-stroke rehabilitation and may result in poor long-term recovery, leading to loss of independence, social isolation and depression [12].

Individuals with VFD cannot process images in the same way as those with a full visual field [13]. Those with normal visual function use their peripheral field of vision as a guidance system and cue for generating eye movements to look towards objects of interest. To attain the highest quality of visual information, one must position the area of interest on the fovea [14‐16]. Gaze scanning can be accomplished through eye, head and body movements, with the choice of movement depending on the demands of the activity and the environment. For example, when switching visual attention from one target to a closely adjacent target, the task usually requires only small eye movements. Conversely, when crossing the street, a task that involves acquiring information over a large area, individuals prefer to make a head movement to increase the scan area in a short period. This occurs because, in an outdoor environment, about 85% of naturally occurring human saccades have magnitudes of ≤ 15° [17]. Head movements also serve to recentre the head on the torso and serve as a reference frame for body movements, important for walking and maintaining consistent heading direction [18].

Individuals with normal or corrected-to-normal vision always move their eyes during the acquisition of visual information, even when attempting to maintain a steady gaze on a single point. Rapid gaze shifts known as saccades typically occur 2–3 times per second, bringing a new portion of the visual scene on to the fovea. In between these movements, the eyes essentially stop scanning about the scene, holding the central foveal vision in place so that the visual system can take in detailed information about what is being looked at [16, 19, 20]. Impaired peripheral vision (as occurs in hemianopia), will affect the visual feedback system that guides and cues eye movements into the affected visual field [21, 22]. Those with HH receive no visual cues from peripheral vision as to when to scan or how far to scan into the blind hemifield (BHF) and spend most of their time looking towards their BHF when viewing simple patterns in order to bring more of the visual scene into their seeing hemifield (SHF). They demonstrate numerous refixations (additional eye movements) and inaccurate saccades which result in impaired scanning, longer search times (trying to find objects) and the failure to detect relevant objects [23‐26].

Training programmes exist to improve these eye movements—visual scanning or visual search strategies [27]. Research on the impact of HH on eye movements plus research on improving eye movements through visual scanning training is largely based on computerised tasks with participants seated in head-fixed positions [28]. While more recent research includes studies with free head movement, there has been limited investigation regarding the impact of hemianopia on eye movements when individuals are walking around with free head and trunk movements [29].

To provide a comprehensive systematic overview of the biomechanical alterations to post-stroke VFD to identify which movement parameters are the most relevant, commonly used or have specific clinical relevance. This will guide current practice and aid in the design of future research into this subject area. In this review, the term biomechanics refers to changes in eye, head or body movements in response to the visual field loss.

This systematic review aimed to bring together the biomechanical evidence relating to eye, head and body movements in stroke-related VFD. The review was observed and reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines (Supplementary Figure 1) [31]. A detailed protocol was developed prior to the review and registered with PROSPERO (international prospective register of systematic reviews; CRD42020194403) [32].

Figure 1 illustrates the flowchart for this review. Thirty-six articles (1123 participants) published in English were included and the overall Kappa score for inter-rater agreement was 0.863 indicating substantial agreement. Due to the heterogeneity across the included studies with respect to reporting of outcomes as well as recruitment and selection of participants, a meta-analysis of studies could not be undertaken. A narrative summary of the data is presented in relation to included studies to highlight how visual field loss impacted on eye, head or body movements across the included studies. Results are split into simulated HH and true VFD and then discussed by type of movement analysis (eye/head/body movement). Data analysis was conducted by one reviewer (AE) and double checked by another two reviewers (FR, LH).

The aim of this systematic review was to gather and summarise the available evidence on biomechanical alterations to post-stroke VFD. In simulated HH, healthy adults temporarily deprived of information from half of their visual field tended to preferentially move their eyes towards their sighted field of vision, especially during tasks that required complex cognitive processing [37, 38]. Nonetheless, the bias to preferentially search the SHF persisted, even in easy search, and participants continued to direct eye movements into the SHF even when these eye movements gained them very little new information and impeded search performance. Training or repeated exposure to a simulated VFD led to the development of a more efficient visual search strategy. Participants’ fixations moved progressively deeper into the BHF, and this shift was seen in the easy search condition, and to a lesser extent, in the hard condition [38]. Saccades into the BHF were strongly associated with improved search performance.

The scanning behaviour of participants with true HH was mostly characterised by a significantly increased number and duration of fixations, duration of saccades and scan path length with shorter mean saccadic amplitude and lower peak velocity of saccades [25, 26, 56, 57, 59]. This abnormal scanning behaviour was associated with impaired visual exploration, longer visual search times, target omissions and longer, unsystematic scanpaths. Driving was also considered to be problematic for participants with HH. The majority of on-road studies and simulator experiments highlighted poor steering control, incorrect lane position and difficulty in gap judgment [51, 59, 66]. The gaze pattern of drivers with HH was also characterised by increased numbers of fixations, longer search times, longer saccadic amplitudes and more head movements, particularly towards moving objects of interest on their BHF.

In contrast to the shifting bias observed in simulated HH, participants with post-stroke HH tended to spend more time overall looking to the side associated with the deficit during free viewing tasks. These compensatory strategies of biasing gaze in the direction of the BHF were found to be most evident when participants with HH were in dynamic and unpredictable environments [66], where they could not rely on spatial memory to locate salient objects. The differences found between the simulated HH and the true HH may be attributed to several reasons. First, it may be that because of the limited time duration of simulated HH participants did not develop a consistent search strategy. Second, participants with simulated HH are normally aware that their deficit will end with the experiment, whereas participants with HH would be more motivated and have more time to adapt to a long-term deficit. Third, there may be a particular effect of brain damage over and above the visual deficit that is responsible for the specific eye movement pattern. Tant et al. [64] stated that the visual deficit is the main but not the only factor that contributes to the abnormal oculomotor behaviour seen in post-stroke HH. Fourth, participants with HH move more to their BHF because they possess some residual visual abilities in their affected visual field that guides their search more effectively while healthy participants with simulated HH do not have any residual visual information in their blind side. This hemifield bias could also be related to the fact that eye movements in studies involving participants with HH were largely recorded in the chronic stage [57]. Machner et al. [56] recorded eye movements while participants with HH in an acute stage searched for targets among distractors. Both participants with true and simulated HH displayed no direction-specific bias, i.e. saccades directed towards the BHF did not differ in frequency or amplitude from those directed towards the SHF suggesting that compensation had not yet occurred. Some participants discussed in the true hemianopia studies had visual field defects other than hemianopia, for example quadrantanopia and bitemporal visual field loss. However, in the simulated HH group, only the complete right or left hemianopia condition was simulated, and this might account for some differences found in the scanning behaviour across studies. Finally, some individuals with HH are not aware of their visual field loss (especially when combined with spatial neglect) and cannot use voluntary, cognitive control to guide their blind side scanning or have multiple visual impairments that can exacerbate the impact of their hemianopia.

The extent to which conclusions drawn from any experiment using simulated HH can be applied to individuals with visual field deficits may be limited. The method employed to simulate HH works by completely removing all the visual information from one half of the display screen in a gaze-contingent manner. This method of “hard edge” hemianopia is only an approximation of what happens in post-stroke VFD and is not entirely consistent with the effects of damage to postgeniculate visual pathways. The loss of vision in the contralateral visual field is sometimes accompanied by residual visual capacity, known as blind sight [69]. Furthermore, the majority of included studies recorded eye and head movements in stroke survivors with HH in the chronic stage and little is known about search behaviour during exploratory visual search tasks within acute phase, in the first few weeks following a stroke.

Findings from this comprehensive review will underpin future clinical research. The review highlights that numerous studies have explored the eye and head movements and scanning behaviour of participants with HH in well-controlled laboratory-based settings but that there has been only limited investigation into what happens under real-world conditions. Future research should aim to establish the extent to which people with HH use effective scanning strategies in real-world situations, whether they are able to adapt their scanning strategies in response to differing task demands, and whether scanning training can be generalised to everyday mobility tasks. The review outlines an extensive list of eye, head and body movement parameters that have been used in the scientific literature to examine scanning behaviour in individuals with HH.

Findings from this review have important implications for clinical practice. Some stroke survivors appear to spontaneously adopt some compensatory strategies [68], and those who do not can be trained to do so. One effective strategy to compensate for a lateralised field deficit is to fixate and saccade as far into the BHF as possible to maximise the proportion of the search area that falls into the SHF [25, 38, 58, 62]. Based on self-report, encouraging stroke survivors with HH to utilise such strategies in real life improves general functioning [58]. Real-life improvements were demonstrated by Bahnemann et al. [44], who compared participants with HH with high and low hazard detection rates in a simulated driving task on a number of eye and head movement measures. Successful performance appeared to be related to compensatory mechanisms of visual exploratory behaviour, namely, an increase in the amplitude and peak velocity of saccades, widening horizontally the distribution of eye movements and a shift of the overall distribution of saccades into the BHF. Similarly, large eye and head movements directed towards the BHF improved search for specific items in a supermarket [52] and collision avoidance [51, 59, 66].

The benefits of rehabilitation for individuals with HH are often perceived as offering only marginal gains. However, we propose that practitioners should be directed to promote active rehabilitation programmes to improve scanning/search performance for individuals with HH. These could employ simple yet effective, user-friendly techniques that can be practised in people’s own homes, causing minimal disruption to their daily lives.

This systematic review provides a substantial amount of evidence about the inefficient oculomotor scanning behaviour of individuals with HH and healthy participants with simulated HH. Under simulated HH, participants were consistently biased towards the visible part of their visual field whereas the gaze behaviour of participants with HH was biased in the direction of the blind side. With practice, participants with true and simulated HH developed compensatory mechanisms of visual exploratory behaviour, namely, an increase in the amplitude and peak velocity of saccades, widening horizontally the distribution of eye movements and a shift of the overall distribution of fixations and saccades into the blind side. This evidence can be used to underpin the further development, refinement and implementation of visual rehabilitation programmes for hemianopia.