There are numerous ways to identify a person’s cognitive impairment. Various neuropsychological tests are conducted with the assistance of trained healthcare professionals. MMSE [12], TMT [14], Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) [7], and Frontal Assessment Battery (FAB) [7] are some of the frequently used tests to diagnose cognitive impairment and should be carried out by professional evaluators. While these neuropsychological tests are valid and trustworthy, they are not simple or brief enough to be utilized as regular dementia screening tools. MMSE [17] and MoCA [13] are some of the clinical tools to assess cognitive impairment. But they have limitations in identifying mild cognitive impairment. These scores can also be affected by age and education level.

Traditional methods use self-reporting questionnaires to detect cognitive decline in a person. There are well-validated and standardized questionnaires to detect cognitive decline, but they can be psychologically biased. Memory lapse, carelessness, or if the respondent voluntarily changes the feedback can affect the detection of cognitive changes.

Despite being accurate and reliable, these conventional cognitive tests have certain limitations. Senior patients may take a longer time to complete these tests. A more precise evaluation is required to detect the severity of cognitive impairment. Since they must respond to several questions during the examination, subjects may feel psychological stress. Since the proficiency of the assessor can influence the outcomes, these tests must be correctly administered by professional neuropsychologists with extensive training. Since some of these cognitive tests include writing and drawing, patients with motor dysfunction, which is frequently present in people with dementia, can impact the results.

Eye-tracking data have a significant role in capturing the involuntary physiological responses of a person, which accurately helps to understand the characteristics or cognitive inhibitions of an individual [18]. Clinical assessments may miss identifying cognitive inhibitions in the earlier stage of disease, whereas simple eye-tracking measures can point that out [5,19].

Eye-tracking measures can distinguish among subtypes of mild cognitive impairment [19]. The antisaccadic task’s error rate was considered a significant measure to classify the types of mild cognitive impairment. Digit Span [20] and Spatial [21] Tests were performed on participants in the 55–90 age group. The analysis of variance (ANOVA) test could significantly point to the difference in the error rates in the antisaccadic tasks performed by different types of mildly cognitively impaired participants.

In a study performed with several memory tasks, the eye-tracking based score correlated with the MMSE score and could discriminate the control group from the Alzheimer’s disease (AD) and MCI groups [12]. Gaze tracking is widely accepted as a tool for monitoring a person’s cognitive functions and neurological disorders [22].

Eye-tracking technology can be utilized to assess and monitor various aspects of diseases like amyotrophic lateral sclerosis (ALS), AD, Parkinson’s disease (PD) [23], multiple sclerosis (MS), and epilepsy [24]. Eye tracking can detect early cognitive impairment by observing how individuals perform tasks such as looking away from sudden stimuli (antisaccadic task), smoothly tracking moving targets (smooth-pursuit task), and efficiently scanning visual scenes (visual-scanning task). Difficulty or errors in these tasks can indicate early changes in inhibitory control, motor control, attention, and scanning abilities, providing valuable insights into cognitive decline before conventional evaluations can detect them [19].

ALS patients exhibit cognitive and behavioral deficits due to their motor impairment. A higher antisaccadic error rate and saccadic latency were observed in these patients. In the successive stages of this disease, the patient loses the ability to write and speak, making the conventional paper–pencil method an inappropriate cognitive assessment tool [24]. The Edinburgh Cognitive and Behavioral ALS Screen (ECAS) is a standardized method to assess ALS patients [25]. The ECAS was developed exclusively for ALS patients and may not be appropriate for measuring cognitive and behavioral changes in people with other neurological disorders. The ECAS does not assess all aspects of cognitive function and is not sensitive to changes in cognitive function in people with early-stage ALS [26].

Lower motor neuron atrophy causes patients to lose their capacity to talk or write; at this point, these conventional measures are no longer appropriate for cognitive assessments [27]. An eye-tracking variant of the ECAS test could reduce the test duration and improve the evaluation effectiveness. Several studies show that eye tracking is a timely, efficient, and accurate way to evaluate cognitive performance in ALS patients [28,29].

Progressive memory loss is observed in AD patients and leads to dementia [30]. The saccades, fixations, and smooth pursuit performed by a patient could yield more accurate inferences of the stage of the disease.AD patients are slower in fixating on a target and have reduced fixation spans and less precise saccadic motions [24]. Gradual loss of attention and deterioration in visual attention were observed in AD patients [31].

While performing memory tasks, impaired visual attention and diminished visual interest were observed in AD patients. The memory-and-recall task [32,33], deductive reasoning [12], the working memory task [7], etc., helped to discriminate AD from the control group. Visual working memory tasks can also differentiate AD from MCI. A deductive reasoning task can distinguish the MCI group from the normal control group. The Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) and the MMSE [34] are some of the established standard tests used to detect Alzheimer’s disease [35]. But these tests take a longer time to complete, and subjects may feel highly stressed due to the pressure of responding to a series of questions.

PD is a neurodegenerative disease that results in the patient’s cognitive decline [36]. In addition, ocular abnormalities and a longer response time were observed while performing saccadic tasks [24]. Degenerative changes can cause the impairment of focused attention. A decline in focused attention was observed in PD patients [37]. The visual search behavior of a PD patient is impaired, and there can be changes in fixational and non-fixational eye movements [38].

Standard conventional assessments like Parkinson’s Disease-Cognition (SCOPA-COG) and the Parkinson’s Disease-Cognitive Rating Scale (PD-CRS) [39] are not very sensitive in detecting cognitive abnormalities in the initial phases of PD. Eye-tracking measures are correlated with Parkinson’s disease severity, indicating that they may be used to forecast disease development in patients.

Disengagement of visual attention was noticed in people with cognitive impairment in their older age [31]. ’Gap’ and ’overlap’ conditions were introduced while displaying the stimulus to understand the saccadic movements of the participants. A blank screen was introduced between the fixation and target displays under the first condition, whereas an overlap of fixation and target was introduced between the fixation and target displays. Prosaccadic errors were observed in participants with dementia and old age.

The memory test visual paired-comparison (VPC) task is used to understand memory impairment [40]. Eye movement features like fixations, saccades, and re-fixations were considered to understand the participants’ behavior while viewing novel and repeated stimuli. The machine learning algorithm support vector machine (SVM) could accurately distinguish the normal control group from the MCI group. The VPC task with eye-tracking technology was used as a screening tool to detect MCI [41]. Eye-tracking features like total looking time, fixation count, and percentage of time spent on the novel image were considered for analysis. The novel image was viewed by the control group and PD patients for more than 70% of their total viewing time but only for 53% of the time by the MCI group.

A deficit in sustained attention is observed in the early stage of dementia and leads to severe impairment in the later stage [42]. An earlier diagnosis helps to slow down the disease’s growth in a person with MCI [43,44,45]. But, unfortunately, the clinical biomarkers to detect these diseases earlier are quite expensive and invasive [19]. Eye tracking provides non-invasive and involuntary measures that serve as a critical biomarker in the earlier diagnosis of these diseases. Advanced neurophysiological eye-tracking measures are gaining researchers’ attention, considering the low responsiveness of conventional approaches to identify cognitive abnormalities in the initial phases of disorders [24].

It is challenging to detect MCI in an early stage based on clinical evaluations [46]. However, the eye-tracking measures [47] captured while performing the working memory task can distinguish healthy individuals from people with cognitive impairment. When conventional assessment methods fail to detect minute impairment, simple eye-tracking techniques can pinpoint that impairment. Various tasks can be used to understand the different types of cognitive-impairment diseases. Different types of tests are performed to understand different cognitive-impairment diseases [43].

The myelin sheath, optic neurons, and the spinal cord are all harmed by the disease MS [24]. The impairment of memory, executive function, and attention is increasingly recognized as a substantial functional weakness in MS. Neurophysiological examinations and brain MRI have traditionally been adopted as diagnostic tools. Using eye tracking, abnormal visuospatial behavior in MS can be detected. The most popular method for evaluating oculomotor function in MS patients is the use of saccadic tasks because of their direct relationship with ocular-nerve damage.

Cognitive impairment associated with stroke includes deficits in attention, memory, language, and executive functions [48]. These impairment types significantly impact the quality of life in stroke survivors, and there is a high potential for the development of dementia within the first year of stroke onset. After a stroke, cognitive impairment, including memory problems, can be detected with neuropsychological assessments such as MMSE, MoCA, and TMT, and language tests like phonological and semantic fluency token tests. An eye-tracking-based study was performed in stroke patients with cognitive impairment [49]. They underwent eye-tracking linkage attention training and showed significant improvements in visuospatial and memory tests, suggesting that eye-tracking measures can detect cognitive impairment and contribute to its rehabilitation in stroke patients.

People with Huntington’s disease (HD) can experience cognitive decline that makes it difficult for them to think, remember, and learn. This can happen even before the motor symptoms of HD appear [50]. Researchers found that premanifest (Pre-HD) people made more errors and took longer to respond when the task required inhibitory control, working memory, or fronto-executive function [51]. People with HD have lower saccadic latency and are more likely to make disinhibited saccades [52]. Eye tracking is a promising tool for detecting changes in saccadic eye movements, which could serve as biomarkers for tracking Huntington’s disease (HD) progression.

The various diseases associated with cognitive impairment, the standard assessment tools used to detect impairment and these tools’ shortcomings, and the eye-tracking measures used for impairment detection are shown in Table 1. The various tasks performed to screen mild cognitive impairment are memory tasks [7], attention and calculation tasks [7], TMT-A, TMT-B [14], the Word Memory Test [53], identifying some objects, and counting backward [54]. People with AD progressively lose their ability to exert effective inhibitory control over their actions and their attention. In particular, the capacity to control and inhibit voluntary gaze shifting away and towards the salient stimulus is impaired. Physicians have a significant opportunity with eye tracking to diagnose Alzheimer’s disease [55] in its earliest stages during the MCI phase [56].

The TMT is a neuropsychological test [58] that measures the capability of the brain to perform visual attention and task switching [59]. It provides details regarding executive functioning, visual search speed, scanning, processing speed, focused attention, and mental flexibility. Many types of brain dysfunction, especially those affecting the frontal lobes, can be detected and diagnosed using the TMT. This area of the brain regulates high-level cognitive skills, such as planning, consciousness, memory, emotion, and attention. It was used as a standard test to evaluate soldiers’ brain damage during the Second World War. The test was administered using paper and a pencil in a conventional manner. To identify cognitive impairment, only the error rate and overall completion time were taken into consideration and could not offer a detailed analysis [60]. The TMT’s objective is to carry out the examinations as promptly and precisely as possible in order to identify any potential indicators of cognitive impairment. A psychologist should assist the patient throughout the conduct of the test. People who suffer from motor impairment may have difficulty in completing the test and take longer to complete it. There have been studies on different TMT variants to overcome the limitations of existing conventional methods.

The digital TMT (dTMT) precisely monitors a variety of distinct elements along with the overall completion time and the number of errors, such as the number of viewing pauses, the duration of each pause, lifting, lifting duration, duration within the circle, and the amount of time across the circles [61].

The benefits of combining infrared eye tracking with the TMT task is another significant factor [62]. Research on infrared eye tracking is becoming well known for its ability to diagnose cognitive impairment. Eye tracking was employed in an ongoing study to gather objective, quantitative data on each participant’s visual, attentional, and memory functions [63]. In addition to the basic task-completion-time metric, eye tracking enabled a number of potentially insightful and sensitive measurements.

The study of related works revealed a variety of cognitive deficits, including memory loss, lower visual interest, atypical visuospatial behavior, attentional disengagement, motor impairment, and impaired mobility, and their association with diseases like AD, PD, MCI, MS, ALS, HD, stroke, and epilepsy. Eye-tracking features like inattentional blindness, error rate, total completion time, scanpath comparison score, fixation duration, saccadic latency, and smooth pursuit could allow for the drawing of inferences to understand those deficits, as shown in Table 2. The eye-tracking version of the TMT provides those eye-tracking features and can allow for the drawing of inferences on detecting cognitive impairment.

In a previous study, [1], a comparison of various versions of the TMT that are performed digitally, using paper–pencil, or with eye tracking was reported. The benefits of the eye-tracking version of the TMT were also pointed out based on our findings. The study presented individual and group profiles, which aids in comprehending a group of individuals performing the TMT with a similar level of cognitive decline [1].

The proposed ETMT model is a screening tool for cognitive impairment based on the changes observed in eye-tracking measures while performing eye-tracking versions of TMT-A and TMT-B. The ETMT model provides a detailed understanding of the participant’s focused attention and visual search speed other than their cognitive impairment. By utilizing eye-tracking technology, the model enhances practitioners’ understanding of these cognitive aspects, enabling a more detailed evaluation of participants’ cognitive abilities and potential deficits.