Tag: eye movement

Intelligent Eye Tracker Integrated with Cylindrical Capacitive Sensors for Chronic Fatigue Assessment

Abstract:

Fatigue negatively impacts health, safety, and productivity, yet current monitoring methods are often subjective, labor-intensive, and inaccurate. To address these challenges, this study presents a capacitive sensor-based eye tracker leveraging cylindrical carbon nanotube-paper composite (CCPC) sensors for chronic fatigue (CF) assessment.

Fabricated by novel wet-fracture and paper-rolling methods, CCPC sensors demonstrate superior proximity sensitivity with a small form factor. These one-dimensional sensors are seamlessly integrated into an eyeglass frame for noncontact monitoring of blink rates and eye closures. A 15-minute testing protocol, combining cognitive tasks and noise exposure, is designed to induce acute fatigue and identify CF. By analyzing changes in the digital markers against established fatigue indicators, CF is assessed with the aid of machine learning models for the evaluation of accuracy, sensitivity, and specificity.

This real-time, wearable monitoring platform provides an objective, effortless, and noncontact approach to fatigue assessment. With further testing and optimization, it holds the potential for user-friendly evaluation of acute fatigue or fatigue-associated diseases, such as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS).

Source: Li T, Park SH, Lee C, Kim S, Kwon Y, Kim H, Chung JH. Intelligent Eye Tracker Integrated with Cylindrical Capacitive Sensors for Chronic Fatigue Assessment. Adv Sens Res. 2025 Jul;4(7):e00027. doi: 10.1002/adsr.202500027. Epub 2025 May 22. PMID: 40662140; PMCID: PMC12259227. https://pmc.ncbi.nlm.nih.gov/articles/PMC12259227/ (Full text)

Exploring Cognitive Dysfunction in Long COVID Patients: Eye Movement Abnormalities and Frontal-Subcortical Circuits Implications via Eye-Tracking and Machine Learning

Abstract:

Background: Cognitive dysfunction is regarded as one of the most severe aftereffects following coronavirus disease 2019 (COVID-19). Eye movements, controlled by various brain regions, including the dorsolateral prefrontal cortex and frontal-thalamic circuits, offer a potential metric for evaluating cognitive dysfunction. We aimed to examine the utility of eye movement measurements in identifying cognitive impairments in long COVID patients.

Methods: We recruited 40 long COVID patients experiencing subjective cognitive complaints and 40 healthy controls and used a certified eye-tracking medical device to record saccades and antisaccades. Machine learning was applied to enhance the analysis of eye movement data.

Results: Patients did not differ from the healthy controls regarding age, sex, and years of education. However, the patients’ Montreal Cognitive Assessment total score was significantly lower than healthy controls. Most eye movement parameters were significantly worse in patients: the latencies, gain, and velocity of visually and memory-guided saccades, the number of correct memory saccades, the latencies and duration of reflexive saccades, and the number of errors in the antisaccade test. Machine learning permitted distinguishing between long COVID patients experiencing subjective cognitive complaints and healthy controls.

Conclusion: Our findings suggest impairments in frontal subcortical circuits in long COVID patients experiencing subjective cognitive complaints. Eye-tracking, combined with machine learning, offers a novel, efficient way to assess and monitor long COVID patients’ cognitive dysfunctions, suggesting its utility in clinical settings for early detection and personalized treatment strategies. Further research is needed to determine the long-term implications of these findings and the reversibility of cognitive dysfunctions.

Source: Benito-León J, Lapeña J, García-Vasco L, Cuevas C, Viloria-Porto J, Calvo-Córdoba A, Arrieta-Ortubay E, Ruiz-Ruigómez M, Sánchez-Sánchez C, García-Cena C. Exploring Cognitive Dysfunction in Long COVID Patients: Eye Movement Abnormalities and Frontal-Subcortical Circuits Implications via Eye-Tracking and Machine Learning. Am J Med. 2024 Apr 5:S0002-9343(24)00217-1. doi: 10.1016/j.amjmed.2024.04.004. Epub ahead of print. PMID: 38583751. https://pubmed.ncbi.nlm.nih.gov/38583751/

Characterising eye movement dysfunction in myalgic encephalomyelitis/chronic fatigue syndrome

Abstract:

BACKGROUND: People who suffer from myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) often report that their eye movements are sluggish and that they have difficulties tracking moving objects. However, descriptions of these visual problems are based solely on patients’ self-reports of their subjective visual experiences, and there is a distinct lack of empirical evidence to objectively verify their claims. This paper presents the first experimental research to objectively examine eye movements in those suffering from ME/CFS.

METHODS: Patients were assessed for ME/CFS symptoms and were compared to age, gender, and education matched controls for their ability to generate saccades and smooth pursuit eye movements.

RESULTS: Patients and controls exhibited similar error rates and saccade latencies (response times) on prosaccade and antisaccade tasks. Patients showed relatively intact ability to accurately fixate the target (prosaccades), but were impaired when required to focus accurately in a specific position opposite the target (antisaccades). Patients were most markedly impaired when required to direct their gaze as closely as possible to a smoothly moving target (smooth pursuit).

CONCLUSIONS: It is hypothesised that the effects of ME/CFS can be overcome briefly for completion of saccades, but that continuous pursuit activity (accurately tracking a moving object), even for a short time period, highlights dysfunctional eye movement behaviour in ME/CFS patients. Future smooth pursuit research may elucidate and improve diagnosis of ME/CFS.

 

Source: Badham SP, Hutchinson CV. Characterising eye movement dysfunction in myalgic encephalomyelitis/chronic fatigue syndrome. Graefes Arch Clin Exp Ophthalmol. 2013 Dec;251(12):2769-76. doi: 10.1007/s00417-013-2431-3. Epub 2013 Aug 6. https://www.ncbi.nlm.nih.gov/pubmed/23918092