Objective: First, to ascertain whether a smartphone-based application measuring saccadic parameters can differentiate between patients with Parkinson’s disease (PD) and healthy controls (HC). Second, to assess whether abnormalities in saccades may be used to monitor PD progression.

Background: Saccadic abnormalities have been well documented in PD, with hypometric saccades suggested as being one of the best biomarkers for PD. [1] However, clinical translation of this knowledge has thus far been limited due to the cost of conventional eye tracking equipment. Previous work has demonstrated that smartphone-based software is able to reproduce similar data on saccadic parameters to that obtained from a specialised high-speed camera. [2] A novel smartphone-based application for tracking eye movements was used for this study.

Method: Eligible participants were recruited from the East London Parkinson’s Disease Project, a larger case-control study. Cognitive function was quantified using MoCA, with a score below 26 used to define cognitive impairment. Automated oculomotor tests with pre-recorded instructions were performed and recorded using software downloaded onto an iPhone 13 Pro. Data on saccadic latency, velocity and amplitude was analysed in Python v3.8.

Results: Recordings were performed on 25 PD patients and 24 age-matched HC. Mean age was 68.7 years for patients and 67.3 years for controls. Absolute mean velocity (p=0.001) and absolute maximum velocity (p=0.021) were significantly lower in PD patients (1.41, 2.67 deg/s) when compared to HC (2.00, 3.18 deg/s). The ratio of hypometric/large saccades was significantly higher in PD patients (0.77) compared to controls (0.18), meaning that a greater proportion of saccades were of small amplitude (p<0.001, AUC 0.812). Amongst PD patients, mean velocity was significantly lower in those with cognitive impairment (0.28 deg/s) compared to those without (0.71 deg/s) (p=0.004).

Conclusion: Smartphone-based analysis of saccades may represent a useful test for PD, helping to facilitate a timely diagnosis. Further research is needed to evaluate the place for such neuro-ocular biomarker technology on a larger scale. Our work also provides evidence for reduction in saccadic velocity being a potential means of monitoring cognitive impairment in PD.

References: [1] Pretegiani E, Optican LM. Eye Movements in Parkinson’s Disease and Inherited Parkinsonian Syndromes. Frontiers in Neurology. 2017; 8: 592.
[2] Lai HY, Saavedra-Peña G, Sodini C, Heldt T, Sze V, Heldt T. Measuring Saccade Latency Using Smartphone Cameras. IEE Journal of Biomedical and Health Informatics. 2020; 24(3): 885-897.

« Back to 2024 International Congress

MDS Abstracts - https://www.mdsabstracts.org/abstract/performance-of-a-smartphone-based-oculomotor-test-as-a-diagnostic-tool-for-parkinsons-disease/