phat 19(17): e4

Research Article

Analysis for Extracted Features of Pupil Light Reflex to Chromatic Stimuli in Alzheimer’s Patients

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  • @ARTICLE{10.4108/eai.13-7-2018.161750,
        author={Wioletta  Nowak and Minoru  Nakayama and Tomasz  Kręcicki and Elzbieta  Trypka and Artur  Andrzejak and Andrzej Hachoł},
        title={Analysis for Extracted Features of Pupil Light Reflex to Chromatic Stimuli in Alzheimer’s Patients},
        journal={EAI Endorsed Transactions on Pervasive Health and Technology},
        keywords={Pupil Light Reflex, Alzheimer’s Disease, light colour, feature extraction, classification},
  • Wioletta Nowak
    Minoru Nakayama
    Tomasz Kręcicki
    Elzbieta Trypka
    Artur Andrzejak
    Andrzej Hachoł
    Year: 2019
    Analysis for Extracted Features of Pupil Light Reflex to Chromatic Stimuli in Alzheimer’s Patients
    DOI: 10.4108/eai.13-7-2018.161750
Wioletta Nowak1, Minoru Nakayama2,*, Tomasz Kręcicki3, Elzbieta Trypka3, Artur Andrzejak3, Andrzej Hachoł1
  • 1: Wrocław University of Science and Technology, Wybrzeże Wyspianskiego 27, Wrocław, 50-370 Poland
  • 2: Information and Communications Engineering, Tokyo Institute of Technology, O-okayama, Meguro-ku, Tokyo, 152–8552 Japan
  • 3: Wrocław Medical University, Wybrzeże L. Pasteura 1, Wrocław, 50-367 Poland
*Contact email:


INTRODUCTION: Some Alzheimer’s Disease (AD) patients respond to chromatic light stimulus, which may influence intrinsically photosensitive retinal ganglion cells (ipRGCs), due to factors common to both AD and Age-Related Macular Disease (AMD).

OBJECTIVES: In this study, short light pulses of three colours were introduced to a novel diagnostic procesure for AD patients such as classification techniques using waveform features of pupil light reflexs (PLRs), and their prediction performances were evaluated.

METHOD: PLRs to 1s pulses of red, blue and white stimuli shown at high and low photopic levels followed by a 7s restoration process were recorded after the stimuli were shown to 7 AD patients and 12 non-AD participants (aged 42-89). Features of waveform shapes of PLRs in 5 dimensions and 15 features of PLRs were extracted.

RESULTS: In a classification analysis, most non-AD participants were correctly identified using the same level of performance we reported when PLRs for red and blue stimuli were used to measure the performance of AD patients. There were significant differences in some of the features of PLRs extracted from the two groups (AD and non-AD participants), particularly with the features for blue light stimuli in high brightness, which produced significant reactions in AD patients. The classification performance of using 15 features of the response to blue light stimuli was the highest among responses for all three colours, and was higher than the performance using the procedure in the previous study. Also, a few of the features extracted using the three colours of stimuli changed significantly across age ranges (70 and under, 71-80, and over 80), so these may indicate factors related to ageing.

CONCLUSION: These results confirm that some specific features of PLRs, in particular the response to blue light, can indicate the existence of AD in patients. Also, a few of the features may reveal factors related to ageing during evaluations which use PLRs. This evidence may help in the better understanding of features of PLRs.