FoGGAN: Generating Realistic Parkinson’s Disease Freezing of Gait Data Using GANs

Author:

Peppes Nikolaos1ORCID,Tsakanikas Panagiotis1ORCID,Daskalakis Emmanouil1ORCID,Alexakis Theodoros1ORCID,Adamopoulou Evgenia1ORCID,Demestichas Konstantinos2ORCID

Affiliation:

1. Institute of Communication and Computer Systems, National Technical University of Athens, 15773 Athens, Greece

2. Department of Agricultural Economics and Rural Development, Agricultural University of Athens, 11855 Athens, Greece

Abstract

Data scarcity in the healthcare domain is a major drawback for most state-of-the-art technologies engaging artificial intelligence. The unavailability of quality data due to both the difficulty to gather and label them as well as due to their sensitive nature create a breeding ground for data augmentation solutions. Parkinson’s Disease (PD) which can have a wide range of symptoms including motor impairments consists of a very challenging case for quality data acquisition. Generative Adversarial Networks (GANs) can help alleviate such data availability issues. In this light, this study focuses on a data augmentation solution engaging Generative Adversarial Networks (GANs) using a freezing of gait (FoG) symptom dataset as input. The data generated by the so-called FoGGAN architecture presented in this study are almost identical to the original as concluded by a variety of similarity metrics. This highlights the significance of such solutions as they can provide credible synthetically generated data which can be utilized as training dataset inputs to AI applications. Additionally, a DNN classifier’s performance is evaluated using three different evaluation datasets and the accuracy results were quite encouraging, highlighting that the FOGGAN solution could lead to the alleviation of the data shortage matter.

Funder

European Union through the Horizon 2020 Research and Innovation Programme

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference59 articles.

1. World Health Organization (WHO) (2023, May 16). Parkinson Disease. Available online: https://www.who.int/news-room/fact-sheets/detail/parkinson-disease.

2. Parkinson’s Disease;Kalia;Lancet,2015

3. NINDS (2023, September 01). Parkinson’s Disease Information Page, Available online: https://www.ninds.nih.gov/health-information/disorders/parkinsons-disease.

4. The Clinical Symptoms of Parkinson’s Disease;Sveinbjornsdottir;J. Neurochem.,2016

5. Freezing phenomenon in patients with parkinsonian syndromes;Giladi;Mov. Disord.,1997

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