A Systematic Survey of Research Trends in Technology Usage for Parkinson's Disease

Abstract

Parkinson's disease (PD) is a neurological disorder with complicated and disabling motor and non-motor symptoms. The complexity of PD pathology is amplified due to its dependency on patient diaries and the neurologist's subjective assessment of clinical scales. A significant amount of recent research has explored new cost-effective and subjective assessment methods pertaining to PD symptoms to address this challenge. This article analyzes the application areas and use of mobile and wearable technology in PD research using the PRISMA methodology. Based on the published papers, we identify four significant fields of research: diagnosis, prognosis and monitoring, predicting response to treatment, and rehabilitation. Between January 2008 and December 2021, 31,718 articles were published in four databases: PubMed Central, Science Direct, IEEE Xplore, and MDPI. After removing unrelated articles, duplicate entries, non-English publications, and other articles that did not fulfill the selection criteria, we manually investigated 1559 articles in this review. Most of the articles (45%) were published during a recent four-year stretch (2018-2021), and 19% of the articles were published in 2021 alone. This trend reflects the research community's growing interest in assessing PD with wearable devices, particularly in the last four years of the period under study. We conclude that there is a substantial and steady growth in the use of mobile technology in the PD contexts. We share our automated script and the detailed results with the public, making the review reproducible for future publications.

Keywords: Parkinson’s disease; biopotential devices; diagnosis; digital health; prognosis; taxonomy; wearable devices.

Figure 1

The number of research publications between 2008 and 2021 that measure each sign and symptom.

Figure 2

Flow diagram of our systematic review process for PD-assessment research publications (2008–2021).

Figure 3

Keyword blocks constructed according to the PICO strategy to determine the relevance of an article to this review.

Figure 4

The yearly publication trends between 2008 and 2021 in each application area.

Figure 5

Percentage of publications (2008–2021) by application area.

Figure 6

The number of research publications (2008–2021) divided by PD application area: (a) publications about diagnosis, (b) publications about prognosis and monitoring, (c) publications about predicting patient responses to treatments, and (d) publications about rehabilitation.

Figure 7

The heat-map presenting the number of research publications (2008–2021) that address the measuring of motor PD symptoms (the darker the color, the higher the number).

Figure 8

The number of research publications (2008–2021) examining the application of new technologies to specific types of PD symptoms (e.g., FoG, and tremor).

Figure 9

The heat-map presenting the number of research publications (2008–2021) that address the measuring of non-motor PD symptoms (the darker the color, the higher the number).

Figure 10

Number of research publications (2008–2021) examining the application of specific types of new technologies to PD areas.

Figure 11

The number of research publications between 2008 and 2021. (a) Studies that use biopotential devices for PD assessment, (b) studies that use wearable devices for PD assessment. The solid lines shows the trend of the publications in the last 14 years.

Figure 12

The heat-map presenting the number of research publications (2008–2021) that address PD assessment using modern technology (the darker the color, the higher the number.

Figure 13

The distribution of articles published between 2008 and 2021 related to the assessment of Parkinson’s disease using wearable and mobile technology.