2023
DOI: 10.2196/47486
|View full text |Cite
|
Sign up to set email alerts
|

Toward Personalized Medicine Approaches for Parkinson Disease Using Digital Technologies

Amit Khanna,
Graham Jones

Abstract: Parkinson disease (PD) is a complex neurodegenerative disorder that afflicts over 10 million people worldwide, resulting in debilitating motor and cognitive impairment. In the United States alone (with approximately 1 million cases), the economic burden for treating and caring for persons with PD exceeds US $50 billion and myriad therapeutic approaches are under development, including both symptomatic- and disease-modifying agents. The challenges presented in addressing PD are compounded by observations that n… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 74 publications
0
2
0
Order By: Relevance
“…Moreover, it is crucial for future studies to evaluate their findings in the context of the subgroups identified in recently published large-scale research from more conventional fields than gait analysis (cf. [52][53][54]). These discoveries should also be used to select appropriate features as inputs for clustering.…”
Section: Discussionmentioning
confidence: 99%
“…Moreover, it is crucial for future studies to evaluate their findings in the context of the subgroups identified in recently published large-scale research from more conventional fields than gait analysis (cf. [52][53][54]). These discoveries should also be used to select appropriate features as inputs for clustering.…”
Section: Discussionmentioning
confidence: 99%
“…For example, heart failure events in patients with implanted devices were accurately predicted using a multi-modal approach with the integration of physical activity, heart rate, respiration rate, and other physiological variables (Boehmer et al, 2017 ). Another example could involve evaluating the relationship between sleep quality, heart rate variability, and stress levels during the day (Khanna and Jones, 2023 ). That scenario would require data fusion from various sensors, including actigraphy, respiratory sensors (e.g., nasal airflow sensors), galvanic skin response (GSR), body temperature, and heart rate sensors (Celik and Godfrey, 2023 ).…”
Section: Clinical Challengesmentioning
confidence: 99%