An IOT Assisted Real Time Monitoring System for Parkinson's Disease

Parkinson’s disease (PD) is a progressive neurological disorder that significantly impacts motor and nonmotor functions, reducing the quality of life of affected individuals. The advent of Internet of Things (IoT) technology offers promising solutions for real-time and remote monitoring of PD symptoms, enhancing disease management and patient care. Wearable sensors and environmental monitoring devices play a crucial role in tracking symptoms such as tremors, bradykinesia, and dyskinesia, while AI-powered platforms analyze data trends to predict symptom progression and enable proactive medical interventions. One of the most promising advancements in this field is the integration of fall detection mechanisms with wearable devices. PD patients are at a high risk of falls, which can lead to severe injuries. The objective of this research is to enhance the quality of life of PD patients through the implementation of IoT-based monitoring and intervention systems. By leveraging real-time data collection, IoT-based solutions offer a transformative approach to managing Parkinson’s disease by providing continuous, real-time monitoring and personalized care.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-15
DOI
https://doi.org/10.5281/zenodo.15423314
Primary Topic
Parkinson's Disease Mechanisms and Treatments
Type
article
Field-Weighted Citation Impact
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article

An IOT Assisted Real Time Monitoring System for Parkinson's Disease

Zenodo (CERN European Organization for Nuclear Research)
Parkinson's Disease Mechanisms and Treatments
article

An IOT Assisted Real Time Monitoring System for Parkinson's Disease

article en

Abstract

Parkinson’s disease (PD) is a progressive neurological disorder that significantly impacts motor and nonmotor functions, reducing the quality of life of affected individuals. The advent of Internet of Things (IoT) technology offers promising solutions for real-time and remote monitoring of PD symptoms, enhancing disease management and patient care. Wearable sensors and environmental monitoring devices play a crucial role in tracking symptoms such as tremors, bradykinesia, and dyskinesia, while AI-powered platforms analyze data trends to predict symptom progression and enable proactive medical interventions. One of the most promising advancements in this field is the integration of fall detection mechanisms with wearable devices. PD patients are at a high risk of falls, which can lead to severe injuries. The objective of this research is to enhance the quality of life of PD patients through the implementation of IoT-based monitoring and intervention systems. By leveraging real-time data collection, IoT-based solutions offer a transformative approach to managing Parkinson’s disease by providing continuous, real-time monitoring and personalized care.

Zenodo (CERN European Organization for Nuclear Research)
Institute of Engineering (NP)
Openalex Percentile: Top 41%
Parkinson's Disease Mechanisms and Treatments
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