Use of Wearable Sensors to Assess Fall Risk in Neurological Disorders: Systematic Review.

Area of Science:

• Biomedical Engineering
• Neurorehabilitation
• Gait Analysis

Background:

• Fall risk assessment is crucial for individuals with neurological disorders to prevent hospitalization and maintain functional independence.
• Wearable sensors offer continuous, unsupervised monitoring for real-world fall risk assessment in neurorehabilitation.
• This study focuses on neurological disorders including Parkinson disease, multiple sclerosis, stroke, and Alzheimer disease.

Purpose of the Study:

• Systematically review reliable biomechanical gait parameters from wearable sensors for fall risk assessment in neurological disorders.
• Examine advancements in wearable sensor technology, device placement, and data processing for fall risk assessment.
• Focus on patients with Parkinson disease, multiple sclerosis, stroke, and Alzheimer disease.

Main Methods:

• Conducted a systematic literature search up to April 18, 2025.
• Utilized major databases: PubMed, Web of Science, Embase, and IEEE Xplore.
• Included studies focused on wearable sensors for fall risk in neurological disorders.

Main Results:

• 19 studies involving 2630 patients were included.
• Parkinson disease was the most studied group (87.64%), followed by multiple sclerosis (8.59%), stroke (1.94%), and Alzheimer disease (1.83%).
• The review identified key biomechanical gait parameters and technological advancements.

Conclusions:

• Wearable technologies play a significant role in assessing fall risk in patients with neurological disorders.
• Variations in methods and a technology-centric approach indicate ongoing advancements in the field.
• The lack of standardization in current research reflects the dynamic nature of wearable sensor technology in neurorehabilitation.