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Neurological tremor: sensors, signal processing and emerging applications
Giuliana Grimaldi1, Mario Manto
1FNRS, Neurologie ULB-Erasme, 808 Route de Lennik, 1070 Bruxelles, Belgium. giulianagrim@yahoo.it
Sensors (Basel, Switzerland)
|December 30, 2011
Summary
This review explores sensors and signal processing for neurological tremor, the most common movement disorder in the elderly. It highlights current tools and future wearable solutions for tremor assessment.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Signal Processing
Background:
- Neurological tremor is a prevalent movement disorder, particularly in the elderly population.
- Tremor is characterized as a non-linear, non-stationary phenomenon requiring sophisticated detection methods.
Purpose of the Study:
- To review current instrumentation and signal processing techniques for human tremor characterization.
- To discuss the advantages and disadvantages of existing and emerging tremor sensing technologies.
Main Methods:
- Comprehensive literature review of tremor sensing technologies and signal processing algorithms.
- Analysis of commonly used sensors and novel wearable sensor systems.
- Discussion of sensor integration and fusion for advanced applications.
Main Results:
- Detailed comparison of established and emerging sensors for tremor detection.
- Identification of limitations in current tremor assessment tools.
- Exploration of future directions, including brain-computer interfaces and sensor fusion.
Conclusions:
- Sensor selection is critical for accurate tremor characterization.
- Wearable sensors offer potential for instantaneous tremor assessment.
- Future research should focus on sensor fusion and integration into brain-computer interfaces for enhanced neurological disorder management.
