Fitts Law-Based Performance Metrics to Quantify Tremor in Individuals with Essential Tremor

Intelligent devices for assessing essential tremor: a comprehensive review

Essential tremor (ET) stands as the most prevalent movement disorder, characterized by rhythmic and involuntary shaking of body parts. Achieving an accurate and comprehensive assessment of tremor severity is crucial for effectively diagnosing and managing ET. Traditional methods rely on clinical observation and rating scales, which may introduce subjective biases and hinder continuous evaluation of disease progression. Recent research has explored new approaches to quantifying ET. A promising method involves the use of intelligent devices to facilitate objective and quantitative measurements. These devices include inertial measurement units, electromyography, video equipment, and electronic handwriting boards, and more. Their deployment enables real-time monitoring of human activity data, featuring portability and efficiency. This capability allows for more extensive research in this field and supports the shift from in-lab/clinic to in-home monitoring of ET symptoms. Therefore, this review provides an in-depth analysis of the application, current development, potential characteristics, and roles of intelligent devices in assessing ET.

Upper limb intention tremor assessment: opportunities and challenges in wearable technology

BACKGROUND

Tremors are involuntary rhythmic movements commonly present in neurological diseases such as Parkinson's disease, essential tremor, and multiple sclerosis. Intention tremor is a subtype associated with lesions in the cerebellum and its connected pathways, and it is a common symptom in diseases associated with cerebellar pathology. While clinicians traditionally use tests to identify tremor type and severity, recent advancements in wearable technology have provided quantifiable ways to measure movement and tremor using motion capture systems, app-based tasks and tools, and physiology-based measurements. However, quantifying intention tremor remains challenging due to its changing nature.

METHODOLOGY & RESULTS

This review examines the current state of upper limb tremor assessment technology and discusses potential directions to further develop new and existing algorithms and sensors to better quantify tremor, specifically intention tremor. A comprehensive search using PubMed and Scopus was performed using keywords related to technologies for tremor assessment. Afterward, screened results were filtered for relevance and eligibility and further classified into technology type. A total of 243 publications were selected for this review and classified according to their type: body function level: movement-based, activity level: task and tool-based, and physiology-based. Furthermore, each publication's methods, purpose, and technology are summarized in the appendix table.

CONCLUSIONS

Our survey suggests a need for more targeted tasks to evaluate intention tremors, including digitized tasks related to intentional movements, neurological and physiological measurements targeting the cerebellum and its pathways, and signal processing techniques that differentiate voluntary from involuntary movement in motion capture systems.

A Wearable In-home Tremor Assessment System via Virtual Reality Environment for the Activities in Daily Lives (ADLs)

Currently available diagnostic methods for tremor movements are mostly subjective measurements, and clinicians and researchers typically diagnose patients' symptoms with provocative maneuvers, and the inter-rater and intra-rater variabilities of those methods have been always reported. Even though various sensor-based quantitative approaches have been explored, most of the tools are limited to the tremor metrics (i.e., severity and frequency). A consistent environment that can provide a test setup to evaluate how their performance is affected by the tremor movement for activities of daily living would be needed for a smart tremor diagnosis. Therefore, we developed a virtual reality environment with a custom designed wearable sensor module to quantify tremor characteristics with performance-based assessment while they perform the activities of daily living, and correlated the performance to existing tremor scores (i.e., The Essential Tremor Rating Assessment Scale (TETRAS)). We evaluated this approach with five healthy participants (no tremor), and applied an artificial tremor using a vibration motor to mimic tremor movements as a pilot study. We analyzed three categorized tremor scenarios: resting, postural, and kinetic tremor tasks using six different tasks in virtual 3D space. All the artificial tremor was score as TETRAS=1, and we successfully analyzed the tremor metrics for different tasks by comparing them with TETRAS score, and verified the different tremor characteristics with the artificial tremor. Additionally, we analyzed the performance of 3D spiral drawing on the virtual reality track using "outside area" and "completion time" as the accuracy and speed of the performance. Clinical Relevance- This can be applied to quantify and track the tremor symptom at the patients' home, and ultimately this method can be synchronized with their current treatment parameters (i.e., dosage of medication, and parameters of the stimulation) to optimize/maximize the effect of treatment.

Analyzing the Effects of Parameters for Tremor Modulation via Phase-Locked Electrical Stimulation on a Peripheral Nerve

(1) Background: Non-invasive neuromodulation is a promising alternative to medication or deep-brain stimulation treatment for Parkinson's Disease or essential tremor. In previous work, we developed and tested a wearable system that modulates tremor via the non-invasive, electrical stimulation of peripheral nerves. In this article, we examine the proper range and the effects of various stimulation parameters for phase-locked stimulation. (2) Methods: We recruited nine participants with essential tremor. The subjects performed a bean-transfer task that mimics an eating activity to elicit kinetic tremor while using the wearable stimulation system. We examined the effects of stimulation with a fixed duty cycle, at different stimulation amplitudes and frequencies. The epochs of stimulation were locked to one of four phase positions of ongoing tremor, as measured with an accelerometer. We analyzed stimulation-evoked changes of the frequency and amplitude of tremor. (3) Results: We found that the higher tremor amplitude group experienced a higher rate of tremor power reduction (up to 65%) with a higher amplitude of stimulation when the stimulation was applied at the ±peak of tremor phase. (4) Conclusions: The stimulation parameter can be adjusted to optimize tremor reduction, and this study lays the foundation for future large-scale parameter optimization experiments for personalized peripheral nerve stimulation.