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Related Experiment Video

Updated: Feb 21, 2026

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

Published on: March 14, 2017

Characterizing Orthostatic Tremor Using a Smartphone Application.

Arjun Balachandar¹, Alfonso Fasano^2,3

¹University of Toronto Medical School, Toronto, Ontario, Canada.

Tremor and Other Hyperkinetic Movements (New York, N.Y.)

|October 5, 2017

Summary

This summary is machine-generated.

Orthostatic tremor diagnosis can be challenging as it is often invisible. An iPhone app successfully detected tremor in a patient, showing potential for accessible lower limb tremor assessment.

Keywords:

Accelerometer diagnosis orthostatic tremor smartphone wearable

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Last Updated: Feb 21, 2026

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

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Published on: March 14, 2017

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

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Published on: December 11, 2015

Home-Based Monitor for Gait and Activity Analysis

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Published on: August 8, 2019

Area of Science:

Neurology
Biomedical Engineering

Background:

Orthostatic tremor (OT) diagnosis can be challenging due to its subtle presentation, often necessitating electromyography.
Lower limb tremor may not be clinically apparent, complicating diagnosis.

Observation:

An iPhone 5 running the iSeismometer application was utilized to record tremor in a patient's sock.
Accelerometer data captured a distinct tremor at 16.4 Hz in both lower limbs.

Findings:

The study demonstrates the feasibility of using a smartphone application for quantitative analysis of orthostatic tremor.
The iPhone's accelerometer effectively detected and recorded tremor frequency.

Implications:

This approach offers a simple, rapid, and quantitative method for assessing lower limb tremors.
Smartphone-based accelerometry presents a potential tool for broader clinical application in tremor assessment.