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Related Experiment Video

Updated: Apr 11, 2026

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

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

Published on: December 11, 2015

A wearable smartphone-enabled camera-based system for gait assessment.

Albert Kim¹, Junyoung Kim¹, Shirley Rietdyk²

¹School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA; Birck Nanotechnology Center, Purdue University, West Lafayette, IN, USA.

|June 11, 2015

Summary

A new smartphone system, SmartGait, offers a low-cost, portable solution for measuring spatiotemporal gait parameters. It shows good agreement with traditional systems, making it a viable option for gait analysis.

Keywords:

Gait assessment SmartGait Step width Variability Wearable

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Last Updated: Apr 11, 2026

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

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

Published on: December 11, 2015

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

Published on: March 14, 2017

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults

Published on: November 7, 2014

Area of Science:

Biomechanics
Wearable Technology
Gait Analysis

Background:

Traditional gait analysis systems are often expensive, bulky, and confined to lab settings.
Wearable systems offer a more accessible and portable alternative for gait assessment.

Purpose of the Study:

To introduce and validate SmartGait, a smartphone-enabled camera-based wearable system for measuring spatiotemporal gait parameters.
To assess the concurrent validity of SmartGait against a commercial pressure-sensing walkway (GaitRite).

Main Methods:

Fifteen healthy young adults walked at various speeds (slow, preferred, fast).
Spatiotemporal gait parameters (step length, width, time, gait speed, double support time) and their variability were measured using SmartGait and GaitRite.
Agreement was assessed using absolute error and intra-class correlation coefficients (ICCs).

Main Results:

SmartGait demonstrated modest to excellent agreement with GaitRite for measured gait parameters (ICCs ranging from 0.731 to 0.982).
The system accurately captured various gait metrics across different walking speeds.

Conclusions:

SmartGait is a promising, cost-effective wearable system for quantitative gait assessment.
It serves as a strong alternative for both laboratory and community-based gait analysis, enhancing accessibility and portability.