Literature DB >> 21097067

Implementation of an iPhone as a wireless accelerometer for quantifying gait characteristics.

Robert Lemoyne1, Timothy Mastroianni, Michael Cozza, Cristian Coroian, Warren Grundfest.   

Abstract

The capacity to quantify and evaluate gait beyond the general confines of a clinical environment under effectively autonomous conditions may alleviate rampant strain on limited and highly specialized medical resources. An iPhone consists of a three dimensional accelerometer subsystem with highly robust and scalable software applications. With the synthesis of the integral iPhone features, an iPhone application, which constitutes a wireless accelerometer system for gait quantification and analysis, has been tested and evaluated in an autonomous environment. The acquired gait cycle data was transmitted wireless and through email for subsequent post-processing in a location remote to the location where the experiment was conducted. The iPhone application functioning as a wireless accelerometer for the acquisition of gait characteristics has demonstrated sufficient accuracy and consistency.

Mesh:

Year:  2010        PMID: 21097067     DOI: 10.1109/IEMBS.2010.5627699

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  15 in total

1.  Evaluation of a smartphone platform as a wireless interface between tongue drive system and electric-powered wheelchairs.

Authors:  Jeonghee Kim; Xueliang Huo; Julia Minocha; Jaimee Holbrook; Anne Laumann; Maysam Ghovanloo
Journal:  IEEE Trans Biomed Eng       Date:  2012-04-16       Impact factor: 4.538

Review 2.  Mobile health use in low- and high-income countries: an overview of the peer-reviewed literature.

Authors:  Andrew Bastawrous; Matthew J Armstrong
Journal:  J R Soc Med       Date:  2013-04       Impact factor: 5.344

3.  Sensitivity of fNIRS measurement to head motion: an applied use of smartphones in the lab.

Authors:  Xu Cui; Joseph M Baker; Ning Liu; Allan L Reiss
Journal:  J Neurosci Methods       Date:  2015-02-14       Impact factor: 2.390

4.  Objective assessment of abnormal gait in patients with rheumatoid arthritis using a smartphone.

Authors:  Minoru Yamada; Tomoki Aoyama; Shuhei Mori; Shu Nishiguchi; Kazuya Okamoto; Tatsuaki Ito; Shinyo Muto; Tatsuya Ishihara; Hiroyuki Yoshitomi; Hiromu Ito
Journal:  Rheumatol Int       Date:  2011-12-23       Impact factor: 2.631

5.  Smartphone-based diagnostic for preeclampsia: an mHealth solution for administering the Congo Red Dot (CRD) test in settings with limited resources.

Authors:  Stephan Michael Jonas; Thomas Martin Deserno; Catalin Sorin Buhimschi; Jennifer Makin; Michael Andrew Choma; Irina Alexandra Buhimschi
Journal:  J Am Med Inform Assoc       Date:  2015-05-29       Impact factor: 4.497

Review 6.  Gait metrics analysis utilizing single-point inertial measurement units: a systematic review.

Authors:  Ralph Jasper Mobbs; Jordan Perring; Suresh Mahendra Raj; Monish Maharaj; Nicole Kah Mun Yoong; Luke Wicent Sy; Rannulu Dineth Fonseka; Pragadesh Natarajan; Wen Jie Choy
Journal:  Mhealth       Date:  2022-01-20

7.  Reliability and criterion-related validity with a smartphone used in timed-up-and-go test.

Authors:  Alejandro Galán-Mercant; Francisco Javier Barón-López; María T Labajos-Manzanares; Antonio I Cuesta-Vargas
Journal:  Biomed Eng Online       Date:  2014-12-02       Impact factor: 2.819

8.  Differences in trunk accelerometry between frail and non-frail elderly persons in functional tasks.

Authors:  Alejandro Galán-Mercant; Antonio I Cuesta-Vargas
Journal:  BMC Res Notes       Date:  2014-02-21

9.  Differences in trunk kinematic between frail and nonfrail elderly persons during turn transition based on a smartphone inertial sensor.

Authors:  Alejandro Galán-Mercant; Antonio I Cuesta-Vargas
Journal:  Biomed Res Int       Date:  2013-11-28       Impact factor: 3.411

10.  Accuracy, Consistency, and Reproducibility of the Triaxial Accelerometer in the iPod Touch: A Pilot Study.

Authors:  Christopher Khoo Chee Han; Rukmanikanthan Al Shanmugam; David Choon Siew Kit
Journal:  JMIR Mhealth Uhealth       Date:  2014-11-24       Impact factor: 4.773

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