Literature DB >> 25405433

Agreement in gait speed from smartphone and stopwatch for five meter walk in laboratory and clinical environments.

Rahul Soangra1, Thurmon E Lockhart.   

Abstract

Gait speed is suggested as an independent predictor of post-operative morbidity and mortality in elderly cardiovascular disease (CVD) patients. Society of thoracic surgeons has recently classified gait speed as the only important indicator of health for CVD patients. It has been seen that patients with slow gait speed above 70 years of age, taking more than 6 seconds to walk 5 meters are particularly at high risk for adverse outcomes. Twelve young participants walked in their self-selected, slow and fast speed with five reflective markers at sternum and heels and toes of both feet in laboratory environment. A smartphone was affixed at the pelvis using a smartphone holster. Simultaneously, an examiner used stopwatch to record the elapsed time necessary to cross 5 meter distance. Smartphone based app also computed gait speed. Intra-class correlation coefficients comparing velocities from camera system, smartphone and stopwatch systems were found to be highly reliable (ICC (3,k)=0.82) for slow walking speed. Similarly, fairly good reliability were found for fast (ICC(3,k)=0.70) and normal walking speed (ICC(3,k)=0.66). Five CVD patients were tested in clinical environment with smartphone and its feasibility was assessed for gait speed. This study shows that the smartphone and stopwatch gait speed methods have clinically acceptable agreement for the measurement of gait velocity in the two different environments. The smartphone based reliable measurements could help patients on their own to assess operative risks and health during perioperative period.

Entities:  

Year:  2014        PMID: 25405433      PMCID: PMC6615543     

Source DB:  PubMed          Journal:  Biomed Sci Instrum        ISSN: 0067-8856


  5 in total

1.  Objective performance tests of cognition and physical function as part of a virtual geriatric assessment.

Authors:  Nupur E Bahl; Emily S Magnavita; Tammy Hshieh; Marcia Testa; Dae Kim; Brad Manor; Jane A Driver; Gregory A Abel; Clark DuMontier
Journal:  J Geriatr Oncol       Date:  2021-03-29       Impact factor: 3.599

2.  Analysis of a Smartphone-Based Architecture with Multiple Mobility Sensors for Fall Detection with Supervised Learning.

Authors:  José Antonio Santoyo-Ramón; Eduardo Casilari; José Manuel Cano-García
Journal:  Sensors (Basel)       Date:  2018-04-10       Impact factor: 3.576

3.  Inertial Sensor-Based Variables Are Indicators of Frailty and Adverse Post-Operative Outcomes in Cardiovascular Disease Patients.

Authors:  Rahul Soangra; Thurmon E Lockhart
Journal:  Sensors (Basel)       Date:  2018-06-02       Impact factor: 3.576

4.  Smartphone-Based Prediction Model for Postoperative Cardiac Surgery Outcomes Using Preoperative Gait and Posture Measures.

Authors:  Rahul Soangra; Thurmon Lockhart
Journal:  Sensors (Basel)       Date:  2021-03-02       Impact factor: 3.576

5.  Validity and Reliability of the Insole3 Instrumented Shoe Insole for Ground Reaction Force Measurement during Walking and Running.

Authors:  Leora A Cramer; Markus A Wimmer; Philip Malloy; Joan A O'Keefe; Christopher B Knowlton; Christopher Ferrigno
Journal:  Sensors (Basel)       Date:  2022-03-11       Impact factor: 3.576

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.