Literature DB >> 31329138

Smartphone-Based Assessment of Gait During Straight Walking, Turning, and Walking Speed Modulation in Laboratory and Free-Living Environments.

Patima Silsupadol, Paphawee Prupetkaew, Teerawat Kamnardsiri, Vipul Lugade.   

Abstract

As turns and walking speed modulation are crucial for functional mobility, development of a field-based tool to objectively evaluate non-steady-state gait is essential. This study aimed to quantify spatiotemporal gait using three Android smartphones during steady-state walking, turns, and gait speed modulation in laboratory and free-living environments. In total, 24 adults ambulated along a 10-m walkway in both environments under seven conditions: straight walking, 90° left or right turn, and modulating gait speed from usual-slow, usual-fast, slow-fast, and fast-slow. Two smartphones were attached to the body, with another phone placed in a shoulder bag. Gait velocity, step time, step length, cadence, and symmetry were computed from smartphone-based tri-axial accelerometers and validated with motion capture and video, in laboratory and free-living environments, respectively. Validity was assessed using Pearson's correlation and Bland-Altman analysis. Gait velocity results revealed moderate to very high validity across all walking conditions, smartphone models, smartphone locations, and environments. Correlations for gait velocity ranged between 0.87-0.91 and 0.79-0.83 for straight walking, 0.86-0.95 and 0.86-0.89 for turning, and 0.51-0.90 and 0.67-0.89 for speed modulation trials, in laboratory and free-living environments, respectively. Step time, step length, and cadence demonstrated high to very high correlations for straight walking and turns. However, symmetry results revealed high correlations only during straight walking in the laboratory. Conditions that included slow walking showed negligible to moderate validity with a high bias. In conclusion, smartphones can be employed as field-based devices to assess steady-state walking, turning, and speed modulation across environment, model, and placement when walking faster than 0.5 m/s.

Mesh:

Year:  2019        PMID: 31329138     DOI: 10.1109/JBHI.2019.2930091

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  8 in total

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Authors:  M L Weidemann; K Trentzsch; C Torp; T Ziemssen
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2.  A novel smartphone application is reliable for repeat administration and comparable to the Tekscan Strideway for spatiotemporal gait.

Authors:  Marie Kelly; Peter Jones; Ryan Wuebbles; Vipul Lugade; Daniel Cipriani; Nicholas G Murray
Journal:  Measurement (Lond)       Date:  2022-02-11       Impact factor: 3.927

3.  Reliability of Smartphone Accelerometers for Measuring Gait During Data Collection Over Zoom.

Authors:  Nancy T Nguyen; Jefferson W Streepey
Journal:  Telemed Rep       Date:  2022-06-28

4.  Smartphone Monitoring of Gait and Balance During Irregular Surface Walking and Obstacle Crossing.

Authors:  Janeesata Kuntapun; Patima Silsupadol; Teerawat Kamnardsiri; Vipul Lugade
Journal:  Front Sports Act Living       Date:  2020-11-27

5.  Validity and Reliability of a Smartphone App for Gait and Balance Assessment.

Authors:  Usman Rashid; David Barbado; Sharon Olsen; Gemma Alder; Jose L L Elvira; Sue Lord; Imran Khan Niazi; Denise Taylor
Journal:  Sensors (Basel)       Date:  2021-12-25       Impact factor: 3.576

6.  Smart Eyeglasses: A Valid and Reliable Device to Assess Spatiotemporal Parameters during Gait.

Authors:  Justine Hellec; Frédéric Chorin; Andrea Castagnetti; Olivier Guérin; Serge S Colson
Journal:  Sensors (Basel)       Date:  2022-02-04       Impact factor: 3.576

7.  Artificial intelligence, machine learning, and deep learning in orthopedic surgery.

Authors:  O Şahap Atik
Journal:  Jt Dis Relat Surg       Date:  2022

8.  The validity and reliability of the OneStep smartphone application under various gait conditions in healthy adults with feasibility in clinical practice.

Authors:  Jesse C Christensen; Ethan C Stanley; Evan G Oro; Hunter B Carlson; Yuval Y Naveh; Rotem Shalita; Levi S Teitz
Journal:  J Orthop Surg Res       Date:  2022-09-14       Impact factor: 2.677

  8 in total

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