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

• Main Authors: Patima Silsupadol, Paphawee Prupetkaew, Teerawat Kamnardsiri, Vipul Lugade
• Format: Journal
• Published: 2020
• Subjects: Biochemistry, Genetics and Molecular Biology; Computer Science; Engineering; Health Professions
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85074302030&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/70246
• Institution: Chiang Mai University

© 2013 IEEE. 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.