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A Mobile Phone–Based Gait Assessment App for the Elderly: Development and Evaluation

步态 移动电话 移动应用程序 健康 心理学 物理医学与康复 计算机科学 医学 万维网 人机交互 心理干预 护理部 电信
作者
Runting Zhong,Pei‐Luen Patrick Rau
出处
期刊:Jmir mhealth and uhealth [JMIR Publications]
卷期号:8 (5): e14453-e14453 被引量:45
标识
DOI:10.2196/14453
摘要

Background Gait disorders are common among older adults. With an increase in the use of technology among older adults, a mobile phone app provides a solution for older adults to self-monitor their gait quality in daily life. Objective This study aimed to develop a gait-monitoring mobile phone app (Pocket Gait) and evaluate its acceptability and usability among potential older users. Methods The app was developed to allow older adults to track their gait quality, including step frequency, acceleration root mean square (RMS), step regularity, step symmetry, and step variability. We recruited a total of 148 community-dwelling older adults aged 60 years and older from two cities in China: Beijing and Chongqing. They walked in three ways (single task, dual task, and fast walking) using a smartphone with the gait-monitoring app installed and completed an acceptability and usability survey after the walk test. User acceptability was measured by a questionnaire including four quantitative measures: perceived ease of use, perceived usefulness, ease of learning, and intention to use. Usability was measured using the System Usability Scale (SUS). Interviews were conducted with participants to collect open-ended feedback questions. Results Task type had a significant effect on all gait parameters, namely, step frequency, RMS, step variability, step regularity, and step symmetry (all P values <.001). Age had a significant effect on step frequency (P=.01), and region had a significant effect on step regularity (P=.04). The acceptability of the gait-monitoring app was positive among older adults. Participants identified the usability of the system with an overall score of 59.7 (SD 10.7) out of 100. Older adults from Beijing scored significantly higher SUS compared with older adults from Chongqing (P<.001). The age of older adults was significantly associated with their SUS score (P=.048). Older adults identified improvements such as a larger font size, inclusion of reference values for gait parameters, and inclusion of heart rate and blood pressure monitoring. Conclusions This mobile phone app is a health management tool for older adults to self-manage their gait quality and prevent adverse outcomes. In the future, it will be important to take factors such as age and region into consideration while designing a mobile phone–based gait assessment app. The feedback of the participants would help to design more elderly-friendly products.

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