An exploratory user study on the design of smart walking aids for community-dwelling older adults

Population aging has increasingly become an issue of concern globally. Aging inevitably reduces older adults’ physical capacity (e.g., mobility) and further affects their ability to live independently or perform daily activities. Walking aids (e.g., canes) are generally used as assistive devices to provide physical support and reduce fall risk in daily activities. Given the rapid development of artificial intelligence algorithms and hardware computing capability, smart walking aids with functions like fall alert, health monitoring, and positioning have become promising in elderly care. However, it remains unclear whether community-dwelling older adults are ready for smart walking aids. The present study aims to explore community-dwelling older adults’ attitudes and perceptions of smart walking aids, especially on the functions of fall alert, health monitoring, pill reminder, positioning, and topography detection. The results are expected to guide future designs of smart walking aids to increase users’ well-being in daily life. A convenience sampling method was applied to collect data via an online questionnaire for demographic information, attitudes, and design expectations toward smart walking aids. Chi-square tests and binary logistic regression models were used to analyze the associations among demographics, attitudes, and design expectations. The data were collected from 264 valid respondents (148 males and 116 females; 60.5±7.4 years). The results showed safety assurance, sturdy products, and additional intelligent functions were the most expected design elements in smart walking aids. Community-dwelling older adults preferred three intelligent functions: fall alert, health monitoring, and positioning. However, complex operations would resist users from adopting smart walking aids, showing the importance of usability in future designs. No significant group differences were found in purchase preference and attitudes toward smart walking aids among gender (p > 0.06), education (p > 0.35), and living arrangement (p > 0.06). The results of binary logistic regressions showed that individuals with a user history of smart walking aids are about ten times more likely to buy smart walking aids than those with no user history (p = 0.025, OR = 10.376). Older adults aged 71-80 preferred smart walking aids over other age groups (p = 0.048). Individuals aged 61-70 years are more interested in the intelligent functions of fall alert (p = 0.002) and health monitoring (p = 0.021). Community-dwelling older adults showed positive attitudes to smart walking aids with functions such as fall alerts, health monitoring, and positioning to support their independence in their daily lives. User-centered designs are crucially needed to speed up the successful implementation of smart walking aids in the community.