Smart walkers extend conventional walking aids by integrating sensing, computation, feedback, braking, or powered actuation to support mobility, navigation, safety, gait assessment, and rehabilitation. This systematic review synthesizes smart-walker research published between January 2016 and August 2026, with emphasis on mechanical architecture, sensing, human–robot interaction, navigation, clinical validation, and translation to practice. A structured search across IEEE Xplore, PubMed, Scopus, Web of Science, and the Cochrane Central Register of Controlled Trials yielded 854 records. After duplicate removal, screening, and full-text eligibility assessment, 104 publications were retained. To avoid double counting, the corpus was separated into 97 primary studies and seven non-primary sources comprising six reviews and one study protocol. Quantitative synthesis was restricted to the 97 primary studies and was obtained from the study-level coding table. Within this coded corpus, 71 studies (73.2%) investigated active or hybrid systems and 26 studies (26.8%) investigated passive systems. Force/pressure sensing was the most frequently coded modality (46 studies, 47.4%), followed by inertial sensing (29 studies, 29.9%), vision (27 studies, 27.8%), LiDAR (25 studies, 25.8%), and ultrasonic/infrared ranging (7 studies, 7.2%); modalities were non-mutually exclusive. Validation remained heterogeneous: 37 studies (38.1%) involved no human participants, 30 studies (30.9%) used healthy/asymptomatic participants only, 24 studies (24.7%) evaluated target clinical or end-user populations, and 6 studies (6.2%) used mixed or stakeholder cohorts. The review shows substantial progress in shared control, admittance-based interaction, environmental perception, and multimodal assistance, but also identifies persistent limitations in clinical evidence, standardized evaluation, long-term deployment, and regulatory alignment. Future work should prioritize reproducible study-level reporting, patient-centered trials, robust low-cost sensing and force estimation, fail-safe shared control, and validation in realistic home and community environments.
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