Design of smart wheelchairs integrated with voice and joystick control, and obstacle detection system for Zimbabwe people: a review paper.

Smart wheelchairs are increasingly recognised as essential assistive technologies that support independence and mobility. Despite significant progress, their adoption remains limited by design fragmentation, inconsistent performance metrics, and insufficient adaptation to diverse user needs and resource-constrained contexts. This review synthesises evidence on three key control approaches: voice control, joystick control, and obstacle detection, while highlighting practical challenges and opportunities for improvement. A PRISMA-guided systematic review of Scopus and ProQuest (2017-2025) identified 2,252 records, of which 90 peer-reviewed studies met the inclusion criteria. Data extraction focused on control methods, obstacle detection technologies, performance outcomes, and reported limitations. Voice control offers hands-free convenience but suffers from recognition errors in noisy environments, poor support for local languages, and limited offline modes. Joystick control remains the most robust but induces fatigue and excludes users with severe impairments. Obstacle detection systems, from ultrasonic to LiDAR and sensor fusion, show strong accuracy in controlled settings but lack standardised benchmarks for real-world deployment. Across studies, major limitations include the absence of Safe Mode and fallback mechanisms, fragmented evaluation frameworks, limited user-centred testing, and little adaptation for low-resource settings such as Zimbabwe. Future smart wheelchair development should prioritise hybrid control paradigms, lightweight AI for efficiency, clean-energy power solutions, and participatory co-design models that integrate caregivers and local contexts. This review not only consolidates current evidence but also outlines a roadmap for inclusive, sustainable, and context-responsive smart wheelchair innovation.