Emerging hardware and software technologies have increased the development of technological solutions for people, particularly those focused on older adults’ healthcare. Human-computer interaction is a research area that uses motion capture devices as input interaction devices, e.g., touch screen devices, wearables, eye trackers, and more. Numerous primary studies have provided support and training tools for older people with physical and cognitive diseases. However, there is a need for more secondary studies that systematically summarize and evidence these solutions. To address this gap, a systematic literature review was conducted to identify and interpret all studies from 2006 to 2023 that present human-computer techniques, motion capture devices, tools, and methodologies for older adults’ physical and cognitive training and support. The review aims to answer the research question: " What devices and applications of Human-Computer Interaction (HCI) can be used to support the neuropsychological and motor condition of older adults?". The review identified 1140 potential papers from automatic searches in three digital libraries and manual searches in specialized journals and conferences. Three domain experts (computer engineer, electronics engineer, and psychologist) reviewed the papers based on inclusion and exclusion criteria and selected 79 papers for the review. Additionally, Fleiss’ kappa measure was used to achieve agreement between raters. The results provide a comprehensive overview of the state of research in this area, which can assist researchers in identifying weaknesses, directing research efforts, and new research lines. Additionally, the results can serve as a reference guide for professionals in technical and health areas who can contribute to creating better and innovative solutions to aid the older population’s physical and cognitive training and support.

Building Information Modeling-based (BIM) Digital Twins (DT) are increasingly adopted to support sustainable building management; however, the growing body of secondary literature—systematic reviews, surveys, and bibliometric studies—remains methodologically fragmented and lacks a consolidated tertiary synthesis. This fragmentation prevents researchers and practitioners from identifying consistent guidelines, validated frameworks, and comparable software ecosystems across the field. To address this gap, this study conducts a tertiary review of 57 secondary studies published between 2018 and 2025, following Kitchenham and Charters’ evidence-based guidelines and the PICOC framework. Data extraction and comparative analysis were conducted across seven criteria, including methodological approaches, proposed frameworks, enabling technologies, software tools, and reported limitations. The results reveal that bibliometric analyses and systematic literature reviews dominate the field, with few yielding structured frameworks and taxonomies; nearly half of the reviewed studies do not assess specific software platforms. Artificial intelligence and the internet of things are among the most widely studied enabling technologies, primarily associated with energy management, predictive maintenance, and structural monitoring, yet their integration with BIM-based DT platforms is inconsistently documented. The findings expose persistent interoperability constraints, insufficient data governance structures, limited maturity models, and a lack of large-scale empirical validation—gaps that this tertiary synthesis maps and prioritizes to guide future research toward reproducible, scalable, and sustainability-oriented DT implementations in the architecture, engineering, and construction sector.