Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, India.
Disabil Rehabil Assist Technol. 2022 Aug;17(6):605-623. doi: 10.1080/17483107.2020.1817992. Epub 2020 Sep 30.
Despite the rapid proliferation and emphasis on technology, the use of assistive technology among individuals with varying disabilities and age is different. This situation instigates the need for a systematic review to gain a realistic understanding of prominent issues, research trends and assistive technology applications with minimal bias.
Identification of leading researchers and prominent publications in assistive technologies. Subsequently, semantic relation between qualitative and quantitative research literature on assistive technologies was explored to future research directions.
A manual search across reputed research databases was done to find out relevant literature from January 2005 to April 2020. In this paper, latent semantic analysis (LSA) was done to develop an information model for achieving defined objectives.
A corpus of 367 research papers published during 2005-2020 was processed using LSA. Term frequency, inverse document frequency of high loading terms provided five major topic solutions. Marcia Scherer, Rory Cooper and Stefano Federici are most noticed authors in assistive technology research. "Smart Assistive Technologies" and "Wearable Technologies for Rehabilitation" came out as contemporary research trends within assistive technologies.
The manuscript concludes the fact that assistive technologies for rehabilitation are experiencing a transition from standalone mechanical devices towards smart, wearable and connected devices.Implications for RehabilitationCustomized assistive devices could be programmed for multiple uses.User data privacy and internet dependency of smart assistive technologies must be taken care of while designing smart assistive devices for rehabilitation.Fog devices could eliminate the latency issues associated with cloud-based rehabilitation services.
尽管技术迅速普及和重视，但不同残疾程度和年龄段的个体对辅助技术的使用情况存在差异。这种情况促使我们需要进行系统评价，以真实了解辅助技术的突出问题、研究趋势和应用，同时尽量减少偏见。
确定辅助技术领域的主要研究人员和重要出版物。然后，探索辅助技术定性和定量研究文献之间的语义关系，以确定未来的研究方向。
通过手动搜索知名研究数据库，查找 2005 年 1 月至 2020 年 4 月期间的相关文献。在本文中，我们使用潜在语义分析（LSA）来开发信息模型，以实现既定目标。
使用 LSA 处理 2005-2020 年期间发表的 367 篇研究论文。高负荷项的词频、逆文档频率提供了五个主要的主题解决方案。Marcia Scherer、Rory Cooper 和 Stefano Federici 是辅助技术研究中最受关注的作者。“智能辅助技术”和“康复用可穿戴技术”是辅助技术领域的当代研究趋势。
本文的结论是，康复辅助技术正经历从独立机械装置向智能、可穿戴和互联设备的转变。对康复的启示：可针对多种用途为定制的辅助设备编程。在设计康复用智能辅助设备时，必须注意用户数据隐私和智能辅助技术对互联网的依赖。雾计算设备可以消除基于云的康复服务相关的延迟问题。
