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Review Articles

A survey of research trends in assistive technologies using information modelling techniques

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Pages 605-623 | Received 27 Feb 2020, Accepted 28 Aug 2020, Published online: 30 Sep 2020
 

Abstract

Background

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.

Objective

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.

Methods

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.

Results

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.

Conclusions

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 Rehabilitation

  • Customized 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.

Acknowledgements

The authors are thankful to Chitkara University, Punjab for the support and successful completion of this research.

Author contributions

Nandini Modi; Literature Analysis, conceptualizeconceptualise, designed and written the paper.

Jaiteg Singh Khaira; Reviewed, advised and interpreted the data. Edited and proofread the paper. Jaiteg Singh Khaira is the corresponding author of this manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

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