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

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. 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.

Tags
Data and Resources
To access the resources you must log in

This item has no data

Identity

Description: The Identity category includes attributes that support the identification of the resource.

Field Value
PID https://www.doi.org/10.1080/17483107.2020.1817992
PID https://www.doi.org/10.6084/m9.figshare.13027691.v1
PID https://www.doi.org/10.6084/m9.figshare.13027691
URL https://www.tandfonline.com/doi/pdf/10.1080/17483107.2020.1817992
URL http://dx.doi.org/10.6084/m9.figshare.13027691.v1
URL http://dx.doi.org/10.6084/m9.figshare.13027691
URL http://dx.doi.org/10.1080/17483107.2020.1817992
Access Modality

Description: The Access Modality category includes attributes that report the modality of exploitation of the resource.

Field Value
Access Right Restricted
Attribution

Description: Authorships and contributors

Field Value
Author Modi, Nandini
Author Jaiteg Singh
Publishing

Description: Attributes about the publishing venue (e.g. journal) and deposit location (e.g. repository)

Field Value
Collected From Datacite; Crossref
Hosted By figshare; Disability and Rehabilitation Assistive Technology
Journal Disability and Rehabilitation: Assistive Technology, null, null
Publication Date 2020-09-30
Publisher Informa UK Limited
Additional Info
Field Value
Language Undetermined
Resource Type Other literature type; Article
keyword FOS: Biological sciences
keyword FOS: Computer and information sciences
keyword keywords.Physical Therapy, Sports Therapy and Rehabilitation
system:type publication
Management Info
Field Value
Source https://science-innovation-policy.openaire.eu/search/publication?articleId=dedup_wf_001::048ff12e82daa2e07dc30a2baf646a59
Author jsonws_user
Last Updated 26 December 2020, 05:12 (CET)
Created 26 December 2020, 05:12 (CET)