Evidence map›Paper›PMID 41739755›Full record

ArticlePloS one2026

Mapping human augmentation technologies for societal impact: A multilevel framework for classification and innovation potential.

Yousif Elsamani, Cristian Mejia, Yuya Kajikawa

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yousif ElsamaniInstitute for Future Initiatives, The University of Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0002-8519-9260
Cristian MejiaInstitute for Future Initiatives, The University of Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0002-3465-4761
Yuya KajikawaInstitute for Future Initiatives, The University of Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0003-3577-5167

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While human augmentation (HA) technologies offer significant potential for addressing societal challenges, their specific application towards social goals like sustainability, quality of life, and well-being remains understudied. This study addresses this gap by investigating the central research question: How do current HA research landscapes align with global social targets, and what are the comparative advantages of these technologies across individual, organizational and societal levels? To answer this, we employ a comprehensive bibliometric analysis of 6,284 papers across 60 specific research topics. Using citation network analysis and text similarity mapping, we reveal that although HA literature is smaller in volume, it exhibits high topical diversity and distinct specialization. Semantic mapping identifies selective but significant intersections between HA research and social domains, particularly through three influential subclusters: Industrial Worker Augmentation Systems, Human-Building Interface Assessment Technologies, and Assistive Augmentation Technologies. Based on these findings, we developed a novel nine-dimensional performance framework for multi-level evaluation of HA's societal value. The practical applicability of this framework is validated through real-world case studies, including industrial exoskeleton deployments at Ford and VR training at Walmart, demonstrating tangible gains in productivity, safety, and learning acceleration. This framework offers actionable insights for assessing HA's social impact, guiding responsible innovation, and identifying commercialization opportunities aligned with well-being, productivity, and sustainability.

Indexed as

InventionsBibliometricsHumansQuality of Life

Identifiers

PMID41739755
PMCPMC12935241

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.