Skip to main content
Enterprise AI Analysis: Robots for Older Adults: A Scoping Review

ENTERPRISE AI ANALYSIS

Robots for Older Adults: A Scoping Review

Authors: SAMUEL A. OLATUNJI, YAO-LIN TSAI, SAATHVEEK A. GOWRISHANKAR, MEGAN A. BAYLES, WENDY A. ROGERS

Publication: ACM Transactions on Human-Robot Interaction - 03 March 2026

Discuss Your Enterprise AI Strategy

Executive Impact Summary

Key metrics from the research, highlighting the quantitative impact and scope of the study for enterprise decision-makers.

205 Total Studies Reviewed
12 Years Covered
93.2 Average Intercoder Reliability
74 Mean Age of Participants

Deep Analysis & Enterprise Applications

Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.

52% of robots focused on Enhanced Activities of Daily Living (EADLs)

Tasks Explored for Robots Supporting Older Adults (RQ3)

Description: More than half (52%) of robots focused on Enhanced Activities of Daily Living (EADLs), including companionship, entertainment, and video communication. Common Instrumental Activities of Daily Living (IADLs) supported were medication reminders, retrieving/delivering items, housekeeping, and shopping assistance. Few robots supported basic Activities of Daily Living (ADLs) directly, with most ADL-focused robots still in development.

Key Takeaway: EADLs dominate current robot support, with significant opportunities for growth in ADLs and IADLs to address higher-need areas for older adults.

PRISMA Flow Diagram

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed to ensure comprehensive and transparent reporting. The process involved defining a review protocol, documenting a search strategy, specifying inclusion/exclusion criteria, and developing a coding scheme.

Records identified from Google Scholar (n = 3036)
→
Records removed before screening: Duplicates removed (n = 677)
→
Records Screened: Title and Abstract (n = 2359)
→
Records excluded (n = 1796) - Does not include older adults (n = 1031), No robots (n = 313), Review articles (n = 249), Survey articles, technical reports, white papers & other grey literature (n = 46), Position papers (n = 28), Purely virtual agents (n = 9), Human-computer interaction (n = 22), No human-robot interaction (n = 31), Records before 2000 (n = 2), No access to article (n=24), Additional duplicates removed (n = 41)
→
Reports assessed for eligibility (n = 563)
→
Reports excluded (n = 358) - Book chapter (n = 84), Proposal paper (n = 52), Does not include older adults (n = 38), Review articles (n = 29), Position paper (n = 5), No human-robot interaction (n = 150)
→
Studies included in review (n = 205)

Remote HRI Studies During COVID-19

Description: The COVID-19 pandemic necessitated remote Human-Robot Interaction (HRI) studies, opening new dimensions for research. These included robot delivery, Wizard-of-Oz experiments through telepresence, video-enhanced web-surveys, and 'Stay at Home' experiments where simple robots were delivered or participants used their own (e.g., Roomba). This period highlighted adaptability and innovation in research methodology.

Key Takeaway: Remote HRI methods advanced significantly during the pandemic, revealing new avenues for research despite in-person interaction limitations.

Diversity of Health Conditions Focused in Past Years

The research highlights a diversity of health conditions addressed by robot interventions for older adults, moving beyond solely 'healthy' participants.
Health ConditionsDescription/ExamplesReferences
Hearing ImpairmentDifficulty or inability to hear sounds
  • Frennert et al. (2013)
  • Lammer et al. (2014)
  • Bajones et al. (2019)
  • Nault et al. (2022)
Visual ImpairmentEyesight that cannot be corrected to a normal level, from mild vision impairment to total blindness
  • Frennert et al. (2013)
  • Lammer et al. (2014)
  • Bajones et al. (2019)
Mobility ImpairmentDifficulty in ambulation resulting from functional limitation in the lower extremities
  • Mertens et al. (2011)
  • McGlynn et al. (2013)
  • Lebec et al. (2013)
  • Frennert et al. (2013)
  • Sabanovic et al. (2013)
  • Efthimiou et al. (2016)
  • Lewis et al. (2016)
  • Bajones et al. (2019)
  • Mucchiani et al. (2020)
  • Ferrari et al. (2020)
  • Chugo et al. (2022)
Cognitive ImpairmentProblems with a person's ability to think, learn, remember, use judgement, and make decisions
  • Sheba et al. (2012)
  • Louie et al. (2012)
  • Yamazaki et al. (2012)
  • D. McColl et al. (2013)
  • Begum et al. (2013)
  • Lebec et al. (2013)
  • Chang et al. (2013)
  • Sabanovic et al. (2013)
  • Pino et al. (2013)
  • Wu et al. (2014)
  • Khosla et al. (2014)
  • Prange et al. (2015)
  • Pino et al. (2015)
  • Sabanovic et al. (2015)
  • D Casey et al. (2016)
  • D. Hebesberger et al. (2016)
  • Lane et al. (2016)
  • Gerling et al. (2016)
  • Efthimiou et al. (2016)
  • Lewis et al. (2016)
  • Khosla et al. (2016)
  • Fan et al. (2016)
  • Wang et al. (2016)
  • Hebesberger et al. (2017)
  • Chu et al. (2017)
  • Moro et al. (2018)
  • Gerłowska et al. (2018)
  • Adams et al. (2018)
  • Moro et al. (2018)
  • Ercolano et al. (2019)
  • Feng et al. (2019)
  • Wesselink et al. (2019)
  • Whelan et al. (2020)
  • Casey et al. (2020)
  • Persson et al. (2020)
  • Lio et al. (2020)
  • Obayashi et al. (2020)
  • Mucchiani et al. (2020)
  • Salichs et al. (2020)
  • Sumioka et al. (2020)
  • Airola et al. (2020)
  • Raghunath et al. (2020)
  • Fitter et al. (2020)
  • Rossi et al. (2020)
  • Palestra et al. (2020)
  • Fernández-Rodicio et al. (2020)
  • Coşar et al. (2020)
  • Oh et al. (2020)
  • Gasteiger et al. (2022)
  • Abdollahi et al. (2022)
  • Lin et al. (2022)
  • Nault et al. (2022)
  • Nelson et al. (2022)
  • Castellano et al. (2022)
60% of studies focused on generally healthy older adults, with growing attention to specific health challenges.

Robot Categories and Functions

A comprehensive overview of robot types developed and evaluated for older adults, categorizing them by their primary functions and providing examples.
Robot CategoryDefinitionFunctionsRobot Names
SocialRobots that interact with humans and each other in a socially acceptable fashion, conveying intention in a human-perceptible way and following social norms, behaviors, and values.Companionship, emotional support, pet therapy, conversational agents
  • AIBO
  • Betty
  • Bomy
  • Bono Bot
  • CLARC
  • Cota
  • DOBOT
  • eBear
  • EMYS
  • ERIC
  • FriWalk
  • Giraff
  • Golden Pup
  • GrowMu
  • HealthBot
  • Hiro
  • Hobbit
  • iCat
  • Jibo
  • JustoCat
  • Ka Ka
  • MARIO
  • Matilda
  • Max
  • MOBOT
  • Nadine
  • Nao
  • PALRO
  • Partner-type-Personal-Robot (PaPeRo)
  • Paro
  • Pepper
  • PLEO
  • Poppy
  • Personal Robot 2 (PR2)
  • Robovie2
  • Ryan
  • Sanne
  • SCITOS G3
  • SociBot Mini
  • TIAGO
  • Yeonheebot
  • Zoomer
  • Prototypes*
AssistiveRobots that give aid or support to a human user. These devices can provide physical assistance based on an individual's clinical needs.Provide physical support for daily activities.
  • ASTRO
  • Care-O-bot 3
  • Charlie
  • DARCI
  • DoRo
  • Ed
  • Florence
  • FURo-Desk
  • Hobbit
  • Hobbit P2
  • Home+
  • I-Support
  • Kompai
  • Nabaztag
  • Nao
  • Pioneer 3-DX
  • Personal Robot 2 (PR2)
  • RAMCIP
  • RAS
  • SAM
  • Savioke Relay Robot
  • SCITOS
  • SCITOS G5
  • Sophie
  • SYMPARTNER
  • Tangy
  • Zenbo
  • Prototypes*
TelepresenceRobots with video conferencing capabilities that can facilitate human interaction from a distance.Telemedicine, remote interactions with healthcare professionals, family members, and friends, telehealth monitoring tasks, virtual tours and social gatherings.
  • Double
  • Ed
  • Giraff
  • Giraff-X
  • Ohmni
  • TIAGO Iron

Advanced ROI Calculator for HRI Implementation

Estimate the potential return on investment for integrating Human-Robot Interaction solutions into your enterprise.

$0 Annual Cost Savings
0 Hours Reclaimed Annually

Enterprise AI Implementation Timeline

A strategic roadmap to guide your organization through the successful integration of AI and HRI technologies, leveraging insights from current research.

Phase 1: Needs Assessment & Strategic Alignment

Define specific challenges older adults face that robots can address. Align robot functionalities with ADL, IADL, and EADL classifications to ensure targeted support. Involve older adults and care providers in early-stage design.

Phase 2: Pilot Program & Iterative Development

Deploy prototypes in controlled environments (labs, facilities) for feasibility and usability testing. Prioritize robots addressing mobility/cognitive impairments and ADLs. Collect diverse user feedback for iterative design improvements.

Phase 3: Real-World Deployment & Evaluation

Transition successful pilots to home and naturalistic settings. Implement stringent safety protocols. Collaborate with healthcare professionals to ensure ethical and effective deployment. Standardize reporting of participant demographics and robot capabilities.

Phase 4: Scalability & Continuous Improvement

Develop scalable solutions based on robust evidence. Foster interdisciplinary collaboration for ongoing research and development. Refine robot designs to promote successful aging and address a broader range of needs, moving beyond stereotypes.

Schedule a Strategic AI Consultation

Ready to Get Started?

Book Your Free Consultation.

Let's Discuss Your AI Strategy!

Lets Discuss Your Needs


AI Consultation Booking

Big Competitive Advantage With Ai

Learn More

Our Demos

Research Center

Contact Us

1 888 985 3025

Solutions@OwnYourAi.com

Get Your Ai

Own You Ai  –  All Rights Reserved  – Terms Of Service – Privacy Policy