This study empirically investigates the embodiment of occupational exoskeletons (OEs) through repeated use.
Background
OEs are wearable devices designed to assist operators’ movements. Their embodiment— the phenomenon by which they come to be perceived as an integral part of oneself — remains underexplored, thus limiting our understanding of OE adoption. We operationalize embodiment through readiness-to-hand (using the device with minimal conscious attention) and sense of ownership (perceiving the device as part of oneself).
Method
Study 1 is a laboratory study using a within-subject design to examine the evolution of embodiment through two single-item scales over repeated training sessions with an upper-limb exoskeleton in a sample of 14 participants. Study 2 is a field study using a cross-sectional design to investigate differences in OE embodiment across 27 operators with varying experience of OE use. Embodiment was assessed using the same measures as in Study 1.
Results
Study 1 showed that repeated use shifted attention from the device to the task. Additionally, repeated use led to a progressive integration of the exoskeleton within oneself. Study 2 provided similar results, showing that experienced users focused more on the task when using their OEs and exhibited a greater integration of OEs into the self than novice users.
Conclusion
Repeated OE use is linked to the cognitive disappearance of the exoskeleton and merging of self and device.
Application
Understanding embodiment can guide the development of OEs. Integrating embodiment assessments can optimize implementation strategies and strengthen our understanding of users’ adoption and rejection.
AkanmuA.OkunolaA.JebelliH.AmmarA.AfolabiA. (2024). Cognitive load assessment of active back-support exoskeletons in construction: A case study on construction framing. Advanced Engineering Informatics, 62(Part D), 102905. https://doi.org/10.1016/j.aei.2024.102905
2.
AlemiM. M.MadineiS.KimS.SrinivasanD.NussbaumM. A. (2020). Effects of two passive back-support exoskeletons on muscle activity, energy expenditure, and subjective assessments during repetitive lifting. Human Factors, 62(3), 458–474. https://doi.org/10.1177/0018720819897669
3.
AlonsoV.De La PuenteP. (2018). System transparency in shared autonomy: A mini review. Frontiers in Neurorobotics, 12, 83. https://doi.org/10.3389/fnbot.2018.00083
4.
AlzayatA.HancockM.NacentaM. A. (2017). Measuring readiness-to-hand through differences in attention to the task vs. attention to the tool. In Proceedings of the 2017 ACM International Conference on Interactive Surfaces and Spaces (pp. 42–51). Association for Computing Machinery. https://doi.org/10.1145/3132272.3134114
5.
AlzayatA.HancockM.NacentaM. A. (2019). Quantitative measurement of tool embodiment for virtual reality input alternatives. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems(pp. 1–11). Association for Computing Machinery. https://doi.org/10.1145/3290605.3300673
6.
AngerbauerK.Van WagonerP.HalachT.VogelsangJ.HubeN.SmithA.KeplingerK.SedlmairM. (2024). Is it part of me? Exploring experiences of inclusive avatar use for visible and invisible disabilities in social VR. In Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’24) (Article 54). Association for Computing Machinery.https://doi.org/10.1145/3663548.3675601
7.
AronA.AronE. N.SmollanD. (1992). Inclusion of other in the self scale and the structure of interpersonal closeness. Journal of Personality and Social Psychology, 63(4), 596–612. https://doi.org/10.1037/0022-3514.63.4.596
8.
AronA.AronE. N.TudorM.NelsonG. (1991). Close relationships as including other in the self. Journal of Personality and Social Psychology, 60(2), 241–253. https://doi.org/10.1037//0022-3514.60.2.241
9.
Atain KouadioJ.-J.KeranguevenL.Turpin-LegendreE. (2023). Acquisition and integration of exoskeletons in establishments: Guide for safety professionals. Institut National de Recherche et de Sécurité (INRS).
10.
BärM.LugerT.SeibtR.GabrielJ.RiegerM. A.SteinhilberB. (2022). Effects of a passive back-support exoskeleton on knee joint loading during simulated static sorting and dynamic lifting tasks. International Journal of Environmental Research and Public Health, 19(16), 9965. https://doi.org/10.3390/ijerph19169965
11.
BelkR. W. (1988). Possessions and the extended self. Journal of Consumer Research, 15(2), 139–168. https://doi.org/10.1086/209154
12.
BennettD.RoudautA.MetatlaO. (2022, April). Multifractal mice: Operationalising dimensions of readiness-to-hand via a feature of hand movement. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (pp. 1–18). Association for Computing Machinery. https://doi.org/10.1145/3491102.3517601
BradleyM. M.LangP. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. Journal of Behavior Therapy and Experimental Psychiatry, 25(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9
15.
BrehmerB.DörnerD. (1993). Experiments with computer-simulated microworlds: Escaping both the narrow straits of the laboratory and the deep blue sea of the field study. Computers in Human Behavior, 9(2-3), 171–184. https://doi.org/10.1016/0747-5632(93)90005-d
CardinaliL.BrozzoliC.FinosL.RoyA. C.FarnèA. (2016). The rules of tool embodiment: Tool morpho-functional & sensori-motor constraints. Cognition, 149, 1–5. https://doi.org/10.1016/j.cognition.2016.01.001
18.
CardinaliL.FrassinettiF.BrozzoliC.UrquizarC.RoyA. C.FarnèA. (2009). Tool-use induces morphological updating of the body schema. Current Biology: CB, 19(12), R478–R479. https://doi.org/10.1016/j.cub.2009.05.009
19.
CarijóF. H.de AlmeidaM. C.KastrupV. (2013). On haptic and motor embodiment of tools and other objects. Phenomenology and the Cognitive Sciences, 12, 685–701. https://doi.org/10.1007/s11097-012-9269-8
20.
ChenL.ZhouD.LengY. (2024). A systematic review on rigid exoskeleton robot design for wearing comfort: Joint self-alignment, attachment interface, and structure customization. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 32, 3815–3827. https://doi.org/10.1109/TNSRE.2024.3479283
21.
CohenJ. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
22.
Del BussoL.BrottveitG.Torp LøkkebergS.GluppeG. (2022). Women’s embodied experiences of using wearable digital self-tracking health technology: A review of the qualitative research literature. Health Care for Women International, 43(12), 1355–1379. https://doi.org/10.1080/07399332.2021.1884682
23.
de LoozeM. P.Kuijt-EversL. F.Van DieenJ. A. A. P. (2003). Sitting comfort and discomfort and the relationships with objective measures. Ergonomics, 46(10), 985–997. https://doi.org/10.1080/0014013031000121977
24.
de VriesA. W.BaltruschS. J.De LoozeM. P. (2023). Field study on the use and acceptance of an arm support exoskeleton in plastering. Ergonomics, 66(10), 1622–1632. https://doi.org/10.1080/00140139.2022.2159067
25.
Diamond-OuelletteG.TelonioA.KarakolisT.LeblondJ.BouyerL. J.BestK. L. (2022). Exploring the change in metabolic cost of walking before and after familiarization with a passive load-bearing exoskeleton: A case series. IISE Transactions on Occupational Ergonomics and Human Factors, 10(3), 161–172. https://doi.org/10.1080/24725838.2022.2124325
26.
DotovD.NieL.WojcikK.JinksA.YuX.ChemeroA. (2017). Cognitive and movement measures reflect the transition to presence-at-hand. New Ideas in Psychology, 45, 1–10. https://doi.org/10.1016/j.newideapsych.2017.01.001
27.
DourishP. (2004). Where the action is: The foundations of embodied interaction. The MIT Press.
28.
DufraisseM.CegarraJ.Atain KouadioJ. J.Clerc-UrmèsI.WiolandL. (2025a). From unknown to familiar: An exploratory longitudinal field study on occupational exoskeletons adoption. Applied Ergonomics, 122, 104393. https://doi.org/10.1016/j.apergo.2024.104393
29.
DufraisseM.WiolandL.Atain KouadioJ. J.Clerc-UrmèsI.CegarraJ. (2025). Becoming a User: Understanding the Journeys Towards the Adoption of Occupational Exoskeletons. International Journal of Human–Computer Interaction, 1–21. https://doi.org/10.1080/10447318.2025.2543996
30.
El HusainiM.MaberryA.MartinA. E. (2023). Validation of a modified visual analogue scale to measure user-perceived comfort of a lower-limb exoskeleton. Scientific Reports, 13(1), 20484. https://doi.org/10.1038/s41598-023-47430-z
31.
ElpramaS. A.VanderborghtB.JacobsA. (2022). An industrial exoskeleton user acceptance framework based on a literature review of empirical studies. Applied Ergonomics, 100, 103615. https://doi.org/10.1016/j.apergo.2021.103615
32.
ElstubL. J.FineS. J.ZelikK. E. (2021). Exoskeletons and exosuits could benefit from mode-switching body interfaces that loosen/tighten to improve thermal comfort. International Journal of Environmental Research and Public Health, 18(24), 13115. https://doi.org/10.3390/ijerph182413115
33.
EspinosaM.Nathan-RobertsD. (2019). Understanding prosthetic abandonment. Proceedings of the Human Factors and Ergonomics Society - Annual Meeting, 63(1), 1644–1648. https://doi.org/10.1177/1071181319631508
FavennecA.FrèreJ.MornieuxG. (2024). Changes in human motor behavior during the familiarization with a soft back-support occupational exoskeleton. Applied Sciences, 14(3), 1160. https://doi.org/10.3390/app14031160
36.
FeiseR. J. (2002). Do multiple outcome measures require p-value adjustment?BMC Medical Research Methodology, 2, 1–4. https://doi.org/10.1186/1471-2288-2-8
37.
GilottaS.SpadaS.GhibaudoL.IsoardiM.MossoC. O. (2019). Acceptability beyond usability: A manufacturing case study. In Proceedings of the 20th congress of the international ergonomics association (IEA 2018) volume VII: Ergonomics in design, design for all, activity theories for work analysis and design, affective design 20 (pp. 922–934). Springer International Publishing.
38.
GoldingerS. D.PapeshM. H.BarnhartA. S.HansenW. A.HoutM. C. (2016). The poverty of embodied cognition. Psychonomic Bulletin & Review, 23(4), 959–978. https://doi.org/10.3758/s13423-015-0860-1
HoxJ. J. (2002). Multilevel analysis: Techniques and applications. Lawrence Erlbaum Associate.
42.
HoxJ. J. (2010). Multilevel analysis: Techniques and applications (2nd ed.). Routledge.
43.
HybartR. L.FerrisD. P. (2022). Embodiment for robotic lower-limb exoskeletons: A narrative review. IEEE Transactions on Neural Systems and Rehabilitation Engineering: A Publication of the IEEE Engineering in Medicine and Biology Society, 31, 657–668. https://doi.org/10.1109/TNSRE.2022.3229563
44.
JarrasséN.PaikJ.PasquiV.MorelG. (2008). How can human motion prediction increase transparency? In 2008 IEEE international conference on robotics and automation (pp. 2134–2139). IEEE.
45.
KatilaJ.TurjaT. (2021). Capturing the nurse’s kinesthetic experience of wearing an exoskeleton: The benefits of using intercorporeal perspective to video analysis. Social Interaction. Video-Based Studies of Human Sociality, 4(3). https://doi.org/10.7146/si.v4i3.128149
46.
KranenborgS. E.GreveC.RenemanM. F.RoossienC. C. (2023). Side-effects and adverse events of a shoulder-and back-support exoskeleton in workers: A systematic review. Applied Ergonomics, 111, 104042. https://doi.org/10.1016/j.apergo.2023.104042
47.
LiZ.LiuH.YinZ.ChenK. (2019). Muscle synergy alteration of human during walking with lower limb exoskeleton. Frontiers in Neuroscience, 12, 1050. https://doi.org/10.3389/fnins.2018.01050
48.
LimayemM.HirtS. G.CheungC. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705–737. https://doi.org/10.2307/25148817
49.
LinY.LiuQ.QiD.ZhangJ.DingZ. (2023). Smartphone embodiment: The effect of smartphone use on body representation. Current Psychology, 42(30), 26356–26374. https://doi.org/10.1007/s12144-022-03740-5
50.
LokeL.SchiphorstT. (2018). The somatic turn in human-computer interaction. Interactions, 25(5), 54–5863. https://doi.org/10.1145/3236675
51.
LugerT.BaerM.SeibtR.RimmeleP.RiegerM. A.SteinhilberB. (2021). A passive back exoskeleton supporting symmetric and asymmetric lifting in stoop and squat posture reduces trunk and hip extensor muscle activity and adjusts body posture–A laboratory study. Applied Ergonomics, 97, 103530. https://doi.org/10.1016/j.apergo.2021.103530
MauriceP.ČamernikJ.GorjanD.SchirrmeisterB.BornmannJ.TagliapietraL.BabičJ.PucciD.FritzscheL.IvaldiS.BabičJ. (2019). Evaluation of PAEXO, a novel passive exoskeleton for overhead work. Computer Methods in Biomechanics and Biomedical Engineering, 22(sup1), S448–S450. https://doi.org/10.1080/10255842.2020.1714977
54.
MedranoR. L.ThomasG. C.RouseE. J. (2022). Can humans perceive the metabolic benefit provided by augmentative exoskeletons?Journal of NeuroEngineering and Rehabilitation, 19(1), 26. https://doi.org/10.1186/s12984-022-01002-w
55.
MurrayC. D. (2004). An interpretative phenomenological analysis of the embodiment of artificial limbs. Disability & Rehabilitation, 26(16), 963–973. https://doi.org/10.1080/09638280410001696764
56.
NelsonE. C.SoolsA. M.Vollenbroek-HuttenM. M.VerhagenT.NoordzijM. L. (2020). Embodiment of wearable technology: Qualitative longitudinal study. JMIR mHealth and uHealth, 8(11), e16973. https://doi.org/10.2196/16973
57.
NelsonE. C.VerhagenT.Vollenbroek-HuttenM.NoordzijM. L. (2019). Is wearable technology becoming part of us? Developing and validating a measurement scale for wearable technology embodiment. JMIR mHealth and uHealth, 7(8), Article e12771. https://doi.org/10.2196/12771
58.
NelsonE. C.VerhagenT.Vollenbroek-HuttenM. M.NoordzijM. L. (2024). When it is part of me, I can do it: Using embodied empowerment to predict adherence to wearable self-care technology. Computers in Human Behavior, 158, 108314. https://doi.org/10.1016/j.chb.2024.108314
Papp-SchmittE.WölfelC.KrzywinskiJ. (2024). Embodied experience of exoskeletons. Design Research Society.
61.
PazzagliaM.MolinariM. (2016). The embodiment of assistive devices—from wheelchair to exoskeleton. Physics of Life Reviews, 16, 163–175. https://doi.org/10.1016/j.plrev.2015.11.006
62.
PratvielY.Deschodt-ArsacV.LarrueF.ArsacL. M. (2022). Tool embodiment is reflected in movement multifractal nonlinearity. Fractal and Fractional, 6(5), 240. https://doi.org/10.3390/fractalfract6050240
63.
ProiettiT.CrocherV.Roby-BramiA.JarrasseN. (2016). Upper-limb robotic exoskeletons for neurorehabilitation: A review on control strategies. IEEE Reviews in Biomedical Engineering, 9, 4–14. https://doi.org/10.1109/RBME.2016.2552201
RobinsR. W.HendinH. M.TrzesniewskiK. H. (2001). Measuring global self-esteem: Construct validation of a single-item measure and the Rosenberg Self-Esteem Scale. Personality and Social Psychology Bulletin, 27(2), 151–161. https://doi.org/10.1177/0146167201272002
66.
RussoB.BoessS.HekkertP. (2011). ‘What’s love got to do with It?’ The experience of love in person-product relationships. The Design Journal, 14(1), 8–27. https://doi.org/10.2752/175630610x12877385838687
67.
SchettlerA.RajaV.AndersonM. L. (2019). The embodiment of objects: Review, analysis, and future directions. Frontiers in Neuroscience, 13, 1332. https://doi.org/10.3389/fnins.2019.01332
68.
SchwartzM.DesbrossesK.TheurelJ.MornieuxG. (2023). Biomechanical consequences of using passive and active back-support exoskeletons during different manual handling tasks. International Journal of Environmental Research and Public Health, 20(15), 6468. https://doi.org/10.3390/ijerph20156468
69.
SegilJ. L.RoldanL. M.GraczykE. L. (2022). Measuring embodiment: A review of methods for prosthetic devices. Frontiers in Neurorobotics, 16, 902162. https://doi.org/10.3389/fnbot.2022.902162
70.
SiedlS. M.MaraM. (2023). What drives acceptance of occupational exoskeletons? Focus group insights from workers in food retail and corporate logistics. International Journal of Human-Computer Interaction, 39(20), 4080–4089. https://doi.org/10.1080/10447318.2022.2108969
71.
SiedlS. M.MaraM. (2024). Am I still human? Wearing an exoskeleton impacts self-perceptions of warmth, competence, attractiveness, and machine-likeness. Computers in Human Behavior: Artificial Humans, 2(2), 100073. https://doi.org/10.1016/j.chbah.2024.100073
72.
SiedlS. M.MaraM.StiglbauerB. (2024). The role of social feedback in technology acceptance: A one-week diary study with exoskeleton users at the workplace. International Journal of Human-Computer Interaction, 41(13), 1–14. https://doi.org/10.1080/10447318.2024.2406119
73.
SiedlS. M.WolfM.MaraM. (2021). Exoskeletons in the supermarket: Influences of comfort, strain relief and task-technology fit on retail workers’ post-trial intention to use [Paper presentation]. Companion of the 2021 ACM/IEEE International Conference on Human-Robot. Interaction, 397–401, 3434074.3447200. https://doi.org/10.1145/3434074.3447200
74.
SmelikA.ToussaintL.Van DongenP. (2016). Solar fashion: An embodied approach to wearable technology. International Journal of Fashion Studies, 3(2), 287–303. https://doi.org/10.1386/infs.3.2.287_1
75.
SobuhM. M.KenneyL. P.GalpinA. J.ThiesS. B.McLaughlinJ.KulkarniJ.KyberdP. (2014). Visuomotor behaviours when using a myoelectric prosthesis. Journal of NeuroEngineering and Rehabilitation, 11, 72. https://doi.org/10.1186/1743-0003-11-72
76.
SongS.HaynesC. A.BradfordJ. C. (2024). Novice users’ brain activity and biomechanics change after practicing walking with an ankle exoskeleton. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 32, 2522–2532. https://doi.org/10.1109/TNSRE.2024.3423696
77.
SouzaA. O.GrenierJ.CharpilletF.IvaldiS.MauriceP. (2024, November). Enhancing exoskeleton transparency with motion prediction: An experimental study. In 2024 IEEE-RAS 23rd international conference on humanoid robots (humanoids) (pp. 744–751). IEEE.
78.
SpositoM.PolieroT.Di NataliC. D.ToxiriS.AnastasiS.DraicchioF.MonicaL.CaldwellD.De MomiE. D.OrtizJ. (2021). Physical comfort of occupational exoskeletons: Influence of static fit on subjective scores. ACM International Conference Proceeding Series, 60–68. https://doi.org/10.1145/3453892.3453995
79.
StirlingL.Kelty-StephenD.FinemanR.JonesM. L.Daniel ParkB. K.ReedM. P.ChoiH. J. (2020). Static, dynamic, and cognitive fit of exosystems for the human operator. Human Factors, 62(3), 424–440. https://doi.org/10.1177/0018720819896898
80.
SungJ.GrinterR. E.ChristensenH. I. (2010). Domestic robot ecology: An initial framework to unpack long-term acceptance of robots at home. International Journal of Social Robotics, 2(4), 417–429. https://doi.org/10.1007/s12369-010-0065-8
81.
TheurelJ.DesbrossesK. (2019). Occupational exoskeletons: Overview of their benefits and limitations in preventing work-related musculoskeletal disorders. IISE Transactions on Occupational Ergonomics and Human Factors, 7(3-4), 264–280. https://doi.org/10.1080/24725838.2019.1638331
82.
VarelaF. J.ThompsonE.RoschE. (1991). The embodied mind: Cognitive science and human experience. MIT Press.
83.
Ventre-DomineyJ.GibertG.Bosse-PlatiereM.FarnèA.DomineyP. F.PavaniF. (2019). Embodiment into a robot increases its acceptability. Scientific Reports, 9(1), 10083. https://doi.org/10.1038/s41598-019-46528-7
84.
VerplankenB.OrbellS. (2003). Reflections on past behavior: A self-report index of habit strength 1. Journal of Applied Social Psychology, 33(6), 1313–1330. https://doi.org/10.1111/j.1559-1816.2003.tb01951.x
85.
WanousJ. P.ReichersA. E.HudyM. J. (1997). Overall job satisfaction: How good are single-item measures?Journal of Applied Psychology, 82(2), 247–252. https://doi.org/10.1037/0021-9010.82.2.247
86.
WeserV.ProffittD. R. (2019). Tool embodiment: The tool’s output must match the user’s input. Frontiers in Human Neuroscience, 12, 537. https://doi.org/10.3389/fnhum.2018.00537
87.
WeserV. U.ProffittD. R. (2021). Expertise in tool use promotes tool embodiment. Topics in Cognitive Science, 13(4), 597–609. https://doi.org/10.1111/tops.12538
88.
WilliamsA. M.HodgesN. J. (2023). Effective practice and instruction: A skill acquisition framework for excellence. Journal of Sports Sciences, 41(9), 833–849. https://doi.org/10.1080/02640414.2023.2240630
89.
WinogradT.FloresF. (1986). Understanding computers and cognition: A new foundation for design (335). Ablex publishing corporation.
90.
WiolandL.Atain KouadioJ. J.BréardH.Clerc-UrmèsI.PatyB. (2024). The adoption of occupational exoskeletons: From acceptability to situated acceptance, questionnaire surveys. International Journal of Human-Computer Interaction, 41(2), 1446–1458. https://doi.org/10.1080/10447318.2024.2314359
91.
ZhuY.WestonE. B.MehtaR. K.MarrasW. S. (2021). Neural and biomechanical tradeoffs associated with human-exoskeleton interactions. Applied Ergonomics, 96, 103494. https://doi.org/10.1016/j.apergo.2021.103494
