Abstract
The increased life expectancy poses certain challenges such as bringing the required facilities to the elderly or infirm to help them keep their autonomy as long as possible. At any age, we are all prone to diseases or accidents that can affect our autonomy for activities we perform daily, the so-called Activities of Daily Living (ADL). After the ability to perform some ADLs is lost or reduced to some extent, a rehabilitation process is required. Doing rehabilitation in a controlled environment, such as a virtual one, brings interesting benefits, such as precise monitoring, a safe environment or a rehabilitation setting customized to each user’s progress. In this work, we present UrbanRehab, a tool designed in collaboration with specialists aimed at building customized rehabilitation experiences especially for Instrumental Activities of Daily Living that runs in a virtual urban environment (VUE) that can be built by the specialist visually by adding new buildings, street junctions, traffic lights or even dynamic objects such as people or cars. Billboards can be placed in the virtual scenario to provide further assistance to the user whenever required. The user interacts with the VUE by moving around in a natural manner. To assess the tool, an acceptance evaluation was conducted inspired by an UAUT2 model. Thirty specialists took part in this evaluation. The specialists gave the tool a score greater than 5 out of 7 for Behavioral Intention, thus showing the interest of these specialists in using our tool in a clinical environment.
Similar content being viewed by others
Availability of data and material
The video used in the evaluation is available (https://www.youtube.com/watch?v=2U19u6J0Iac).
References
Akalin N, Kiselev A, Kristoffersson A, Loutfi A (2017) An evaluation tool of the effect of robots in eldercare on the sense of safety and security. Lect Notes Comput Sci (including Subser Lect Notes Artif Intell Lect Notes Bioinformatics) 10652 LNAI:628–637. https://doi.org/https://doi.org/10.1007/978-3-319-70022-9_62
Almojaibel A (2017) Understanding intention to use telerehabilitation: applicability of the technology acceptance model (TAM)
Alrawashdeh TA, Elbes MW, Almomani A et al (2019) User acceptance model of open source software: an integrated model of OSS characteristics and UTAUT. J Ambient Intell Hum Comput. https://doi.org/10.1007/s12652-019-01524-7
Baños RM, Botella C, Alcañiz M et al (2004) Immersion and emotion: their impact on the sense of presence. CyberPsychology Behav 7:734–741. https://doi.org/10.1089/cpb.2004.7.734
Barclay DW, Higgins C, Thompson R (1995) The partial least squares (PLS) approach to casual modeling: personal computer adoption and use as an illustration. Technol Stud 2:285–309
Bombín González I, Cifuentes Rodríguez A, Climent Martínez G et al (2014) Validez ecológica y entornos multitarea en la evaluación de las funciones ejecutivas. Rev Neurol 59:77. https://doi.org/10.3358/rn.5902.2013578
Bowman DA, Davis ET, Hodges LF, Badre AN (1999) Maintaining spatial orientation during travel in an immersive virtual environment. Presence 8:618–631
Cipresso P, Albani G, Serino S et al (2014) Virtual multiple errands test (VMET): a virtual reality-based tool to detect early executive functions deficit in Parkinsonâ€TMs disease. Front Behav Neurosci. https://doi.org/10.3389/fnbeh.2014.00405
de Arruda HF, Silva FN, da Costa L, F, Amancio DR, (2017) Knowledge acquisition: a complex networks approach. Inf Sci (Ny) 421:154–166. https://doi.org/10.1016/j.ins.2017.08.091
Dias P, Silva R, Amorim P et al (2019) Using virtual reality to increase motivation in poststroke rehabilitation. IEEE Comput Gr Appl 39:64–70. https://doi.org/10.1109/MCG.2018.2875630
Dimbwadyo-Terrer I, Trincado-Alonso F, De los Reyes-Guzmán A et al (2016) Activities of daily living assessment in spinal cord injury using the virtual reality system Toyra®: functional and kinematic correlations. Virtual Real 20:17–26. https://doi.org/10.1007/s10055-015-0276-2
Faria AL, Andrade A, Soares L, i Badia SB (2016) Benefits of virtual reality based cognitive rehabilitation through simulated activities of daily living: a randomized controlled trial with stroke patients. J Neuroeng Rehabil 13:96. https://doi.org/10.1186/s12984-016-0204-z
Feldstein I, Dietrich A, Milinkovic S, Bengler K (2016) A pedestrian simulator for urban crossing scenarios. IFAC-PapersOnLine 49:239–244. https://doi.org/10.1016/j.ifacol.2016.10.531
Fong TG, Gleason LJ, Wong B et al (2015) Cognitive and physical demands of activities of daily living in older adults: validation of expert panel ratings. PM&R 7:727–735. https://doi.org/10.1016/j.pmrj.2015.01.018
Frank JS, Patla AE (2003) Balance and mobility challenges in older adults. Implications for preserving community mobility. Am J Prev Med 25:157–163. https://doi.org/10.1016/S0749-3797(03)00179-X
García AS, Fernández-Sotos P, Fernández-Caballero A et al (2019) Acceptance and use of a multi-modal avatar-based tool for remediation of social cognition deficits. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-019-01418-8
Gervasi O, Magni R, Zampolini M (2010) Nu!RehaVR: virtual reality in neuro tele-rehabilitation of patients with traumatic brain injury and stroke. Virtual Real 14:131–141. https://doi.org/10.1007/s10055-009-0149-7
Gutierrez FJ, Muñoz D, Ochoa SF, Tapia JM (2019) Assembling mass-market technology for the sake of wellbeing: a case study on the adoption of ambient intelligent systems by older adults living at home. J Ambient Intell Hum Comput 10:2213–2233. https://doi.org/10.1007/s12652-017-0591-4
Hair JF, Risher JJ, Sarstedt M, Ringle CM (2019) When to use and how to report the results of PLS-SEM. Eur Bus Rev 31:2–24. https://doi.org/10.1108/EBR-11-2018-0203
Henseler J, Hubona G, Ray PA (2016) Using PLS path modeling in new technology research: updated guidelines. Ind Manag Data Syst 116:2–20. https://doi.org/10.1108/IMDS-09-2015-0382
Hernández-Sampieri R, Mendoza C (2018) Metodología de la investigación las rutas cuantitativa,cualitativa y mixta
Hsieh M-Y (2018) SoLoMo technology: exploring the most critical determinants of SoLoMo technology in the contemporary mobile communication technology era. J Ambient Intell Hum Comput 9:307–318. https://doi.org/10.1007/s12652-016-0375-2
HTC (2020) Vive cosmos elite overview. https://www.vive.com/us/product/vive-cosmos-elite/overview/. Accessed 22 Jul 2020
Khalilzadeh J, Ozturk AB, Bilgihan A (2017) Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry. Comput Hum Behav 70:460–474. https://doi.org/10.1016/j.chb.2017.01.001
Laumer S, Gubler F, Maier C, Weitzel T (2018) Job seekers’ acceptance of job recommender systems: results of an empirical study. In: Proc 51st Hawaii int conf syst sci. https://doi.org/https://doi.org/10.24251/hicss.2018.491
Lee JH, Ku J, Cho W et al (2003) A virtual reality system for the assessment and rehabilitation of the activities of daily living. CyberPsychol Behav 6:383–388. https://doi.org/10.1089/109493103322278763
Liu L, Miguel Cruz A, Rios Rincon A et al (2015) What factors determine therapists’ acceptance of new technologies for rehabilitation—a study using the Unified Theory of Acceptance and Use of Technology (UTAUT). Disabil Rehabil 37:447–455. https://doi.org/10.3109/09638288.2014.923529
Lobjois R, Cavallo V (2009) The effects of aging on street-crossing behavior: from estimation to actual crossing. Accid Anal Prev 41:259–267. https://doi.org/10.1016/j.aap.2008.12.001
LoUISE Research Group (2020) UrbanRehab—virtual spaces design. https://www.youtube.com/watch?v=2U19u6J0Iac. Accessed 29 Jul 2020
MakeHuman (2019) MakeHuman: Open Source tool for making 3D characters
Manis KT, Choi D (2019) The virtual reality hardware acceptance model (VR-HAM): extending and individuating the technology acceptance model (TAM) for virtual reality hardware. J Bus Res 100:503–513. https://doi.org/10.1016/j.jbusres.2018.10.021
Mrakic-Sposta S, Di Santo SG, Franchini F et al (2018) Effects of combined physical and cognitive virtual reality-based training on cognitive impairment and oxidative stress in MCI patients: a pilot study. Front Aging Neurosci. https://doi.org/10.3389/fnagi.2018.00282
Navarro M-D, Lloréns R, Noé E et al (2013) Validation of a low-cost virtual reality system for training street-crossing. A comparative study in healthy, neglected and non-neglected stroke individuals. Neuropsychol Rehabil 23:597–618. https://doi.org/10.1080/09602011.2013.806269
Navarro E, González P, López-Jaquero V et al (2018) Adaptive, multisensorial, physiological and social: the next generation of telerehabilitation systems. Front Neuroinform. https://doi.org/10.3389/fninf.2018.00043
Özsungur F (2019) A research on the effects of successful aging on the acceptance and use of technology of the elderly. Assist Technol. https://doi.org/10.1080/10400435.2019.1691085
Parsons TD (2015) Virtual reality for enhanced ecological validity and experimental control in the clinical, affective and social neurosciences. Front Hum Neurosci. https://doi.org/10.3389/fnhum.2015.00660
Pedroli E, Cipresso P, Serino S et al (2013) Virtual Multiple Errands Test: reliability, usability and possible applications. Stud Health Technol Inform 191:38–42
Plechatá A, Sahula V, Fayette D, Fajnerová I (2019) Age-related differences with immersive and non-immersive virtual reality in memory assessment. Front Psychol. https://doi.org/10.3389/fpsyg.2019.01330
Poncet F, Swaine B, Dutil E et al (2017) How do assessments of activities of daily living address executive functions: a scoping review. Neuropsychol Rehabil 27:618–666. https://doi.org/10.1080/09602011.2016.1268171
Reed KL, Sanderson SN (1980) Concepts of occupational therapy. Lippincott Williams and Wilkins
Rizzo AA, Buckwalter JG, Neumann U (1997) Virtual reality and cognitive rehabilitation: a brief review of the future. J. Head Trauma Rehabil 12:1
Roberts AC, Yeap YW, Seah HS et al (2019) Assessing the suitability of virtual reality for psychological testing. Psychol Assess 31:318–328. https://doi.org/10.1037/pas0000663
Romero-Ayuso D, Castillero-Perea Á, González P et al (2019a) Assessment of cognitive instrumental activities of daily living: a systematic review. Disabil Rehabil. https://doi.org/10.1080/09638288.2019.1665720
Romero-Ayuso D, Castillero-Perea Á, González P et al (2019b) Assessment of cognitive instrumental activities of daily living: a systematic review. Disabil Rehabil. https://doi.org/10.1080/09638288.2019.1665720
Rong F, Zhang Y, Wang Z, Li Y (2019) Influencing factors of consumer willingness to pay for cold chain logistics: an empirical analysis in China. J Ambient Intell Humaniz Comput 10:3279–3285. https://doi.org/10.1007/s12652-018-1056-0
Sanchez-Vives MV, Slater M (2005) From presence to consciousness through virtual reality. Nat Rev Neurosci 6:332–339. https://doi.org/10.1038/nrn1651
Schmuckler MA (2001) What is ecological validity? A dimensional analysis. Infancy 2:419–436. https://doi.org/10.1207/S15327078IN0204_02
Simpson G, Johnston L, Richardson M (2003) An investigation of road crossing in a virtual environment. Accid Anal Prev 35:787–796. https://doi.org/10.1016/S0001-4575(02)00081-7
Slater M, Sanchez-Vives MV (2016) Enhancing our lives with immersive virtual reality. Front Robot AI 3:74
Slater M, Linakis V, Usoh M, Kooper R (1996) Immersion, presence and performance in virtual environments. In: Proceedings of the ACM symposium on virtual reality software and technology—VRST ’96. ACM Press, New York, New York, USA, pp 163–172
Tarnanas I, Schlee W, Tsolaki M et al (2013) Ecological validity of virtual reality daily living activities screening for early dementia: longitudinal study. JMIR Serious Games 1:e1. https://doi.org/10.2196/games.2778
Templeman JN, Denbrook PS, Sibert LE (1999) Virtual locomotion: walking in place through virtual environments. Pres Teleoper Virtual Environ 8:598–617. https://doi.org/10.1162/105474699566512
Unity Technologies (2020) Unity. https://unity3d.com/
van der Ham IJM, Faber AME, Venselaar M et al (2015) Ecological validity of virtual environments to assess human navigation ability. Front Psychol. https://doi.org/10.3389/fpsyg.2015.00637
Venkatesh T, Xu Y (2012) Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q 36:157. https://doi.org/10.2307/41410412
Venkatesh V, Morris MG, Davis GB, Davis F (2003) User acceptance of information technology: toward a unified view. MIS Q 27:425–478. https://doi.org/10.2307/30036540
Vourvopoulos A, Faria AL, Ponnam K, Bermudez i Badia S (2014) RehabCity. In: Proceedings of the 11th conference on advances in computer entertainment technology—ACE ’14. ACM Press, New York, New York, USA, pp 1–8
Vugts MAP, Joosen MCW, van Bergen AHMM, Vrijhoef HJM (2016) Feasibility of applied gaming during interdisciplinary rehabilitation for patients with complex chronic pain and fatigue complaints: a mixed-methods study. JMIR Serious Games 4:e2. https://doi.org/10.2196/games.5088
Wagner S, Joeres F, Gabele M et al (2019) Difficulty factors for VR cognitive rehabilitation training—crossing a virtual road. Comput Gr 83:11–22. https://doi.org/10.1016/j.cag.2019.06.009
Weiss PL, Naveh Y, Katz N (2003) Design and testing of a virtual environment to train stroke patients with unilateral spatial neglect to cross a street safely. Occup Ther Int 10:39–55. https://doi.org/10.1002/oti.176
Youngblut C, Huie O (2003) The relationship between presence and performance in virtual environments: results of a VERTS study. In: IEEE virtual reality, 2003. Proceedings. IEEE Comput. Soc, pp 277–278
Funding
This work was supported by the Spanish Ministry of Science and Innovation and by the EU FEDER funds under Project Grant PID2019-108915RB-I00 and by the Castilla-La Mancha Regional Government/FEDER, UE under the SBPLY/17/180501/000192 Grant.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
Not applicable.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Juan-González, J., García, A.S., Molina, J.P. et al. UrbanRehab: a virtual urban scenario design tool for rehabilitating instrumental activities of daily living. J Ambient Intell Human Comput 14, 1339–1358 (2023). https://doi.org/10.1007/s12652-021-03061-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-021-03061-8