User Centred Design of a Smartphone-based Cognitive Fatigue Assessment Application

Edward Price, George Moore, Leo Galway, Mark Linden

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper presents the user experience design approach taken for a mobile cognitive assessment tool. Taking a multidisciplinary approach with user centred assessment and feedback, the design of this tool was tailored to provide a usable and intuitive user experience. Key to user participation is ease of use and minimal time on task for participant engagement. To address this selected measures were carefully considered as to make the testing process simple and easy to engage with. Following a pre-validated, iterative design approach, an acceptable and engaging user experience was designed while retaining the ability to measure multiple aspects of a user’s condition and environment. Accurate assessment of cognitive fatigue requires a wide range of environmental user data in order to understand the participants’ current cognitive fatigue levels, therefore measures of physical, cognitive, social and emotional aspects were included within the application.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages8
DOIs
Publication statusPublished - 29 Nov 2016
EventThe 14th International Conference on Advances in Mobile Computing & Multimedia - Singapore
Duration: 29 Nov 2016 → …

Conference

ConferenceThe 14th International Conference on Advances in Mobile Computing & Multimedia
Period29/11/16 → …

Fingerprint

Smartphones
Fatigue of materials
Feedback
Testing
User centered design

Keywords

  • Fatigue
  • cognitive fatigue
  • smartphone
  • mobile
  • reaction
  • spatial span
  • mental arithmetic
  • cognitive tests
  • facial features
  • application design.

Cite this

@inproceedings{a30005b3dabb4d4ba386232381633adf,
title = "User Centred Design of a Smartphone-based Cognitive Fatigue Assessment Application",
abstract = "This paper presents the user experience design approach taken for a mobile cognitive assessment tool. Taking a multidisciplinary approach with user centred assessment and feedback, the design of this tool was tailored to provide a usable and intuitive user experience. Key to user participation is ease of use and minimal time on task for participant engagement. To address this selected measures were carefully considered as to make the testing process simple and easy to engage with. Following a pre-validated, iterative design approach, an acceptable and engaging user experience was designed while retaining the ability to measure multiple aspects of a user’s condition and environment. Accurate assessment of cognitive fatigue requires a wide range of environmental user data in order to understand the participants’ current cognitive fatigue levels, therefore measures of physical, cognitive, social and emotional aspects were included within the application.",
keywords = "Fatigue, cognitive fatigue, smartphone, mobile, reaction, spatial span, mental arithmetic, cognitive tests, facial features, application design.",
author = "Edward Price and George Moore and Leo Galway and Mark Linden",
note = "Reference text: [1] F. Tagliaferri, C. Compagnone, M. Korsic, F. Servadei, and J. Kraus, “A systematic review of brain injury epidemiology in Europe,” Acta Neurochir. (Wien)., vol. 148, no. 3, pp. 255–267, 2006. [2] C. V. Faul M, Xu L, Wald MM, “Traumatic brain injury in the United States: emergency department visits, hospitalizations, and deaths,” Centers Dis. Control Prev. Natl. Cent. Inj. Prev. Control, pp. 891–904, 2010. [3] S. L. Hillier, J. E. Hiller, and J. Metzer, “Epidemiology of traumatic brain injury in South Australia.,” Brain Inj., vol. 11, no. 9, pp. 649–59, Sep. 1997. [4] R. Escorpizo, S. Brage, D. Homa, and G. Stucki, Eds., “Handbook of Vocational Rehabilitation and Disability Evaluation.” Springer International Publishing, Cham, 2015. [5] B. Johansson and L. R{\"o}nnb{\"a}ck, “Mental Fatigue and Cognitive Impairment after an Almost Neurological Recovered Stroke,” ISRN Psychiatry, vol. 2012, pp. 1–7, 2012. [6] L. S. Aaronson, C. S. Teel, V. Cassmeyer, G. B. Neuberger, L. Pallikkathayil, and A. W. Janet Pierce, Allan N. Press, Phoebe D. Williams, “Defining and Measuring Fatigue,” J. Nurs. Scholarsh., vol. 31, no. 1, pp. 45–50, 1999. [7] C. Ziino and J. Ponsford, “Measurement and prediction of subjective fatigue following traumatic brain injury,” J. Int. …, pp. 416–425, 2005. [8] B. Johansson, P. Berglund, and L. R{\"o}nnb{\"a}ck, “Mental fatigue and impaired information processing after mild and moderate traumatic brain injury.,” Brain Inj., vol. 23, no. 13–14, pp. 1027–40, Dec. 2009. [9] M. Kay and K. Rector, “PVT-touch: adapting a reaction time test for touchscreen devices,” Pervasive …, pp. 248–251, 2013. [10] D. Wechsler, “Wechsler adult intelligence scale–Fourth Edition (WAIS–IV),” San Antonio, TX NCS Pearson, 2008. [11] R. M. Reitan and D. Wolfson, The Halstead-Reitan neuropsychological test battery: Theory and clinical interpretation, vol. 4. Reitan Neuropsychology, 1985. [12] H. Van Dongen, G. Maislin, J. M. Mullington, and D. F. Dinges, “The cumulative cost of additional wakefulness: dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total,” Sleep, vol. 26, no. 2, pp. 117–126, 2003. [13] D. Gartenberg and R. McGarry, “Development of a Neuroergonomic Application to Evaluate Arousal,” Adv. …, pp. 6378–6387, 2012. [14] S. A. Ferguson, B. P. Smith, M. Browne, and M. J. Rockloff, “Fatigue in Emergency Services Operations : Assessment of the Optimal Objective and Subjective Measures Using a Simulated Wildfire Deployment,” Int. J. Environ. Res. Public Health, vol. 13, no. 2, 2016. [15] K. Liu, B. Li, S. Qian, Q. Jiang, L. Li, and W. Wang, “Mental fatigue after mild traumatic brain injury : a 3D-ASL perfusion study,” Brain Imaging Behav., pp. 1–12, 2016. [16] D. A. Grant, K. A. Honn, M. E. Layton, S. M. Riedy, and H. P. A. Van Dongen, “3-Minute Smartphone-Based and Tablet-Based Psychomotor Vigilance Tests for the Assessment of Reduced Alertness Due To Sleep Deprivation,” Behav. Res. Methods, 2016. [17] B. Johansson and L. R{\"o}nnb{\"a}ck, “Mental Fatigue ; A Common Long Term Consequence After a Brain Injury,” 2009. [18] D. Swendeman, W. S. Comulada, N. Ramanathan, M. Lazar, and D. Estrin, “Reliability and Validity of Daily Self-Monitoring by Smartphone Application for Health-Related Quality-of-Life, Antiretroviral Adherence, Substance Use, and Sexual Behaviors Among People Living with HIV,” AIDS Behav., vol. 19, no. 2, pp. 330–340, 2014. [19] A.-L. L. Engstr{\"o}m, J. Lexell, and M. L. Lund, “Difficulties in using everyday technology after acquired brain injury: a qualitative analysis.,” Scand. J. Occup. Ther., vol. 17, no. 3, pp. 233–243, 2010. [20] E. K. Wise, J. M. Hoffman, J. M. Powell, C. H. Bombardier, and K. R. Bell, “Benefits of exercise maintenance after traumatic brain injury,” Arch. Phys. Med. Rehabil., vol. 93, no. 8, pp. 1319–1323, 2012. [21] M. Schwandt, J. E. Harris, S. Thomas, M. Keightley, A. Snaiderman, and A. Colantonio, “Feasibility and effect of aerobic exercise for lowering depressive symptoms among individuals with traumatic brain injury: a pilot study,” J. Head Trauma Rehabil., vol. 27, no. 2, pp. 99–103, 2012. [22] T. Archer, “Influence of physical exercise on traumatic brain injury deficits: Scaffolding effect,” Neurotox. Res., vol. 21, no. 4, pp. 418–434, 2012. [23] S. J. Blondell, R. Hammersley-Mather, and J. L. Veerman, “Does physical activity prevent cognitive decline and dementia?: A systematic review and meta-analysis of longitudinal studies.,” BMC Public Health, vol. 14, no. 1, p. 510, 2014. [24] D. Laurin, “Physical Activity and Risk of Cognitive Impairment and Dementia in Elderly Persons,” Arch. Neurol., vol. 58, no. 3, pp. 498–504, 2001. [25] M. M. Marques, V. De Gucht, M. J. Gouveia, I. Leal, and S. Maes, “Differential effects of behavioral interventions with a graded physical activity component in patients suffering from Chronic Fatigue (Syndrome): An updated systematic review and meta-analysis,” Clin. Psychol. Rev., vol. 40, pp. 123–137, 2015. [26] R. Moss-Morris, “A Randomized Controlled Graded Exercise Trial for Chronic Fatigue Syndrome: Outcomes and Mechanisms of Change,” J. Health Psychol., vol. 10, no. 2, pp. 245–259, 2005. [27] J. R. Price, E. Mitchell, E. Tidy, and V. Hunot, “Cognitive behaviour therapy for chronic fatigue syndrome in adults.,” Cochrane database Syst. Rev., no. 3, p. CD001027, Jan. 2008. [28] B. D. Castell, N. Kazantzis, and R. E. Moss-Morris, “Cognitive behavioral therapy and graded exercise for chronic fatigue syndrome: A meta-analysis,” Clin. Psychol. Sci. Pract., vol. 18, no. 4, pp. 311–324, 2011. [29] J. Batista, “A drowsiness and point of attention monitoring system for driver vigilance,” IEEE Conf. Intell. Transp. Syst. Proceedings, ITSC, pp. 702–708, 2007. [30] L. Gan, B. Cui, and W. Wang, “Driver Fatigue Detection Based on Eye Tracking,” 2006 6th World Congr. Intell. Control Autom., vol. 2, pp. 5341–5344, 2006. [31] Q. Ji and X. Yang, “Real-Time Eye, Gaze, and Face Pose Tracking for Monitoring Driver Vigilance,” Real-Time Imaging, vol. 8, no. 5, pp. 357–377, Oct. 2002. [32] N. Edenborough, R. Hammoud, a Harbach, a Ingold, B. Kisaˇ, P. Malawey, T. Newman, G. Scharenbroch, S. Skiver, M. Smith, a Wilhelm, G. Witt, E. Yoder, and H. Zhang, “Driver State Monitor from DELPHI Proposal for Demonstration at IEEE CVPR 2005 , San Diego , CA,” System, pp. 1–2, 2005. [33] B.-G. Lee and W.-Y. Chung, “A Smartphone-Based Driver Safety Monitoring System Using Data Fusion,” Sensors, vol. 12, no. 12, pp. 17536–17552, 2012. [34] E. Price, L. Galway, G. Moore, and M. Linden, “Towards a Mobile Assistive Technology for Monitoring and Assessing Cognitive Fatigue in Individuals with Acquired Brain Injury,” IEEE Int. Conf. Comput. Inf. Technol. Ubiquitous Comput. Commun. Dependable, Auton. Secur. Comput. Pervasive Intell. Comput., no. 15, pp. 1487–1491, 2015. [35] D. M. McNair, Manual profile of mood states. Educational & Industrial testing service, 1971. [36] Affectiva, “Affdex SDK.” [Online]. Available: http://www.affectiva.com/solutions/apis-sdks/. [Accessed: 21-Jul-2016]. [37] S. P. a Drummond, A. Bischoff-Grethe, D. F. Dinges, L. Ayalon, S. C. Mednick, and M. J. Meloy, “The neural basis of the psychomotor vigilance task.,” Sleep, vol. 28, no. 9, pp. 1059–1068, 2005. [38] D. R. Thorne, S. G. Genser, H. C. Sing, and F. W. Hegge, “The Walter Reed performance assessment battery.,” Neurobehav. Toxicol. Teratol., 1985. [39] D. F. Dinges and J. W. Powell, “Microcomputer analyses of performance on a portable, simple visual RT task during sustained operations,” Behav. Res. Methods, Instruments, Comput., vol. 17, no. 6, pp. 652–655, 1985. [40] P. Ekman and W. V Friesen, “Constants across cultures in the face and emotion,” Journal of personality and social psychology, vol. 17, no. 2. pp. 124–129, 1971. [41] Y.-J. Chang, S.-F. Chen, and L.-D. Chou, “A feasibility study of enhancing independent task performance for people with cognitive impairments through use of a handheld location-based prompting system.,” IEEE Trans. Inf. Technol. Biomed., vol. 16, no. 6, pp. 1157–63, Nov. 2012. [42] B. Das, B. L. Thomas, A. M. Seelye, D. J. Cook, L. B. Holder, and M. Schmitter-Edgecombe, “Context-aware prompting from your smart phone,” 2012 IEEE Consum. Commun. Netw. Conf., pp. 56–57, Jan. 2012. [43] J. Brooke, “SUS-A quick and dirty usability scale,” Usability Eval. Ind., vol. 189, no. 194, pp. 4–7, 1996.",
year = "2016",
month = "11",
day = "29",
doi = "10.1145/3007120.3007122",
language = "English",
isbn = "978-1-4503-4806-5/16/11",
booktitle = "Unknown Host Publication",

}

Price, E, Moore, G, Galway, L & Linden, M 2016, User Centred Design of a Smartphone-based Cognitive Fatigue Assessment Application. in Unknown Host Publication. The 14th International Conference on Advances in Mobile Computing & Multimedia, 29/11/16. https://doi.org/10.1145/3007120.3007122

User Centred Design of a Smartphone-based Cognitive Fatigue Assessment Application. / Price, Edward; Moore, George; Galway, Leo; Linden, Mark.

Unknown Host Publication. 2016.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - User Centred Design of a Smartphone-based Cognitive Fatigue Assessment Application

AU - Price, Edward

AU - Moore, George

AU - Galway, Leo

AU - Linden, Mark

N1 - Reference text: [1] F. Tagliaferri, C. Compagnone, M. Korsic, F. Servadei, and J. Kraus, “A systematic review of brain injury epidemiology in Europe,” Acta Neurochir. (Wien)., vol. 148, no. 3, pp. 255–267, 2006. [2] C. V. Faul M, Xu L, Wald MM, “Traumatic brain injury in the United States: emergency department visits, hospitalizations, and deaths,” Centers Dis. Control Prev. Natl. Cent. Inj. Prev. Control, pp. 891–904, 2010. [3] S. L. Hillier, J. E. Hiller, and J. Metzer, “Epidemiology of traumatic brain injury in South Australia.,” Brain Inj., vol. 11, no. 9, pp. 649–59, Sep. 1997. [4] R. Escorpizo, S. Brage, D. Homa, and G. Stucki, Eds., “Handbook of Vocational Rehabilitation and Disability Evaluation.” Springer International Publishing, Cham, 2015. [5] B. Johansson and L. Rönnbäck, “Mental Fatigue and Cognitive Impairment after an Almost Neurological Recovered Stroke,” ISRN Psychiatry, vol. 2012, pp. 1–7, 2012. [6] L. S. Aaronson, C. S. Teel, V. Cassmeyer, G. B. Neuberger, L. Pallikkathayil, and A. W. Janet Pierce, Allan N. Press, Phoebe D. Williams, “Defining and Measuring Fatigue,” J. Nurs. Scholarsh., vol. 31, no. 1, pp. 45–50, 1999. [7] C. Ziino and J. Ponsford, “Measurement and prediction of subjective fatigue following traumatic brain injury,” J. Int. …, pp. 416–425, 2005. [8] B. Johansson, P. Berglund, and L. Rönnbäck, “Mental fatigue and impaired information processing after mild and moderate traumatic brain injury.,” Brain Inj., vol. 23, no. 13–14, pp. 1027–40, Dec. 2009. [9] M. Kay and K. Rector, “PVT-touch: adapting a reaction time test for touchscreen devices,” Pervasive …, pp. 248–251, 2013. [10] D. Wechsler, “Wechsler adult intelligence scale–Fourth Edition (WAIS–IV),” San Antonio, TX NCS Pearson, 2008. [11] R. M. Reitan and D. Wolfson, The Halstead-Reitan neuropsychological test battery: Theory and clinical interpretation, vol. 4. Reitan Neuropsychology, 1985. [12] H. Van Dongen, G. Maislin, J. M. Mullington, and D. F. Dinges, “The cumulative cost of additional wakefulness: dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total,” Sleep, vol. 26, no. 2, pp. 117–126, 2003. [13] D. Gartenberg and R. McGarry, “Development of a Neuroergonomic Application to Evaluate Arousal,” Adv. …, pp. 6378–6387, 2012. [14] S. A. Ferguson, B. P. Smith, M. Browne, and M. J. Rockloff, “Fatigue in Emergency Services Operations : Assessment of the Optimal Objective and Subjective Measures Using a Simulated Wildfire Deployment,” Int. J. Environ. Res. Public Health, vol. 13, no. 2, 2016. [15] K. Liu, B. Li, S. Qian, Q. Jiang, L. Li, and W. Wang, “Mental fatigue after mild traumatic brain injury : a 3D-ASL perfusion study,” Brain Imaging Behav., pp. 1–12, 2016. [16] D. A. Grant, K. A. Honn, M. E. Layton, S. M. Riedy, and H. P. A. Van Dongen, “3-Minute Smartphone-Based and Tablet-Based Psychomotor Vigilance Tests for the Assessment of Reduced Alertness Due To Sleep Deprivation,” Behav. Res. Methods, 2016. [17] B. Johansson and L. Rönnbäck, “Mental Fatigue ; A Common Long Term Consequence After a Brain Injury,” 2009. [18] D. Swendeman, W. S. Comulada, N. Ramanathan, M. Lazar, and D. Estrin, “Reliability and Validity of Daily Self-Monitoring by Smartphone Application for Health-Related Quality-of-Life, Antiretroviral Adherence, Substance Use, and Sexual Behaviors Among People Living with HIV,” AIDS Behav., vol. 19, no. 2, pp. 330–340, 2014. [19] A.-L. L. Engström, J. Lexell, and M. L. Lund, “Difficulties in using everyday technology after acquired brain injury: a qualitative analysis.,” Scand. J. Occup. Ther., vol. 17, no. 3, pp. 233–243, 2010. [20] E. K. Wise, J. M. Hoffman, J. M. Powell, C. H. Bombardier, and K. R. Bell, “Benefits of exercise maintenance after traumatic brain injury,” Arch. Phys. Med. Rehabil., vol. 93, no. 8, pp. 1319–1323, 2012. [21] M. Schwandt, J. E. Harris, S. Thomas, M. Keightley, A. Snaiderman, and A. Colantonio, “Feasibility and effect of aerobic exercise for lowering depressive symptoms among individuals with traumatic brain injury: a pilot study,” J. Head Trauma Rehabil., vol. 27, no. 2, pp. 99–103, 2012. [22] T. Archer, “Influence of physical exercise on traumatic brain injury deficits: Scaffolding effect,” Neurotox. Res., vol. 21, no. 4, pp. 418–434, 2012. [23] S. J. Blondell, R. Hammersley-Mather, and J. L. Veerman, “Does physical activity prevent cognitive decline and dementia?: A systematic review and meta-analysis of longitudinal studies.,” BMC Public Health, vol. 14, no. 1, p. 510, 2014. [24] D. Laurin, “Physical Activity and Risk of Cognitive Impairment and Dementia in Elderly Persons,” Arch. Neurol., vol. 58, no. 3, pp. 498–504, 2001. [25] M. M. Marques, V. De Gucht, M. J. Gouveia, I. Leal, and S. Maes, “Differential effects of behavioral interventions with a graded physical activity component in patients suffering from Chronic Fatigue (Syndrome): An updated systematic review and meta-analysis,” Clin. Psychol. Rev., vol. 40, pp. 123–137, 2015. [26] R. Moss-Morris, “A Randomized Controlled Graded Exercise Trial for Chronic Fatigue Syndrome: Outcomes and Mechanisms of Change,” J. Health Psychol., vol. 10, no. 2, pp. 245–259, 2005. [27] J. R. Price, E. Mitchell, E. Tidy, and V. Hunot, “Cognitive behaviour therapy for chronic fatigue syndrome in adults.,” Cochrane database Syst. Rev., no. 3, p. CD001027, Jan. 2008. [28] B. D. Castell, N. Kazantzis, and R. E. Moss-Morris, “Cognitive behavioral therapy and graded exercise for chronic fatigue syndrome: A meta-analysis,” Clin. Psychol. Sci. Pract., vol. 18, no. 4, pp. 311–324, 2011. [29] J. Batista, “A drowsiness and point of attention monitoring system for driver vigilance,” IEEE Conf. Intell. Transp. Syst. Proceedings, ITSC, pp. 702–708, 2007. [30] L. Gan, B. Cui, and W. Wang, “Driver Fatigue Detection Based on Eye Tracking,” 2006 6th World Congr. Intell. Control Autom., vol. 2, pp. 5341–5344, 2006. [31] Q. Ji and X. Yang, “Real-Time Eye, Gaze, and Face Pose Tracking for Monitoring Driver Vigilance,” Real-Time Imaging, vol. 8, no. 5, pp. 357–377, Oct. 2002. [32] N. Edenborough, R. Hammoud, a Harbach, a Ingold, B. Kisaˇ, P. Malawey, T. Newman, G. Scharenbroch, S. Skiver, M. Smith, a Wilhelm, G. Witt, E. Yoder, and H. Zhang, “Driver State Monitor from DELPHI Proposal for Demonstration at IEEE CVPR 2005 , San Diego , CA,” System, pp. 1–2, 2005. [33] B.-G. Lee and W.-Y. Chung, “A Smartphone-Based Driver Safety Monitoring System Using Data Fusion,” Sensors, vol. 12, no. 12, pp. 17536–17552, 2012. [34] E. Price, L. Galway, G. Moore, and M. Linden, “Towards a Mobile Assistive Technology for Monitoring and Assessing Cognitive Fatigue in Individuals with Acquired Brain Injury,” IEEE Int. Conf. Comput. Inf. Technol. Ubiquitous Comput. Commun. Dependable, Auton. Secur. Comput. Pervasive Intell. Comput., no. 15, pp. 1487–1491, 2015. [35] D. M. McNair, Manual profile of mood states. Educational & Industrial testing service, 1971. [36] Affectiva, “Affdex SDK.” [Online]. Available: http://www.affectiva.com/solutions/apis-sdks/. [Accessed: 21-Jul-2016]. [37] S. P. a Drummond, A. Bischoff-Grethe, D. F. Dinges, L. Ayalon, S. C. Mednick, and M. J. Meloy, “The neural basis of the psychomotor vigilance task.,” Sleep, vol. 28, no. 9, pp. 1059–1068, 2005. [38] D. R. Thorne, S. G. Genser, H. C. Sing, and F. W. Hegge, “The Walter Reed performance assessment battery.,” Neurobehav. Toxicol. Teratol., 1985. [39] D. F. Dinges and J. W. Powell, “Microcomputer analyses of performance on a portable, simple visual RT task during sustained operations,” Behav. Res. Methods, Instruments, Comput., vol. 17, no. 6, pp. 652–655, 1985. [40] P. Ekman and W. V Friesen, “Constants across cultures in the face and emotion,” Journal of personality and social psychology, vol. 17, no. 2. pp. 124–129, 1971. [41] Y.-J. Chang, S.-F. Chen, and L.-D. Chou, “A feasibility study of enhancing independent task performance for people with cognitive impairments through use of a handheld location-based prompting system.,” IEEE Trans. Inf. Technol. Biomed., vol. 16, no. 6, pp. 1157–63, Nov. 2012. [42] B. Das, B. L. Thomas, A. M. Seelye, D. J. Cook, L. B. Holder, and M. Schmitter-Edgecombe, “Context-aware prompting from your smart phone,” 2012 IEEE Consum. Commun. Netw. Conf., pp. 56–57, Jan. 2012. [43] J. Brooke, “SUS-A quick and dirty usability scale,” Usability Eval. Ind., vol. 189, no. 194, pp. 4–7, 1996.

PY - 2016/11/29

Y1 - 2016/11/29

N2 - This paper presents the user experience design approach taken for a mobile cognitive assessment tool. Taking a multidisciplinary approach with user centred assessment and feedback, the design of this tool was tailored to provide a usable and intuitive user experience. Key to user participation is ease of use and minimal time on task for participant engagement. To address this selected measures were carefully considered as to make the testing process simple and easy to engage with. Following a pre-validated, iterative design approach, an acceptable and engaging user experience was designed while retaining the ability to measure multiple aspects of a user’s condition and environment. Accurate assessment of cognitive fatigue requires a wide range of environmental user data in order to understand the participants’ current cognitive fatigue levels, therefore measures of physical, cognitive, social and emotional aspects were included within the application.

AB - This paper presents the user experience design approach taken for a mobile cognitive assessment tool. Taking a multidisciplinary approach with user centred assessment and feedback, the design of this tool was tailored to provide a usable and intuitive user experience. Key to user participation is ease of use and minimal time on task for participant engagement. To address this selected measures were carefully considered as to make the testing process simple and easy to engage with. Following a pre-validated, iterative design approach, an acceptable and engaging user experience was designed while retaining the ability to measure multiple aspects of a user’s condition and environment. Accurate assessment of cognitive fatigue requires a wide range of environmental user data in order to understand the participants’ current cognitive fatigue levels, therefore measures of physical, cognitive, social and emotional aspects were included within the application.

KW - Fatigue

KW - cognitive fatigue

KW - smartphone

KW - mobile

KW - reaction

KW - spatial span

KW - mental arithmetic

KW - cognitive tests

KW - facial features

KW - application design.

U2 - 10.1145/3007120.3007122

DO - 10.1145/3007120.3007122

M3 - Conference contribution

SN - 978-1-4503-4806-5/16/11

BT - Unknown Host Publication

ER -