The use of wearable technology to measure and support abilities, disabilities and functional skills in autistic youth: a scoping review

Melissa H Black, Benjamin Milbourn, Nigel T M Chen, Sarah McGarry, Fatema Wali, Armilda S V Ho, Mika Lee, Sven Bölte, Torbjorn Falkmer, Sonya Girdler, Melissa H Black, Benjamin Milbourn, Nigel T M Chen, Sarah McGarry, Fatema Wali, Armilda S V Ho, Mika Lee, Sven Bölte, Torbjorn Falkmer, Sonya Girdler

Abstract

Background: Wearable technology (WT) to measure and support social and non-social functioning in Autism Spectrum Disorder (ASD) has been a growing interest of researchers over the past decade. There is however limited understanding of the WTs currently available for autistic individuals, and how they measure functioning in this population.

Objective: This scoping review explored the use of WTs for measuring and supporting abilities, disabilities and functional skills in autistic youth.

Method: Four electronic databases were searched to identify literature investigating the use of WT in autistic youth, resulting in a total of 33 studies being reviewed. Descriptive and content analysis was conducted, with studies subsequently mapped to the ASD International Classification of Functioning, Disability and Health Core-sets and the ICF Child and Youth Version (ICF-CY).

Results: Studies were predominately pilot studies for novel devices. WTs measured a range of physiological and behavioural functions to objectively measure stereotypical motor movements, social function, communication, and emotion regulation in autistic youth in the context of a range of environments and activities.

Conclusions: While this review raises promising prospects for the use of WTs for autistic youth, the current evidence is limited and requires further investigation.

Keywords: Autism Spectrum Disorder; ICF; physiology; sensors; wearable devices.

Conflict of interest statement

Conflicts of interest Dr. Bölte reports personal fees from Medice, Roche, Prima Psychiatry, Hogrefe, grants from Swedish Research Council, ALF, Hjärnfonden, Clas Groschinsky, Promobilia, Region Stockholm, FORTE, outside this work. All other authors report no conflicts of interest.

© 2020 Authors.

Figures

FIGURE 1.
FIGURE 1.
Study selection process

References

    1. Wright R, Keith L. Wearable technology: If the tech fits, wear it. J Electr Resources Med Libr 2014;11(4):204-16.
    1. Iqbal M, Aydin A, Brunckhorst O, Dasgupta P, Ahmed K. A review of wearable technology in medicine. J R Soc Med 2016;109(10):372-80.
    1. Bonato P. Advances in wearable technology for rehabilitation. Stud Health Technol Inform 2009;145:145-59.
    1. Dias D, Paulo Silva Cunha J. Wearable health devices—Vital sign monitoring, systems and technologies. Sensors (Basel) 2018;18(8):1-28.
    1. Fletcher R, Poh M, Eydgahi H. Wearable sensors: Opportunities and challenges for low-cost health care. 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology; Buenos Aires, Argentina IEEE; 2010. p. 1763-6.
    1. Virnes M, Kärnä E, Vellonen V. Review of research on children with autism spectrum disorder and the use of technology. J Spec Educ Technol 2015;30(1):13-27.
    1. American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders (DSM-5®) 5 ed. Washington, US: American Psychiatric Publishing; 2013.
    1. Bölte S, Madhi S, de Vries P, Granlund M, Robison J, Shulman C, et al. The gestalt of functioning in autism spectrum disorder: Results of the international conference to develop final consensus International Classification of Functioning, Disability and Health core sets. Autism 2019;23(2):449-67.
    1. Schaaf R, Benevides T, Leiby B, Sendecki J. Autonomic dysregulation during sensory stimulation in children with autism spectrum disorder. J Autism Dev Disord 2015;45(2):461-72.
    1. Kushki A, Brian J, Dupuis A, Anagnostou E. Functional autonomic nervous system profile in children with autism spectrum disorder. Mol Autism 2014;5:39.
    1. Klusek J, Roberts J, Losh M. Cardiac autonomic regulation in autism and Fragile X syndrome: A review. Psychol Bull 2015;141(1):141-75.
    1. Lydon S, Healy O, Reed P, Mulhern T, Hughes B, Goodwin M. A systematic review of physiological reactivity to stimuli in autism. Dev Neurorehabil 2016;19(6):335-55.
    1. Picard RW. Future affective technology for autism and emotion communication. Philos Trans R Soc Lond B Biol Sci 2009;364(1535):3575-84.
    1. Torrado J, Gomez J, Montoro G. Emotional Self-Regulation of Individuals with Autism Spectrum Disorders: Smartwatches for Monitoring and Interaction. Sensors (Basel) 2017;17(6):1359.
    1. Koumpouros Y, Kafazis T. Wearables and mobile technologies in Autism Spectrum Disorder interventions: A systematic literature review. Res Autism Spectr Disord 2019;66:101405.
    1. World Health Organization International Classification of Functioning, Disability, and Health: Children & Youth Version: ICF-CY Geneva, Switzerland: World Health Organization; 2007.
    1. Schiariti V, Mahdi S, Bölte S. International classification of functioning, disability and health core sets for cerebral palsy, autism spectrum disorder, and attention-deficit-hyperactivity disorder. Dev Med Child Neurol 2018;60(9):933-41.
    1. Scott M, Milbourn B, Falkmer M, Black M, Bölte S, Halladay A, et al. Factors impacting employment for people with autism spectrum disorder: A scoping review. Autism 2019;23(4):869-901.
    1. Arksey H, O'Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol 2005;8(1):19-32.
    1. Daudt H, van Mossel C, Scott S. Enhancing the scoping study methodology: A large, inter-professional team’s experience with Arksey and O’Malley’s framework. BMC Med Res Methodol 2013;13(48).
    1. Levac D, Colquhoun H, O'Brien K. Scoping studies: Advancing the methodology. Implement Sci 2010;5:69.
    1. World Health Organization International Statistical Classification of Diseases and Realted Health Problems, 10th revision 5 ed. Geneva, Switzerland: World Health Organization; 2016.
    1. American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) Washington, US: American Psychiatric Publishing; 2000.
    1. Kurita H. How to deal with the transition from Pervasive Developmental Disorders in DSM-IV to Autism Spectrum Disorder in DSM-V. Psychiatry Clin Neurosci 2011;65(7):609-10.
    1. Kmet LM, Lee RC, Cook LS. Standard quality assessment criteria for evaluating primary research papers from a variety of fields Edmonton, Alberta, Canada: Alberta Heritage Foundation for Medical Research; 2004.
    1. Lee L, Packer T, Tang S, Girdler S. Self-management education programs for age-related macular degeneration: A systematic review. Australas J Ageing 2008;27(4):170-6.
    1. Cieza A, Brockow T, Ewert T, Amman E, Kollerits B, Chatterji S, et al. Linking health-status measurements to the International Classificataion of Functioning, Disability and Health. J Rehabil Med 2002;34(5):205-10.
    1. Cieza A, Geyh S, Chatterji S, Kostanjsek N, Üstün B, Stucki G. ICF linking rules: An update based on lessons learned. J Rehab Med 2005;37(4):212-8.
    1. Selb M, Escorpizo R, Kostanjsek N, Stucki G, Üstün B, Cieza A. A guide on how to develop an International Classification of Functioning, Disability and Health Core Set. Eur J Phys Rehabilitation Med 2015;51(1):105-17.
    1. Ness S, Manyakov N, Bangerter A, Lewin D, Jagannatha S, Boice M, et al. JAKE® multimodal data capture system: Insights from an observational study of autism spectrum disorder. Front Neurosci 2017;11:517.
    1. Liu R, Salisbury J, Vahabzadeh A, Sahin N. Feasability of an autism-focused augmented reality smartglasses system for social communication and behavioural coaching. Front Pediatr 2017;5:145.
    1. Keshav NU, Salisbury JP, Vahabzadeh A, Sahin NT. Social communication coaching smartglasses: Well tolerated in a diverse sample of children and adults with autism. JMIR mHealth uHealth 2017;5(9):e140.
    1. Sahin NT, Keshav NU, Salisbury JP, Vahabzadeh A. Second version of google glass as a wearable socio-affective aid: Positive school desirability, high usability, and theoretical framework in a sample of children with autism. JMIR Hum Factors 2018;5(1):e1.
    1. Sahin NT, Keshav NU, Salisbury JP, Vahabzadeh A. Safety and lack of negative effects of wearable augmented-reality social communication aid for children and adults with autism. J Clin Med. 2018;7(8):188.
    1. Daniels J, Schwartz J, Voss C, Haber N, Fazel A, Kline A, et al. Exploratory study examining the at-home feasibility of a wearable tool for social-affective learning in children with autism. NPJ Digit Med 2018;1:32.
    1. Voss C, Washington P, Haber N, Kline A, Daniels J, Fazel A, et al. Superpower Glass: Delivering unobtrusive real-Time social cues in wearable systems. Proceedings of the Ubicomp/ISWC'16 Adjunct, September 12-16, 2016, Heidelberg, Germany ACM; 2016:1218-26.
    1. Washington P, Voss C, Haber N, Tanaka S, Daniels J, Feinstein C, et al. A wearable social interaction aid for children with autism. Proceedings of the CHI'16 Extended Abstracts, May 07-12, 2016, San Jose, CA, USA ACM 978-1-4503-4082-3/16/05.
    1. Daniels J, Haber N, Voss C, Schwartz J, Tamura S, Fazel A, et al. Feasibility testing of a wearable behavioral aid for social learning in children with autism. Appl Clin Inform 2018;9(1):129-40.
    1. Vahabzadeh A, Keshav N, Salisbury J, Sahin N. Improvement of attention-deficit/hyperactivity disorder (ADHD) symptoms in school-aged children, adolescents and young adults with autism via a digital smartglasses-based socioemotional coaching aid: short-term, uncontrolled pilot study. JMIR Mental Health. 2018;5(2):e25.
    1. Kinsella BG, Chow S, Kushki A. Evaluating the usability of a wearable social skills training technology for children with autism spectrum disorder. Front Robot AI. 2017;4:31.
    1. Magrelli S, Jermann P, Noris B, Ansermet F, Hentsch F, Nadel J, et al. Social orienting of children with autism to facial expressions and speech: A study with a wearable eye-tracker in naturalistic settings. Front Psychol 2013;4:840.
    1. Magrelli S, Noris B, Jermann P, Ansermet F, Hentsch F, Nadel J, et al. A wearable camera detects gaze peculiarities during social interactions in young children with pervasive developmental disorders. IEEE Trans Auton Ment Dev 2014;6(4):274-85.
    1. Mazzei D, Billeci L, Armato A, Lazzeri N, Cisternino A, Pioggia G, et al., editors. The FACE of autism. Proceedings - IEEE International Workshop on Robot and Human Interactive Communication; 2010.
    1. Spiel K, Makhaeva J, Frauenberger C. Embodied companion technologies for autistic children. TEI 2016 - Proceedings of the 10th Anniversary Conference on Tangible Embedded and Embodied Interaction; Eindhoven, Netherlands ACM; 2016:245-52.
    1. Lee C, Goodwin M, Morris R, Picard R. Lessons learned from a pilot study quantifying face contact and skin conductance in teens with asperger syndrome. Conference on Human Factors in Computing Systems - Proceedings; Florence, Italy: ACM; 2008:3147-52.
    1. Hachisu T, Pan Y, Matsuda S, Bourreau B, Suzuki K. FaceLooks: A smart headband for signaling face-to-face behavior. Sensors (Switzerland). 2018;18(7):2066.
    1. Billeci L, Tonacci A, Tartarisco G, Narzisi A, Di Palma S, Corda D, et al. An integrated approach for the monitoring of brain and autonomic response of children with autism spectrum disorders during treatment by wearable technologies. Front Neurosci 2016;10:276.
    1. Min C, Tewfik A. Automatic characterization and detection of behavioral patterns using linear predictive coding of accelerometer sensor data. 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Buenos Aires, Argentina 2010:220-3.
    1. Min C, Tewfik A. Semi-supervised event detection using higher order statistics for multidimensional time series accelerometer data. Conference Proceedings, 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, Mass, USA 2011:365-8.
    1. Min C, Tewfik A, Kim Y, Menard R. Optimal sensor location for body sensor network to detect self-stimulatory behaviors of children with autism spectrum disorder. Conf Proc IEEE Eng Med Biol Soc 2009;2009:3489-92.
    1. Rad NM, Kia SM, Zarbo C, Jurman G, Venuti P, Furlanello C. Stereotypical Motor Movement Detection in Dynamic Feature Space. Conf Paper: IEEE 16th International Conference on Data Mining Workshops (ICDM), Barcelona, Spain; 2016:487-94.
    1. Albinali F, Goodwin M, Intille S. Detecting stereotypical motor movements in the classroom using accelerometry and pattern recognition algorithms. Pervasive Mob Comput 2012;8(1):103-4.
    1. Goodwin M, Haghighi M, Tang Q, Akcakaya M, Erdogmus D, Intille S. Moving towards a real-time system for automatically recognizing stereotypical motor movements in individuals on the autism spectrum using wireless accelerometry0. UbiComp '14 Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing; Seattle, WA, USA; 2014: 861-72.
    1. Funahashi A, Gruebler A, Aoki T, Kadone H, Suzuki K. Brief report: The smiles of a child with autism spectrum disorder during an animal-assisted activity may facilitate social positive behaviors-Quantitative analysis with smile-detecting interface. J Autism Dev Disord 2014;44(3):685-93.
    1. Hirokawa M, Funahashi A, Pan Y, Itoh Y, Suzuki K, editors. Design of a robotic agent that measures smile and facing behavior of children with Autism Spectrum Disorder. 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN); 2016:843-8.
    1. Di Palma S, Tonacci A, Narzisi A, Domenici C, Pioggia G, Muratori F, et al. Monitoring of autonomic response to sociocognitive tasks during treatment in children with autism spectrum disorders by wearable technologies: A feasibility study. Comput Biol Med 2017;85(1):143-52.
    1. Billeci L, Tonacci A, Narzisi A, Manigrasso Z, Varanini M, Fulceri F, et al. Heart rate variability during a joint attention task in toddlers with autism spectrum disorders. Front Physiol 2018;9:467.
    1. Jiang X, Boyd LE, Chen Y, Hayes GR. ProCom: Designing a mobile and wearable system to support proximity awareness for people with Autism. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, September 12-16, 2016; Heidelberg, Germany ACM; 2016:93-6.
    1. Suzuki K, Hachisu T, Iida K. EnhancedTouch: A smart bracelet for enhancing human-human physical touch. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems San Jose, California: ACM; 2016:1282-93.
    1. Takahashi K, Matsuda S, Suzuki K. A smart clothe for ECG monitoring of children with autism spectrum disorders In: Miesenberger K, Bühler C, Penaz P (eds). Computers helping people with special needs. ICCHP 2016. Lecture notes in Computer Science, vol 9758. Springer, Cham; 2016:555-62.
    1. Marcu G, Dey AK, Kiesler S. Parent-driven use of wearable cameras for autism support: A field study with families. UbiComp'12 - Proceedings of the 2012 ACM Conference on Ubiquitous Computing; Pittsburgh, USA: ACM; 2012:401-10.
    1. Loth E, Murphy DG, Spooren W. Defining Precision Medicine Approaches to Autism Spectrum Disorders: Concepts and Challenges. Front Psychiatry 2016;7:188.
    1. Hayes G, Hirano S, Marcu G, Monibi M, Nguyen D, Yeganyan M. Interactive visual supports for children with autism. Pers Ubiquit Comput 2010;14(7):663-80.
    1. Dobkin BH, Dorsch A. The promise of mHealth: Daily activity monitoring and outcome assessments by wearable sensors. Neurorehabil Neural Repair 2011;25(9):788-98.
    1. Düking P, Fuss F, Holmberg HC, Sperlich B. Recommendations for assessment of the reliability, sensitivity, and validity of data provided by wearable sensors designed for monitoring physical activity. JMIR mHealth uHealth 2018;6(4):e102.
    1. Picard R, Fedor S, Ayzenberg Y. Multiple arousal theory and daily-life electrodermal activity asymmetry Emotion Review 2016;8(1):62-75.
    1. Hopkins WG. Measures of reliability in sports medicine and science. Sports Med 2000;30(1):1-15.
    1. Kientz J, Goodwin M, Hayes G, Abowd G. Interactive technologies for autism. Morgan and Claypool Publ; 2013.
    1. McCann J, Hurford R, A. Martin A. A design process for the development of innovative smart clothing that addresses end-user needs from technical, functional, aesthetic and cultural viewpoints. Ninth IEEE International Symposium on Wearable Computers (ISWC'05), Osaka, 2005: 70-77.

Source: PubMed

スポンサーと協力者

医学的状態

薬物療法

3
購読する