Evaluating the Acceptability of Assistive Robots for Early Detection of Mild Cognitive Impairment

The employment of Social Assistive Robots (SARs) for monitoring elderly users represents a valuable gateway for at-home assistance. Their deployment in the house of the users can provide effective opportunities for early detection of Mild Cognitive Impairment (MCI), a condition of increasing impact in our aging society, by means of digitalized cognitive tests. In this work, we present a system where a specific set of cognitive tests is selected, digitalized, and integrated with a robotic assistant, whose task is the guidance and supervision of the users during the completion of such tests. The system is then evaluated by means of an experimental study involving potential future users, in order to assess its acceptability and identify key directions for technical improvements.

[1]  Morgan Quigley,et al.  ROS: an open-source Robot Operating System , 2009, ICRA 2009.

[2]  Goldie Nejat,et al.  Brian 2.1: A socially assistive robot for the elderly and cognitively impaired , 2013, IEEE Robotics & Automation Magazine.

[3]  Ewa Wressle,et al.  Cognitive impairment and its consequences in everyday life: experiences of people with mild cognitive impairment or mild dementia and their relatives , 2015, International Psychogeriatrics.

[4]  E. Capitani,et al.  Trail making test: normative values from 287 normal adult controls , 1996, The Italian Journal of Neurological Sciences.

[5]  O. Selnes A Compendium of Neuropsychological Tests , 1991, Neurology.

[6]  Antonis A. Argyros,et al.  Hobbit , a care robot supporting independent living at home : First prototype and lessons learned , 2015 .

[7]  Nicola Basilico,et al.  Exergaming for balance training, transparent monitoring, and social inclusion of community-dwelling elderly , 2017, 2017 IEEE 3rd International Forum on Research and Technologies for Society and Industry (RTSI).

[8]  Brian Scassellati,et al.  Integrating socially assistive robotics into mental healthcare interventions: applications and recommendations for expanded use. , 2015, Clinical Psychology Review.

[9]  Maureen Schmitter-Edgecombe,et al.  Multicomponent analysis of a digital Trail Making Test , 2017, The Clinical neuropsychologist.

[10]  M. Matarić,et al.  The use of socially assistive robots in the design of intelligent cognitive therapies for people with dementia , 2009, 2009 IEEE International Conference on Rehabilitation Robotics.

[11]  Liam J Caffery,et al.  Using survey methods in telehealth research: A practical guide , 2017, Journal of telemedicine and telecare.

[12]  Nicola Bellotto,et al.  ENRICHME Integration of Ambient Intelligence and Robotics for AAL , 2017, AAAI Spring Symposia.

[13]  Bruce A. MacDonald,et al.  People respond better to robots than computer tablets delivering healthcare instructions , 2015, Comput. Hum. Behav..

[14]  Takanori Shibata,et al.  Effects of robot assisted activity to elderly people who stay at a health service facility for the aged , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[15]  D. Feil-Seifer,et al.  Defining socially assistive robotics , 2005, 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005..

[16]  Amedeo Cesta,et al.  GiraffPlus: a system for monitoring activities and physiological parameters and promoting social interaction for elderly. , 2014 .

[17]  Carol Persad,et al.  Cognitive Deficits in Healthy Elderly Population With “Normal” Scores on the Mini-Mental State Examination , 2016, Journal of geriatric psychiatry and neurology.

[18]  Horst-Michael Groß,et al.  Robot companion for domestic health assistance: Implementation, test and case study under everyday conditions in private apartments , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[19]  Alessandro Di Nuovo,et al.  Social Robots as Psychometric Tools for Cognitive Assessment: A Pilot Test , 2017, HFR.

[20]  P. Lapuerta,et al.  Impact of early intervention and disease modification in patients with predementia Alzheimer’s disease: a Markov model simulation , 2011, ClinicoEconomics and outcomes research : CEOR.

[21]  G. Mcnicoll World Population Ageing 1950-2050. , 2002 .

[22]  J. Cummings,et al.  The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment , 2005, Journal of the American Geriatrics Society.

[23]  Nicola Basilico,et al.  A Multi-Actor Framework Centered around an Assistive Mobile Robot for Elderly People Living Alone , 2018, IROS 2018.

[24]  L. Gauthier,et al.  The Bells Test: A quantitative and qualitative test for visual neglect. , 1989 .

[25]  R. Reitan Validity of the Trail Making Test as an Indicator of Organic Brain Damage , 1958 .

[26]  M. Vizcaychipi,et al.  Scoping review on the use of socially assistive robot technology in elderly care , 2018, BMJ Open.

[27]  M. Schmitter-Edgecombe,et al.  The Ecological Validity of Neuropsychological Tests: A Review of the Literature on Everyday Cognitive Skills , 2003, Neuropsychology Review.

[28]  Marc Hanheide,et al.  The When, Where, and How: An Adaptive Robotic Info-Terminal for Care Home Residents - A Long-Term Study , 2017, 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI.

[29]  Nicola Basilico,et al.  Validity of digital Trail Making Test and Bells Test in elderlies , 2019, 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI).

[30]  J. Sitzia,et al.  Good practice in the conduct and reporting of survey research. , 2003, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[31]  Angelo Cangelosi,et al.  Digitalized Cognitive Assessment mediated by a Virtual Caregiver , 2018, IJCAI.