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Review of Methods for Data Collection Experiments with People with Dementia and the Impact of COVID-19

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Intelligent Computing Theories and Application (ICIC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12838))

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Abstract

The development of a wearable-based system for detecting difficulties in the daily lives of people with dementia would be highly useful in the day-to-day management of the disease. To develop such a system, it would be necessary to identify physiological indicators of the difficulties, which can be identified by analyzing physiological datasets from people with dementia. However, there is no such data available to researchers. As such, it is vital that data is collected and made available in future. In this paper we perform a review of past physiological data collection experiments conducted with people with dementia and evaluate the methods used at each stage of the experiment. Consideration is also given to the impacts and limitations imposed by the COVID-19 pandemic and lockdowns both on the people with dementia- such people being one of the most at risk and affected groups- and on the efficacy and safety of each of the methods. It is concluded that the choice of method to be utilized in future data collection experiments is heavily dependent on the type and severity of the dementia the participants are experiencing, and that the choice of remote or COVID-secure methods should be used during the COVID-19 pandemic; many of the methods reviewed could allow for the spread of the virus if utilized during a pandemic.

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References

  1. Koumakis, L., Chatzaki, C., Kazantzaki, E., Maniadi, E., Tsiknakis, M.: Dementia care frameworks and assistive technologies for their implementation: a review. IEEE Rev. Biomed. Eng. 12, 4–18 (2019)

    Article  Google Scholar 

  2. PHE: Statistical commentary: dementia profile, April 2019 update.” Gov.uk. https://www.gov.uk/government/publications/dementia-profile-april-2019-data-update/statistical-commentary-dementia-profile-april-2019-update. Accessed 30 Jan 2020

  3. WHO: “Dementia.” World Health Organisation. https://www.who.int/news-room/fact-sheets/detail/dementia. Accessed 5 May 2020

  4. Buckley, J.S., Salpeter, S.R.: A risk-benefit assessment of dementia medications: systematic review of the evidence. Drugs Aging 32(6), 453–467 (2015)

    Article  Google Scholar 

  5. P. Reed and S. Bluethmann, "Voices of Alzheimer's Disease: A summary report on the nationwide town hall meetings for people with early stage dementia. alzheimer's association (2008). https://www.alz.org/national/documents/report_townhall.pdf,” ed (2017)

  6. Connors, M.H., Seeher, K., Teixeira-Pinto, A., Woodward, M., Ames, D., Brodaty, H.: Dementia and caregiver burden: a three-year longitudinal study. Int. J. Geriatr. Psychiatry 35(2), 250–258 (2020)

    Article  Google Scholar 

  7. Aljaaf, A.J., Mallucci, C., Al-Jumeily, D., Hussain, A., Alloghani, M., Mustafina, J.: A study of data classification and selection techniques to diagnose headache patients. In: Applications of Big Data Analytics, pp. 121–134. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-76472-6_6

  8. Aljaaf, A.J., Al-Jumeily, D., Hussain, A.J., Baker, T., Alloghani, M., Mustafina, J.: H-diary: Mobile application for headache diary and remote patient monitoring. In: 2018 11th International Conference on Developments in eSystems Engineering (DeSE), pp. 18–22. IEEE (2018)

    Google Scholar 

  9. Alloghani, M., Aljaaf, A.J., Al-Jumeily, D., Hussain, A., Mallucci, C., Mustafina, J.: Data science to improve patient management system. In: 2018 11th International Conference on Developments in eSystems Engineering (DeSE), pp. 27–30. IEEE (2018)

    Google Scholar 

  10. Alloghani, M., Al-Jumeily, D., Hussain, A., Aljaaf, A.J., Mustafina, J., Petrov, E.: Healthcare services innovations based on the state of the art technology trend industry 4.0. In: 2018 11th International Conference on Developments in eSystems Engineering (DeSE), pp. 64–70. IEEE (2018)

    Google Scholar 

  11. Alloghani, M., Al-Jumeily, D., Aljaaf, A.J., Khalaf, M., Mustafina, J., Tan, S.Y.: The application of artificial intelligence technology in healthcare: a systematic review. In: Khalaf, M.I., Al-Jumeily, D., Lisitsa, A. (eds.) ACRIT 2019. CCIS, vol. 1174, pp. 248–261. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-38752-5_20

    Chapter  Google Scholar 

  12. Harper, M., Ghali, F.: A Systematic review of wearable devices for tracking physiological indicators of Dementia-related difficulties, presented at the Developments in E-Systems, Online (2020)

    Google Scholar 

  13. Bianchetti, A., et al.: Clinical presentation of COVID19 in dementia patients. J. Nutr. Health Aging 24, 560–562 (2020)

    Article  Google Scholar 

  14. Mok, V.C., et al.: Tackling challenges in care of Alzheimer’s disease and other dementias amid the COVID-19 pandemic, now and in the future. Alzheimers Dement. 16(11), 1571–1581 (2020)

    Article  Google Scholar 

  15. Ye, B., et al.: Challenges in collecting big data in a clinical environment with vulnerable population: lessons learned from a study using a multi-modal sensors platform. Sci. Eng. Ethics 25(5), 1447–1466 (2019)

    Article  Google Scholar 

  16. Vuong, N., Chan, S., Lau, C.T., Chan, S., Yap, P.L.K., Chen, A.: Preliminary results of using inertial sensors to detect dementia-related wandering patterns. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3703–3706. IEEE (2015)

    Google Scholar 

  17. Alam, R., et al.: Motion biomarkers for early detection of dementia-related agitation. In: Proceedings of the 1st Workshop on Digital Biomarkers, pp. 15–20 (2017)

    Google Scholar 

  18. Alam, R., Anderson, M., Bankole, A., Lach, J.: Inferring physical agitation in dementia using smartwatch and sequential behavior models. In: 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), pp. 170–173. IEEE (2018)

    Google Scholar 

  19. Alam, R., Bankole, A., Anderson, M., Lach, J.: Multiple-instance learning for sparse behavior modeling from wearables: toward dementia-related agitation prediction. In: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1330–1333. IEEE (2019)

    Google Scholar 

  20. Valembois, L., Oasi, C., Pariel, S., Jarzebowski, W., Lafuente-Lafuente, C., Belmin, J.: Wrist actigraphy: a simple way to record motor activity in elderly patients with dementia and apathy or aberrant motor behavior. J. Nutr. Health Aging 19(7), 759–764 (2015)

    Article  Google Scholar 

  21. Karakostas, A., Lazarou, I., Meditskos, G., Stavropoulos, T.G., Kompatsiaris, I., Tsolaki, M.: Sensor-based in-home monitoring of people with dementia using remote web technologies. In: 2015 International Conference on Interactive Mobile Communication Technologies and Learning (IMCL), pp. 353–357. IEEE (2015)

    Google Scholar 

  22. Khan, S.S., et al.: Agitation detection in people living with dementia using multimodal sensors. In: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3588–3591. IEEE (2019)

    Google Scholar 

  23. Spasojevic, S., et al.: A pilot study to detect agitation in people living with dementia using multi-modal sensors

    Google Scholar 

  24. Melander, C., Martinsson, J., Gustafsson, S.: Measuring electrodermal activity to improve the identification of agitation in individuals with dementia. Dementia and geriatric cognitive disorders extra 7(3), 430–439 (2017)

    Article  Google Scholar 

  25. Goerss, D., et al.: Automated sensor-based detection of challenging behaviors in advanced stages of dementia in nursing homes. Alzheimer's & Dementia (2019)

    Google Scholar 

  26. Teipel, S., et al.: Multidimensional assessment of challenging behaviors in advanced stages of dementia in nursing homes—The insideDEM framework. Alzheimer’s Dementia Diagnosis, Assessment Disease Monitoring 8, 36–44 (2017)

    Article  Google Scholar 

  27. Nesbitt, C., Gupta, A., Jain, S., Maly, K., Okhravi, H.R.: Reliability of wearable sensors to detect agitation in patients with dementia: a pilot study. In: Proceedings of the 2018 10th International Conference on Bioinformatics and Biomedical Technology, pp. 73–77 (2018)

    Google Scholar 

  28. Sefcik, J.S., Ersek, M., Libonati, J.R., Hartnett, S.C., Hodgson, N.A., Cacchione, P.Z.: Heart rate of nursing home residents with advanced dementia and persistent vocalizations. Health Technol. 1–5 (2019)

    Google Scholar 

  29. Kikhia, B., et al.: Utilizing ambient and wearable sensors to monitor sleep and stress for people with BPSD in nursing homes. J. Ambient. Intell. Humaniz. Comput. 9(2), 261–273 (2015). https://doi.org/10.1007/s12652-015-0331-6

    Article  Google Scholar 

  30. NHS: How to get a dementia diagnosis. NHS.uk. https://www.nhs.uk/conditions/dementia/diagnosis/. Accessed 19 Apr 2020

  31. MerseyCare: Important information about changes to our services. NHS. https://www.merseycare.nhs.uk/about-us/news/coronavirus-changes-to-mersey-cares-services/. Accessed 15 Mar 2021

  32. Cuffaro, L., Di Lorenzo, F., Bonavita, S., Tedeschi, G., Leocani, L., Lavorgna, L.: Dementia care and COVID-19 pandemic: a necessary digital revolution. Neurol. Sci. 41(8), 1977–1979 (2020). https://doi.org/10.1007/s10072-020-04512-4

    Article  Google Scholar 

  33. Aveiro, M.: Rapid Response, Dementia patients: a vulnerable population during the COVID-19 Pandemic. BMJ. https://www.bmj.com/content/370/bmj.m3709/rr-6. Accessed 15 Mar 2021

  34. ONS: Number of deaths in care homes notified to the Care Quality Commission, England. GOV.uk. https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/numberofdeathsincarehomesnotifiedtothecarequalitycommissionengland. Accessed 15 Mar 2021

  35. A. Society: ONS figures show 50 per cent of all Covid-19 deaths in care homes also had dementia – Alzheimer’s Society comment. https://www.alzheimers.org.uk/news/2020-07-03/ons-figures-show-50-cent-all-covid-19-deaths-care-homes-also-had-dementia. Accessed 15 Mar 2021

  36. Canevelli, M., et al.: Facing dementia during the COVID‐19 Outbreak. J. Am. Geriatrics Soc. (2020)

    Google Scholar 

  37. McCarthy, I., et al.: Infrastructureless pedestrian navigation to assess the response of Alzheimer's patients to visual cues (2015)

    Google Scholar 

  38. Kolakowski, M., Blachucki, B.: Monitoring wandering behavior of persons suffering from dementia using BLE based localization system. In: 2019 27th Telecommunications Forum (TELFOR), pp. 1–4. IEEE (2019)

    Google Scholar 

  39. Liu, Y., Batrancourt, B., Marin, F., Levy, R.: Evaluation of apathy by single 3D accelerometer in ecological condition: Case of patients with behavioral variant of fronto-temporal dementia. In: 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom), pp. 1–4. IEEE (2018)

    Google Scholar 

  40. Gong, J., et al.: Home wireless sensing system for monitoring nighttime agitation and incontinence in patients with Alzheimer's disease. In: Proceedings of the conference on Wireless Health, pp. 1–8 (2015)

    Google Scholar 

  41. Radziszewski, R., Ngankam, H.K., Grégoire, V., Lorrain, D., Pigot, H., Giroux, S.: Designing calm and non-intrusive ambient assisted living system for monitoring nighttime wanderings. Int. J. Pervasive Comput. Commun. (2017)

    Google Scholar 

  42. Amato, F., et al.: CLONE: a promising system for the remote monitoring of Alzheimer's patients: an experimentation with a wearable device in a village for Alzheimer's care. In: Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good, pp. 255–260 (2018)

    Google Scholar 

  43. Koldrack, P., Henkel, R., Krüger, F., Teipel, S., Kirste, T.: Supporting situation awareness of dementia patients in outdoor environments. In: 2015 9th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), pp. 245–248. IEEE (2015)

    Google Scholar 

  44. Koldrack, P., Henkel, R., Krüger, F., Teipel, S., Kirste, T.: Supporting situation awareness of dementia patients in outdoor environments. In: presented at the Proceedings of the 9th International Conference on Pervasive Computing Technologies for Healthcare, Istanbul, Turkey (2015)

    Google Scholar 

  45. Khan, S.S., et al.: Daad: a framework for detecting agitation and aggression in people living with dementia using a novel multi-modal sensor network. In: 2017 IEEE International Conference on Data Mining Workshops (ICDMW), pp. 703–710. IEEE (2017)

    Google Scholar 

  46. Donaldson, M.: An assistive interface for people with dementia. In: Proceedings of the Australasian Computer Science Week Multiconference, pp. 1–5 (2018)

    Google Scholar 

  47. Kowalska, J., Mazurek, J., Rymaszewska, J.: Analysis of the degree of acceptance of illness among older adults living in a nursing home undergoing rehabilitation–an observational study. Clin. Interv. Aging 14, 925 (2019)

    Article  Google Scholar 

  48. Clare, L., Quinn, C., Jones, I.R., Woods, R.T.: “I Don’t Think Of It As An Illness”: Illness representations in mild to moderate dementia. J. Alzheimers Dis. 51(1), 139–150 (2016)

    Article  Google Scholar 

  49. Grober, E., Wakefield, D., Ehrlich, A.R., Mabie, P., Lipton, R.B.: Identifying memory impairment and early dementia in primary care. Alzheimer’s Dementia: Diagnosis Assessment Disease Monitoring 6, 188–195 (2017)

    Article  Google Scholar 

  50. McGarrigle, L., Howlett, S.E., Wong, H., Stanley, J., Rockwood, K.: Characterizing the symptom of misplacing objects in people with dementia: findings from an online tracking tool. Int. Psychogeriatr. 31(11), 1635–1641 (2019)

    Article  Google Scholar 

  51. Bieber, A., Nguyen, N., Meyer, G., Stephan, A.: Influences on the access to and use of formal community care by people with dementia and their informal caregivers: a scoping review. BMC Health Serv. Res. 19(1), 88 (2019)

    Article  Google Scholar 

  52. Lord, K., Livingston, G., Robertson, S., Cooper, C.: How people with dementia and their families decide about moving to a care home and support their needs: development of a decision aid, a qualitative study. BMC Geriatr. 16(1), 68 (2016)

    Article  Google Scholar 

  53. Pierse, T., O’Shea, E., Carney, P.: Estimates of the prevalence, incidence and severity of dementia in Ireland. Irish J. Psychol. Med. 36(2), 129–137 (2019)

    Article  Google Scholar 

  54. Reed, C., et al.: Factors associated with long-term impact on informal caregivers during Alzheimer’s disease dementia progression: 36-month results from GERAS. Int. Psychogeriatrics, 1–11 (2019)

    Google Scholar 

  55. Romero-Martínez, Á., Hidalgo-Moreno, G., Moya-Albiol, L.: Neuropsychological consequences of chronic stress: the case of informal caregivers. Aging Ment. Health 24(2), 259–271 (2020)

    Article  Google Scholar 

  56. Cheng, K.K., Lam, T.H., Leung, C.C., Wearing face masks in the community during the COVID-19 pandemic: altruism and solidarity. The Lancet (2020)

    Google Scholar 

  57. Cheng, V.C.-C., et al.: The role of community-wide wearing of face mask for control of coronavirus disease 2019 (COVID-19) epidemic due to SARS-CoV-2. J. Infect. 81(1), 107–114 (2020)

    Article  Google Scholar 

  58. Empatica: E4 Wristband. Empatica. https://www.empatica.com/en-gb/research/e4. Accessed 30 Jan 2020

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Authors and Affiliations

  1. Liverpool John Moores University, Liverpool, L3 3AF, UK

    Matthew Harper, Fawaz Ghali, Abir Hussain & Dhiya Al-Jumeily

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  1. Matthew Harper
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  2. Fawaz Ghali
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  3. Abir Hussain
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  4. Dhiya Al-Jumeily
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Correspondence to Matthew Harper .

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Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  3. Shenzhen University, Shenzhen, China

    Jianqiang Li

  4. Far Eastern Branch of the Russian Academy of Sciences, Vladivostok, Russia

    Valeriya Gribova

  5. University of Wollongong, North Wollongong, NSW, Australia

    Prashan Premaratne

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Harper, M., Ghali, F., Hussain, A., Al-Jumeily, D. (2021). Review of Methods for Data Collection Experiments with People with Dementia and the Impact of COVID-19. In: Huang, DS., Jo, KH., Li, J., Gribova, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2021. Lecture Notes in Computer Science(), vol 12838. Springer, Cham. https://doi.org/10.1007/978-3-030-84532-2_13

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  • DOI: https://doi.org/10.1007/978-3-030-84532-2_13

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