Monitoring meaningful activities using small low-cost devices in a smart home

Abstract

A challenge associated with an ageing population is increased demand on health and social care, creating a greater need to enable persons to live independently in their own homes. Ambient assistant living technology aims to address this by monitoring occupants’ ‘activities of daily living’ using smart home sensors to alert caregivers to abnormalities in routine tasks and deteriorations in a person’s ability to care for themselves. However, there has been less focus on using sensing technology to monitor a broader scope of so-called ‘meaningful activities’, which promote a person’s emotional, creative, intellectual, and spiritual needs. In this paper, we describe the development of a toolkit comprised of off-the-shelf, affordable sensors to allow persons with dementia and Parkinson’s disease to monitor meaningful activities as well as activities of daily living in order to self-manage their life and well-being. We describe two evaluations of the toolkit, firstly a lab-based study to test the installation of the system including the acuity and placement of sensors and secondly, an in-the-wild study where subjects who were not target users of the toolkit, but who identified as technology enthusiasts evaluated the feasibility of the toolkit to monitor activities in and around real homes. Subjects from the in-the-wild study reported minimal obstructions to installation and were able to carry out and enjoy activities without obstruction from the sensors, revealing that meaningful activities may be monitored remotely using affordable, passive sensors. We propose that our toolkit may enhance assistive living systems by monitoring a wider range of activities than activities of daily living.

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References

  1. 1.

    Chan M, Estève D, Escriba C, Campo E (2008) A review of smart homes—present state and future challenges. Comput Methods Prog Biomed 91:55–81

    Article  Google Scholar 

  2. 2.

    Wallace M, Shelkey M (2007) Katz index of independence in activities of daily living Urol Nurs 93–94

  3. 3.

    National Institute for Health and Care Excellence (2013) Mental wellbeing of older people in care homes. Quality standard [QS50], p 17. Available from: https://www.nice.org.uk/guidance/qs50. Accessed 12 Jan 2018

  4. 4.

    Roach P, Drummond N (2014) ‘It’s nice to have something to do’: early-onset dementia and maintaining purposeful activity. J Psychiatr Ment Health Nurs 21:889–895

    Article  Google Scholar 

  5. 5.

    Palacios-Ceña D, Gómez-Calero C, Cachón-Pérez JM, Velarde-García JF, Martínez-Piedrola R, Pérez-De-Heredia M (2016) Is the experience of meaningful activities understood in nursing homes? A qualitative study. Geriatr Nurs 37:110–115

    Article  Google Scholar 

  6. 6.

    Lawton MP, Brody EM (1969) Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist 9:179–186

    Article  Google Scholar 

  7. 7.

    Han A, Radel J, McDowd JM, Sabat D (2016) Perspectives of people with dementia about meaningful activities: a synthesis. Am J Alzheimers Dis Other Dement 31:115–123

    Article  Google Scholar 

  8. 8.

    Harmer BJ, Orrell M (2008) What is meaningful activity for people with dementia living in care homes? A comparison of the views of older people with dementia, staff and family carers. Aging Ment Health 12:548–558

    Article  Google Scholar 

  9. 9.

    Morris ME, Adair B, Miller K, Ozanne E, Hansen R, Pearce AJ, Santamaria N, Viega L, Long M, Said CM (2013) Smart-home technologies to assist older people to live well at home. J Aging Sci 1:1–9

    Google Scholar 

  10. 10.

    Mera TO, Heldman DA, Espay AJ, Payne M, Giuffrida JP (2012) Feasibility of home-based automated Parkinson’s disease motor assessment. J Neurosci Methods 203:152–156

    Article  Google Scholar 

  11. 11.

    Pastorino M, Cancela J, Arredondo MT, Pastor-Sanz L, Contardi S, Valzania F (2013) Preliminary results of ON/OFF detection using an integrated system for Parkinson’s disease monitoring. In: Engineering in Medicine and Biology Society (EMBC), 35th Annual International Conference of the IEEE pp 941–944

  12. 12.

    Horak F, King L, Mancini M (2015) Role of body-worn movement monitor technology for balance and gait rehabilitation. Phys Ther 95:461–470

    Article  Google Scholar 

  13. 13.

    Hiorth YH, Larsen JP, Lode K, Tysnes OB, Godfrey A, Lord S, Rochester L, Pedersen KF (2016) Impact of falls on physical activity in people with Parkinson’s disease. J Park Dis 6:175–182

    Google Scholar 

  14. 14.

    Gayathri KS, Elias S, Ravindran B (2015) Hierarchical activity recognition for dementia care using Markov Logic Network. Pers Ubiquit Comput 19:271–285

    Article  Google Scholar 

  15. 15.

    Nef T, Urwyler P, Büchler M, Tarnanas I, Stucki R, Cazzoli D, Müri R, Mosimann U (2015) Evaluation of three state-of-the-art classifiers for recognition of activities of daily living from smart home ambient data. Sensors 15:11725–11740

    Article  Google Scholar 

  16. 16.

    Bradford D, Zhang Q (2016) How to save a life: could real-time Sensor data have saved Mrs Elle? In: ACM CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp 910–920

  17. 17.

    Zhang Q, Karunanithi M, Bradford D, van Kasteren Y (2014) Activity of daily living assessment through wireless sensor data. In: Engineering in Medicine and Biology Society (EMBC) 36th Annual International Conference of the IEEE, pp 1752–1755

  18. 18.

    Arcelus A, Jones MH, Goubran R, Knoefel F (2007) Integration of smart home technologies in a health monitoring system for the elderly. In: IEE advanced information networking and applications workshops. AINAW'07, pp 820–825

  19. 19.

    Hussain S, Schaffner S, Moseychuck D (2009) Applications of wireless sensor networks and RFID in a smart home environment. In IEEE communication networks and services research conference. CNSR'09, pp 153–157

  20. 20.

    Yamazaki T (2006) Beyond the smart home. In IEEE international conference on hybrid information technology. ICHIT'06, pp 350–355

  21. 21.

    Martin PD, Rushanan M, Tantillo T, Lehmann CU, Rubin AD (2016). Applications of secure location sensing in healthcare. In ACM-BCB 7th ACM conference on bioinformatics, computational biology, and health informatics, pp 58–67

  22. 22.

    Tsai, HY, Chen, GH, Lee HC (2017) Using low-cost, non-sensor-equipped BLE beacons to track people’s movements. In: ACM/IEEE International Conference on Information Processing in Sensor Networks, pp 291–292

  23. 23.

    Estimote (n.d.) Estimote. Available from: https://estimote.com. Accessed 11th Jan 2018

  24. 24.

    Sense (n.d.) Sense. Available from: https://sen.se/store/cookie. Accessed 11th Jan 2018

  25. 25.

    Civitarese G, Belfiore S, Bettini C (2016) Let the objects tell what you are doing. In: ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp 773–782

  26. 26.

    Hossain HS, Khan MAAH, Roy N (2017) Active learning enabled activity recognition. Pervasive Mob Comput 38:312–320

    Article  Google Scholar 

  27. 27.

    Rafferty J, Nugent CD, Liu J, Chen L (2017) From activity recognition to intention recognition for assisted living within smart homes. IEEE Trans Hum-Mach Syst 47:368–379

    Article  Google Scholar 

  28. 28.

    openHAB (n.d.) openHAB. Available from: https://www.openhab.org. Accessed 11th Jan 2018

  29. 29.

    Home Assistant (n.d.) Home Assistant. Available from: https://home-assistant.io. Accessed 11th Jan 2018

  30. 30.

    Cook DJ, Crandall AS, Thomas BL, Krishnan NC (2013) CASAS: a smart home in a box. Computer 46:62–69

    Article  Google Scholar 

  31. 31.

    Samsung (n.d.) Samsung. Available from: http://www.samsung.com/uk/smartthings. Accessed 11th Jan 2018

  32. 32.

    Xiaomi (n.d.) Xiaomi. Available from: https://xiaomi-mi.com/. Accessed 11th Jan 2018

  33. 33.

    Panasonic (n.d.) Panasonic. Available from: https://www.panasonic.com/uk/consumer/smart-home.html. Accessed 11th Jan 2018

  34. 34.

    Xiaomi Mi Smart Home Occupancy Sensor. Available from: https://item.mi.com/1164900028.html. Accessed 8th Feb 2019

  35. 35.

    Xiaomi Mi Smart Home Door / Window Sensor. Available from: https://item.mi.com/1164900032.html. Accessed 8th Feb 2019

  36. 36.

    Xiaomi Mi Smart Home Temperature/Humidity Sensor. Available from: https://item.mi.com/1164900031.html. Accessed 8th Feb 2019

  37. 37.

    Xiaomi Mi Smart Home Wireless Switch. Available from: https://item.mi.com/1164900029.html. Accessed 8th Feb 2019

  38. 38.

    Z-Wave TKB TZ69E Wall Plug Switch/Meter—GEN5—UK power sensor. Available from: http://www.tkbhome.com/Z-Wave-Smart-Energy-Plug-in-with-meter-function_012_123.html. Accessed 8th Feb 2019

  39. 39.

    Arun Electronics Pressure Mat PM3 and Fibaro FGK-10x Door/Window Sensor. Available from: http://www.arun-electronics.co.uk/pressure_mat.htm. Accessed 8th Feb 2019

  40. 40.

    AnkhMaway AKMW-iB001M sensor beacon. Available from: https://www.beaconzone.co.uk/ib001m. Accessed 11th Jan 2018

  41. 41.

    Raspberry Pi (n.d.) Raspberry Pi. Available from: https://www.raspberrypi.org/downloads/raspbian. Accessed 11th Jan 2018

  42. 42.

    Room Assistant (n.d.) Room Assistant. Available from: https://github.com/mKeRix/room-assistant. Accessed 11th Jan 2018

  43. 43.

    InfluxData (n.d.) InfluxData. Available from: https://www.influxdata.com. Accessed 11th Jan 2018

  44. 44.

    NHS (n.d.) Physical activity guidelines for older adults. Available from: http://www.nhs.uk/Livewell/fitness/Pages/physical-activity-guidelines-for-older-adults.aspx. Accessed 11th Jan 2018

  45. 45.

    Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13:319–340

    Article  Google Scholar 

  46. 46.

    W3C WAI Site Usability Testing Questions. Available from: https://www.w3.org/WAI/EO/Drafts/UCD/questions.html. Accessed 8th Feb 2019

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Funding

Funding for this project was provided by the UK Engineering and Physical Sciences Research Council.

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Correspondence to Dympna O’Sullivan.

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Tewell, J., O’Sullivan, D., Maiden, N. et al. Monitoring meaningful activities using small low-cost devices in a smart home. Pers Ubiquit Comput 23, 339–357 (2019). https://doi.org/10.1007/s00779-019-01223-2

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Keywords

  • Internet of Things
  • Smart homes
  • Passive sensors
  • Passive health monitoring
  • Meaningful activities