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Ethical Surveillance: Applying Deep Learning and Contextual Awareness for the Benefit of Persons Living with Dementia

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Artificial Intelligence in Health (AIH 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11326))

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Abstract

A significant proportion of the population has become used to sharing private information on the internet with their friends. This information can leak throughout their social network and the extent that personal information propagates can depend on the privacy policy of large corporations. In an era of artificial intelligence, data mining, and cloud computing, is it necessary to share personal information with unidentified people? Our research shows that deep learning is possible using relatively low capacity computing. When applied, this demonstrates promising results in spatio-temporal positioning of subjects, in prediction of movement, and assessment of contextual risk. A private surveillance system is particularly suitable in the care of those who may be considered vulnerable.

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Notes

  1. 1.

    Note that Google Timeline is only used for data gathering in this initial feasibility study. The full solution uses GPS data stored only locally on the mobile device and processed on the home hub.

References

  1. Williams, S., Müller, B.: Agents and dementia—smart risk assessment. In: Criado Pacheco, N., Carrascosa, C., Osman, N., Julián Inglada, V. (eds.) EUMAS/AT-2016. LNCS (LNAI), vol. 10207, pp. 277–284. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59294-7_22

    Chapter  Google Scholar 

  2. Williams, S., Ware, J.M.: Is the use of ‘mobile computer technology’ appropriate for locating people with dementia? In: 2015 Proceedings of GIS Research UK (GISRUK), pp. 659–664. Figshare, Leeds (2015). https://doi.org/10.6084/m9.figshare.1491375

  3. Read, S., Toye, C., Wynaden, D.: Experiences and expectations of living with dementia: a qualitative study. Collegian 24(5), 427–432 (2017). https://doi.org/10.1016/j.colegn.2016.09.003

    Article  Google Scholar 

  4. Silverstein, N.F.: Dementia and Wandering Behavior: Concern for the Lost Elder. Springer, New York (2006). ISBN 0-8261-0272-7

    Google Scholar 

  5. McShane, R., et al.: Getting lost in dementia: a longitudinal study of a behavioral symptom. Int. Psychogeriatr. 10(03), 253–260 (1998). http://www.ncbi.nlm.nih.gov/pubmed/9785146

    Article  Google Scholar 

  6. Ali, N., et al.: Risk assessment of wandering behavior in mild dementia. Int. J. Geriatr. Psychiatry 31, 367–374 (2016). https://doi.org/10.1002/gps.4336

    Article  Google Scholar 

  7. Martyr, A., et al.: Living well with dementia: a systematic review. Alzheimer’s Dement. J. Alzheimer’s Assoc. 13(7), 1567–1568 (2017). https://doi.org/10.1016/j.jalz.2017.07.725

    Article  Google Scholar 

  8. Cipriani, G., Lucetti, C., Nuti, A., Danti, S.: Wandering and dementia. Psychogeriatrics 14, 135–142 (2014). https://doi.org/10.1111/psyg.12044

    Article  Google Scholar 

  9. Riikonen, M., Mäkelä, K., Perälä, S.: Safety and monitoring technologies for the homes of people with dementia. Gerontechnology 9(1), 32–45 (2010). https://doi.org/10.4017/gt.2010.09.01.003.00

    Article  Google Scholar 

  10. Mathews, L.: Data From 540,000 GPS Vehicle Trackers Leaked Online forbes.com (2017). https://www.forbes.com/sites/leemathews/2017/09/22/data-from-540000-vehicle-tracking-devices-leaked-online/#40b9c009274b. Accessed 19 Sept 2018

  11. Trackmageddon website: Multiple vulnerabilities in the online services of (GPS) location tracking devices (2018). https://0x0.li/trackmageddon/. 18 Aug 2018

  12. World Health Organisation: Ensuring a human rights-based approach for people living with dementia (2015). The need for a human-rights based approach: http://www.who.int/mental_health/neurology/dementia/dementia_thematicbrief_human_rights.pdf. Accessed Mar 2018

  13. LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521, 436–444 (2015). https://doi.org/10.1038/nature14539

    Article  Google Scholar 

  14. Schmidhuber, J.: Deep learning in neural networks: an overview. Neural Networks 61, 85–117 (2014). https://doi.org/10.1016/j.neunet.2014.09.003

    Article  Google Scholar 

  15. Brownlee, J.: How to Implement the Backpropagation Algorithm From Scratch in Python (2016). Machine Learning Mastery: https://machinelearningmastery.com/implement-backpropagation-algorithm-scratch-python/. Accessed Mar 2018

  16. Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735–1780 (1997). https://doi.org/10.1162/neco.1997.9.8.1735

    Article  Google Scholar 

  17. Kwapisz, J.R., Weiss, G.M., Moore, S.A.: Activity recognition using cell phone accelerometers. ACM SIGKDD Explor. Newsl. 12(2), 74–82 (2010). https://doi.org/10.1145/1964897.1964918

    Article  Google Scholar 

  18. Ramamurthy, S.R., Roy, N.: Recent trends in machine learning for human activity recognition—a survey. Data Min. Knowl. Discov. 8, 1–19 (2018). https://doi.org/10.1002/widm.1254

    Article  Google Scholar 

  19. Arifoglu, D., Bouchachia, A.: Activity recognition and abnormal behaviour detection with recurrent neural networks. In: 14th International Conference on Mobile Systems and Pervasive Computing (MobiSPC 2017) (2017). Procedia Comput. Sci. 110, 86–93. https://doi.org/10.1016/j.procs.2017.06.121

    Article  Google Scholar 

  20. Batista, E., Borras, F., Casino, F., Solanas, A.: A study on the detection of wandering patterns in human trajectories. In: 6th International Conference on Information, Intelligence, Systems and Applications (IISA), pp. 1–6. IEEE, Corfu (2015)

    Google Scholar 

  21. Maneewongvatana, S., Mount, D.M.: Analysis of approximate nearest neighbor searching with clustered point sets. CoRR arXiv:cs/9901013v1 (1999)

  22. SciPy.Org: Interpolation (scipy.interpolate). https://docs.scipy.org/doc/scipy/reference/interpolate.html. Accessed 17 Mar 2018

  23. Google: Encoded Polyline Algorithm Format. Google Maps Api: https://developers.google.com/maps/documentation/utilities/polylinealgorithm?csw=1. Accessed 17 Mar 2018

  24. Zheng, Y., et al.: Geolife GPS trajectories 1.1. In: Geolife GPS Trajectory Dataset - User Guide. Microsoft Research (2011). https://www.microsoft.com/en-us/research/publication/Geolife-gps-trajectory-dataset-user-guide. Accessed 18 Sept 2018

  25. González, M.C., Hidalgo, C.A., Barabási, A.: Understanding individual human mobility patterns. Nature 453, 779–782 (2008). https://doi.org/10.1038/nature06958

    Article  Google Scholar 

  26. Google Maps Platform: Snap to Roads. Roads API: https://developers.google.com/maps/documentation/roads/snap. Accessed 18 Sept 2018

  27. Fabrice Marchal: TrackMatching API. TrackMatching Website: https://mapmatching.3scale.net/mmswag. Accessed 18 Sept 2018

  28. Google Directions API: Google Directions API. Google Maps: https://developers.google.com/maps/documentation/directions/start. Accessed 18 Sept 2018

  29. Lambertus: YOURS Routing_API. Yet another OpenStreetMap Route Service: https://wiki.openstreetmap.org/wiki/YOURS#Routing_API. Accessed 18 Sept 2018

  30. Laure, P.-D., Yammine, P., Bastuji, H., Croisilef, B.: Sleep and Alzheimer’s disease. Sleep Med. Rev. 19, 29–38 (2015)

    Article  Google Scholar 

  31. Hope, T., et al.: Predictors of institutionalization for people with dementia living at home with a carer. Int. J. Geriatr. Psychiatry 13(10), 682–690 (1998)

    Article  Google Scholar 

  32. McCurry, S., Logsdon, R., Teri, L., Vitiello, M.: Sleep disturbances in caregivers of persons with dementia: contributing factors and treatment implications. Sleep Med. Rev. 11(2), 143–153 (2007)

    Article  Google Scholar 

  33. Brodaty, H.D.: Family caregivers of people with dementia. Dialogues Clin. Neurosci. 11(2), 217–228 (2009). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3181916/. Accessed 17 Apr 2018

    Google Scholar 

  34. Keill, A.K., et al.: Validity of wearable fitness trackers on sleep measure. Med. Sci. Sports Exerc. 48(5S), 10 (2016)

    Article  Google Scholar 

  35. scikit-learn developers: sklearn.cluster.AgglomerativeClustering. http://scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html. Accessed 18 Sept 2018

  36. sklearn.cluster developers: sklearn.cluster.KMeans. scikit-learn: http://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html. Accessed 18 Sept 2018

  37. Dark Sky Website: Dark Sky Weather API. https://darksky.net/dev. Accessed 18 Sept 2018

  38. Gibson, G., et al.: The everyday use of assistive technology by people with dementia and their family carers: a qualitative study. BMC Geriatr. 15, 89 (2015). https://doi.org/10.1186/s12877-015-0091-3

    Article  Google Scholar 

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Acknowledgements

Knowledge Economy Skills Scholarships (KESS) is a pan-Wales higher level skills initiative led by Bangor University on behalf of the HE sectors in Wales. It is part funded by the Welsh Government’s European Social Fund (ESF) convergence programme for West Wales and the Valleys and is supported by the industrial partner SymlConnect Limited.

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Authors and Affiliations

  1. Faculty of Computing, Engineering and Science, University of South Wales, Pontypridd, UK

    Steve Williams & J. Mark Ware

  2. Department of Computer Science, Swansea University, Swansea, UK

    Berndt Müller

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  1. Steve Williams
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  2. J. Mark Ware
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  3. Berndt Müller
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Corresponding author

Correspondence to Berndt Müller .

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Editors and Affiliations

  1. University of Melbourne, Melbourne, VIC, Australia

    Fernando Koch

  2. IIIA-CSIC and Autonomous University of Barcelona, Barcelona, Spain

    Andrew Koster

  3. Universitat Rovira i Virgili, Tarragona, Spain

    David Riaño

  4. Università di Bologna, Cesena, Italy

    Sara Montagna

  5. HES-SO Valais Wallis, Sierre, Switzerland

    Michael Schumacher

  6. VU University Amsterdam, Amsterdam, The Netherlands

    Annette ten Teije

  7. Karolinska Institute, Stockholm, Sweden

    Christian Guttmann

  8. University of Ulm, Ulm, Germany

    Manfred Reichert

  9. State University of New York, Oswego, NY, USA

    Isabelle Bichindaritz

  10. Imperial College London, London, UK

    Pau Herrero

  11. University of Erlangen and Nuremberg, Erlangen, Germany

    Richard Lenz

  12. University of Girona, Girona, Spain

    Beatriz López

  13. Ohio University, Athens, OH, USA

    Cindy Marling

  14. Oxford Brookes University, Oxford, UK

    Clare Martin

  15. Università del Piemonte Orientale, Alessandria, Italy

    Stefania Montani

  16. School of Computing Science and Digital Media, Robert Gordon University, Aberdeen, UK

    Nirmalie Wiratunga

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Williams, S., Ware, J.M., Müller, B. (2019). Ethical Surveillance: Applying Deep Learning and Contextual Awareness for the Benefit of Persons Living with Dementia. In: Koch, F., et al. Artificial Intelligence in Health. AIH 2018. Lecture Notes in Computer Science(), vol 11326. Springer, Cham. https://doi.org/10.1007/978-3-030-12738-1_3

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  • DOI: https://doi.org/10.1007/978-3-030-12738-1_3

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