Assistive technology to monitor activity, health and wellbeing in old age: The wrist wearable unit in the USEFIL project

Technology and Disability

Volumn 27, Issue 1-2, 2015, Pages 17-29

  Ahanathapillai, V ^a   Amor, J D ^b   James, C J ^b  

^a UNIVERSITY OF WARWICK   (United Kingdom)

^b UNIVERSITY OF WARWICK   (United Kingdom)

Author keywords

activity monitoring; Assistive technology; old age; unobtrusive monitoring; wrist wearable device

Indexed keywords

ACCELEROMETER; ADULT; AMBULATORY MONITORING; ARTICLE; ASSISTIVE TECHNOLOGY; BREATHING RATE; CAMERA; COMPUTER SYSTEM; CONTROLLED STUDY; DAILY LIFE ACTIVITY; DECISION SUPPORT SYSTEM; ELECTRONIC MEDICAL RECORD; ENERGY EXPENDITURE; FEMALE; HEART RATE; HOME MONITORING; HUMAN; HUMAN EXPERIMENT; MALE; NORMAL HUMAN; PATIENT MONITOR; SENESCENCE; TELEVISION; WEB BROWSER; WELLBEING; WRIST WEARABLE UNIT;

EID: 84932112620     PISSN: 10554181     EISSN: 1878643X     Source Type: Journal    
DOI: 10.3233/TAD-150425     Document Type: Article

References (40)

1. World Health Organization. Health Topics Ageing [information page on the Internet]. 2014 [cited 2014 Dec 17] Available from: http://tinyurl.com/43qlkr9.
2. Humphereys G. The Health-Care Challenges Posed by Population Ageing. Bull World Health Organ. 2012; 90(2).
3. Wiles JL, Leibing A, Guberman M, Reeve J, Allen RES. The Meaning of "Ageing in Place" to Older People. Gerontologist. 2012; 52(3):357-366.
4. Grguric A. ICT towards elderly independent living. Research and Development Centre, Ericsson Nikola Tesla. 2012. [cited 2014 Dec 17]. Available from: http://tinyurl.com/qxu2vb2.s
5. Prince SA, Adamo KB, Hamel ME, Hardt J, Gorber SC, Tremblay M. A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review. Int J Behav Nutr Phys Act. 2008; 5. doi:10.1186/1479-5868-5-56.
6. World Health Organization. Physical Activity and Older Adults: Recommended levels of physical activity for adults aged 65 and above [information page on the Internet]. 2014 [cited 2014 Dec 17] Available from: http://tinyurl.com/o4js9d5.
7. Shephard RJ. Limits to the measurement of habitual physical activity by questionnaires. Br J Sports Med. 2003; 37:197-206 doi:10.1136/bjsm.37.3.197.
8. Berlin JE, Storti KL, Brach JS. Using Activity Monitors to Measure Physical Activity in Free-Living Conditions. J Am Phys Ther Assoc. 2006; 86:1137-1145.
9. st International Conference on. (2):820-825.
10. Godfrey A, Bourke AK, Olaighin GM, Van de Ven P, Nelson J. Activity classification using a single chest mounted tri-axial accelerometer. Med Eng Phys. 2011; 33:1127-1135.
11. Song W, Ade C, Broxterman R, Nelson T, Warren S. Activity recognition in planetary navigation field tests using classification algorithms applied to accelerometer data. In: Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE. 2012; 1586-1589. doi: 10.1109/EMBC.2012.6346247.
12. Oshima Y, Kawaguchi K, Tanaka S, Ohkawara K, Hikihara Y, Ishikawa-Takata K, et al. Classifying household and locomotive activities using triaxial acceleration. Gait Posture. 2010; 31:370-374.
13. Xu M, Iyengar S, Goldfain A, Roy Chowdhury A, DelloStritto J. A two-stage real time activity monitoring system. In: Body Sensor Networks (BSN), 2011 International Conference on. 2011; 191-193. doi 10.1109/BSN.2011.31.
14. Mathie MJ, Coster ACF, Lovell NH, Celler BG. Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement. Physiol Meas. 2004; 25(2):R1-20.
15. Cleland I, Kikhia B, Nugent C, Boytsov A, Hallberg J, Synnes K, et al. Optimal placement of accelerometers for the detection of everyday activities. Sensors. 2013; 13:9183-9200.
16. Banos O, Damas M, Pomares H, Prieto A, Rojas I. Daily living activity recognition based on statistical feature quality group selection. Expert Syst Appl. 2012; 39:8013-8021.
17. Chien C, Pottie GJ. A universal hybrid decision tree classifier design for human activity classification. In: Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE. 2012; 1065-1068. doi 10.1109/EMBC.2012.6346118.
18. Murphy SL. Review of physical activity measurement using accelerometers in older adults: considerations for research design and conduct. Prev Med. 2009; 48:108-114.
19. Najafi B, Aminian K, Loew F, Blanc Y, Robert PA. Measurement of Stand-Sit and Sit-Stand Transitions using a miniature Gyroscope and its application in fall risk evaluation in the elderly. IEEE Trans Biomed Eng. 2002; 49(8):843-851.
20. Benzo R. Activity monitoring in chronic obstructive pulmonary disease. J Cardiopulm Rehabil Prev. 200; 29(6):341-347.
21. Haeuber E, Shaughnessy M, Forrester LW, Coleman KL, Macko RF. Accelerometer monitoring of home- and community-based ambulatory activity after stroke. Arch Phys Med Rehabil. 2004; 85(12):1997-2001.
22. Kop WJ, Lyden A, Berlin AA, Ambrose K, Olsen C, Gracely RH, Williams DA, Clauw DJ. Ambulatory monitoring of physical activity and symptoms in fibromyalgia and chronic fatigue syndrome. Arthritis Rheumatol. 2005; 52:296-303.
23. Hong Y-J, Kim I-J, Ahn SC, Kim H-G. Mobile health monitoring system based on activity recognition using accelerometer. Simulation Modelling Practice and Theory. 2010; 18(4):446-455.
24. USEFIL Consortium. Welcome to USEFIL [project home page on the Internet]. 2014 [cited 2014 Dec 17]. Available from: http:// www.usefil.eu/.
25. ActiGraph, LLC. Actigraph [product home page on the Internet]. 2014 [cited 2014 Dec 17]. Available from: http://www.actigraphcorp.com/.
26. Fitbit Inc. Fitbit [product home page on the Internet]. 2014 [cited 2014 Dec 17]. Available from: http://www.fitbit.com/uk.
27. Jawbone. Up 24 [product home page on the internet]. 2014 [cited 2014 Dec 17]. Available from: http://jawbone.com/store/buy/up24.
28. Linuxslate.com. Linuxslate.com Independent Review Z1/Rock Android 2.2 GSM Watch Phone [product review on the Internet]. 2012 [updated 20 July 2012, cited 2014 Dec 17]. Available from: http://tinyurl.com/ljsyaup.
29. Amor JD, Detecting and monitoring behavioural change through personalised ambient monitoring. University of Southampton, Institute of Sound and Vibrarion Research, Doctoral Thesis. 2011.
30. Easton C, Philip N, Aleksandravicius A, Pawlak J. Muggeridge DJ, Domene PA, et al. Validity of Smartphone Accelerometers for Assessing Energy Expenditure during Fast Running. In: XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013 IFMBE Proceedings. 2014; 41:1911-1914.
31. Amor JD, Ahanathapillai V, James C. Detecting and analysing activity levels for the wrist wearable unit in the USEFIL project. In: XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013 IFMBE Proceedings. 2014; 41:1201-1204.
32. Hatano Y. Use of the pedometer for promoting daily walking exercise. Intern Council for Health, Phys Educ, and Recreation. 1993; 29:4-8.
33. Bravata DM, Smith-Spangler C, Sundaram V, Gienger AL, Lin N, Lewis R, et al. Using Pedometers to Increase Physical Activity and Improve Health: A Systematic Review. JAMA. 2007; 298:2296-2304.
34. Leidy NK, Kimel M, Ajagbe L, Kim K, Hamilton A, Becker K. Designing trials of behavioral interventions to increase physical activity in patients with copd: insights from the chronic disease literature. Respir Med. 2013; 108(3):472-481.
35. Rustand A. Ambient-light photoplethysmography. Institutt for elektronikk og telekommunikasjon. Master's Thesis. 2012.
36. Noury N, Berenguer M, Teyssier H, Bouzid M-J, Giordani M. Building an Index of Human Activity from the activity on the Residential Electrical Power Line. IEEE Trans Inf Technol Biomed. 2011; 15(5):758-66.
37. Ahanathapillai V, Amor JD, Tadeusiak M, James CJ. Wristworn accelerometer to detect postural transitions and walking patterns. In: XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013 IFMBE Proceedings. 2014; 41:1515-1518.
38. Bourke AK, O'Brien JV, Lyons GM. Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm. Gait Posture. 2007; 26:194-199.
39. Parkka J. Ermes M, Korpipaa P, Mantyjarvi J, Peltola J, Korhonen I. Activity classification using realistic data from wearable sensors. IEEE Trans Inf Technol Biomed. 2006; 10(1):119,128.
40. LG Electronics. G Watch R [product home page on the internet]. 2014 [cited 2014 Dec 19]. Available from: http://tinyurl.com/nwh9sh8.