nach oben

Erschienen in:

2015 | OriginalPaper | Buchkapitel

Towards Pervasive Mobility Assessments in Clinical and Domestic Environments

verfasst von : Melvin Isken, Thomas Frenken, Melina Frenken, Andreas Hein

Erschienen in: Smart Health

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

This paper provides an overview of current research and open problems in sensor-based mobility analysis. It is focused on geriatric assessment tests and the idea to provide easier and more objective results by using sensor technologies. A lot of research has been done in the field of measuring personal movement/mobility by technical approaches but there are few developments to measure a complete geriatric assessment test. Such automated tests can very likely offer more accurate, reliable and objective results than currently used methods. Additionally, those tests may reduce costs in public health systems as well as set standards for comparability of the tests. New sensor technologies and initiatives for data standardization in health processes offer increased possibilities in system development. This paper will highlight some open problems that still exist to bring automated mobility assessment tests into pervasive clinical and domestic use.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Spatial Health Systems

Nächstes Kapitel Personalized Physical Activity Monitoring Using Wearable Sensors

Abellanas, A., Calderón Estévez, L., Ceres Ruíz, R., Frizera Neto, A., Raya, R.: Ultrasonic time of flight estimation in assistive mobility: improvement of the model-echo fitting. In: Proceedings of Eurosensors XXII, pp. 464–467. VDI/VDE, Elsevier (2008)

Alwan, M., Ledoux, A., Wasson, G., Sheth, P., Huang, C.: Basic walker-assisted gait characteristics derived from forces and moments exerted on the walker’s handles: results on normal subjects. Med. Eng. Phys. 29(3), 380–389 (2007)CrossRef

Alzheimer’s Disease International. World Alzheimer Report 2009 (2009)

Aminian, K., Rezakhanlou, K., De Andres, E., Fritsch, C., Leyvraz, P., Robert, P.: Temporal feature estimation during walking using miniature accelerometers: an analysis of gait improvement after hip arthroplasty. Med. Biol. Eng. Comput. 37, 686–691 (1999)CrossRef

Auvinet, B., Berrut, G., Touzard, C., Moutel, L., Collet, N., Chaleil, D., Barrey, E.: Reference data for normal subjects obtained with an accelerometric device. Gait Posture 16(2), 124–134 (2002)CrossRef

Bachmann, C., Gerber, H., Stacoff, A.: Messsysteme, Messmethoden und Beispiele zur instrumentierten Ganganalyse. Schweizerische Zeitschrift für Sportmedizin und Sporttraumatologie 56(2), 29–34 (2008)

Bamberg, S., Benbasat, A.Y., Scarborough, D.M., Krebs, D.E., Paradiso, J.A.: Gait analysis using a shoe-integrated wireless sensor system. IEEE Trans. Inf. Technol. Biomed. 12(4), 413–423 (2008)CrossRef

Beauchet, O., Allali, G., Berrut, G., Hommet, C., Dubost, V., Assal, F.: Gait analysis in demented subjects: interests and perspectives. Neuropsychiatr. Dis. Treat. 4(1), 155–160 (2008)CrossRef

Beer, J.M., Prakash, A., Mitzner, T.L., Rogers, W.A.: Understanding robot acceptance. Georgia Institute of Technology (2011)

10.

Berg, K.: Measuring balance in the elderly: preliminary development of an instrument. Physiother. Can. 41(6), 304–311 (1989)CrossRef

11.

Bergmann, J.H.M., McGregor, A.H.: Body-worn sensor design: what do patients and clinicians want? Ann. Biomed. Eng. 39(9), 2299–2312 (2011)CrossRef

12.

Boonstra, M.C., van der Slikke, R.M.A., Keijsers, N.L.W., van Lummel, R.C., de Waal Malefijt, M.C., Verdonschot, N.: The accuracy of measuring the kinematics of rising from a chair with accelerometers and gyroscopes. J. Biomech. 39(2), 354–358 (2006)CrossRef

13.

Bussmann, J., Damen, L., Stam, H.: Analysis and decomposition of signals obtained by thigh-fixed uni-axial accelerometry during normal walking. Med. Biol. Eng. Comput. 38, 632–638 (2000)CrossRef

14.

Butler, A.A., Menant, J.C., Tiedemann, A.C., Lord, S.R.: Age and gender differences in seven tests of functional mobility. J. Neuroeng. Rehabil. 6, 31 (2009)CrossRef

15.

Cameron, K., Hughes, K., Doughty, K.: Reducing fall incidence in community elders by telecare using predictive systems. In: Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 30 October–2 November 1997, vol. 3, pp. 1036–1039 (1997)

16.

Cao, E., Inoue, Y., Liu, T., Shibata, K.: A sit-to-stand trainer system in lower limb rehabilitation. In: Proceedings of the IEEE/ASME International Advanced Intelligent Mechatronics (AIM) Conference, pp. 116–121 (2011)

17.

Celler, B.G., Hesketh, T., Earnshaw, W., Ilsar, E.: An instrumentation system for the remote monitoring of changes in functional health status of the elderly at home. In: Proceedings of the 16th Annual International Conference of the IEEE Engineering Advances: New Opportunities for Biomedical Engineers Engineering in Medicine and Biology Society, pp. 908–909 (1994)

18.

Chan, M., Hariton, C., Ringeard, P., Campo, E.: Smart house automation system for the elderly and the disabled. In: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics Intelligent Systems for the 21st Century, 22–25 October 1995, vol. 2, pp. 1586–1589 (1995)

19.

Chao, E.Y.: Justification of triaxial goniometer for the measurement of joint rotation. J. Biomech. 13(12), 989–1006 (1980)CrossRef

20.

Chen, C.L., Chen, H.C., Wong, M.K., Tang, F.T., Chen, R.S.: Temporal stride and force analysis of cane-assisted gait in people with hemiplegic stroke. Arch. Phys. Med. Rehabil. 82(1), 43–48 (2001)CrossRef

21.

Chen, M., Huang, B., Xu, Y.: Intelligent shoes for abnormal gait detection. In: Proceedings of the IEEE International Conference on Robotics and Automation ICRA 2008, 19–23 May 2008, pp. 2019–2024 (2008)

22.

Chen, Y.-C., Lin, Y.-W.: Indoor RFID gait monitoring system for fall detection. In: Proceedings of the 2nd International Aware Computing (ISAC) Symposium, pp. 207–212 (2010)

23.

Chiari, L., Dozza, M., Cappello, A., Horak, F.B., Macellari, V., Giansanti, D.: Audio-biofeedback for balance improvement: an accelerometry-based system. IEEE Trans. Biomed. Eng. 52(12), 2108–2111 (2005)CrossRef

24.

Cho, C.Y., Kamen, G.: Detecting balance deficits in frequent fallers using clinical and quantitative evaluation tools. J. Am. Geriatr. Soc. 46(4), 426–430 (1998)

25.

Clark, R.A., Bryant, A.L., Pua, Y., McCrory, P., Bennell, K., Hunt, M.: Validity and reliability of the nintendo wii balance board for assessment of standing balance. Gait Posture 31(3), 307–310 (2010)CrossRef

26.

Currie, G., Rafferty, D., Duncan, G., Bell, F., Evans, A.: Measurement of gait by accelerometer and walkway: a comparison study. Med. Biol. Eng. Comput. 30, 669–670 (1992)CrossRef

27.

Czaja, S.J., Charness, N., Fisk, A.D., Hertzog, C., Nair, S.N., Rogers, W.A., Sharit, J.: Factors predicting the use of technology: findings from the center for research and education on aging and technology enhancement (create). Psychol. Aging 21(2), 333 (2006)CrossRef

28.

de Bruin, E., Najafi, B., Murer, K., Uebelhart, D., Aminian, K.: Quantification of everyday motor function in a geriatric population. J. Rehabil. Res. Dev. 44, 417–428 (2007)CrossRef

29.

DeLisa, J., Scientific, U.S. Veterans Health Administration, Technical Publications Section: Gait analysis in the science of rehabilitation. Monograph (United States. Veterans Health Administration. Rehabilitation Research and Development Service). Department of Veterans Affairs, Veterans Health Administration, Rehabilitation Research and Development Service. Scientific and Technical Publications Section (1998)

30.

Ezer, N., Fisk, A.D., Rogers, W.A.: Attitudinal and intentional acceptance of domestic robots by younger and older adults. In: Stephanidis, C. (ed.) UAHCI 2009, Part II. LNCS, vol. 5615, pp. 39–48. Springer, Heidelberg (2009)

31.

Ezer, N., Fisk, A.D., Rogers, W.A.: More than a servant: self-reported willingness of younger and older adults to having a robot perform interactive and critical tasks in the home. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 53, pp. 136–140. SAGE Publications (2009)

32.

Fortuny-Guasch, J., Sammartino, P.F., Petit, J.: Radar techniques for human gait automatic recognition. In: Proceedings of the 43rd Annual 2009 International Security Technology Carnahan Conference, pp. 221–226 (2009)

33.

Frenken, T.: Technischer Ansatz zur unaufdringlichen Mobilitätsanalyse im Rahmen geriatrischer Assessments. Ph.D. thesis. University of Oldenburg, VDI Verlag, Düsseldorf, January 2013

34.

Frenken, T., Gövercin, M., Mersmann, S., Hein, A.: Precise assessment of self-selected gait velocity in domestic environments. In: Pervasive Computing Technologies for Healthcare (PervasiveHealth) (2010)

35.

Frenken, T., Lipprandt, M., Brell, M., Wegel, S., Gövercin, M., Steinhagen-Thiessen, E., Hein, A.: Novel approach to unsupervised mobility assessment tests: field trial for aTUG. In: Proceedings of the 6th International Pervasive Computing Technologies for Healthcare (PervasiveHealth) Conference (2012)

36.

Frenken, T., Vester, B., Brell, M., Hein, A.: aTUG: fully-automated timed up and go assessment using ambient sensor technologies. In: 2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) (2011)

37.

Fuerstenberg, K.C., Dietmayer, K.: Object tracking and classification for multiple active safety and comfort applications using a multilayer laser scanner. In: Proceedings of IEEE Intelligent Vehicles Symposium, pp. 802–807 (2004)

38.

Gabel, M., Gilad-Bachrach, R., Renshaw, E., Schuster, A.: Full body gait analysis with kinect. In: 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1964–1967. IEEE (2012)

39.

Geisheimer, J.L., Marshall, W.S., Greneker, E.: A continuous-wave (CW) radar for gait analysis. In: Proceedings of the Conference on Signals, Systems and Computers Record of the Thirty-Fifth Asilomar Conference, vol. 1, pp. 834–838 (2001)

40.

Gill, T.M., Williams, C.S., Tinetti, M.E.: Assessing risk for the onset of functional dependence among older adults: the role of physical performance. J. Am. Geriatr. Soc. 43(6), 603–609 (1995)

41.

Goffredo, M., Carter, J.N., Nixon, M.S.: Front-view gait recognition. In: Proceedings of the 2nd IEEE International Conference on Biometrics: Theory, Applications and Systems BTAS 2008, pp. 1–6 (2008)

42.

Greene, B.R., Donovan, A.O., Romero-Ortuno, R., Cogan, L., Ni Scanaill, C., Kenny, R.A.: Quantitative falls risk assessment using the timed up and go test. IEEE Trans. Biomed. Eng. 57(12), 2918–2926 (2010)CrossRef

43.

Hagler, S., Austin, D., Hayes, T.L., Kaye, J., Pavel, M.: Unobtrusive and ubiquitous in-home monitoring: a methodology for continuous assessment of gait velocity in elders. IEEE Trans. Biomed. Eng. 57(4), 813–820 (2010)CrossRef

44.

Hausdorff, J.M., Ladin, Z., Wei, J.Y.: Footswitch system for measurement of the temporal parameters of gait. J. Biomech. 28(3), 347–351 (1995)CrossRef

45.

Health Level Seven International. CDA Release 2. Technical report (2005)

46.

Helmer, A., Lipprandt, M., Frenken, T., Eichelberg, M., Hein, A.: 3DLC: a comprehensive model for personal health records supporting new types of medical applications. J. Healthc. Eng. 2(3), 321–336 (2011)CrossRef

47.

Henriksen, M., Lund, H., Moe-Nilssen, R., Bliddal, H., Danneskiod-Samsøe, B.: Test-retest reliability of trunk accelerometric gait analysis. Gait Posture 19(3), 288–297 (2004)CrossRef

48.

Holzinger, A., Searle, G., Wernbacher, M.: The effect of previous exposure to technology on acceptance and its importance in usability and accessibility engineering. Univ. Access Inf. Soc. 10(3), 245–260 (2011)CrossRef

49.

Hornsteiner, C., Detlefsen, J.: Characterisation of human gait using a continuous-wave radar at 24 GHz. Adv. Radio Sci. 6, 67–70 (2008)CrossRef

50.

Huang, B., Chen, M., Shi, X., Xu, Y.: Gait event detection with intelligent shoes. In: Proceedings of International Conference on Information Acquisition ICIA 2007, 8–11 July 2007, pp. 579–584 (2007)

51.

Huitema, R.B., Hof, A.L., Postema, K.: Ultrasonic motion analysis system-measurement of temporal and spatial gait parameters. J. Biomech. 35(6), 837–842 (2002)CrossRef

52.

Imms, F.J., Edholm, O.G.: Studies of gait and mobility in the elderly. Age Ageing 10(3), 147–156 (1981)CrossRef

53.

Jang, Y., Shin, S., Lee, J.W., Kim, S.: A preliminary study for portable walking distance measurement system using ultrasonic sensors. In: Proceedings of 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS 2007, pp. 5290–5293 (2007)

54.

Kamen, G., Patten, C., Du, C.D., Sison, S.: An accelerometry-based system for the assessment of balance and postural sway. Gerontology 44(1), 40–45 (1998)CrossRef

55.

Kerr, K., White, J., Barr, D., Mollan, R.: Standardization and definitions of the sit-stand-sit movement cycle. Gait Posture 2(3), 182–190 (1994)CrossRef

56.

Kiselev, J., Gövercin, M., Frenken, T., Hein, A., Steinhagen-Thiessen, E., Wegel, S.: A new device for the assessment of gait and mobility with an automated timed up & go (atug): study protocol of an initial validation study. Contemporary Clinical Trials (2012, submitted)

57.

Kiss, R.: Comparison between kinematic and ground reaction force techniques for determining gait events during treadmill walking at different walking speeds. Med. Eng. Phys. 32(6), 662–667 (2010)CrossRef

58.

Knight, H., Lee, J.-K., Ma, H.: Chair Alarm for patient fall prevention based on Gesture Recognition and Interactivity. In: Proceedings of 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS 2008, 20–25 August 2008, pp. 3698–3701 (2008)

59.

Kong, K., Tomizuka, M.: A gait monitoring system based on air pressure sensors embedded in a shoe. IEEE/ASME Trans. Mechatron. 14(3), 358–370 (2009)CrossRef

60.

Lai, D.T.H., Wrigley, T.V., Palaniswami, M.: Ultrasound monitoring of inter-knee distances during gait. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBC 2009, pp. 725–728 (2009)

61.

Leu, A., Ristic-Durrant, D., Graser, A.: A robust markerless vision-based human gait analysis system. In: Proceedings of 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI), pp. 415–420 (2011)

62.

Liao, H.-F., Mao, P.-J., Hwang, A.-W.: Test-retest reliability of balance tests in children with cerebral palsy. Dev. Med. Child Neurol. 43(3), 180–186 (2001)

63.

Liao, T.-Y., Miaou, S.-G., Li, Y.-R.: A vision-based walking posture analysis system without markers. In: Proceedings of the 2nd International Conference on Signal Processing Systems (ICSPS), vol. 3, pp. 254–258 (2010)

64.

Lim, D.-W., Kim, D.-H., Shen, L., Kim, H.-M., Kim, S., Yu, H.K.: Stride rate estimation using UWB impulse radar. In: Proceedings of the 3rd Asia-Pacific International Conference on Synthetic Aperture Radar (APSAR), pp. 1–3 (2011)

65.

Liu, J., Lockhart, T.E., Jones, M., Martin, T.: Local dynamic stability assessment of motion impaired elderly using electronic textile pants. IEEE Trans. Autom. Sci. Eng. 5(4), 696–702 (2008)CrossRef

66.

Lombardi, R., Buizza, A., Gandolfi, R., Vignarelli, C., Guaita, A., Panella, L.: Measurement on tinetti test: instrumentation and procedures. Technol. Health Care J. Eur. Soc. Eng. Med. 9(5), 403–416 (2001)

67.

Mancini, M., Salarian, A., Carlson-Kuhta, P., Zampieri, C., King, L., Chiari, L., Horak, F.B., et al.: Isway: a sensitive, valid and reliable measure of postural control. J. Neuroengineering Rehabil. 9(1), 59 (2012)CrossRef

68.

Mancini, M., Zampieri, C., Carlson-Kuhta, P., Chiari, L., Horak, F.B.: Anticipatory postural adjustments prior to step initiation are hypometric in untreated parkinsons disease: an accelerometer-based approach. Eur. J. Neurol. 16(9), 1028–1034 (2009)CrossRef

69.

Marschollek, M., Goevercin, M., Wolf, K.-H., Song, B., Gietzelt, M., Haux, R., Steinhagen-Thiessen, E.: A performance comparison of accelerometry-based step detection algorithms on a large, non-laboratory sample of healthy and mobility-impaired persons. In: Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS 2008, pp. 1319–1322 (2008)

70.

Marschollek, M., Nemitz, G., Gietzelt, M., Wolf, K., Meyer zu Schwabedissen, H., Haux, R.: Predicting in-patient falls in a geriatric clinic. Zeitschrift fr Gerontologie und Geriatrie 42, 317–322 (2009)CrossRef

71.

Mathie, M.J., Coster, A.C.F., Lovell, N.H., Celler, B.G.: Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement. Physiol. Meas. 25(2), R1 (2004)CrossRef

72.

Mayagoitia, R.E., Lotters, J.C., Veltink, P.H.: Standing stability evaluation using a triaxial accelerometer. In: Proceedings of 18th Annual International Conference of the IEEE Bridging Disciplines for Biomedicine Engineering in Medicine and Biology Society, October 31–November 3 1996, vol. 2, pp. 573–574 (1996)

73.

Melenhorst, A.-S., Rogers, W.A., Bouwhuis, D.G.: Older adults’ motivated choice for technological innovation: evidence for benefit-driven selectivity. Psychol. Aging 21(1), 190 (2006)CrossRef

74.

Menz, H.B., Lord, S.R., Fitzpatrick, R.C.: Age-related differences in walking stability. Age Ageing 32(2), 137–142 (2003)CrossRef

75.

Montero-Odasso, M., Schapira, M., Soriano, E.R., Varela, M., Kaplan, R., Camera, L.A., Mayorga, L.M.: Gait velocity as a single predictor of adverse events in healthy seniors aged 75 years and older. J. Gerontol. A Biol. Sci. Med. Sci. 60(10), 1304–1309 (2005)CrossRef

76.

Muras, J.: SMOOTH - a system for mobility training at home for people with Parkinson’s disease. Ph.D. thesis, Trinity College Dublin (2010)

77.

Najafi, B., Aminian, K., Loew, F., Blanc, Y., Robert, P.A.: 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. 49(8), 843–851 (2002)CrossRef

78.

Narayanan, M.R., Redmond, S.J., Scalzi, M.E., Lord, S.R., Celler, B.G., Ast, N.H.L.: Longitudinal falls-risk estimation using triaxial accelerometry. IEEE Trans. Biomed. Eng. 57(3), 534–541 (2010)CrossRef

79.

Nester, C., Jones, R.K., Liu, A., Howard, D., Lundberg, A., Arndt, A., Lundgren, P., Stacoff, A., Wolf, P.: Foot kinematics during walking measured using bone and surface mounted markers. J. Biomech. 40(15), 3412–3423 (2007)CrossRef

80.

Organization, W.H., et al.: International classification of functioning disability and health (ICF). resolution WHA 54.21 (2001)

81.

Otero, M.: Application of a continuous wave radar for human gait recognition. In: Kadar, I. (ed.) Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, vol. 5809, pp. 538–548, May 2005

82.

Pallejà, T., Teixidó, M., Tresanchez, M., Palacín, J.: Measuring gait using a ground laser range sensor. Sensors 9(11), 9133–9146 (2009)CrossRef

83.

Pappas, I.P.I., Keller, T., Mangold, S., Popovic, M.R., Dietz, V., Morari, M.: A reliable gyroscope-based gait-phase detection sensor embedded in a shoe insole. IEEE Sens. J. 4(2), 268–274 (2004)CrossRef

84.

Pavel, M., Hayes, T., Tsay, I., Erdogmus, D., Paul, A., Larimer, N., Jimison, H., Nutt, J.: Continuous assessment of gait velocity in Parkinson’s disease from unobtrusive measurements. In: Proceedings of the 3rd International IEEE/EMBS Conference on Neural Engineering CNE 2007, 2–5 May 2007, pp. 700–703 (2007)

85.

Pavel, M., Hayes, T.L., Adami, A., Jimison, H., Kaye, J.: Unobtrusive assessment of mobility. In: Proceedings of the 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS 2006, pp. 6277–6280, August 2006

86.

Perez, C., Oates, A., Hughey, L., Fung, J.: Development of a force-sensing cane instrumented within a treadmill-based virtual reality locomotor system. In: Proceedings of the International Conference on Virtual Rehabilitation, pp. 154–159 (2009)

87.

Perry, M., Dowdall, A., Lines, L., Hone, K.: Multimodal and ubiquitous computing systems: supporting independent-living older users. IEEE Trans. Inf. Technol. Biomed. 8(3), 258–270 (2004)CrossRef

88.

Podsiadlo, D., Richardson, S.: The timed “Up & Go”: a test of basic functional mobility for frail elderly persons. J. Am. Geriatr. Soc. 39(2), 142–148 (1991)

89.

Poppe, R.: Vision-based human motion analysis: an overview. Comput. Vis. Image Underst. 108, 4–18 (2007)CrossRef

90.

Ram, S.S., Li, Y., Lin, A., Ling, H.: Doppler-based detection and tracking of humans in indoor environments. J. Franklin Inst. 345(6), 679–699 (2008)CrossRefMATH

91.

Salarian, A., Horak, F.B., Zampieri, C., Carlson-Kuhta, P., Nutt, J.G., Aminian, K.: iTUG, a sensitive and reliable measure of mobility. IEEE Trans. Neural Syst. Rehabil. Eng. 18(3), 303–310 (2010)CrossRef

92.

Scanaill, C.N., Carew, S., Barralon, P., Noury, N., Lyons, D., Lyons, G.M.: A review of approaches to mobility telemonitoring of the elderly in their living environment. Ann. Biomed. Eng. 34(4), 547–563 (2006)CrossRef

93.

Shao, X., Zhao, H., Nakamura, K., Katabira, K., Shibasaki, R., Nakagawa, Y.: Detection and tracking of multiple pedestrians by using laser range scanners. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007, IROS 2007, pp. 2174–2179 (2007)

94.

Sixsmith, A.J.: An evaluation of an intelligent home monitoring system. J. Telemedicine Telecare 6(2), 63–72 (2000)CrossRefMathSciNet

95.

Skelly, M.M., Chizeck, H.J.: Real-time gait event detection for paraplegic FES walking. IEEE Trans. Neural Syst. Rehabil. Eng. 9(1), 59–68 (2001)CrossRef

96.

Smarr, C.-A., Fausset, C.B., Rogers, W.A.: Understanding the potential for robot assistance for older adults in the home environment. Georgia Institute of Technology (2011)

97.

Smith, G.E., Ahmad, F., Amin, M.G.: Micro-Doppler processing for ultra-wideband radar data. In: SPIE Defense, Security, and Sensing, pp. 83610L–83610L. International Society for Optics and Photonics (2012)

98.

Spehr, J., Gietzelt, M., Wegel, S., Költzsch, Y., Winkelbach, S., Marschollek, M., Gövercin, M., Wahl, F., Haux, R., Steinhagen-Thiessen, E.: Vermessung von Gangparametern zur Sturzprädikation durch Vision- und Beschleunigungssensorik. In: Demographischer Wandel - Assistenzsysteme aus der Forschung in den Markt (AAL 2011), p. 5 (2011)

99.

Steen, E.-E., Eichelberg, M., Nebel, W., Hein, A.: A novel indoor localization approach using dynamic changes in ultrasonic echoes. In: Wichert, R., Eberhardt, B. (eds.) Ambient Assisted Living. Advanced Technologies and Societal Change, pp. 61–76. Springer, Heidelberg (2012)

100.

Stolze, H., Klebe, S., Baecker, C., Zechlin, C., Friege, L., Pohle, S., Deuschl, G.: Prevalence of gait disorders in hospitalized neurological patients. Mov. Disord. 20(1), 89–94 (2005)CrossRef

101.

Stone, E., Skubic, M.: Mapping kinect-based in-home gait speed to tug time: a methodology to facilitate clinical interpretation. In: 2013 7th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), pp. 57–64 (2013)

102.

Stone, E.E., Skubic, M.: Evaluation of an inexpensive depth camera for passive in-home fall risk assessment. In: Proceedings of 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), pp. 71–77 (2011)

103.

Stone, E.E., Skubic, M.: Passive in-home measurement of stride-to-stride gait variability comparing vision and kinect sensing. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, pp. 6491–6494. IEEE (2011)

104.

Stone, E.-E., Skubic, M.: Passive, in-home gait measurement using an inexpensive depth camera: initial results. In: Proceedings of the 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), pp. 183–186 (2012)

105.

Sutherland, D.H.: The evolution of clinical gait analysis part l: kinesiological EMG. Gait Posture 14(1), 61–70 (2001)CrossRefMathSciNet

106.

Sutherland, D.H.: The evolution of clinical gait analysis: Part II Kinematics. Gait Posture 16(2), 159–179 (2002)CrossRef

107.

Sutherland, D.H.: The evolution of clinical gait analysis part III - kinetics and energy assessment. Gait Posture 21(4), 447–461 (2005)CrossRef

108.

Tinetti, M.E.: Performance-oriented assessment of mobility problems in elderly patients. J. Am. Geriatr. Soc. 34(2), 119–126 (1986)

109.

Tung, J., Gage, W., Zabjek, K., Brooks, D., Maki, D., Mihailidis, A., Fernie, G.R., McIlroy, W.E.: iWalker: a ‘real-world’ mobility assessment tool. In: 30th Canadian Medical and Biological Engineering Society. Canadian Medical & Biological Engineering Society (2007)

110.

van Doorn, C., Gruber-Baldini, A.L., Zimmerman, S., Hebel, J.R., Port, C.L., Baumgarten, M., Quinn, C.C., Taler, G., May, C., Magaziner, J., Epidemiology of Dementia in Nursing Homes Research Group: Dementia as a risk factor for falls and fall injuries among nursing home residents. J. Am. Geriatr. Soc. 51(9), 1213–1218 (2003)CrossRef

111.

Verghese, J., Lipton, R.B., Hall, C.B., Kuslansky, G., Katz, M.J., Buschke, H.: Abnormality of gait as a predictor of non-Alzheimer’s dementia. N. Engl. J. Med. 347(22), 1761–1768 (2002)CrossRef

112.

Vignaud, L., Ghaleb, A., Le Kernec, J., Nicolas, J.-M.: Radar high resolution range & micro-Doppler analysis of human motions. In: Proceedings of the International RADAR Conference-Surveillance for a Safer World, pp. 1–6 (2009)

113.

Virone, G., Noury, N., Demongeot, J.: A system for automatic measurement of circadian activity deviations in telemedicine. IEEE Trans. Biomed. Eng. 49(12), 1463–1469 (2002)CrossRef

114.

Wahab, Y., Bakar, N.A.: Microsystem based portable shoe integrated instrumentation using ultrasonic for gait analysis measurement. In: Proceedings of the 4th International Conference on Mechatronics (ICOM), pp. 1–4 (2011)

115.

Wall, J.C., Bell, C., Campbell, S., Davis, J.: The timed Get-up-and-Go test revisited: measurement of the component tasks. J. Rehabil. Res. Dev. 37(1), 109–113 (2000)

116.

Wang, F., Skubic, M., Abbott, C., Keller, J.M.: Body sway measurement for fall risk assessment using inexpensive webcams. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 2225–2229 (2010)

117.

Wang, Y., Fathy, A.E.: Range-time-frequency representation of a pulse Doppler radar imaging system for indoor localization and classification. In: 2013 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNet), pp. 34–36. IEEE (2013)

118.

Weir, R.F., Childress, D.S.: Portable devices for the clinical measurement of gait performance and outcomes. In: Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 3, pp. 1873–1875 (2000)

119.

Weiss, A., Herman, T., Plotnik, M., Brozgol, M., Giladi, N., Hausdorff, J.M.: An instrumented timed up and go: the added value of an accelerometer for identifying fall risk in idiopathic fallers. Physiol. Meas. 32(12), 2003 (2011)CrossRef

120.

Whitney, J.C., Lord, S.R., Close, J.C.T.: Streamlining assessment and intervention in a falls clinic using the Timed Up and Go Test and Physiological Profile Assessments. Age Ageing 34(6), 567–571 (2005)CrossRef

121.

Williamson, R., Andrews, B.J.: Gait event detection for FES using accelerometers and supervised machine learning. IEEE Trans. Rehabil. Eng. 8(3), 312–319 (2000)CrossRef

122.

Yack, H.J., Berger, R.C.: Dynamic stability in the elderly: identifying a possible measure. J. Gerontol. 48(5), M225–M230 (1993)CrossRef

123.

Yamada, M., Kamiya, K., Kudo, M., Nonaka, H., Toyama, J.: Soft authentication and behavior analysis using a chair with sensors attached: hipprint authentication. Pattern Anal. Appl. 12, 251–260 (2009)CrossRefMathSciNet

124.

Yardibi, T., Cuddihy, P., Genc, S., Bufi, C., Skubic, M., Rantz, M., Liu, L., Phillips, C.: Gait characterization via pulse-Doppler radar. In: Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), pp. 662–667 (2011)

125.

Zampieri, C., Salarian, A., Carlson-Kuhta, P., Aminian, K., Nutt, J.G., Horak, F.B.: The instrumented timed up and go test: potential outcome measure for disease modifying therapies in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 81(2), 171–176 (2010)CrossRef

126.

Zampieri, C., Salarian, A., Carlson-Kuhta, P., Nutt, J.G., Horak, F.B.: Assessing mobility at home in people with early Parkinson’s disease using an instrumented Timed Up and Go test. Parkinsonism Relat. Disord. 17(4), 277–280 (2011).http://dx.doi.org/10.1016/j.parkreldis.2010.08.001

127.

Zhu, H.S., Wertsch, J.J., Harris, G.F., Loftsgaarden, J.D., Price, M.B.: Foot pressure distribution during walking and shuffling. Arch. Phys. Med. Rehabil. 72(6), 390–397 (1991)

128.

Zijlstra, W.: Assessment of spatio-temporal parameters during unconstrained walking. Eur. J. Appl. Physiol. 92, 39–44 (2004)CrossRef

129.

Zijlstra, W., Hof, A.L.: Assessment of spatio-temporal gait parameters from trunk accelerations during human walking. Gait Posture 18(2), 1–10 (2003)CrossRef

130.

Zubeyde Gurbtiz, S., Melvin, W.L., Williams, D.B.: Comparison of radar-based human detection techniques. In: Proceedings of the Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers ACSSC 2007, pp. 2199–2203 (2007)

Titel: Towards Pervasive Mobility Assessments in Clinical and Domestic Environments
verfasst von: Melvin Isken
Thomas Frenken
Melina Frenken
Andreas Hein
Verlag: Springer International Publishing
Buch: Smart Health
Print ISBN: 978-3-319-16225-6

Electronic ISBN: 978-3-319-16226-3

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-16226-3_4

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"