Preprocessing techniques for context recognition from accelerometer data

Personal Technologies - Tập 14 Số 7 - Trang 645-662 - 2010
Davide Figo1, Pedro C. Diniz1, Diogo R. Ferreira1, João M. P. Cardoso2
1IST, Technical University of Lisbon, Avenida Prof. Dr. Cavaco Silva, 2744-016, Porto Salvo, Portugal
2Faculty of Engineering, University of Porto (FEUP), Rua Dr. Roberto Frias 4200-465 Porto, Portugal

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Al-ani T, Ba QTL, Monacelli E (2006) On-line automatic detection of human activity in home using wavelet and hidden markov models scilab toolkits. In: Proceedings of the 16th international conference on control applications (ICCA)

Aminian K, Robert P, Jequier E, Schutz Y (1995) Estimation of speed and incline of walking using neural network. IEEE Trans Instrum Meas 44(3):743–746

Aminian K, Robert P, Buchser E, Rutschmann B, Hayoz D, Depairon M (1999) Physical activity monitoring based on accelerometry: validation and comparison with video observation. Med Biol Eng Comput 37(1):304–308

Ashbrook D (1999) Context sensing with the twiddler keyboard. In: Proceedings of the third international symposium on wearable computers (ISWC’99), pp 197–198

Bao L, Intille SS (2004) Activity recognition from user-annotated acceleration data. In: Proceedings of the interantional conference on pervasive computing (PERVASIVE’04). Springer, Lecture notes on computer sciences (LNCS), vol 3001, pp 1–17

Bouten C, Koekkoek K, Verduin M, Kodde R, Janssen J (1997) A triaxial accelerometer and portable data processing unit for the assessment of daily physical activity. IEEE Trans Biomed Eng 44(3):136–147

Brown G, Bajcsy R, Eklund M (2005) An accelerometer based fall detector: development, experimentation, and analysis. Technical Report 12, University of California at Berkeley

Chambers G, Venkatesh S, West G, Bui H (2002) Hierarchical recognition of intentional human gestures for sports video annotation. In: Proceedings of the 16th international conference on pattern recognition, vol 2, pp 1082–1085

Chen J, Kwong K, Chang D, Luk J, Bajcs R (2005) Wearable sensors for reliable fall detection. In: Proceedings of the 27th annual IEEE conference on engineering in medicine and biology (EMB’05)

Dargie W (2006) A distributed architecture for computing context in mobile devices. Master’s thesis, Dresden University of Technology, Department of Computer Science

Farringdon J, Moore AJ, Tilbury N, Church J, Biemond PD (1999) Wearable sensor badge and sensor jacket for context awareness. In: Proceedings of the IEEE international symposium on wearable computers (ISWC’99). IEEE Computer Society, pp 107–114

Golding A, Lesh N (1999) Indoor navigation using a diverse set of cheap, wearable sensors. In: Proceedings of the 3rd IEEE international symposium on wearable computers, pp 29–36

Guerreiro T, Gamboa R, Jorge J (2008) Mnemonical body shortcuts: improving mobile interaction. In: Proceedings of the 15th European conference on cognitive ergonomics (ECCE’08). ACM, pp 1–8

Gusfield D (1997) Algorithms on strings, trees, and sequences. Cambridge University Press, Cambridge

Healey J, Logan B (2005) Wearable wellness monitoring using ecg and accelerometer data. In: Proceedings of the ninth IEEE international symposium on wearable computers (ISWC’05). IEEE Computer Society Press, Washington, DC, pp 220–221

Ho J (2004) Interruptions: using activity transitions to trigger proactive messages. Master’s thesis, Massachusetts Institute of Technology

Huynh T, Schiele B (2005) Analyzing features for activity recognition. In: sOc-EUSAI ’05: Proceedings of the 2005 joint conference on smart objects and ambient intelligence, pp 159–163

Intille SS, Bao L, Tapia EM, Rondoni J (2004) Acquiring in situ training data for context-aware ubiquitous computing applications. In: Proceedings of the SIGCHI conference on human factors in computing systems (CHI’04). ACM Press, pp 1–8

Jeong DU, Kim SJ, Chung WY (2007) Classification of posture and movement using a 3-axis accelerometer. In: Proceedings of the 2007 international conference on convergence information technology (ICCIT’07). IEEE Computer Society, Washington, DC, USA, pp 837–844

Jin G, Lee S, Lee T (2007) Context awareness of human motion states using accelerometer. J Med Syst 32(2):93–100

Karantonis D, Narayanan M, Mathie M, Lovell N, Celler B (2006) Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring. IEEE Trans Inform Technol Biomed 10(1):156–167

Kawahara HSY, Hisashi Kurasawa HM, Aoyama T (2005) A context-aware collaborative filtering algorithm for real world oriented content delivery service. In: Proceedings of ubiPCMM

Kawahara Y, Kurasawa H, Morikawa H (2007) Recognizing user context using mobile handsets with acceleration sensors. In: (IEEE) international conference on portable information devices (PORTABLE’07), pp 1–5

Kawaharaq Y, Ryu N, Asami T (2009) Monitoring daily energy expenditure using a 3-axis accelerometer with a low-power microprocessor. e-Minds: Int J Hum Comput Interact 1(5):145–154

Keogh E, Pazzani M (2001) Derivative dynamic time warping. In: Proceedings of the first SIAM international conference on data mining (SDMÕ2001)

Keogh E, Lonardi S, Ratanamahatana CA, Wei L, Lee SH, Handley J (2007) Compression-based data mining of sequential data. Data Min Knowl Discov 14(1):99–129

Kern N, Schiele B, Schmidt A (2007) Recognizing context for annotating a live life recording. Pers Ubiquit Comput 11(4):251–263

Kim IJ, Im S, Hong E, Ahn SC, Kim HG (2007) ADL classification using triaxial accelerometers and RFID. In: International workshop on ubiquitous convergence technology (IWUCT’07)

Krause A, Siewiorek D, Smailagic A, Farringdon J (2003) Unsupervised, dynamic identification of physiological and activity context in wearable computing. In: Proceedings of seventh IEEE international symposium on wearable computers (ISWC’03), pp 88–97

Lee SW, Mase K (2002) Activity and location recognition using wearable sensors. IEEE Pervasive Comput 1(3):24–32

Lin J, Keogh E, Lonardi S, Chiu B (2003) A symbolic representation of time series, with implications for streaming algorithms. In: Proceedings of the 8th ACM SIGMOD workshop on research issues in data mining and knowledge discovery

Lin J, Keogh E, Wei L, Lonardi S (2007) Experiencing SAX: a novel symbolic representation of time series. Data Min Knowl Discover 15(2):107–144

Liu J, Wang Z, Zhong L, Wickramasuriya J, Vasudevan V (2008) uWave: accelerometer-based personalized gesture recognition. TR0630-08, Rice University and Motorola Labs, Houston, Texas

Mallat S (1999) A wavelet tour of signal processing. Academic Press, Berlin

Mäntyjärvi J (2003) Sensor-based context recognition for mobile applications. Ph.D. thesis, University of Oulu, Finland, Faculty of Technology, Department of Electrical and Information Engineering, Information Processing Laboratory

Martens W (1992) The Fast Time Frequency Transform (F.T.F.T.): a novel on-line approach to the instantaneous spectrum. In: Engineering in Medicine and Biology Society, vol 14. Proceedings of the annual international conference of the IEEE, vol 6, pp 2594–2595

Mathie M (2003) Monitoring and interpreting human movement patterns using a triaxial accelerometer. Ph.D. thesis, University of New South Wales

Mathie M, Celler B, Lovell N, Coster A (2004) Classification of basic daily movements using a triaxial accelerometer. Med Biol Eng Comput 42(5):679–687

Muscillo R, Conforto S, Schmid M, Caselli P, D’Alessio T (2007) Classification of motor activities through derivative dynamic time warping applied on accelerometer data. In: Proceedings of the 29th IEEE annual international conference on Engineering in Medicine and Biology Society (EMBS’07), pp 4930–4933

Nambu M (2007) Body surface mounted biomedical monitoring system using bluetooth. In: Proceedings of the 29th annual international conference of the IEEE on Engineering in Medicine and Biology Society, (EMBS’07), pp 1824–1825

Nham B, Siangliulue K, Yeung S (2008) Predicting mode of transport from iphone accelerometer data. CS 229: Machine Learning Final Projects, Stanford University, Stanford, California

Randell C, Muller H (2000) Context awareness by analyzing accelerometer data. In: Proceedings of the 4th IEEE international symposium on wearable computers (ISWC’00). IEEE Computer Society, Washington, DC, USA, pp 175–176

Ravi N, Dandekar N, Mysore P, Littman ML (2005) Activity recognition from accelerometer data. In: IAAI’05: Proceedings of the 17th conference on innovative applications of artificial intelligence. AAAI Press, pp 1541–1546

Robert B, White B, Renter D, Larson R (2009) Evaluation of three-dimensional accelerometers to monitor and classify behavior patterns in cattle. Comput Electron Agric 67(1–2):80–84

Rodgers J, Nicewander W (1988) Thirteen ways to look at the correlation coefficient. Am Stat 42(1):59–66

Sakoe H, Chiba S (1978) Dynamic programming algorithm optimization for spoken word recognition. IEEE Trans Acoust Speech Signal Process 26(1):43– 49

Santos AC, Tarrataca L, Cardoso JMP, Ferreira DR, Diniz PC, Chainho P (2009) Context inference for mobile applications in the UPCASE project. In: Proceedings of the 2nd international conference on mobile wireless middleware, operating systems, and applications (MOBILWARE 2009). Springer, no. 7 in LNICST, pp 352–365

Schmidt A (2002) Ubiquitous computing—computing in context. PhD thesis, Lancaster University, England, UK

Schmidt A, van Laerhoven K (2001) How to build smart appliances? Pers Commun IEEE 8(4):66–71

Schmidt A, Beigl M, Gellersen HW (1999a) There is more to context than location. Comput Graph 23:893–901

Schmidt A, Gellersen HW, Beigl M (1999b) A wearable context-awareness component. finally a good reason to wear a tie. In: Proceedings of the 1999 international symposium on wearable computers, (ISWC’99), pp 176–177

Sekine M, Tamura T, Ogawa M, Togawa T, Fukui Y (1998) Classification of acceleration waveform in a continuous walking record. In: Proceedings of the 20th annual IEEE international conference of the engineering in medicine and biology society, vol 3, pp 1523–1526

Sekine M, Tamura T, Fujimoto T, Fukui Y (2000) Classification of walking pattern using acceleration waveform in elderly people. In: Proceedings of the 22nd annual IEEE international conference of the engineering in medicine and biology society, vol 2, pp 1356–1359

Sekine M, Tamura T, Akay M, Fujimoto T, Togawa T, Fukui Y (2002) Discrimination of walking patterns using wavelet-based fractal analysis. IEEE Trans Neural Syst Rehabil Eng 10:188–196

Siewiorek D, Smailagic A, Furukawa J, Krause A, Moraveji N, Reiger K, Shaffer J, Wong F (2003) Sensay: a context-aware mobile phone. In: Proceedings of the 7th international symposium on wearable computers (ISWC)

Stiefmeier T, Roggen D, Tröster G (2007) Gestures are strings: efficient online gesture spotting and classification using string matching. In: Proceedings of international conference BodyNets 07

Vail D, Veloso M (2004) Learning from accelerometer data on a legged robot. In: Proceedings of the 5th IFAC/EURON symposium on intelligent autonomous vehicles

Van Laerhoven K, Cakmakci O (2000) What shall we teach our pants. In: Proceedings of the fourth international symposium on wearable computers (ISWC’00)

Van Laerhoven K, Aidoo K, Lowette S (2001) Real-time analysis of data from many sensors with neural networks. In: Proceedings of the 5th international symposium on wearable computers (ISWC’01), pp 115–122

Veltink P, Bussmann H, de Vries W, Martens W, Van Lummel R (1996) Detection of static and dynamic activities using uniaxial accelerometers. IEEE Trans Rehabil Eng 4(4):375–385

Wang S, Pentney W, Popescu AM (2007) Common sense based joint training of human activity recognizers. In: Proceedings of the 20th international joint conference on artificial intelligence (IJCAI’07), pp 2237–2242

Welbourne E, Lester J, LaMarca A, Borriello G (2007) Mobile context inference using low-cost sensors. In: Proceedings of the first international workshop on Location- and Context-Awareness (LoCA 2005), Springer, LNCS, vol 3479, pp 254–263

Wiggins H (2008) Gesture recognition of Nintendo Wiimote input using an artificial neural network. Cognitive Systems, University of British Columbia, Vancouver, Canada