Living activity recognition using off-the-shelf sensors on mobile phones

Annales des Telecommunications/Annals of Telecommunications

Volumn 67, Issue 7-8, 2012, Pages 387-395

  Ouchi, Kazushige ^a   Doi, Miwako ^a  

^a TOSHIBA CORPORATION   (Japan)

Author keywords

Accelerometer; Living activity recognition; Microphone; Mobile phone

Indexed keywords

ACCELERATION SENSING; ACOUSTIC SENSING; ACTIVITY RECOGNITION; INTERACTIVE COMMUNICATIONS; RECOGNITION METHODS; ROBOTIC TECHNOLOGIES;

ACCELEROMETERS; CELLULAR TELEPHONES; MICROPHONES; MOBILE DEVICES; MOBILE PHONES; ROBOTICS; SENSORS; WALKING AIDS;

EXPERIMENTS;

EID: 84864540039     PISSN: 00034347     EISSN: 19589395     Source Type: Journal    
DOI: 10.1007/s12243-012-0308-9     Document Type: Article

References (17)

1. Cabinet Office Director-General for Policies on Cohesive Society (2009) White paper on the aging society (Summary) FY 2009 (in Japanese
2. Fujii A et al (2008) Behavior description algorithm based on home sensor data using nonlinear transformations. In: International Conference on Networked Sensing Systems (INSS2008), pp 63-66
3. Kern N, Schiele B, Schmidt A (2003) Multi-sensor activity context detection for wearable computing. In: Proceedings of the First European Symposium on Ambient Intelligence (EUSAI 2003), LNCS 2875, pp 220-232
4. Bao L, Intille SS (2004) Activity recognition from user-annotated acceleration data. In: Proceedings of the Second International Conference on Pervasive Computing (PERVASIVE 2004), LNCS 3001, pp 1-17
5. iSuppli Press Release (July 9, 2009) http://www.isuppli.com/MEMS-and- Sensors/News/Pages/One-Third-of-Mobile-Phonesto-Use-Accelerometers-by-2010- Spurred-by-iPhone-and-Palm-Pre.aspx
6. Iso T, Yamazaki K (2006) Gait analyzer based on a cell phone with a single three-axis accelerometer. In: Proc. MobileHCI 2006, pp 141-144
7. Cho K, Iketani N, Setoguchi H, Hattori M (2009) Human activity recognizer for mobile devices with multiple sensors, UIC-ATC. In: Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, pp 114-119
8. Stäger M, Lukowicz P, Perera N, von Büren T, Tröster G, Starner T (2003) SoundButton: Design of a low power wearable audio classification system. In: Proc. of the 7th IEEE International Symposium on Wearable Computers (ISWC '03), pp 12-17
9. Kobayashi A, Iwamoto T, Nishiyama S (2009) Shaka: method for estimating user movement using mobile phone. Trans Inform Process Soc Jpn 50(1):193-208, In Japanese
10. Siewiorek D, Smailagic A, Furukawa J, Krause A, Moraveji N, Reiger K, Shaffer J, Wong F (2003) SenSay: A context-aware mobile phone. In: Poster of 7th IEEE International Symposium on Wearable Computers (ISWC 2003
11. Maekawa T, Yanagisawa Y, Kishino Y, Ishiguro K, Kamei K, Sakurai Y, Okadome T (2010) Object-based activity recognition with heterogeneous sensors on wrist. In: Proceedings of the Eighth International Conference on Pervasive Computing (PERVASIVE 2010), LNCS, vol 6030, pp 246-264
12. Wang S, Pentney W, Popescu A-M, Choudhury T, Philipose M (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
13. Van Laerhoven K, Kilian D, Schiele B (2008) Using rhythm awareness in long-term activity recognition. In: Proc. of the 12th IEEE International Symposium on Wearable Computers (ISWC '08), pp 63-66
14. Katz S (1983) Assessing self-maintenance: Activities of daily living, mobility, and instrumental activities of daily living. J Am Geriatr Soc 31(12):721-727
15. Cole RJ et al (1992) Automatic sleep/wake identification from wrist actigraphy. Sleep 15:461-469
16. Chen J et al (2005) Bathroom activity monitoring based on sound. In: Proceedings of the Third International Conference on Pervasive Computing (PERVASIVE 2005), LNCS, vol 3468, pp 47-61
17. Kobayashi Y et al (2010) Design targeting voice interface robot capable of active listening. In: Proceedings of the 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2010), pp 161-162