86 related articles for article (PubMed ID: 29028218)
1. Activity Recognition Using Complex Network Analysis.
Jalloul N; Poree F; Viardot G; L Hostis P; Carrault G; Jalloul N; Poree F; Viardot G; L' Hostis P; Carrault G
IEEE J Biomed Health Inform; 2018 Jul; 22(4):989-1000. PubMed ID: 29028218
[TBL] [Abstract][Full Text] [Related]
2. Automatic Recognition of Activities of Daily Living Utilizing Insole-Based and Wrist-Worn Wearable Sensors.
Hegde N; Bries M; Swibas T; Melanson E; Sazonov E; Hegde N; Bries M; Swibas T; Melanson E; Sazonov E
IEEE J Biomed Health Inform; 2018 Jul; 22(4):979-988. PubMed ID: 28783651
[TBL] [Abstract][Full Text] [Related]
3. Comparing supervised learning techniques on the task of physical activity recognition.
Dalton A; OLaighin G
IEEE J Biomed Health Inform; 2013 Jan; 17(1):46-52. PubMed ID: 23070357
[TBL] [Abstract][Full Text] [Related]
4. Physical Activities Monitoring Using Wearable Acceleration Sensors Attached to the Body.
Arif M; Kattan A
PLoS One; 2015; 10(7):e0130851. PubMed ID: 26203909
[TBL] [Abstract][Full Text] [Related]
5. Evaluation of accelerometer based multi-sensor versus single-sensor activity recognition systems.
Gao L; Bourke AK; Nelson J
Med Eng Phys; 2014 Jun; 36(6):779-85. PubMed ID: 24636448
[TBL] [Abstract][Full Text] [Related]
6. Activity classification based on inertial and barometric pressure sensors at different anatomical locations.
Moncada-Torres A; Leuenberger K; Gonzenbach R; Luft A; Gassert R
Physiol Meas; 2014 Jul; 35(7):1245-63. PubMed ID: 24853451
[TBL] [Abstract][Full Text] [Related]
7. SoM: a smart sensor for human activity monitoring and assisted healthy ageing.
Naranjo-Hernández D; Roa LM; Reina-Tosina J; Estudillo-Valderrama MÁ
IEEE Trans Biomed Eng; 2012 Nov; 59(11):3177-84. PubMed ID: 23086195
[TBL] [Abstract][Full Text] [Related]
8. Performance of Activity Classification Algorithms in Free-Living Older Adults.
Sasaki JE; Hickey AM; Staudenmayer JW; John D; Kent JA; Freedson PS
Med Sci Sports Exerc; 2016 May; 48(5):941-50. PubMed ID: 26673129
[TBL] [Abstract][Full Text] [Related]
9. Human activity classification with inertial sensors.
Silva J; Monteiro M; Sousa F
Stud Health Technol Inform; 2014; 200():101-4. PubMed ID: 24851971
[TBL] [Abstract][Full Text] [Related]
10. A wearable sensor module with a neural-network-based activity classification algorithm for daily energy expenditure estimation.
Lin CW; Yang YT; Wang JS; Yang YC
IEEE Trans Inf Technol Biomed; 2012 Sep; 16(5):991-8. PubMed ID: 22875251
[TBL] [Abstract][Full Text] [Related]
11. Feature selection and activity recognition system using a single triaxial accelerometer.
Gupta P; Dallas T
IEEE Trans Biomed Eng; 2014 Jun; 61(6):1780-6. PubMed ID: 24691526
[TBL] [Abstract][Full Text] [Related]
12. An Activity Recognition Framework Deploying the Random Forest Classifier and A Single Optical Heart Rate Monitoring and Triaxial AccelerometerWrist-Band.
Mehrang S; Pietilä J; Korhonen I
Sensors (Basel); 2018 Feb; 18(2):. PubMed ID: 29470385
[TBL] [Abstract][Full Text] [Related]
13. Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data.
Nef T; Urwyler P; Büchler M; Tarnanas I; Stucki R; Cazzoli D; Müri R; Mosimann U
Sensors (Basel); 2015 May; 15(5):11725-40. PubMed ID: 26007727
[TBL] [Abstract][Full Text] [Related]
14. Recognizing upper limb movements with wrist worn inertial sensors using k-means clustering classification.
Biswas D; Cranny A; Gupta N; Maharatna K; Achner J; Klemke J; Jöbges M; Ortmann S
Hum Mov Sci; 2015 Apr; 40():59-76. PubMed ID: 25528632
[TBL] [Abstract][Full Text] [Related]
15. A system for activity recognition using multi-sensor fusion.
Gao L; Bourke AK; Nelson J
Annu Int Conf IEEE Eng Med Biol Soc; 2011; 2011():7869-72. PubMed ID: 22256164
[TBL] [Abstract][Full Text] [Related]
16. Posture and activity recognition and energy expenditure estimation in a wearable platform.
Sazonov E; Hegde N; Browning RC; Melanson EL; Sazonova NA
IEEE J Biomed Health Inform; 2015 Jul; 19(4):1339-46. PubMed ID: 26011870
[TBL] [Abstract][Full Text] [Related]
17. Selecting Power-Efficient Signal Features for a Low-Power Fall Detector.
Wang C; Redmond SJ; Lu W; Stevens MC; Lord SR; Lovell NH
IEEE Trans Biomed Eng; 2017 Nov; 64(11):2729-2736. PubMed ID: 28212076
[TBL] [Abstract][Full Text] [Related]
18. Classification of physical activities based on body-segments coordination.
Fradet L; Marin F
Comput Biol Med; 2016 Sep; 76():134-42. PubMed ID: 27441831
[TBL] [Abstract][Full Text] [Related]
19. Accelerometer-based wireless body area network to estimate intensity of therapy in post-acute rehabilitation.
Choquette S; Hamel M; Boissy P
J Neuroeng Rehabil; 2008 Sep; 5():20. PubMed ID: 18764954
[TBL] [Abstract][Full Text] [Related]
20. Characterization of physical activity in COPD patients: validation of a robust algorithm for actigraphic measurements in living situations.
Perriot B; Argod J; Pepin JL; Noury N
IEEE J Biomed Health Inform; 2014 Jul; 18(4):1225-31. PubMed ID: 24058044
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
