249 related articles for article (PubMed ID: 32295298)
1. Analyzing the Effectiveness and Contribution of Each Axis of Tri-Axial Accelerometer Sensor for Accurate Activity Recognition.
Javed AR; Sarwar MU; Khan S; Iwendi C; Mittal M; Kumar N
Sensors (Basel); 2020 Apr; 20(8):. PubMed ID: 32295298
[TBL] [Abstract][Full Text] [Related]
2. Human Physical Activity Recognition Using Smartphone Sensors.
Voicu RA; Dobre C; Bajenaru L; Ciobanu RI
Sensors (Basel); 2019 Jan; 19(3):. PubMed ID: 30678039
[TBL] [Abstract][Full Text] [Related]
3. The effectiveness of simple heuristic features in sensor orientation and placement problems in human activity recognition using a single smartphone accelerometer.
Barua A; Jiang X; Fuller D
Biomed Eng Online; 2024 Feb; 23(1):21. PubMed ID: 38368358
[TBL] [Abstract][Full Text] [Related]
4. An Activity-Aware Sampling Scheme for Mobile Phones in Activity Recognition.
Chen Z; Chen J; Huang X
Sensors (Basel); 2020 Apr; 20(8):. PubMed ID: 32294935
[TBL] [Abstract][Full Text] [Related]
5. A feasibility study on smartphone accelerometer-based recognition of household activities and influence of smartphone position.
Della Mea V; Quattrin O; Parpinel M
Inform Health Soc Care; 2017 Dec; 42(4):321-334. PubMed ID: 28005434
[TBL] [Abstract][Full Text] [Related]
6. Activity recognition with smartphone support.
Guiry JJ; van de Ven P; Nelson J; Warmerdam L; Riper H
Med Eng Phys; 2014 Jun; 36(6):670-5. PubMed ID: 24641812
[TBL] [Abstract][Full Text] [Related]
7. Prediction of activity type in preschool children using machine learning techniques.
Hagenbuchner M; Cliff DP; Trost SG; Van Tuc N; Peoples GE
J Sci Med Sport; 2015 Jul; 18(4):426-31. PubMed ID: 25088983
[TBL] [Abstract][Full Text] [Related]
8. Coarse-Fine Convolutional Deep-Learning Strategy for Human Activity Recognition.
Avilés-Cruz C; Ferreyra-Ramírez A; Zúñiga-López A; Villegas-Cortéz J
Sensors (Basel); 2019 Mar; 19(7):. PubMed ID: 30935117
[TBL] [Abstract][Full Text] [Related]
9. Hip and Wrist-Worn Accelerometer Data Analysis for Toddler Activities.
Kwon S; Zavos P; Nickele K; Sugianto A; Albert MV
Int J Environ Res Public Health; 2019 Jul; 16(14):. PubMed ID: 31330889
[TBL] [Abstract][Full Text] [Related]
10. A Public Domain Dataset for Real-Life Human Activity Recognition Using Smartphone Sensors.
Garcia-Gonzalez D; Rivero D; Fernandez-Blanco E; Luaces MR
Sensors (Basel); 2020 Apr; 20(8):. PubMed ID: 32295028
[TBL] [Abstract][Full Text] [Related]
11. Smartphone-Based Activity Recognition Using Multistream Movelets Combining Accelerometer and Gyroscope Data.
Huang EJ; Yan K; Onnela JP
Sensors (Basel); 2022 Mar; 22(7):. PubMed ID: 35408232
[TBL] [Abstract][Full Text] [Related]
12. A hybrid deep approach to recognizing student activity and monitoring health physique based on accelerometer data from smartphones.
Xiao L; Luo K; Liu J; Foroughi A
Sci Rep; 2024 Jun; 14(1):14006. PubMed ID: 38890409
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Child activity recognition based on cooperative fusion model of a triaxial accelerometer and a barometric pressure sensor.
Nam Y; Park JW
IEEE J Biomed Health Inform; 2013 Mar; 17(2):420-6. PubMed ID: 24235114
[TBL] [Abstract][Full Text] [Related]
15. Smartphone Motion Sensor-Based Complex Human Activity Identification Using Deep Stacked Autoencoder Algorithm for Enhanced Smart Healthcare System.
Alo UR; Nweke HF; Teh YW; Murtaza G
Sensors (Basel); 2020 Nov; 20(21):. PubMed ID: 33167424
[TBL] [Abstract][Full Text] [Related]
16. A universal, accurate intensity-based classification of different physical activities using raw data of accelerometer.
Vähä-Ypyä H; Vasankari T; Husu P; Suni J; Sievänen H
Clin Physiol Funct Imaging; 2015 Jan; 35(1):64-70. PubMed ID: 24393233
[TBL] [Abstract][Full Text] [Related]
17. On the Problem of State Recognition in Injection Molding Based on Accelerometer Data Sets.
Brunthaler J; Grabski P; Sturm V; Lubowski W; Efrosinin D
Sensors (Basel); 2022 Aug; 22(16):. PubMed ID: 36015925
[TBL] [Abstract][Full Text] [Related]
18. Machine Learning on Prediction of Relative Physical Activity Intensity Using Medical Radar Sensor and 3D Accelerometer.
Biró A; Szilágyi SM; Szilágyi L; Martín-Martín J; Cuesta-Vargas AI
Sensors (Basel); 2023 Mar; 23(7):. PubMed ID: 37050655
[TBL] [Abstract][Full Text] [Related]
19. SUPAR: Smartphone as a ubiquitous physical activity recognizer for u-healthcare services.
Fahim M; Lee S; Yoon Y
Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():3666-9. PubMed ID: 25570786
[TBL] [Abstract][Full Text] [Related]
20. Accuracy of Samsung Gear S Smartwatch for Activity Recognition: Validation Study.
Davoudi A; Wanigatunga AA; Kheirkhahan M; Corbett DB; Mendoza T; Battula M; Ranka S; Fillingim RB; Manini TM; Rashidi P
JMIR Mhealth Uhealth; 2019 Feb; 7(2):e11270. PubMed ID: 30724739
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]