544 related articles for article (PubMed ID: 26303929)
21. Quantitative description of the lie-to-sit-to-stand-to-walk transfer by a single body-fixed sensor.
Bagalà F; Klenk J; Cappello A; Chiari L; Becker C; Lindemann U
IEEE Trans Neural Syst Rehabil Eng; 2013 Jul; 21(4):624-33. PubMed ID: 23221832
[TBL] [Abstract][Full Text] [Related]
22. Automation of Functional Mobility Assessments at Home Using a Multimodal Sensor System Integrating Inertial Measurement Units and Computer Vision (IMU-Vision).
Spangler J; Mitjans M; Collimore A; Gomes-Pires A; Levine DM; Tron R; Awad LN
Phys Ther; 2024 Feb; 104(2):. PubMed ID: 38159106
[TBL] [Abstract][Full Text] [Related]
23. Energy expenditure estimation during normal ambulation using triaxial accelerometry and barometric pressure.
Wang J; Redmond SJ; Voleno M; Narayanan MR; Wang N; Cerutti S; Lovell NH
Physiol Meas; 2012 Nov; 33(11):1811-30. PubMed ID: 23110944
[TBL] [Abstract][Full Text] [Related]
24. Systematic review on the application of wearable inertial sensors to quantify everyday life motor activity in people with mobility impairments.
Rast FM; Labruyère R
J Neuroeng Rehabil; 2020 Nov; 17(1):148. PubMed ID: 33148315
[TBL] [Abstract][Full Text] [Related]
25. Would a thermal sensor improve arm motion classification accuracy of a single wrist-mounted inertial device?
Lui J; Menon C
Biomed Eng Online; 2019 May; 18(1):53. PubMed ID: 31064354
[TBL] [Abstract][Full Text] [Related]
26. Evaluation of a smartphone human activity recognition application with able-bodied and stroke participants.
Capela NA; Lemaire ED; Baddour N; Rudolf M; Goljar N; Burger H
J Neuroeng Rehabil; 2016 Jan; 13():5. PubMed ID: 26792670
[TBL] [Abstract][Full Text] [Related]
27. Using decision trees to measure activities in people with stroke.
Zhang T; Fulk GD; Tang W; Sazonov ES
Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():6337-40. PubMed ID: 24111190
[TBL] [Abstract][Full Text] [Related]
28. Detecting compensatory movements of stroke survivors using pressure distribution data and machine learning algorithms.
Cai S; Li G; Zhang X; Huang S; Zheng H; Ma K; Xie L
J Neuroeng Rehabil; 2019 Nov; 16(1):131. PubMed ID: 31684970
[TBL] [Abstract][Full Text] [Related]
29. Classification of Horse Gaits Using FCM-Based Neuro-Fuzzy Classifier from the Transformed Data Information of Inertial Sensor.
Lee JN; Lee MW; Byeon YH; Lee WS; Kwak KC
Sensors (Basel); 2016 May; 16(5):. PubMed ID: 27171098
[TBL] [Abstract][Full Text] [Related]
30. Detection and classification of postural transitions in real-world conditions.
Ganea R; Paraschiv-lonescu A; Aminian K
IEEE Trans Neural Syst Rehabil Eng; 2012 Sep; 20(5):688-96. PubMed ID: 22692942
[TBL] [Abstract][Full Text] [Related]
31. Quantifying sit-to-stand and stand-to-sit transitions in free-living environments using the activPAL thigh-worn activity monitor.
Pickford CG; Findlow AH; Kerr A; Banger M; Clarke-Cornwell AM; Hollands KL; Quinn T; Granat MH
Gait Posture; 2019 Sep; 73():140-146. PubMed ID: 31325738
[TBL] [Abstract][Full Text] [Related]
32. A description of an accelerometer-based mobility monitoring technique.
Lyons GM; Culhane KM; Hilton D; Grace PA; Lyons D
Med Eng Phys; 2005 Jul; 27(6):497-504. PubMed ID: 15990066
[TBL] [Abstract][Full Text] [Related]
33. Using sensors to measure activity in people with stroke.
Fulk GD; Sazonov E
Top Stroke Rehabil; 2011; 18(6):746-57. PubMed ID: 22436312
[TBL] [Abstract][Full Text] [Related]
34. Interactions between posture and locomotion: motor patterns in humans walking with bent posture versus erect posture.
Grasso R; Zago M; Lacquaniti F
J Neurophysiol; 2000 Jan; 83(1):288-300. PubMed ID: 10634872
[TBL] [Abstract][Full Text] [Related]
35. Accuracy of gait and posture classification using movement sensors in individuals with mobility impairment after stroke.
Pohl J; Ryser A; Veerbeek JM; Verheyden G; Vogt JE; Luft AR; Easthope CA
Front Physiol; 2022; 13():933987. PubMed ID: 36225292
[No Abstract] [Full Text] [Related]
36. Automated stand-up and sit-down detection for robot-assisted body-weight support training with the FLOAT.
Bannwart M; Emst D; Easthope C; Bolliger M; Rauter G
IEEE Int Conf Rehabil Robot; 2017 Jul; 2017():412-417. PubMed ID: 28813854
[TBL] [Abstract][Full Text] [Related]
37. Ambulatory monitoring of human posture and walking speed using wearable accelerometer sensors.
Yeoh WS; Pek I; Yong YH; Chen X; Waluyo AB
Annu Int Conf IEEE Eng Med Biol Soc; 2008; 2008():5184-7. PubMed ID: 19163885
[TBL] [Abstract][Full Text] [Related]
38. Detection of daily postures and walking modalities using a single chest-mounted tri-axial accelerometer.
Nazarahari M; Rouhani H
Med Eng Phys; 2018 Jul; 57():75-81. PubMed ID: 29691130
[TBL] [Abstract][Full Text] [Related]
39. Automatic recognition of postures and activities in stroke patients.
Sazonov ES; Fulk G; Sazonova N; Schuckers S
Annu Int Conf IEEE Eng Med Biol Soc; 2009; 2009():2200-3. PubMed ID: 19965152
[TBL] [Abstract][Full Text] [Related]
40. Validation of a body-worn accelerometer to measure activity patterns in octogenarians.
Taylor LM; Klenk J; Maney AJ; Kerse N; Macdonald BM; Maddison R
Arch Phys Med Rehabil; 2014 May; 95(5):930-4. PubMed ID: 24486241
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
