Format
Sort by
Items per page

Send to

Choose Destination

Links from PubMed

Items: 1 to 20 of 66

1.

Creating a behavioural classification module for acceleration data: using a captive surrogate for difficult to observe species.

Campbell HA, Gao L, Bidder OR, Hunter J, Franklin CE.

J Exp Biol. 2013 Dec 15;216(Pt 24):4501-6. doi: 10.1242/jeb.089805. Epub 2013 Sep 12.

2.

On-line classification of human activity and estimation of walk-run speed from acceleration data using support vector machines.

Mannini A, Sabatini AM.

Conf Proc IEEE Eng Med Biol Soc. 2011;2011:3302-5. doi: 10.1109/IEMBS.2011.6090896.

PMID:
22255045
3.

Identification of behaviour in freely moving dogs (Canis familiaris) using inertial sensors.

Gerencsér L, Vásárhelyi G, Nagy M, Vicsek T, Miklósi A.

PLoS One. 2013 Oct 18;8(10):e77814. doi: 10.1371/journal.pone.0077814. eCollection 2013.

4.

Movement activity based classification of animal behaviour with an application to data from cheetah (Acinonyx jubatus).

Grünewälder S, Broekhuis F, Macdonald DW, Wilson AM, McNutt JW, Shawe-Taylor J, Hailes S.

PLoS One. 2012;7(11):e49120. doi: 10.1371/journal.pone.0049120. Epub 2012 Nov 19.

5.

Love thy neighbour: automatic animal behavioural classification of acceleration data using the K-nearest neighbour algorithm.

Bidder OR, Campbell HA, Gómez-Laich A, Urgé P, Walker J, Cai Y, Gao L, Quintana F, Wilson RP.

PLoS One. 2014 Feb 21;9(2):e88609. doi: 10.1371/journal.pone.0088609. eCollection 2014.

6.

Optimizing acceleration-based ethograms: the use of variable-time versus fixed-time segmentation.

Bom RA, Bouten W, Piersma T, Oosterbeek K, van Gils JA.

Mov Ecol. 2014 Mar 28;2(1):6. doi: 10.1186/2051-3933-2-6. eCollection 2014.

7.

Using tri-axial acceleration data to identify behavioral modes of free-ranging animals: general concepts and tools illustrated for griffon vultures.

Nathan R, Spiegel O, Fortmann-Roe S, Harel R, Wikelski M, Getz WM.

J Exp Biol. 2012 Mar 15;215(Pt 6):986-96. doi: 10.1242/jeb.058602. Review.

8.

Falls classification using tri-axial accelerometers during the five-times-sit-to-stand test.

Doheny EP, Walsh C, Foran T, Greene BR, Fan CW, Cunningham C, Kenny RA.

Gait Posture. 2013 Sep;38(4):1021-5. doi: 10.1016/j.gaitpost.2013.05.013. Epub 2013 Jun 21.

PMID:
23791781
9.

The Use of Acceleration to Code for Animal Behaviours; A Case Study in Free-Ranging Eurasian Beavers Castor fiber.

Graf PM, Wilson RP, Qasem L, Hackländer K, Rosell F.

PLoS One. 2015 Aug 28;10(8):e0136751. doi: 10.1371/journal.pone.0136751. eCollection 2015.

10.

Identification of animal movement patterns using tri-axial magnetometry.

Williams HJ, Holton MD, Shepard ELC, Largey N, Norman B, Ryan PG, Duriez O, Scantlebury M, Quintana F, Magowan EA, Marks NJ, Alagaili AN, Bennett NC, Wilson RP.

Mov Ecol. 2017 Mar 27;5:6. doi: 10.1186/s40462-017-0097-x. eCollection 2017.

11.

Accelerometer tags: detecting and identifying activities in fish and the effect of sampling frequency.

Broell F, Noda T, Wright S, Domenici P, Steffensen JF, Auclair JP, Taggart CT.

J Exp Biol. 2013 Apr 1;216(Pt 7):1255-64. doi: 10.1242/jeb.077396. Epub 2012 Nov 29. Erratum in: J Exp Biol. 2013 Apr 15;216(Pt 8):1522.

12.

Using accelerometers to remotely and automatically characterize behavior in small animals.

Hammond TT, Springthorpe D, Walsh RE, Berg-Kirkpatrick T.

J Exp Biol. 2016 Jun 1;219(Pt 11):1618-24. doi: 10.1242/jeb.136135. Epub 2016 Mar 18.

13.

Classification of a known sequence of motions and postures from accelerometry data using adapted Gaussian mixture models.

Allen FR, Ambikairajah E, Lovell NH, Celler BG.

Physiol Meas. 2006 Oct;27(10):935-51. Epub 2006 Jul 25.

PMID:
16951454
14.

The need for speed: testing acceleration for estimating animal travel rates in terrestrial dead-reckoning systems.

Bidder OR, Soresina M, Shepard EL, Halsey LG, Quintana F, Gómez-Laich A, Wilson RP.

Zoology (Jena). 2012 Feb;115(1):58-64. doi: 10.1016/j.zool.2011.09.003. Epub 2012 Jan 11.

PMID:
22244455
15.

Movement, resting, and attack behaviors of wild pumas are revealed by tri-axial accelerometer measurements.

Wang Y, Nickel B, Rutishauser M, Bryce CM, Williams TM, Elkaim G, Wilmers CC.

Mov Ecol. 2015 Jan 22;3(1):2. doi: 10.1186/s40462-015-0030-0. eCollection 2015.

16.

Computer-assisted lip diagnosis on Traditional Chinese Medicine using multi-class support vector machines.

Li F, Zhao C, Xia Z, Wang Y, Zhou X, Li GZ.

BMC Complement Altern Med. 2012 Aug 16;12:127. doi: 10.1186/1472-6882-12-127.

17.

Influence of treadmill acceleration on actual walk-to-run transition.

Van Caekenberghe I, Segers V, De Smet K, Aerts P, De Clercq D.

Gait Posture. 2010 Jan;31(1):52-6. doi: 10.1016/j.gaitpost.2009.08.244. Epub 2009 Sep 30.

PMID:
19796948
18.

Development of an automated physical activity classification application for mobile phones.

Xia Y, Cheung V, Garcia E, Ding H, Karunaithi M.

Stud Health Technol Inform. 2011;168:188-94.

PMID:
21893928
19.

AcceleRater: a web application for supervised learning of behavioral modes from acceleration measurements.

Resheff YS, Rotics S, Harel R, Spiegel O, Nathan R.

Mov Ecol. 2014 Dec 25;2(1):27. doi: 10.1186/s40462-014-0027-0. eCollection 2014.

20.

Tri-axial dynamic acceleration as a proxy for animal energy expenditure; should we be summing values or calculating the vector?

Qasem L, Cardew A, Wilson A, Griffiths I, Halsey LG, Shepard EL, Gleiss AC, Wilson R.

PLoS One. 2012;7(2):e31187. doi: 10.1371/journal.pone.0031187. Epub 2012 Feb 17.

Supplemental Content

Support Center