{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T16:15:29Z","timestamp":1770912929816,"version":"3.50.1"},"reference-count":13,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2013,10,30]],"date-time":"2013-10-30T00:00:00Z","timestamp":1383091200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Purpose: To compare raw acceleration output of the ActiGraph\u2122 GT3X+ and GENEA activity monitors. Methods: A GT3X+ and GENEA were oscillated in an orbital shaker at frequencies ranging from 0.7 to 4.0 Hz (ten 2-min trials\/frequency) on a fixed radius of 5.08 cm. Additionally, 10 participants (age = 23.8 \u00b1 5.4 years) wore the GT3X+ and GENEA on the dominant wrist and performed treadmill walking (2.0 and 3.5 mph) and running (5.5 and 7.5 mph) and simulated free-living activities (computer work, cleaning a room, vacuuming and throwing a ball) for 2-min each. A linear mixed model was used to compare the mean triaxial vector magnitude (VM) from the GT3X+ and GENEA at each oscillation frequency. For the human testing protocol, random forest machine-learning technique was used to develop two models using frequency domain (FD) and time domain (TD) features for each monitor. We compared activity type recognition accuracy between the GT3X+ and GENEA when the prediction model was fit using one monitor and then applied to the other. Z-statistics were used to compare the proportion of accurate predictions from the GT3X+ and GENEA for each model. Results: GENEA produced significantly higher (p &lt; 0.05, 3.5 to 6.2%) mean VM than GT3X+ at all frequencies during shaker testing. Training the model using TD input features on the GENEA and applied to GT3X+ data yielded significantly lower (p &lt; 0.05) prediction accuracy. Prediction accuracy was not compromised when interchangeably using FD models between monitors. Conclusions: It may be inappropriate to apply a model developed on the GENEA to predict activity type using GT3X+ data when input features are TD attributes of raw acceleration.<\/jats:p>","DOI":"10.3390\/s131114754","type":"journal-article","created":{"date-parts":[[2013,10,30]],"date-time":"2013-10-30T12:19:46Z","timestamp":1383135586000},"page":"14754-14763","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":63,"title":["Comparison of Raw Acceleration from the GENEA and ActiGraph\u2122 GT3X+ Activity Monitors"],"prefix":"10.3390","volume":"13","author":[{"given":"Dinesh","family":"John","sequence":"first","affiliation":[{"name":"Health Sciences, Northeastern University, 316D Robinson Hall, 360 Huntington Ave.,  Boston, MA 02115, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffer","family":"Sasaki","sequence":"additional","affiliation":[{"name":"Department of Kinesiology, University of Massachusetts, Amherst, MA 01003, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"Staudenmayer","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, University of Massachusetts, Amherst,  MA 01003, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marianna","family":"Mavilia","sequence":"additional","affiliation":[{"name":"College of Osteopathic Medicine, University of New England, ME 04103, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patty","family":"Freedson","sequence":"additional","affiliation":[{"name":"Department of Kinesiology, University of Massachusetts, Amherst, MA 01003, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2013,10,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1249\/MSS.0b013e3182399b7e","article-title":"Assessment of physical activity using wearable monitors: recommendations for monitor calibration and use in the field","volume":"44","author":"Freedson","year":"2012","journal-title":"Med. Sci. Sport Exerc."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1300","DOI":"10.1152\/japplphysiol.00465.2009","article-title":"An artificial neural network to estimate physical activity energy expenditure and identify physical activity type from an accelerometer","volume":"107","author":"Staudenmayer","year":"2009","journal-title":"J. appl. Physiol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1249\/MSS.0b013e31823bf95c","article-title":"Physical activity classification using the GENEA wrist-worn accelerometer","volume":"44","author":"Zhang","year":"2012","journal-title":"Med. Sci. Sport Exerc."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1473","DOI":"10.1088\/0967-3334\/32\/9\/009","article-title":"Calibrating a novel multi-sensor physical activity measurement system","volume":"32","author":"John","year":"2011","journal-title":"Physiol. Meas."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1249\/MSS.0b013e3182399f5e","article-title":"ActiGraph and Actical physical activity monitors: A peek under the hood","volume":"44","author":"John","year":"2012","journal-title":"Med. Sci. Sport Exerc."},{"key":"ref_6","unstructured":"National Health and Nutrition Examination Survey: Physical Activity Monitor (PAM) Procedures Manual. Available online: http:\/\/www.cdc.gov\/nchs\/data\/nhanes\/nhanes_11_12\/Physical_Activity_Monitor_Manual.pdf."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1249\/MSS.0b013e31820513be","article-title":"Validation of the GENEA Accelerometer","volume":"43","author":"Esliger","year":"2011","journal-title":"Med. Sci. Sport Exerc."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1016\/j.medengphy.2012.02.005","article-title":"Technical variability of the GT3X accelerometer","volume":"34","author":"Marin","year":"2012","journal-title":"Med. Eng. Phys."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1682\/JRRD.2003.10.0150","article-title":"The effect of walking speed on center of mass displacement","volume":"41","author":"Orendurff","year":"2004","journal-title":"J. Rehabil. Res. Dev."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.1152\/japplphysiol.90641.2008","article-title":"Comparing the performance of three generations of ActiGraph accelerometers","volume":"105","author":"Rothney","year":"2008","journal-title":"J. Appl. Physiol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1088\/0967-3334\/33\/2\/219","article-title":"Biomechanical examination of the \u2018plateau phenomenon\u2019 in ActiGraph vertical activity counts","volume":"33","author":"John","year":"2012","journal-title":"Physiol. Meas."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.scitotenv.2013.02.092","article-title":"Simple to complex modeling of breathing volume using a motion sensor","volume":"454\u2013455","author":"John","year":"2013","journal-title":"Sci. Total Environ."},{"key":"ref_13","unstructured":"Miller, J. (2013, January 17\u201319). Accelerometer Technologies, Specifications and Limitations. Amherst, MA, USA."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/13\/11\/14754\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:50:15Z","timestamp":1760219415000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/13\/11\/14754"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,10,30]]},"references-count":13,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2013,11]]}},"alternative-id":["s131114754"],"URL":"https:\/\/doi.org\/10.3390\/s131114754","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,10,30]]}}}