{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T23:49:14Z","timestamp":1769816954207,"version":"3.49.0"},"reference-count":86,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2009,10,27]],"date-time":"2009-10-27T00:00:00Z","timestamp":1256601600000},"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>This paper provides a comparative study on the different techniques of classifying human leg motions that are performed using two low-cost uniaxial piezoelectric gyroscopes worn on the leg. A number of feature sets, extracted from the raw inertial sensor data in different ways, are used in the classification process. The classification techniques implemented and compared in this study are: Bayesian decision making (BDM), a rule-based algorithm (RBA) or decision tree, least-squares method (LSM), k-nearest neighbor algorithm (k-NN), dynamic time warping (DTW), support vector machines (SVM), and artificial neural networks (ANN). A performance comparison of these classification techniques is provided in terms of their correct differentiation rates, confusion matrices, computational cost, and training and storage requirements. Three different cross-validation techniques are employed to validate the classifiers. The results indicate that BDM, in general, results in the highest correct classification rate with relatively small computational cost.<\/jats:p>","DOI":"10.3390\/s91108508","type":"journal-article","created":{"date-parts":[[2009,10,27]],"date-time":"2009-10-27T11:24:16Z","timestamp":1256642656000},"page":"8508-8546","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":50,"title":["Classifying Human Leg Motions with Uniaxial Piezoelectric Gyroscopes"],"prefix":"10.3390","volume":"9","author":[{"given":"Orkun","family":"Tun\u00e7el","sequence":"first","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Bilkent University, Bilkent 06800 Ankara, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kerem","family":"Altun","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Bilkent University, Bilkent 06800 Ankara, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Billur","family":"Barshan","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Bilkent University, Bilkent 06800 Ankara, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2009,10,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1109\/70.768189","article-title":"A high integrity IMU\/GPS navigation loop for autonomous land vehicle applications","volume":"15","author":"Sukkarieh","year":"1999","journal-title":"IEEE Trans. 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