{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T16:20:19Z","timestamp":1770913219904,"version":"3.50.1"},"reference-count":22,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2018,2,6]],"date-time":"2018-02-06T00:00:00Z","timestamp":1517875200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents a novel methodology for detecting the gait phase of human walking on level ground. The previous threshold method (TM) sets a threshold to divide the ground contact forces (GCFs) into on-ground and off-ground states. However, the previous methods for gait phase detection demonstrate no adaptability to different people and different walking speeds. Therefore, this paper presents a self-tuning triple threshold algorithm (STTTA) that calculates adjustable thresholds to adapt to human walking. Two force sensitive resistors (FSRs) were placed on the ball and heel to measure GCFs. Three thresholds (i.e., high-threshold, middle-threshold andlow-threshold) were used to search out the maximum and minimum GCFs for the self-adjustments of thresholds. The high-threshold was the main threshold used to divide the GCFs into on-ground and off-ground statuses. Then, the gait phases were obtained through the gait phase detection algorithm (GPDA), which provides the rules that determine calculations for STTTA. Finally, the STTTA reliability is determined by comparing the results between STTTA and Mariani method referenced as the timing analysis module (TAM) and Lopez\u2013Meyer methods. Experimental results show that the proposed method can be used to detect gait phases in real time and obtain high reliability when compared with the previous methods in the literature. In addition, the proposed method exhibits strong adaptability to different wearers walking at different walking speeds.<\/jats:p>","DOI":"10.3390\/s18020481","type":"journal-article","created":{"date-parts":[[2018,2,6]],"date-time":"2018-02-06T15:18:05Z","timestamp":1517930285000},"page":"481","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Self-Tuning Threshold Method for Real-Time Gait Phase Detection Based on Ground Contact Forces Using FSRs"],"prefix":"10.3390","volume":"18","author":[{"given":"Jing","family":"Tang","sequence":"first","affiliation":[{"name":"School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China"},{"name":"Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China"}]},{"given":"Jianbin","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China"},{"name":"Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China"}]},{"given":"Yang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China"},{"name":"Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China"}]},{"given":"Lie","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Electronic and Electrical Engineering, Wuhan Textile University, Hongshan District, Wuhan 430070, China"}]},{"given":"Enqi","family":"Zhan","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China"},{"name":"Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China"}]},{"given":"Qiuzhi","family":"Song","sequence":"additional","affiliation":[{"name":"School of Electromechanical, Beijing Institute of Technology, Beijing 100081, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,2,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.robot.2014.08.012","article-title":"A survey of sensor fusion methods in wearable robotics","volume":"73","author":"Novak","year":"2015","journal-title":"Robot. Auton. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Senanayake, C., Member, S., Senanayake, S.M.N.A., and Member, S. (2009, January 4\u20137). Fuzzy Logic based Implementation of a Real-Time Gait Phase Detection Algorithm using Kinematical Parameters for Walking. Proceedings of the International Conference of Soft Computing and Pattern Recognition, Malacca, Malaysia.","DOI":"10.1109\/SoCPaR.2009.116"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1109\/7333.928571","article-title":"A Reliable Gait Phase Detection System","volume":"9","author":"Pappas","year":"2001","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.gaitpost.2012.07.012","article-title":"Quantitative estimation of foot-flat and stance phase of gait using foot-worn inertial sensors","volume":"37","author":"Mariani","year":"2013","journal-title":"Gait Posture"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"594","DOI":"10.1109\/TITB.2011.2112773","article-title":"Automatic Detection of Temporal Gait Parameters in Poststroke Individuals","volume":"15","author":"Fulk","year":"2011","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1109\/TMECH.2008.2008803","article-title":"A Gait Monitoring System Based on Air Pressure Sensors Embedded in a Shoe","volume":"14","author":"Kong","year":"2009","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.gaitpost.2012.06.029","article-title":"Characterization of gait pattern by 3D angular accelerations in hemiparetic and healthy gait","volume":"37","author":"Rueterbories","year":"2013","journal-title":"Gait Posture"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1109\/86.867873","article-title":"Gait Event Detection for FES Using Accelerometers and Supervised Machine Learning","volume":"8","author":"Williamson","year":"2000","journal-title":"IEEE Trans. Rehabil. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1007\/s11517-011-0736-0","article-title":"Quasi real-time gait event detection using shank-attached gyroscopes","volume":"49","author":"Lee","year":"2011","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1251","DOI":"10.1007\/s11517-010-0692-0","article-title":"An adaptive gyroscope-based algorithm for temporal gait analysis","volume":"48","author":"Greene","year":"2010","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.medengphy.2014.12.004","article-title":"A robust real-time gait event detection using wireless gyroscope and its application on normal and altered gaits","volume":"37","author":"Gouwanda","year":"2015","journal-title":"Med. Eng. Phys."},{"key":"ref_12","unstructured":"Seel, T., Landgraf, L., Escobar, V.C., and Schauer, T. (2014). Online gait detection with automatic to gait velocity changes using accelerometers and gyroscopes. Biomed. Tech., 59."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1109\/TNSRE.2014.2337914","article-title":"A Novel Adaptive, Real-Time Algorithm to Detect Gait Events From Wearable Sensors","volume":"23","author":"Bejarano","year":"2015","journal-title":"IEEE Trans. Neural Syst. Rehibil. Eng."},{"key":"ref_14","unstructured":"M\u00fcller, P., Seel, T., and Schauer, T. (2015, January 12\u201313). Experimental Evaluation of a Novel Inertial Sensor Based Realtime Gait Phase Detection Algorithm. Proceedings of the European Conference on Technically Assisted Rehabilitation, Berlin, Germany."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1109\/86.506403","article-title":"Application of Tilt Sensors in Functional Electrical 1s ti minlation","volume":"4","author":"Dai","year":"1996","journal-title":"IEEE Trans. Rehabil. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/S0966-6362(99)00019-3","article-title":"Temporal parameters and patterns of the foot roll over during walking: Normative data for healthy adults","volume":"10","author":"Blanc","year":"1999","journal-title":"Gait Posture"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.gaitpost.2013.06.003","article-title":"Influence of long-term wearing of unstable shoes on compensatory control of posture: An electromyography-based analysis","volume":"39","author":"Sousa","year":"2014","journal-title":"Gait Posture"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"759","DOI":"10.1007\/s10514-016-9566-0","article-title":"An oscillator-based smooth real-time estimate of gait phase for wearable robotics","volume":"41","author":"Yan","year":"2017","journal-title":"Auton. Robot."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1016\/j.gaitpost.2008.01.019","article-title":"Detection of gait events using an F-Scan in-shoe pressure measurement system","volume":"28","author":"Catalfamo","year":"2008","journal-title":"Gait Posture"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1016\/j.gaitpost.2014.10.019","article-title":"Adaptive method for real-time gait phase detection based on ground contract forces","volume":"41","author":"Yu","year":"2015","journal-title":"Gait Posture"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/TNSRE.2002.1021583","article-title":"Evaluation of Force-Sensing Resistors for Gait Event Detection to Trigger Electrical Stimulation to Improve Walking in the Child With Cerebral Palsy","volume":"10","author":"Smith","year":"2002","journal-title":"IEEE Trans. Neural Syst. Rehabi. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1109\/JSEN.2004.823671","article-title":"A Reliable Gyroscope-Based Gait-Phase Detection Sensor Embedded in a Shoe Insole","volume":"4","author":"Pappas","year":"2004","journal-title":"IEEE Sens. J."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/2\/481\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:53:58Z","timestamp":1760194438000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/2\/481"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,2,6]]},"references-count":22,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2018,2]]}},"alternative-id":["s18020481"],"URL":"https:\/\/doi.org\/10.3390\/s18020481","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,2,6]]}}}