{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T04:46:15Z","timestamp":1791348375716,"version":"4.3.1"},"reference-count":36,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2025,10,26]],"date-time":"2025-10-26T00:00:00Z","timestamp":1761436800000},"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>The standard motion analysis systems are limited to laboratory settings; therefore, an individual\u2019s gait may not be realistic, as it is removed from the day-to-day environment in which people ambulate. The modern world and advanced technologies have driven portable, affordable, and wearable sensors for real-world gait assessment that can be used outside the laboratory and during day-to-day activities. Wearable sensors offer a promising solution; however, despite that, the reliability of many wearable systems, especially under unsupervised and real-world-like conditions, remains insufficiently validated. This study aimed to establish intra- and inter-rater reliability of the inertial sensors as a tool used in gait analysis in a quasi-real-world environment. Ninety-eight healthy participants (52% females) aged 19\u201333 years took part in this reliability study. The research procedures included two separate measurements of gait analysis at participants\u2019 preferred walking speed, conducted by two raters assessing selected spatiotemporal parameters. The reliability was calculated using intraclass correlation coefficients (ICC), and the bias was assessed using the Bland\u2013Altman method. The analysis of intraclass correlation coefficients (ICC) revealed excellent, or near-excellent, reliability for walking speed, cadence, and stride length between raters (ICC = 0.932\u20130.941, 0.950\u20130.957, and 0.916\u20130.938, respectively) and between measurements (ICC = 0.916\u20130.928, 0.934\u20130.938, and 0.888\u20130.906, respectively). Bland\u2013Altman plots confirmed minimal systematic bias for both inter- and intra-rater assessments, with differences in walking speed below 0.038 km\/h, cadence below 0.283 steps\/min, and stride length below 0.827 cm. The examined sensors are reliable tools for walking speed, cadence, and stride length in a quasi-real-world environment gait assessment. Future studies should include gait analysis involving random path and direction changes, turns, uneven or slippery surfaces, and natural environments. Additionally, research should consider individuals ambulating with various walking aids, or those with unilateral disorders, such as stroke.<\/jats:p>","DOI":"10.3390\/s25216597","type":"journal-article","created":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T05:48:46Z","timestamp":1761716926000},"page":"6597","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Reliability Study of Small, Portable, Easy-to-Use, and IMU-Based Sensors for Gait Assessment"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0174-7133","authenticated-orcid":false,"given":"Maciej Tomasz","family":"Kochman","sequence":"first","affiliation":[{"name":"Department of Clinical Physiotherapy in Musculoskeletal Disorders, Faculty of Health Sciences and Psychology, Institute of Physiotherapy, College Medicum, University of Rzesz\u00f3w, Tadeusza Rejtana Avenue 16C, 35-310 Rzesz\u00f3w, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-3884-780X","authenticated-orcid":false,"given":"Aleksandra","family":"Kielar","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, College Medicum, University of Rzesz\u00f3w, Tadeusza Rejtana Avenue 16C, 35-310 Rzesz\u00f3w, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2789-9843","authenticated-orcid":false,"given":"Marta","family":"Kasprzak","sequence":"additional","affiliation":[{"name":"Department of Clinical Physiotherapy in Musculoskeletal Disorders, Faculty of Health Sciences and Psychology, Institute of Physiotherapy, College Medicum, University of Rzesz\u00f3w, Tadeusza Rejtana Avenue 16C, 35-310 Rzesz\u00f3w, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1981-8454","authenticated-orcid":false,"given":"Wojciech","family":"Kasperek","sequence":"additional","affiliation":[{"name":"Department of Clinical Physiotherapy in Musculoskeletal Disorders, Faculty of Health Sciences and Psychology, Institute of Physiotherapy, College Medicum, University of Rzesz\u00f3w, Tadeusza Rejtana Avenue 16C, 35-310 Rzesz\u00f3w, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin","family":"Dutko","sequence":"additional","affiliation":[{"name":"Rockfield Software Limited, Swansea SA1 8AS, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adam","family":"Vellender","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Aberystwyth University, Aberystwyth SY23 3BZ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Grzegorz","family":"Przysada","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, College Medicum, University of Rzesz\u00f3w, Tadeusza Rejtana Avenue 16C, 35-310 Rzesz\u00f3w, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mariusz","family":"Dru\u017cbicki","sequence":"additional","affiliation":[{"name":"Department of Clinical Physiotherapy in Musculoskeletal Disorders, Faculty of Health Sciences and Psychology, Institute of Physiotherapy, College Medicum, University of Rzesz\u00f3w, Tadeusza Rejtana Avenue 16C, 35-310 Rzesz\u00f3w, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1411","DOI":"10.1093\/gerona\/glz121","article-title":"Gait as an Integrative Measure and Predictor of Health Across Species","volume":"74","author":"LeBrasseur","year":"2019","journal-title":"J. Gerontol. Ser. A"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Wu, X., Li, X., Xu, M., Zhang, Z., He, L., and Li, Y. (2021). Sarcopenia Prevalence and Associated Factors among Older Chinese Population: Findings from the China Health and Retirement Longitudinal Study. PLoS ONE, 16.","DOI":"10.1371\/journal.pone.0247617"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1483","DOI":"10.1016\/j.medengphy.2013.03.018","article-title":"Assessment of Gait Sensitivity Norm as a Predictor of Risk of Falling during Walking in a Neuromusculoskeletal Model","volume":"35","author":"Thangal","year":"2013","journal-title":"Med. Eng. Phys."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Takayanagi, N., Sudo, M., Yamashiro, Y., Chiba, I., Lee, S., Niki, Y., and Shimada, H. (2022). Predictivity of Daily Gait Speed Using Tri-Axial Accelerometers for Two-Year Incident Disability Among Japanese Older Adults. Sci. Rep., 12.","DOI":"10.1038\/s41598-022-14304-9"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Soltani, A., Abolhassani, N., Marques-Vidal, P., Aminian, K., Vollenweider, P., and Paraschiv-Ionescu, A. (2021). Real-World Gait Speed Estimation, Frailty and Handgrip Strength: A Cohort-Based Study. Sci. Rep., 11.","DOI":"10.1038\/s41598-021-98359-0"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1159\/000489927","article-title":"Gait Variability Can Predict the Risk of Cognitive Decline in Cognitively Normal Older People","volume":"45","author":"Byun","year":"2018","journal-title":"Dement. Geriatr. Cogn. Disord."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.1111\/jgs.13442","article-title":"Decline in Fast Gait Speed as a Predictor of Disability in Older Adults","volume":"63","author":"Artaud","year":"2015","journal-title":"J. Am. Geriatr. Soc."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez-Molinero, A., Herrero-Larrea, A., Mi\u00f1arro, A., Narvaiza, L., G\u00e1lvez-Barr\u00f3n, C., Gonzalo Le\u00f3n, N., Valldosera, E., De Mingo, E., Macho, O., and Aivar, D. (2019). The Spatial Parameters of Gait and Their Association with Falls, Functional Decline and Death in Older Adults: A Prospective Study. Sci. Rep., 9.","DOI":"10.1038\/s41598-019-45113-2"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Leal-Junior, A., and Frizera-Neto, A. (2022). Chapter 3-Gait Analysis: Overview, Trends, and challenges: This Chapter Is Carried out with the Participation of Laura Susana Vargas Valencia. Optical Fiber Sensors for the Next Generation of Rehabilitation Robotics, Academic Press.","DOI":"10.1016\/B978-0-32-385952-3.00011-1"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Scataglini, S., Verwulgen, S., Roosens, E., Haelterman, R., and Van Tiggelen, D. (2021). Measuring Spatiotemporal Parameters on Treadmill Walking Using Wearable Inertial System. Sensors, 21.","DOI":"10.3390\/s21134441"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.gaitpost.2011.03.024","article-title":"Normative Spatiotemporal Gait Parameters in Older Adults","volume":"34","author":"Hollman","year":"2011","journal-title":"Gait Posture"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Botros, A., Gyger, N., Sch\u00fctz, N., Single, M., Nef, T., and Gerber, S.M. (2021). Contactless Gait Assessment in Home-like Environments. Sensors, 21.","DOI":"10.3390\/s21186205"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1016\/j.physio.2013.03.001","article-title":"Affordable Clinical Gait Analysis: An Assessment of the Marker Tracking Accuracy of a New Low-Cost Optical 3D Motion Analysis System","volume":"99","author":"Carse","year":"2013","journal-title":"Physiotherapy"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"36333","DOI":"10.1007\/s11042-021-11014-8","article-title":"Measurement Method of Determining Natural and Unnatural Gaits Using Autocorrelation Coefficients","volume":"81","author":"Park","year":"2022","journal-title":"Multimed. Tools Appl."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.medengphy.2020.10.001","article-title":"Prediction of Ground Reaction Force and Joint Moments Based on Optical Motion Capture Data during Gait","volume":"86","author":"Mundt","year":"2020","journal-title":"Med. Eng. Phys."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Azhand, A., Rabe, S., M\u00fcller, S., Sattler, I., and Heimann-Steinert, A. (2021). Algorithm Based on One Monocular Video Delivers Highly Valid and Reliable Gait Parameters. Sci. Rep., 11.","DOI":"10.1038\/s41598-021-93530-z"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Hii, C.S.T., Gan, K.B., Zainal, N., Mohamed Ibrahim, N., Azmin, S., Mat Desa, S.H., Van De Warrenburg, B., and You, H.W. (2023). Automated Gait Analysis Based on a Marker-Free Pose Estimation Model. Sensors, 23.","DOI":"10.3390\/s23146489"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.medengphy.2015.02.003","article-title":"Instrumenting Gait with an Accelerometer: A System and Algorithm Examination","volume":"37","author":"Godfrey","year":"2015","journal-title":"Med. Eng. Phys."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Prasanth, H., Caban, M., Keller, U., Courtine, G., Ijspeert, A., Vallery, H., and Von Zitzewitz, J. (2021). Wearable Sensor-Based Real-Time Gait Detection: A Systematic Review. Sensors, 21.","DOI":"10.3390\/s21082727"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.gaitpost.2014.03.189","article-title":"Quantified Self and Human Movement: A Review on the Clinical Impact of Wearable Sensing and Feedback for Gait Analysis and Intervention","volume":"40","author":"Shull","year":"2014","journal-title":"Gait Posture"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s40279-022-01760-6","article-title":"Wearables for Running Gait Analysis: A Systematic Review","volume":"53","author":"Mason","year":"2023","journal-title":"Sports Med."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.gaitpost.2018.04.047","article-title":"The Use of Wearable Devices for Walking and Running Gait Analysis Outside of the Lab: A Systematic Review","volume":"63","author":"Benson","year":"2018","journal-title":"Gait Posture"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1186\/s12984-020-00685-3","article-title":"Validity and Reliability of Wearable Inertial Sensors in Healthy Adult Walking: A Systematic Review and Meta-Analysis","volume":"17","author":"Kobsar","year":"2020","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Laidig, D., Jocham, A.J., Guggenberger, B., Adamer, K., Fischer, M., and Seel, T. (2021). Calibration-Free Gait Assessment by Foot-Worn Inertial Sensors. Front. Digit. Health, 3.","DOI":"10.3389\/fdgth.2021.736418"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Oleksy, \u0141., Kr\u00f3likowska, A., Mika, A., Reichert, P., Kentel, M., Kentel, M., Po\u015bwiata, A., Roksela, A., Kozak, D., and Bienias, K. (2022). A Reliability of Active and Passive Knee Joint Position Sense Assessment Using the Luna EMG Rehabilitation Robot. IJERPH, 19.","DOI":"10.3390\/ijerph192315885"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.jcm.2016.02.012","article-title":"A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research","volume":"15","author":"Koo","year":"2016","journal-title":"J. Chiropr. Med."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"141","DOI":"10.11613\/BM.2015.015","article-title":"Understanding Bland Altman Analysis","volume":"25","author":"Giavarina","year":"2015","journal-title":"Biochem. Med"},{"key":"ref_28","first-page":"124","article-title":"The TripAnalyser: A Wearable System to Assess Gait and Potential Tripping","volume":"72","author":"Tsakonas","year":"2021","journal-title":"Acta Orthop. Et Traumatol. Hell."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"e1743","DOI":"10.1002\/pri.1743","article-title":"Associations between Gait Speed and Well-known Fall Risk Factors among Community-dwelling Older Adults","volume":"24","author":"Kyrdalen","year":"2019","journal-title":"Physiother. Res. Int."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"802","DOI":"10.1093\/gerona\/glac013","article-title":"Free-Living Gait Cadence Measured by Wearable Accelerometer: A Promising Alternative to Traditional Measures of Mobility for Assessing Fall Risk","volume":"78","author":"Urbanek","year":"2023","journal-title":"J. Gerontol. Ser. A"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Singh, P., Esposito, M., Barrons, Z., Clermont, C.A., Wannop, J., and Stefanyshyn, D. (2021). Measuring Gait Velocity and Stride Length with an Ultrawide Bandwidth Local Positioning System and an Inertial Measurement Unit. Sensors, 21.","DOI":"10.3390\/s21092896"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1016\/j.jshs.2022.02.001","article-title":"Do People with Low Back Pain Walk Differently? A Systematic Review and Meta-Analysis","volume":"11","author":"Smith","year":"2022","journal-title":"J. Sport Health Sci."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Byty\u00e7i, I., and Henein, M.Y. (2021). Stride Length Predicts Adverse Clinical Events in Older Adults: A Systematic Review and Meta-Analysis. JCM, 10.","DOI":"10.3390\/jcm10122670"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.gaitpost.2023.11.002","article-title":"Measuring Highly Accurate Foot Position and Angle Trajectories with Foot-Mounted IMUs in Clinical Practice","volume":"108","author":"Jocham","year":"2024","journal-title":"Gait Posture"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1080\/17483107.2018.1447611","article-title":"A Review in Gait Rehabilitation Devices and Applied Control Techniques","volume":"13","year":"2018","journal-title":"Disabil. Rehabil. Assist. Technol."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Springer, S., and Yogev Seligmann, G. (2016). Validity of the Kinect for Gait Assessment: A Focused Review. Sensors, 16.","DOI":"10.3390\/s16020194"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/25\/21\/6597\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T05:56:19Z","timestamp":1761717379000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/25\/21\/6597"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,26]]},"references-count":36,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2025,11]]}},"alternative-id":["s25216597"],"URL":"https:\/\/doi.org\/10.3390\/s25216597","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,26]]}}}